This application is a continuation of U.S. patent application Ser. No. 13/299,000, filed Nov. 17, 2011, which claims priority to provisional application 61/415,490, filed Nov. 19, 2010, which is herein incorporated by reference in its entirety.
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT This invention was made with government support under CA069568, CA132874 and CA111275 awarded by the National Institutes of Health and W81XWH-09-2-0014 awarded by the Army Medical Research and Material Command. The government has certain rights in the invention.
FIELD OF THE INVENTION The present invention relates to compositions and methods for cancer diagnosis, research and therapy, including but not limited to, cancer markers. In particular, the present invention relates to ncRNAs as diagnostic markers and clinical targets for prostate, lung, breast and pancreatic cancer.
BACKGROUND OF THE INVENTION A central aim in cancer research is to identify altered genes that are causally implicated in oncogenesis. Several types of somatic mutations have been identified including base substitutions, insertions, deletions, translocations, and chromosomal gains and losses, all of which result in altered activity of an oncogene or tumor suppressor gene. First hypothesized in the early 1900's, there is now compelling evidence for a causal role for chromosomal rearrangements in cancer (Rowley, Nat Rev Cancer 1: 245 (2001)). Recurrent chromosomal aberrations were thought to be primarily characteristic of leukemias, lymphomas, and sarcomas. Epithelial tumors (carcinomas), which are much more common and contribute to a relatively large fraction of the morbidity and mortality associated with human cancer, comprise less than 1% of the known, disease-specific chromosomal rearrangements (Mitelman, Mutat Res 462: 247 (2000)). While hematological malignancies are often characterized by balanced, disease-specific chromosomal rearrangements, most solid tumors have a plethora of non-specific chromosomal aberrations. It is thought that the karyotypic complexity of solid tumors is due to secondary alterations acquired through cancer evolution or progression.
Two primary mechanisms of chromosomal rearrangements have been described. In one mechanism, promoter/enhancer elements of one gene are rearranged adjacent to a proto-oncogene, thus causing altered expression of an oncogenic protein. This type of translocation is exemplified by the apposition of immunoglobulin (IG) and T-cell receptor (TCR) genes to MYC leading to activation of this oncogene in B- and T-cell malignancies, respectively (Rabbitts, Nature 372: 143 (1994)). In the second mechanism, rearrangement results in the fusion of two genes, which produces a fusion protein that may have a new function or altered activity. The prototypic example of this translocation is the BCR-ABL gene fusion in chronic myelogenous leukemia (CML) (Rowley, Nature 243: 290 (1973); de Klein et al., Nature 300: 765 (1982)). Importantly, this finding led to the rational development of imatinib mesylate (Gleevec), which successfully targets the BCR-ABL kinase (Deininger et al., Blood 105: 2640 (2005)). Thus, diagnostic methods that specifically identify epithelial tumors are needed.
SUMMARY OF THE INVENTION The present invention relates to compositions and methods for cancer diagnosis, research and therapy, including but not limited to, cancer markers. In particular, the present invention relates to ncRNAs as diagnostic markers and clinical targets for prostate, lung, breast and pancreatic cancer.
Embodiments of the present invention provide compositions, kits, and methods useful in the detection and screening of prostate cancer. Experiments conducted during the course of development of embodiments of the present invention identified upreguation of non-coding RNAs in prostate cancer. Some embodiments of the present invention provide compositions and methods for detecting expression levels of such ncRNAs. Identification of ncRNAs finds use in screening, diagnostic and research uses.
For example, in some embodiments, the present invention provides a method of screening for the presence of prostate cancer in a subject, comprising contacting a biological sample from a subject with a reagent for detecting the level of expression of one or more non-coding RNAs (ncRNA) (e.g., PCAT1, PCAT14, PCAT43 and PCAT 109); and detecting the level of expression of the ncRNA in the sample, for example, using an in vitro assay, wherein an increased level of expression of the ncRNA in the sample (e.g., relative to the level in normal prostate cells, increase in level relative to a prior time point, increase relative to a pre-established threshold level, etc.) is indicative of prostate cancer in the subject. In some embodiments, the ncRNAs are described by SEQ ID NOs: 1-9. In some embodiments, the sample is tissue, blood, plasma, serum, urine, urine supernatant, urine cell pellet, semen, prostatic secretions or prostate cells. In some embodiments, the detection is carried out utilizing a sequencing technique, a nucleic acid hybridization technique, a nucleic acid amplification technique, or an immunoassay. However, the invention is not limited to the technique employed. In some embodiments, the nucleic acid amplification technique is polymerase chain reaction, reverse transcription polymerase chain reaction, transcription-mediated amplification, ligase chain reaction, strand displacement amplification or nucleic acid sequence based amplification. In some embodiments, the prostate cancer is localized prostate cancer or metastatic prostate cancer. In some embodiments, the reagent is a pair of amplification oligonucleotides or an oligonucleotide probe.
Additional embodiments provide a method of screening for the presence of prostate cancer in a subject, comprising contacting a biological sample from a subject with a reagent for detecting the level of expression of two or more (e.g., 10 or more, 25 or more, 50 or more, 100 or more or all 121) non-coding RNAs (ncRNA) selected from, for example, PCAT1, PCAT2, PCAT3, PCAT4, PCAT5, PCAT6, PCAT7, PCAT8, PCAT9, PCAT10, PCAT11, PCAT12, PCAT13, PCAT14, PCAT15, PCAT16, PCAT17, PCAT18, PCAT19, PCAT20, PCAT21, PCAT22, PCAT23, PCAT24, PCAT25, PCAT26, PCAT27, PCAT28, PCAT29, PCAT30, PCAT31, PCAT32, PCAT33, PCAT34, PCAT35, PCAT36, PCAT37, PCAT38, PCAT39, PCAT40, PCAT41, PCAT42, PCAT43, PCAT44, PCAT45, PCAT46, PCAT47, PCAT48, PCAT49, PCAT50, PCAT51, PCAT52, PCAT53, PCAT54, PCAT55, PCAT56, PCAT57, PCAT58, PCAT59, PCAT60, PCAT61, PCAT62, PCAT63, PCAT64, PCAT65, PCAT66, PCAT67, PCAT68, PCAT69, PCAT70, PCAT71, PCAT72, PCAT73, PCAT74, PCAT75, PCAT76, PCAT77, PCAT78, PCAT79, PCAT80, PCAT81, PCAT82, PCAT83, PCAT84, PCAT85, PCAT86, PCAT87, PCAT88, PCAT89, PCAT90, PCAT91, PCAT92, PCAT93, PCAT94, PCAT95, PCAT96, PCAT97, PCAT98, PCAT99, PCAT100, PCAT101, PCAT102, PCAT103, PCAT104, PCAT105, PCAT106, PCAT107, PCAT108, PCAT109, PCAT110, PCAT111, PCAT112, PCAT113, PCAT114, PCAT115, PCAT116, PCAT117, PCAT118, PCAT119, PCAT120, or PCAT121; and detecting the level of expression of the ncRNA in the sample using an in vitro assay, wherein an increased level of expression of the ncRNA in the sample relative to the level in normal prostate cells in indicative of prostate cancer in the subject.
Further embodiments of the present invention provide an array, comprising reagents for detecting the level of expression of two or more (e.g., 10 or more, 25 or more, 50 or more, 100 or more or all 121) non-coding RNAs (ncRNA) selected from, for example, PCAT1, PCAT2, PCAT3, PCAT4, PCAT5, PCAT6, PCAT7, PCAT8, PCAT9, PCAT10, PCAT11, PCAT12, PCAT13, PCAT14, PCAT15, PCAT16, PCAT17, PCAT18, PCAT19, PCAT20, PCAT21, PCAT22, PCAT23, PCAT24, PCAT25, PCAT26, PCAT27, PCAT28, PCAT29, PCAT30, PCAT31, PCAT32, PCAT33, PCAT34, PCAT35, PCAT36, PCAT37, PCAT38, PCAT39, PCAT40, PCAT41, PCAT42, PCAT43, PCAT44, PCAT45, PCAT46, PCAT47, PCAT48, PCAT49, PCAT50, PCAT51, PCAT52, PCAT53, PCAT54, PCAT55, PCAT56, PCAT57, PCAT58, PCAT59, PCAT60, PCAT61, PCAT62, PCAT63, PCAT64, PCAT65, PCAT66, PCAT67, PCAT68, PCAT69, PCAT70, PCAT71, PCAT72, PCAT73, PCAT74, PCAT75, PCAT76, PCAT77, PCAT78, PCAT79, PCAT80, PCAT81, PCAT82, PCAT83, PCAT84, PCAT85, PCAT86, PCAT87, PCAT88, PCAT89, PCAT90, PCAT91, PCAT92, PCAT93, PCAT94, PCAT95, PCAT96, PCAT97, PCAT98, PCAT99, PCAT100, PCAT101, PCAT102, PCAT103, PCAT104, PCAT105, PCAT106, PCAT107, PCAT108, PCAT109, PCAT110, PCAT111, PCAT112, PCAT113, PCAT114, PCAT115, PCAT116, PCAT117, PCAT118, PCAT119, PCAT120, or PCAT121. In some embodiments, the reagent is a pair of amplification oligonucleotides or an oligonucleotide probe.
In some embodiments, the present invention provides a method for screening for the presence of lung cancer in a subject, comprising contacting a biological sample from a subject with a reagent for detecting the level of expression of one or more non-coding RNAs (e.g., M41 or ENST-75); and detecting the level of expression of the ncRNA in the sample, for example, using an in vitro assay, wherein an increased level of expression of the ncRNA in the sample (e.g., relative to the level in normal lung cells, increase in level relative to a prior time point, increase relative to a pre-established threshold level, etc.) is indicative of lung cancer in the subject.
In some embodiments, the present invention provides a method for screening for the presence of breast cancer in a subject, comprising contacting a biological sample from a subject with a reagent for detecting the level of expression of one or more non-coding RNAs (e.g., TU0011194, TU0019356, or TU0024146); and detecting the level of expression of the ncRNA in the sample, for example, using an in vitro assay, wherein an increased level of expression of the ncRNA in the sample (e.g., relative to the level in normal breast cells, increase in level relative to a prior time point, increase relative to a pre-established threshold level, etc.) is indicative of breast cancer in the subject.
In some embodiments, the present invention provides a method for screening for the presence of pancreatic cancer in a subject, comprising contacting a biological sample from a subject with a reagent for detecting the level of expression of one or more non-coding RNAs (e.g., TU0009141, TU0062051, or TU0021861); and detecting the level of expression of the ncRNA in the sample, for example, using an in vitro assay, wherein an increased level of expression of the ncRNA in the sample (e.g., relative to the level in normal pancreatic cells, increase in level relative to a prior time point, increase relative to a pre-established threshold level, etc.) is indicative of pancreatic cancer in the subject.
Additional embodiments are described herein.
DESCRIPTION OF THE FIGURES FIG. 1 shows that prostate cancer transcriptome sequencing reveals dysregulation of exemplary transcripts identified herein. a. A global overview of transcription in prostate cancer. b. A line graph showing the cumulative fraction of genes that are expressed at a given RPKM level. c. Conservation analysis comparing unannotated transcripts to known genes and intronic controls shows a low but detectable degree of purifying selection among intergenic and intronic unannotated transcripts. d-g. Intersection plots displaying the fraction of unannotated transcripts enriched for H3K4me2 (d), H3K4me3 (e), Acetyl-H3 (f) or RNA polymerase II (g) at their transcriptional start site (TSS) using ChIP-Seq and RNA-Seq data for the VCaP prostate cancer cancer cell line. h. A heatmap representing differentially expressed transcripts, including novel unannotated transcripts, in prostate cancer.
FIG. 2 shows that unannotated intergenic transcripts differentiate prostate cancer and benign prostate samples. a. A histogram plotting the genomic distance between an unannotated ncRNA and the nearest protein-coding gene. b. A Circos plot displaying the location of annotated transcripts and unannotated transcripts on Chr15q. c. A heatmap of differentially expressed or outlier unannotated intergenic transcripts clusters benign samples, localized tumors, and metastatic cancers by unsupervised clustering analyses. d. Cancer outlier profile analysis (COPA) outlier analysis for the prostate cancer transcriptome reveals known outliers (SPINK1, ERG, and ETV1), as well as numerous unannotated transcripts.
FIG. 3 shows validation of tissue-specific prostate cancer-associated non-coding RNAs. a-c. Quantitative real-time PCR was performed on a panel of prostate and non-prostate samples to measure expression levels of three nominated non-coding RNAs (ncRNAs), PCAT-43, PCAT-109, and PCAT-14, upregulated in prostate cancer compared to normal prostate tissues. a. PCAT-43 is a 20 kb ncRNA located 40 kb upstream of PMEPA1 on chr20q13.31. b. PCAT-109, located in a large, 0.5 Mb gene desert region on chr2q31.3 displays widespread transcription in prostate tissues, particularly metastases. c. PCAT-14, a genomic region on chr22q11.23 encompassing a human endogenous retrovirus exhibits marked upregulation in prostate tumors but not metastases.
FIG. 4 shows that prostate cancer ncRNAs populate the Chr8q24 gene desert. a. A schematic of the chr8q24 region. b. Comprehensive analysis of the chr8q24 region by RNA-Seq and ChIP-Seq reveals numerous transcripts supported by histone modifications, such as Acetyl-H3 and H3K4me3, demarcating active chromatin. c. RT-PCR and Sanger sequencing validation of the PCAT-1 exon-exon junction. d. The genomic location of PCAT-1 determined by 5′ and 3′ RACE. Sequence analysis of PCAT-1 shows that it is a viral long terminal repeat (LTR) promoter splicing to a marniner family transposase that has been bisected by an Alu repeat. e. qPCR on a panel of prostate and non-prostate samples shows prostate-specific expression and upregulation in prostate cancers and metastases compared to benign prostate samples. f. Four matched tumor/normal pairs included in the analysis in e. demonstrate somatic upregulation of PCAT-1 in matched cancer samples.
FIG. 5 shows that ncRNAs serve as urine biomarkers for prostate cancer. a-c. Three ncRNAs displaying biomarker status in prostate cancer tissues were evaluated on a cohort of urine samples from 77 patients with prostate cancer and 31 controls with negative prostate biopsy results and absence of the TMPRSS2-ERG fusion transcript. PCA3 (a); PCAT-1 (b); and PCAT-14 (c).
d. Scatter plots demonstrating distinct patient subsets scoring positively for PCA3, PCAT-1, or PCAT-14 expression. e. A heatmap displaying patients positive and negative for several different prostate cancer biomarkers in urine sediment samples. f. A table displaying the statistical significance of the ncRNA signature. g. A model for non-coding RNA (ncRNA) activation in prostate cancer.
FIG. 6 shows Ab initio assembly of the prostate cancer transcriptome. (a) Reads were mapped with TopHat and assembled into library-specific transcriptomes by Cufflinks. (b) Transcripts corresponding to processed pseudogenes were isolated, and the remaining transcripts were categorized based on overlap with an aggregated set of known gene annotations.
FIG. 7 shows classification tree results for Chromosome 1. The recursive regression and partitioning trees (rpart) machine learning algorithm was used to predict expressed transcripts versus background signal.
FIG. 8 shows transcript assembly of known genes. ab initio transcript assembly on prostate transcriptome sequencing data was used to reconstruct the known prostate transcriptome. a. SPINK1, a biomarker for prostate cancer. b. PRUNE2 with the PCA3 non-coding RNA within its intronic regions. c. NFKB1. d. COL9A2.
FIG. 9 shows analysis of EST support for exemplary transcripts. ESTs from the UCSC database table “Human ESTs” were used to evaluate the amount of overlap between ESTs and novel transcripts. a. A line graph showing the fraction of genes whose transcripts are supported by a particular fraction of ESTs. b. A table displaying the number of ESTs supporting each class of transcripts
FIG. 10 shows analysis of coding potential of unannotated transcripts. DNA sequences for each transcript were extracted and searched for open reading frames (ORFs) using the txCdsPredict program from the UCSC source tool set.
FIG. 11 shows repetitive content of novel transcripts. The percentage of repetitive sequences was assessed in all transcripts by calculating the percentage of repeat masked nucleotides in each sequence.
FIG. 12 shows distinct ChIP-Seq signatures for repeat-associated and nonrepeat novel ncRNAs. Unannotated transcripts were divided into two groups, repeat-associated and non-repeat, and intersected with ChIP-Seq data for Acetyl-H3 and H3K4me3, two histone modifications strongly associated with transcriptional start sites (TSS), in two prostate cancer cell lines. a. Acetyl-H3 in LNCaP cells. b. H3K4me3 in LNCaP cells. c. Acetyl-H3 in VCaP cells. d. H3K4me3 in VCaP cells.
FIG. 13 shows overlap of unannotated transcripts with ChIP-Seq data in VCaP cells. Previously published ChIP-Seq data for VCaP prostate cancer cells were intersected with unannotated prostate cancer transcripts and annotated control genes. a. H3K4me1 b. H3K36me3.
FIG. 14 shows overlap of unannotated transcripts with ChIP-Seq data in LNCaP cells. ChIP-Seq data for LNCaP prostate cancer cells were intersected with unannotated transcripts and annotated control genes. ncRNAs were divided into intergenic and intronic. a. H3K4me1 b. H3K4me2 c. H3K4me3 d. Acetyl-H3 e. H3K36me3 f. RNA polymerase II.
FIG. 15 shows validation of a novel transcript on chromosome 15. a. Coverage maps showing the average expression levels (RPKM) across the benign, localized tumor, and metastatic samples shows upregulation of a novel transcript downstream of TLE3. b. Several predicted isoforms of this transcript were nominated which retained common exons 1 and 2. c. The exon-exon boundary between exons 1 and 2, as well as an internal portion of exon 3, was validated by RT-PCR in prostate cell line models. d. Sanger sequencing of the RT-PCR product confirmed the junction of exon 1 and exon 2.
FIG. 16 shows clustering of prostate cancer with outliers. Transcripts with outlier profile scores in the top 10% were clustered using hierarchical trees.
FIG. 17 shows validation of novel transcripts in prostate cell lines. 11/14 unannotated transcripts selected for validation by RT-PCR and qPCR were confirmed in cell line models. a. RT-PCR gels showing expected bands for the 11 transcripts that validated. b. Representative qPCR results using primers selected from a. The primers used in b are indicated by a red asterisk in a.
FIG. 18 shows that PCAT-14 is upregulated by androgen signaling. VCaP and LNCaP cells were treated 5 nM R1881 or vehicle (ethanol) control.
FIG. 19 shows that PCAT-14 is upregulated in matched tumor tissues. Four matched tumor-normal patient tissue samples were assayed for PCAT-14 expression by qPCR.
FIG. 20 shows analysis of PCAT-14 transcript structure. a. Representative 5′RACE results using a 3′ primer confirms the presence of the sense transcript PCAT-14. Predicted novel transcripts are displayed above the RACE results. b. DNA sequence analysis of PCAT-14 indicates expected splice donor sites, splice acceptor sites, and a polyadenylation site.
FIG. 21 shows analysis of PCAT-1 transcript structure. 5′ and 3′ RACE experiments showed a ncRNA transcript containing two exons.
FIG. 22 shows that knockdown of PCAT-1 does not affect invasion or proliferation of VCaP cells. VCaP cells were transfected with custom-made siRNAs targeting PCAT-1 or non-targeting controls. a. Knockdown efficiency for four siRNA oligos individually and pooled. b.-d. siRNAs 2-4 were tested for functional effect due to their higher efficiency of knockdown. b. A cell proliferation assay performed with a Coulter counter shows no significant difference in cell proliferation following knockdown of PCAT-1. c. A WST-1 assay indicates no change in VCaP cell viability following PCAT-1 knockdown. d. A transmembrane invasion assay shows no change in VCaP cell invasiveness following PCAT-1 knockdown.
FIG. 23 shows transcription of two Alu elements in a CACNA1D intron. a. Coverage maps representing average expression in RPKM in benign samples, localized tumors, and prostate metastases. b. RPKM expression values for the CACNA1D Alu transcript across the prostate transcriptome sequencing cohort. c. RT-PCR validation of the Alu transcript in cell line models. d. Sanger sequencing confirmation of RT-PCR fragments verifies the presence of AluSp transcript sequence. e. Raw sequencing data of a portion of the AluSp sequence.
FIG. 24 shows transcription of numerous repeat elements at the SChLAP1 locus. a. Coverage maps representing repeat elements transcribed at the chr2q31.3 locus. b. RPKM expression expression values for the LINE-1 repeat region on chr2q31.3 across the prostate transcriptome sequencing cohort. c. RTPCR validation of the LINE-1 repetitive element in cell line models. A 402 bp fragment was amplified. d. Sanger sequencing of the PCR fragment confirms identity of the LINE-1 amplicon.
FIG. 25 shows a heatmap of repeats clusters prostate cancer samples. Unannotated transcripts that contained repeat elements were used to cluster prostate cancer samples in an unsupervised manner.
FIG. 26 shows that the SChLAP1 locus spans >500 kb. Visualization of transcriptome sequencing data in the UCSC genome browser indicates that a large, almost 1 Mb section of chromosome 2 is highly activated in cancer, contributing to many individual transcripts regulated in a coordinated fashion.
FIG. 27 shows that the SChLAP1 locus is associated with ETS positive tumors. a. Expression of the SChLAP1 locus was assayed by qPCR as display in FIG. 3b on a cohort of 14 benign prostate tissues, 47 localized prostate tumors and 10 metastatic prostate cancers. b. Quantification of the SChLAP1 association with ETS status using the threshold indicated by the blue dotted line in a.
FIG. 28 shows the sequence of PCAT-1 and PCAT-14.
FIG. 29 shows that PCAT-1 expression sensitizes prostate cancer cells to treatment with PARP-1 inhibitors. (a-d) treatment with the PARP1 inhibitor olaparib, (e-h) treatment with the PARP1 inhibitor ABT-888. Stable PCAT-1 knockdown in LNCAP prostate cells reduces sensitivity to olaparib (a) and ABT-888 (e). Stable overexpression in Du145 prostate cancer and RWPE benign prostate cells increases sensitivity to olaparib (b,c) and ABT-888 (f,g). Overexpression of PCAT-1 in MCF7 breast cancer cells does not recapitulate this effect (d,h).
FIG. 30 shows that PCAT-1 expression sensitizes prostate cancer cells to radiation treatment. (a) Stable PCAT-1 knockdown in LNCAP prostate cells reduces sensitivity to radiation. (b,c) Stable overexpression in Du145 prostate cancer and RWPE benign prostate cells increases sensitivity to radiation. (d). Overexpression of PCAT-1 in MCF7 breast cancer cells does not recapitulate this effect.
FIG. 31 shows that unannotated intergenic transcripts differentiate prostate cancer and benign samples. (a) The genomic location and exon structure of SChLAP-1. SChLAP-1 is located on chromosome 2 in a previously unannotated region. (b) The isoform structure of SChLAP-1. (c) Cell fractionation into nuclear and cytoplasmic fractions demonstrates that SChLAP-1 is predominantly nuclear in its localization. (d) Expression of SChLAP-1 in a cohort of prostate cancer and benign tissues indicates that SChLAP-1 is a prostate cancer outlier associated with cancers.
FIG. 32 shows that SChLAP-1 is required for prostate cancer cell invasion and proliferation. (a) Prostate and non-prostate cancer cell lines were treated with SChLAP-1 siRNAs. (b and c) As in (a), prostate and non-prostate cell lines were assayed for cell proliferation following SChLAP-1 knockdown. (d) The three most abundant isoforms of SChLAP-1 were cloned and overexpressed in RWPE benign immortalized prostate cells at levels similar to LNCaP cancer cells. (e) RWPE cells overexpressing SChLAP-1 isoforms show an increased ability to invade through Matrigel in Boyden chamber assays.
FIG. 33 shows that deletion analysis of SChLAP-1 identifies a region essential for its function. (a) RWPE cells overexpressing SChLAP-1 deletion constructs or full-length isoform #1 were generated as shown in the schematic of the constructs. (b) RWPE cells overexpressing SChLAP-1 deletion construct5 demonstrated an impaired ability to invade through Matrigel, while the other deletion constructs showed no reduction in their ability to induce RWPE cell invasion compared to the wild type SChLAP-1.
FIG. 34 shows detection of prostate cancer RNAs in patient urine samples. (a-e). (a) PCA3 (b) PCAT-14 (c) PCAT-1 (d) SChLAP-1 (e) PDLIM5
FIG. 35 shows multiplexing urine SChLAP-1 measurements with serum PSA improves prostate cancer risk stratification.
FIG. 36 shows analysis of the lung cancer transcriptome. (a) 38 lung cell lines were analyzed by RNA-Seq and then lncRNA transcripts were reconstructed. (b) Expression levels of transcripts observed in lung cell lines. (c) An outlier analyses of 13 unannotated transcripts shows the presence of novel lncRNAs in subtypes of lung cancer cell lines.
FIG. 37 shows discovery of M41 and ENST-75 in lung cancer. (a) The genomic location of M41, which resides in an intron of DSCAM. M41 is poorly conserved across species. (b) qPCR of M41 demonstrates outlier expression in 15-20% of lung adenocarcinomas as well as high expression in breast cells. (c) The genomic location of ENST-75, which demonstrates high conservation across species. (d) qPCR of ENST-75 shows up-regulation in lung cancer but not breast or prostate cancers. High expression is observed in normal testis.
FIG. 38 shows lncRNAs are drivers and biomarkers in lung cancer. (a) Knockdown of ENST-75 in H1299 cells with independent siRNAs achieving >70% knockdown. (b) Knockdown of ENST-75 in H1299 cells impairs cell proliferation. Error bars represent s.e.m. (c) ENST-75 expression in lung adenocarcinomas stratifies patient overall survival. (d) Serum detection levels of ENST-75 in normal and lung cancer patients. (e) Average ENST-75 expression in lung cancer patient sera compared to normal patient sera. Error bars represent s.e.m.
FIG. 39 shows nomination of cancer-associated lncRNAs in breast and pancreatic cancer. (a-c) (a) TU0011194 (b) TU0019356 (c) TU0024146 (d-f) Three novel pancreatic cancer lncRNAs nominated from RNA-Seq data. All show outlier expression patterns in pancreatic cancer samples but not benign samples. (d) TU0009141 (e) TU0062051 (f) TU0021861
DEFINITIONS To facilitate an understanding of the present invention, a number of terms and phrases are defined below:
As used herein, the terms “detect”, “detecting” or “detection” may describe either the general act of discovering or discerning or the specific observation of a detectably labeled composition.
As used herein, the term “subject” refers to any organisms that are screened using the diagnostic methods described herein. Such organisms preferably include, but are not limited to, mammals (e.g., murines, simians, equines, bovines, porcines, canines, felines, and the like), and most preferably includes humans.
The term “diagnosed,” as used herein, refers to the recognition of a disease by its signs and symptoms, or genetic analysis, pathological analysis, histological analysis, and the like.
A “subject suspected of having cancer” encompasses an individual who has received an initial diagnosis (e.g., a CT scan showing a mass or increased PSA level) but for whom the stage of cancer or presence or absence of ncRNAs indicative of cancer is not known. The term further includes people who once had cancer (e.g., an individual in remission). In some embodiments, “subjects” are control subjects that are suspected of having cancer or diagnosed with cancer.
As used herein, the term “characterizing cancer in a subject” refers to the identification of one or more properties of a cancer sample in a subject, including but not limited to, the presence of benign, pre-cancerous or cancerous tissue, the stage of the cancer, and the subject's prognosis. Cancers may be characterized by the identification of the expression of one or more cancer marker genes, including but not limited to, the ncRNAs disclosed herein.
As used herein, the term “characterizing prostate tissue in a subject” refers to the identification of one or more properties of a prostate tissue sample (e.g., including but not limited to, the presence of cancerous tissue, the presence or absence of ncRNAs, the presence of pre-cancerous tissue that is likely to become cancerous, and the presence of cancerous tissue that is likely to metastasize). In some embodiments, tissues are characterized by the identification of the expression of one or more cancer marker genes, including but not limited to, the cancer markers disclosed herein.
As used herein, the term “stage of cancer” refers to a qualitative or quantitative assessment of the level of advancement of a cancer. Criteria used to determine the stage of a cancer include, but are not limited to, the size of the tumor and the extent of metastases (e.g., localized or distant).
As used herein, the term “nucleic acid molecule” refers to any nucleic acid containing molecule, including but not limited to, DNA or RNA. The term encompasses sequences that include any of the known base analogs of DNA and RNA including, but not limited to, 4-acetylcytosine, 8-hydroxy-N6-methyladenosine, aziridinylcytosine, pseudoisocytosine, 5-(carboxyhydroxylmethyl) uracil, 5-fluorouracil, 5-bromouracil, 5-carboxymethylaminomethyl-2-thiouracil, 5-carboxymethylaminomethyluracil, dihydrouracil, inosine, N6-isopentenyladenine, 1-methyladenine, 1-methylpseudouracil, 1-methylguanine, 1-methylinosine, 2,2-dimethylguanine, 2-methyladenine, 2-methylguanine, 3-methyl cytosine, 5-methylcytosine, N6-methyladenine, 7-methylguanine, 5-methylaminomethyluracil, 5-methoxy-aminomethyl-2-thiouracil, beta-D-mannosylqueosine, 5′-methoxycarbonylmethyluracil, 5-methoxyuracil, 2-methylthio-N6-isopentenyladenine, uracil-5-oxyacetic acid methylester, uracil-5-oxyacetic acid, oxybutoxosine, pseudouracil, queosine, 2-thiocytosine, 5-methyl-2-thiouracil, 2-thiouracil, 4-thiouracil, 5-methyluracil, N-uracil-5-oxyacetic acid methylester, uracil-5-oxyacetic acid, pseudouracil, queosine, 2-thiocytosine, and 2,6-diaminopurine.
The term “gene” refers to a nucleic acid (e.g., DNA) sequence that comprises coding sequences necessary for the production of a polypeptide, precursor, or RNA (e.g., rRNA, tRNA). The polypeptide can be encoded by a full length coding sequence or by any portion of the coding sequence so long as the desired activity or functional properties (e.g., enzymatic activity, ligand binding, signal transduction, immunogenicity, etc.) of the full-length or fragments are retained. The term also encompasses the coding region of a structural gene and the sequences located adjacent to the coding region on both the 5′ and 3′ ends for a distance of about 1 kb or more on either end such that the gene corresponds to the length of the full-length mRNA. Sequences located 5′ of the coding region and present on the mRNA are referred to as 5′ non-translated sequences. Sequences located 3′ or downstream of the coding region and present on the mRNA are referred to as 3′ non-translated sequences. The term “gene” encompasses both cDNA and genomic forms of a gene. A genomic form or clone of a gene contains the coding region interrupted with non-coding sequences termed “introns” or “intervening regions” or “intervening sequences.” Introns are segments of a gene that are transcribed into nuclear RNA (hnRNA); introns may contain regulatory elements such as enhancers. Introns are removed or “spliced out” from the nuclear or primary transcript; introns therefore are absent in the messenger RNA (mRNA) transcript. The mRNA functions during translation to specify the sequence or order of amino acids in a nascent polypeptide.
As used herein, the term “oligonucleotide,” refers to a short length of single-stranded polynucleotide chain. Oligonucleotides are typically less than 200 residues long (e.g., between 15 and 100), however, as used herein, the term is also intended to encompass longer polynucleotide chains. Oligonucleotides are often referred to by their length. For example a 24 residue oligonucleotide is referred to as a “24-mer”. Oligonucleotides can form secondary and tertiary structures by self-hybridizing or by hybridizing to other polynucleotides. Such structures can include, but are not limited to, duplexes, hairpins, cruciforms, bends, and triplexes.
As used herein, the terms “complementary” or “complementarity” are used in reference to polynucleotides (i.e., a sequence of nucleotides) related by the base-pairing rules. For example, the sequence “5′-A-G-T-3′,” is complementary to the sequence “3′-T-C-A-5′.” Complementarity may be “partial,” in which only some of the nucleic acids' bases are matched according to the base pairing rules. Or, there may be “complete” or “total” complementarity between the nucleic acids. The degree of complementarity between nucleic acid strands has significant effects on the efficiency and strength of hybridization between nucleic acid strands. This is of particular importance in amplification reactions, as well as detection methods that depend upon binding between nucleic acids.
The term “homology” refers to a degree of complementarity. There may be partial homology or complete homology (i.e., identity). A partially complementary sequence is a nucleic acid molecule that at least partially inhibits a completely complementary nucleic acid molecule from hybridizing to a target nucleic acid is “substantially homologous.” The inhibition of hybridization of the completely complementary sequence to the target sequence may be examined using a hybridization assay (Southern or Northern blot, solution hybridization and the like) under conditions of low stringency. A substantially homologous sequence or probe will compete for and inhibit the binding (i.e., the hybridization) of a completely homologous nucleic acid molecule to a target under conditions of low stringency. This is not to say that conditions of low stringency are such that non-specific binding is permitted; low stringency conditions require that the binding of two sequences to one another be a specific (i.e., selective) interaction. The absence of non-specific binding may be tested by the use of a second target that is substantially non-complementary (e.g., less than about 30% identity); in the absence of non-specific binding the probe will not hybridize to the second non-complementary target.
As used herein, the term “hybridization” is used in reference to the pairing of complementary nucleic acids. Hybridization and the strength of hybridization (i.e., the strength of the association between the nucleic acids) is impacted by such factors as the degree of complementary between the nucleic acids, stringency of the conditions involved, the Tm of the formed hybrid, and the G:C ratio within the nucleic acids. A single molecule that contains pairing of complementary nucleic acids within its structure is said to be “self-hybridized.”
As used herein the term “stringency” is used in reference to the conditions of temperature, ionic strength, and the presence of other compounds such as organic solvents, under which nucleic acid hybridizations are conducted. Under “low stringency conditions” a nucleic acid sequence of interest will hybridize to its exact complement, sequences with single base mismatches, closely related sequences (e.g., sequences with 90% or greater homology), and sequences having only partial homology (e.g., sequences with 50-90% homology). Under ‘medium stringency conditions,” a nucleic acid sequence of interest will hybridize only to its exact complement, sequences with single base mismatches, and closely relation sequences (e.g., 90% or greater homology). Under “high stringency conditions,” a nucleic acid sequence of interest will hybridize only to its exact complement, and (depending on conditions such a temperature) sequences with single base mismatches. In other words, under conditions of high stringency the temperature can be raised so as to exclude hybridization to sequences with single base mismatches.
The term “isolated” when used in relation to a nucleic acid, as in “an isolated oligonucleotide” or “isolated polynucleotide” refers to a nucleic acid sequence that is identified and separated from at least one component or contaminant with which it is ordinarily associated in its natural source. Isolated nucleic acid is such present in a form or setting that is different from that in which it is found in nature. In contrast, non-isolated nucleic acids as nucleic acids such as DNA and RNA found in the state they exist in nature. For example, a given DNA sequence (e.g., a gene) is found on the host cell chromosome in proximity to neighboring genes; RNA sequences, such as a specific mRNA sequence encoding a specific protein, are found in the cell as a mixture with numerous other mRNAs that encode a multitude of proteins. However, isolated nucleic acid encoding a given protein includes, by way of example, such nucleic acid in cells ordinarily expressing the given protein where the nucleic acid is in a chromosomal location different from that of natural cells, or is otherwise flanked by a different nucleic acid sequence than that found in nature. The isolated nucleic acid, oligonucleotide, or polynucleotide may be present in single-stranded or double-stranded form. When an isolated nucleic acid, oligonucleotide or polynucleotide is to be utilized to express a protein, the oligonucleotide or polynucleotide will contain at a minimum the sense or coding strand (i.e., the oligonucleotide or polynucleotide may be single-stranded), but may contain both the sense and anti-sense strands (i.e., the oligonucleotide or polynucleotide may be double-stranded).
As used herein, the term “purified” or “to purify” refers to the removal of components (e.g., contaminants) from a sample. For example, antibodies are purified by removal of contaminating non-immunoglobulin proteins; they are also purified by the removal of immunoglobulin that does not bind to the target molecule. The removal of non-immunoglobulin proteins and/or the removal of immunoglobulins that do not bind to the target molecule results in an increase in the percent of target-reactive immunoglobulins in the sample. In another example, recombinant polypeptides are expressed in bacterial host cells and the polypeptides are purified by the removal of host cell proteins; the percent of recombinant polypeptides is thereby increased in the sample.
As used herein, the term “sample” is used in its broadest sense. In one sense, it is meant to include a specimen or culture obtained from any source, as well as biological and environmental samples. Biological samples may be obtained from animals (including humans) and encompass fluids, solids, tissues, and gases. Biological samples include blood products, such as plasma, serum and the like. Such examples are not however to be construed as limiting the sample types applicable to the present invention.
DETAILED DESCRIPTION OF THE INVENTION The present invention relates to compositions and methods for cancer diagnosis, research and therapy, including but not limited to, cancer markers. In particular, the present invention relates to ncRNAs as diagnostic markers and clinical targets for prostate, lung, breast and pancreatic cancer.
Experiments conducted during the development of embodiments of the present invention utilized RNA-Seq analyses of tissue samples and ab initio transcriptome assembly to predict the complete polyA+ transcriptome of prostate cancer. 6,144 novel ncRNAs found in prostate cancer were identified, including 121 ncRNAs that associated with disease progression (FIGS. 1, 2, 16 and 25). These data demonstrate the global utility of RNA-Seq in defining functionally-important elements of the genome.
The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless, although the biological role of these RNAs, especially the differentially-expressed ones, is not yet known, these results indicate a model in which specific intergenic loci are activated in prostate cancer, enabling the transcription of numerous disease-specific and tissue-specific ncRNAs (FIG. 5g). Clinically, these ncRNA signatures are suitable for urine-based assays to detect and diagnose prostate cancer in a non-invasive manner (See e.g., Example 1). It is further contemplated that specific ncRNA signatures occur universally in all disease states and applying these methodologies to other diseases reveals clinically important biomarkers, particularly for diseases that currently lack good protein biomarkers.
While traditional approaches have focused on the annotated reference genome, data generated during the course of development of embodiments of the present invention implicate large swaths of unannotated genomic loci in prostate cancer progression and prostate-specific expression. One example of this is the SChLAP1 locus, which represents a >500 kb stretch of coordinately regulated expression, and the chr8q24 locus, which contains a prostate specific region with the prostate cancer biomarker PCAT-1. The fact that the SChLAP1 locus is almost exclusively expressed in prostate cancers harboring an ETS gene fusion further confirms the capacity of ncRNAs to identify patient disease subtypes. In addition, these analyses reveal novel cancer-specific drivers of tumorigenesis. For example, the long ncRNA HOTAIR is known to direct cancer-promoting roles for EZH2 in breast cancer (Gupta et al., Nature 464 (7291), 1071 (2010)), while in the PC3 prostate cancer cell line a similar role has been proposed for the ANRIL ncRNA (Yap et al., Mol Cell 38 (5), 662 (2010)).
I. Diagnostic and Screening Methods As described above, embodiments of the present invention provide diagnostic and screening methods that utilize the detection of ncRNAs (e.g., PCAT-1, PCAT-14, PCAT-43 and PCAT-109; SEQ ID NOs: 1-9). Exemplary, non-limiting methods are described below.
Any patient sample suspected of containing the ncRNAs may be tested according to methods of embodiments of the present invention. By way of non-limiting examples, the sample may be tissue (e.g., a prostate biopsy sample or a tissue sample obtained by prostatectomy), blood, urine, semen, prostatic secretions or a fraction thereof (e.g., plasma, serum, urine supernatant, urine cell pellet or prostate cells). A urine sample is preferably collected immediately following an attentive digital rectal examination (DRE), which causes prostate cells from the prostate gland to shed into the urinary tract.
In some embodiments, the patient sample is subjected to preliminary processing designed to isolate or enrich the sample for the ncRNAs or cells that contain the ncRNAs. A variety of techniques known to those of ordinary skill in the art may be used for this purpose, including but not limited to: centrifugation; immunocapture; cell lysis; and, nucleic acid target capture (See, e.g., EP Pat. No. 1 409 727, herein incorporated by reference in its entirety).
The ncRNAs may be detected along with other markers in a multiplex or panel format. Markers are selected for their predictive value alone or in combination with the gene fusions. Exemplary prostate cancer markers include, but are not limited to: AMACR/P504S (U.S. Pat. No. 6,262,245); PCA3 (U.S. Pat. No. 7,008,765); PCGEM1 (U.S. Pat. No. 6,828,429); prostein/P501S, P503S, P504S, P509S, P510S, prostase/P703P, P710P (U.S. Publication No. 20030185830); RAS/KRAS (Bos, Cancer Res. 49:4682-89 (1989); Kranenburg, Biochimica et Biophysica Acta 1756:81-82 (2005)); and, those disclosed in U.S. Pat. Nos. 5,854,206 and 6,034,218, 7,229,774, each of which is herein incorporated by reference in its entirety. Markers for other cancers, diseases, infections, and metabolic conditions are also contemplated for inclusion in a multiplex or panel format.
In some embodiments, multiplex or array formats are utilized to detected multiple markers in combination. For example, in some embodiments, the level of expression of two or more (e.g., 10 or more, 25 or more, 50 or more, 100 or more or all 121) non-coding RNAs (ncRNA) selected from, for example, PCAT1, PCAT2, PCAT3, PCAT4, PCAT5, PCAT6, PCAT7, PCAT8, PCAT9, PCAT10, PCAT11, PCAT12, PCAT13, PCAT14, PCAT15, PCAT16, PCAT17, PCAT18, PCAT19, PCAT20, PCAT21, PCAT22, PCAT23, PCAT24, PCAT25, PCAT26, PCAT27, PCAT28, PCAT29, PCAT30, PCAT31, PCAT32, PCAT33, PCAT34, PCAT35, PCAT36, PCAT37, PCAT38, PCAT39, PCAT40, PCAT41, PCAT42, PCAT43, PCAT44, PCAT45, PCAT46, PCAT47, PCAT48, PCAT49, PCAT50, PCAT51, PCAT52, PCAT53, PCAT54, PCAT55, PCAT56, PCAT57, PCAT58, PCAT59, PCAT60, PCAT61, PCAT62, PCAT63, PCAT64, PCAT65, PCAT66, PCAT67, PCAT68, PCAT69, PCAT70, PCAT71, PCAT72, PCAT73, PCAT74, PCAT75, PCAT76, PCAT77, PCAT78, PCAT79, PCAT80, PCAT81, PCAT82, PCAT83, PCAT84, PCAT85, PCAT86, PCAT87, PCAT88, PCAT89, PCAT90, PCAT91, PCAT92, PCAT93, PCAT94, PCAT95, PCAT96, PCAT97, PCAT98, PCAT99, PCAT100, PCAT101, PCAT102, PCAT103, PCAT104, PCAT105, PCAT106, PCAT107, PCAT108, PCAT109, PCAT110, PCAT111, PCAT112, PCAT113, PCAT114, PCAT115, PCAT116, PCAT117, PCAT118, PCAT119, PCAT120, or PCAT121 is utilized in the research, screening, diagnostic and prognositic compositions and methods described herein.
i. DNA and RNA Detection
The ncRNAs of the present invention are detected using a variety of nucleic acid techniques known to those of ordinary skill in the art, including but not limited to: nucleic acid sequencing; nucleic acid hybridization; and, nucleic acid amplification.
1. Sequencing
Illustrative non-limiting examples of nucleic acid sequencing techniques include, but are not limited to, chain terminator (Sanger) sequencing and dye terminator sequencing. Those of ordinary skill in the art will recognize that because RNA is less stable in the cell and more prone to nuclease attack experimentally RNA is usually reverse transcribed to DNA before sequencing.
Chain terminator sequencing uses sequence-specific termination of a DNA synthesis reaction using modified nucleotide substrates. Extension is initiated at a specific site on the template DNA by using a short radioactive, or other labeled, oligonucleotide primer complementary to the template at that region. The oligonucleotide primer is extended using a DNA polymerase, standard four deoxynucleotide bases, and a low concentration of one chain terminating nucleotide, most commonly a di-deoxynucleotide. This reaction is repeated in four separate tubes with each of the bases taking turns as the di-deoxynucleotide. Limited incorporation of the chain terminating nucleotide by the DNA polymerase results in a series of related DNA fragments that are terminated only at positions where that particular di-deoxynucleotide is used. For each reaction tube, the fragments are size-separated by electrophoresis in a slab polyacrylamide gel or a capillary tube filled with a viscous polymer. The sequence is determined by reading which lane produces a visualized mark from the labeled primer as you scan from the top of the gel to the bottom.
Dye terminator sequencing alternatively labels the terminators. Complete sequencing can be performed in a single reaction by labeling each of the di-deoxynucleotide chain-terminators with a separate fluorescent dye, which fluoresces at a different wavelength.
A variety of nucleic acid sequencing methods are contemplated for use in the methods of the present disclosure including, for example, chain terminator (Sanger) sequencing, dye terminator sequencing, and high-throughput sequencing methods. Many of these sequencing methods are well known in the art. See, e.g., Sanger et al., Proc. Natl. Acad. Sci. USA 74:5463-5467 (1997); Maxam et al., Proc. Natl. Acad. Sci. USA 74:560-564 (1977); Drmanac, et al., Nat. Biotechnol. 16:54-58 (1998); Kato, Int. J. Clin. Exp. Med. 2:193-202 (2009); Ronaghi et al., Anal. Biochem. 242:84-89 (1996); Margulies et al., Nature 437:376-380 (2005); Ruparel et al., Proc. Natl. Acad. Sci. USA 102:5932-5937 (2005), and Harris et al., Science 320:106-109 (2008); Levene et al., Science 299:682-686 (2003); Korlach et al., Proc. Natl. Acad. Sci. USA 105:1176-1181 (2008); Branton et al., Nat. Biotechnol. 26(10):1146-53 (2008); Eid et al., Science 323:133-138 (2009); each of which is herein incorporated by reference in its entirety.
2. Hybridization
Illustrative non-limiting examples of nucleic acid hybridization techniques include, but are not limited to, in situ hybridization (ISH), microarray, and Southern or Northern blot. In situ hybridization (ISH) is a type of hybridization that uses a labeled complementary DNA or RNA strand as a probe to localize a specific DNA or RNA sequence in a portion or section of tissue (in situ), or, if the tissue is small enough, the entire tissue (whole mount ISH). DNA ISH can be used to determine the structure of chromosomes. RNA ISH is used to measure and localize mRNAs and other transcripts (e.g., ncRNAs) within tissue sections or whole mounts. Sample cells and tissues are usually treated to fix the target transcripts in place and to increase access of the probe. The probe hybridizes to the target sequence at elevated temperature, and then the excess probe is washed away. The probe that was labeled with either radio-, fluorescent- or antigen-labeled bases is localized and quantitated in the tissue using either autoradiography, fluorescence microscopy or immunohistochemistry, respectively. ISH can also use two or more probes, labeled with radioactivity or the other non-radioactive labels, to simultaneously detect two or more transcripts.
In some embodiments, ncRNAs are detected using fluorescence in situ hybridization (FISH). In some embodiments, FISH assays utilize bacterial artificial chromosomes (BACs). These have been used extensively in the human genome sequencing project (see Nature 409: 953-958 (2001)) and clones containing specific BACs are available through distributors that can be located through many sources, e.g., NCBI. Each BAC clone from the human genome has been given a reference name that unambiguously identifies it. These names can be used to find a corresponding GenBank sequence and to order copies of the clone from a distributor.
The present invention further provides a method of performing a FISH assay on human prostate cells, human prostate tissue or on the fluid surrounding said human prostate cells or human prostate tissue. Specific protocols are well known in the art and can be readily adapted for the present invention. Guidance regarding methodology may be obtained from many references including: In situ Hybridization: Medical Applications (eds. G. R. Coulton and J. de Belleroche), Kluwer Academic Publishers, Boston (1992); In situ Hybridization: In Neurobiology; Advances in Methodology (eds. J. H. Eberwine, K. L. Valentino, and J. D. Barchas), Oxford University Press Inc., England (1994); In situ Hybridization: A Practical Approach (ed. D. G. Wilkinson), Oxford University Press Inc., England (1992)); Kuo, et al., Am. J. Hum. Genet. 49:112-119 (1991); Klinger, et al., Am. J. Hum. Genet. 51:55-65 (1992); and Ward, et al., Am. J. Hum. Genet. 52:854-865 (1993)). There are also kits that are commercially available and that provide protocols for performing FISH assays (available from e.g., Oncor, Inc., Gaithersburg, Md.). Patents providing guidance on methodology include U.S. Pat. No. 5,225,326; 5,545,524; 6,121,489 and 6,573,043. All of these references are hereby incorporated by reference in their entirety and may be used along with similar references in the art and with the information provided in the Examples section herein to establish procedural steps convenient for a particular laboratory.
3. Microarrays
Different kinds of biological assays are called microarrays including, but not limited to: DNA microarrays (e.g., cDNA microarrays and oligonucleotide microarrays); protein microarrays; tissue microarrays; transfection or cell microarrays; chemical compound microarrays; and, antibody microarrays. A DNA microarray, commonly known as gene chip, DNA chip, or biochip, is a collection of microscopic DNA spots attached to a solid surface (e.g., glass, plastic or silicon chip) forming an array for the purpose of expression profiling or monitoring expression levels for thousands of genes simultaneously. The affixed DNA segments are known as probes, thousands of which can be used in a single DNA microarray. Microarrays can be used to identify disease genes or transcripts (e.g., ncRNAs) by comparing gene expression in disease and normal cells. Microarrays can be fabricated using a variety of technologies, including but not limiting: printing with fine-pointed pins onto glass slides; photolithography using pre-made masks; photolithography using dynamic micromirror devices; ink-jet printing; or, electrochemistry on microelectrode arrays.
Southern and Northern blotting is used to detect specific DNA or RNA sequences, respectively. DNA or RNA extracted from a sample is fragmented, electrophoretically separated on a matrix gel, and transferred to a membrane filter. The filter bound DNA or RNA is subject to hybridization with a labeled probe complementary to the sequence of interest. Hybridized probe bound to the filter is detected. A variant of the procedure is the reverse Northern blot, in which the substrate nucleic acid that is affixed to the membrane is a collection of isolated DNA fragments and the probe is RNA extracted from a tissue and labeled.
3. Amplification
Nucleic acids (e.g., ncRNAs) may be amplified prior to or simultaneous with detection. Illustrative non-limiting examples of nucleic acid amplification techniques include, but are not limited to, polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), transcription-mediated amplification (TMA), ligase chain reaction (LCR), strand displacement amplification (SDA), and nucleic acid sequence based amplification (NASBA). Those of ordinary skill in the art will recognize that certain amplification techniques (e.g., PCR) require that RNA be reversed transcribed to DNA prior to amplification (e.g., RT-PCR), whereas other amplification techniques directly amplify RNA (e.g., TMA and NASBA).
The polymerase chain reaction (U.S. Pat. Nos. 4,683,195, 4,683,202, 4,800,159 and 4,965,188, each of which is herein incorporated by reference in its entirety), commonly referred to as PCR, uses multiple cycles of denaturation, annealing of primer pairs to opposite strands, and primer extension to exponentially increase copy numbers of a target nucleic acid sequence. In a variation called RT-PCR, reverse transcriptase (RT) is used to make a complementary DNA (cDNA) from mRNA, and the cDNA is then amplified by PCR to produce multiple copies of DNA. For other various permutations of PCR see, e.g., U.S. Pat. Nos. 4,683,195, 4,683,202 and 4,800,159; Mullis et al., Meth. Enzymol. 155: 335 (1987); and, Murakawa et al., DNA 7: 287 (1988), each of which is herein incorporated by reference in its entirety.
Transcription mediated amplification (U.S. Pat. Nos. 5,480,784 and 5,399,491, each of which is herein incorporated by reference in its entirety), commonly referred to as TMA, synthesizes multiple copies of a target nucleic acid sequence autocatalytically under conditions of substantially constant temperature, ionic strength, and pH in which multiple RNA copies of the target sequence autocatalytically generate additional copies. See, e.g., U.S. Pat. Nos. 5,399,491 and 5,824,518, each of which is herein incorporated by reference in its entirety. In a variation described in U.S. Publ. No. 20060046265 (herein incorporated by reference in its entirety), TMA optionally incorporates the use of blocking moieties, terminating moieties, and other modifying moieties to improve TMA process sensitivity and accuracy.
The ligase chain reaction (Weiss, R., Science 254: 1292 (1991), herein incorporated by reference in its entirety), commonly referred to as LCR, uses two sets of complementary DNA oligonucleotides that hybridize to adjacent regions of the target nucleic acid. The DNA oligonucleotides are covalently linked by a DNA ligase in repeated cycles of thermal denaturation, hybridization and ligation to produce a detectable double-stranded ligated oligonucleotide product.
Strand displacement amplification (Walker, G. et al., Proc. Natl. Acad. Sci. USA 89: 392-396 (1992); U.S. Pat. Nos. 5,270,184 and 5,455,166, each of which is herein incorporated by reference in its entirety), commonly referred to as SDA, uses cycles of annealing pairs of primer sequences to opposite strands of a target sequence, primer extension in the presence of a dNTPaS to produce a duplex hemiphosphorothioated primer extension product, endonuclease-mediated nicking of a hemimodified restriction endonuclease recognition site, and polymerase-mediated primer extension from the 3′ end of the nick to displace an existing strand and produce a strand for the next round of primer annealing, nicking and strand displacement, resulting in geometric amplification of product. Thermophilic SDA (tSDA) uses thermophilic endonucleases and polymerases at higher temperatures in essentially the same method (EP Pat. No. 0 684 315).
Other amplification methods include, for example: nucleic acid sequence based amplification (U.S. Pat. No. 5,130,238, herein incorporated by reference in its entirety), commonly referred to as NASBA; one that uses an RNA replicase to amplify the probe molecule itself (Lizardi et al., BioTechnol. 6: 1197 (1988), herein incorporated by reference in its entirety), commonly referred to as Qβ replicase; a transcription based amplification method (Kwoh et al., Proc. Natl. Acad. Sci. USA 86:1173 (1989)); and, self-sustained sequence replication (Guatelli et al., Proc. Natl. Acad. Sci. USA 87: 1874 (1990), each of which is herein incorporated by reference in its entirety). For further discussion of known amplification methods see Persing, David H., “In Vitro Nucleic Acid Amplification Techniques” in Diagnostic Medical Microbiology: Principles and Applications (Persing et al., Eds.), pp. 51-87 (American Society for Microbiology, Washington, D.C. (1993)).
4. Detection Methods
Non-amplified or amplified nucleic acids can be detected by any conventional means. For example, the ncRNAs can be detected by hybridization with a detectably labeled probe and measurement of the resulting hybrids. Illustrative non-limiting examples of detection methods are described below.
One illustrative detection method, the Hybridization Protection Assay (HPA) involves hybridizing a chemiluminescent oligonucleotide probe (e.g., an acridinium ester-labeled (AE) probe) to the target sequence, selectively hydrolyzing the chemiluminescent label present on unhybridized probe, and measuring the chemiluminescence produced from the remaining probe in a luminometer. See, e.g., U.S. Pat. No. 5,283,174 and Norman C. Nelson et al., Nonisotopic Probing, Blotting, and Sequencing, ch. 17 (Larry J. Kricka ed., 2d ed. 1995, each of which is herein incorporated by reference in its entirety).
Another illustrative detection method provides for quantitative evaluation of the amplification process in real-time. Evaluation of an amplification process in “real-time” involves determining the amount of amplicon in the reaction mixture either continuously or periodically during the amplification reaction, and using the determined values to calculate the amount of target sequence initially present in the sample. A variety of methods for determining the amount of initial target sequence present in a sample based on real-time amplification are well known in the art. These include methods disclosed in U.S. Pat. Nos. 6,303,305 and 6,541,205, each of which is herein incorporated by reference in its entirety. Another method for determining the quantity of target sequence initially present in a sample, but which is not based on a real-time amplification, is disclosed in U.S. Pat. No. 5,710,029, herein incorporated by reference in its entirety.
Amplification products may be detected in real-time through the use of various self-hybridizing probes, most of which have a stem-loop structure. Such self-hybridizing probes are labeled so that they emit differently detectable signals, depending on whether the probes are in a self-hybridized state or an altered state through hybridization to a target sequence. By way of non-limiting example, “molecular torches” are a type of self-hybridizing probe that includes distinct regions of self-complementarity (referred to as “the target binding domain” and “the target closing domain”) which are connected by a joining region (e.g., non-nucleotide linker) and which hybridize to each other under predetermined hybridization assay conditions. In a preferred embodiment, molecular torches contain single-stranded base regions in the target binding domain that are from 1 to about 20 bases in length and are accessible for hybridization to a target sequence present in an amplification reaction under strand displacement conditions. Under strand displacement conditions, hybridization of the two complementary regions, which may be fully or partially complementary, of the molecular torch is favored, except in the presence of the target sequence, which will bind to the single-stranded region present in the target binding domain and displace all or a portion of the target closing domain. The target binding domain and the target closing domain of a molecular torch include a detectable label or a pair of interacting labels (e.g., luminescent/quencher) positioned so that a different signal is produced when the molecular torch is self-hybridized than when the molecular torch is hybridized to the target sequence, thereby permitting detection of probe:target duplexes in a test sample in the presence of unhybridized molecular torches. Molecular torches and a variety of types of interacting label pairs are disclosed in U.S. Pat. No. 6,534,274, herein incorporated by reference in its entirety.
Another example of a detection probe having self-complementarity is a “molecular beacon.” Molecular beacons include nucleic acid molecules having a target complementary sequence, an affinity pair (or nucleic acid arms) holding the probe in a closed conformation in the absence of a target sequence present in an amplification reaction, and a label pair that interacts when the probe is in a closed conformation. Hybridization of the target sequence and the target complementary sequence separates the members of the affinity pair, thereby shifting the probe to an open conformation. The shift to the open conformation is detectable due to reduced interaction of the label pair, which may be, for example, a fluorophore and a quencher (e.g., DABCYL and EDANS). Molecular beacons are disclosed in U.S. Pat. Nos. 5,925,517 and 6,150,097, herein incorporated by reference in its entirety.
Other self-hybridizing probes are well known to those of ordinary skill in the art. By way of non-limiting example, probe binding pairs having interacting labels, such as those disclosed in U.S. Pat. No. 5,928,862 (herein incorporated by reference in its entirety) might be adapted for use in the present invention. Probe systems used to detect single nucleotide polymorphisms (SNPs) might also be utilized in the present invention. Additional detection systems include “molecular switches,” as disclosed in U.S. Publ. No. 20050042638, herein incorporated by reference in its entirety. Other probes, such as those comprising intercalating dyes and/or fluorochromes, are also useful for detection of amplification products in the present invention. See, e.g., U.S. Pat. No. 5,814,447 (herein incorporated by reference in its entirety).
ii. Data Analysis
In some embodiments, a computer-based analysis program is used to translate the raw data generated by the detection assay (e.g., the presence, absence, or amount of a given marker or markers) into data of predictive value for a clinician. The clinician can access the predictive data using any suitable means. Thus, in some preferred embodiments, the present invention provides the further benefit that the clinician, who is not likely to be trained in genetics or molecular biology, need not understand the raw data. The data is presented directly to the clinician in its most useful form. The clinician is then able to immediately utilize the information in order to optimize the care of the subject.
The present invention contemplates any method capable of receiving, processing, and transmitting the information to and from laboratories conducting the assays, information provides, medical personal, and subjects. For example, in some embodiments of the present invention, a sample (e.g., a biopsy or a serum or urine sample) is obtained from a subject and submitted to a profiling service (e.g., clinical lab at a medical facility, genomic profiling business, etc.), located in any part of the world (e.g., in a country different than the country where the subject resides or where the information is ultimately used) to generate raw data. Where the sample comprises a tissue or other biological sample, the subject may visit a medical center to have the sample obtained and sent to the profiling center, or subjects may collect the sample themselves (e.g., a urine sample) and directly send it to a profiling center. Where the sample comprises previously determined biological information, the information may be directly sent to the profiling service by the subject (e.g., an information card containing the information may be scanned by a computer and the data transmitted to a computer of the profiling center using an electronic communication systems). Once received by the profiling service, the sample is processed and a profile is produced (i.e., expression data), specific for the diagnostic or prognostic information desired for the subject.
The profile data is then prepared in a format suitable for interpretation by a treating clinician. For example, rather than providing raw expression data, the prepared format may represent a diagnosis or risk assessment (e.g., presence or absence of a ncRNA) for the subject, along with recommendations for particular treatment options. The data may be displayed to the clinician by any suitable method. For example, in some embodiments, the profiling service generates a report that can be printed for the clinician (e.g., at the point of care) or displayed to the clinician on a computer monitor.
In some embodiments, the information is first analyzed at the point of care or at a regional facility. The raw data is then sent to a central processing facility for further analysis and/or to convert the raw data to information useful for a clinician or patient. The central processing facility provides the advantage of privacy (all data is stored in a central facility with uniform security protocols), speed, and uniformity of data analysis. The central processing facility can then control the fate of the data following treatment of the subject. For example, using an electronic communication system, the central facility can provide data to the clinician, the subject, or researchers.
In some embodiments, the subject is able to directly access the data using the electronic communication system. The subject may chose further intervention or counseling based on the results. In some embodiments, the data is used for research use. For example, the data may be used to further optimize the inclusion or elimination of markers as useful indicators of a particular condition or stage of disease or as a companion diagnostic to determine a treatment course of action.
iiii. In Vivo Imaging
ncRNAs may also be detected using in vivo imaging techniques, including but not limited to: radionuclide imaging; positron emission tomography (PET); computerized axial tomography, X-ray or magnetic resonance imaging method, fluorescence detection, and chemiluminescent detection. In some embodiments, in vivo imaging techniques are used to visualize the presence of or expression of cancer markers in an animal (e.g., a human or non-human mammal). For example, in some embodiments, cancer marker mRNA or protein is labeled using a labeled antibody specific for the cancer marker. A specifically bound and labeled antibody can be detected in an individual using an in vivo imaging method, including, but not limited to, radionuclide imaging, positron emission tomography, computerized axial tomography, X-ray or magnetic resonance imaging method, fluorescence detection, and chemiluminescent detection. Methods for generating antibodies to the cancer markers of the present invention are described below.
The in vivo imaging methods of embodiments of the present invention are useful in the identification of cancers that express ncRNAs (e.g., prostate cancer). In vivo imaging is used to visualize the presence or level of expression of a ncRNA. Such techniques allow for diagnosis without the use of an unpleasant biopsy. The in vivo imaging methods of embodiments of the present invention can further be used to detect metastatic cancers in other parts of the body.
In some embodiments, reagents (e.g., antibodies) specific for the cancer markers of the present invention are fluorescently labeled. The labeled antibodies are introduced into a subject (e.g., orally or parenterally). Fluorescently labeled antibodies are detected using any suitable method (e.g., using the apparatus described in U.S. Pat. No. 6,198,107, herein incorporated by reference).
In other embodiments, antibodies are radioactively labeled. The use of antibodies for in vivo diagnosis is well known in the art. Sumerdon et al., (Nucl. Med. Biol 17:247-254 [1990] have described an optimized antibody-chelator for the radioimmunoscintographic imaging of tumors using Indium-111 as the label. Griffin et al., (J Clin Onc 9:631-640 [1991]) have described the use of this agent in detecting tumors in patients suspected of having recurrent colorectal cancer. The use of similar agents with paramagnetic ions as labels for magnetic resonance imaging is known in the art (Lauffer, Magnetic Resonance in Medicine 22:339-342 [1991]). The label used will depend on the imaging modality chosen. Radioactive labels such as Indium-111, Technetium-99m, or Iodine-131 can be used for planar scans or single photon emission computed tomography (SPECT). Positron emitting labels such as Fluorine-19 can also be used for positron emission tomography (PET). For MRI, paramagnetic ions such as Gadolinium (III) or Manganese (II) can be used.
Radioactive metals with half-lives ranging from 1 hour to 3.5 days are available for conjugation to antibodies, such as scandium-47 (3.5 days) gallium-67 (2.8 days), gallium-68 (68 minutes), technetiium-99m (6 hours), and indium-111 (3.2 days), of which gallium-67, technetium-99m, and indium-111 are preferable for gamma camera imaging, gallium-68 is preferable for positron emission tomography.
A useful method of labeling antibodies with such radiometals is by means of a bifunctional chelating agent, such as diethylenetriaminepentaacetic acid (DTPA), as described, for example, by Khaw et al. (Science 209:295 [1980]) for In-111 and Tc-99m, and by Scheinberg et al. (Science 215:1511 [1982]). Other chelating agents may also be used, but the 1-(p-carboxymethoxybenzyl)EDTA and the carboxycarbonic anhydride of DTPA are advantageous because their use permits conjugation without affecting the antibody's immunoreactivity substantially.
Another method for coupling DPTA to proteins is by use of the cyclic anhydride of DTPA, as described by Hnatowich et al. (Int. J. Appl. Radiat. Isot. 33:327 [1982]) for labeling of albumin with In-111, but which can be adapted for labeling of antibodies. A suitable method of labeling antibodies with Tc-99m which does not use chelation with DPTA is the pretinning method of Crockford et al., (U.S. Pat. No. 4,323,546, herein incorporated by reference).
A method of labeling immunoglobulins with Tc-99m is that described by Wong et al. (Int. J. Appl. Radiat. Isot., 29:251 [1978]) for plasma protein, and recently applied successfully by Wong et al. (J. Nucl. Med., 23:229 [1981]) for labeling antibodies.
In the case of the radiometals conjugated to the specific antibody, it is likewise desirable to introduce as high a proportion of the radiolabel as possible into the antibody molecule without destroying its immunospecificity. A further improvement may be achieved by effecting radiolabeling in the presence of the ncRNA, to insure that the antigen binding site on the antibody will be protected. The antigen is separated after labeling.
In still further embodiments, in vivo biophotonic imaging (Xenogen, Almeda, Calif.) is utilized for in vivo imaging. This real-time in vivo imaging utilizes luciferase. The luciferase gene is incorporated into cells, microorganisms, and animals (e.g., as a fusion protein with a cancer marker of the present invention). When active, it leads to a reaction that emits light. A CCD camera and software is used to capture the image and analyze it.
iv. Compositions & Kits
Compositions for use in the diagnostic methods described herein include, but are not limited to, probes, amplification oligonucleotides, and the like.
The probe and antibody compositions of the present invention may also be provided in the form of an array.
II. Drug Screening Applications In some embodiments, the present invention provides drug screening assays (e.g., to screen for anticancer drugs). The screening methods of the present invention utilize ncRNAs. For example, in some embodiments, the present invention provides methods of screening for compounds that alter (e.g., decrease) the expression or activity of ncRNAs. The compounds or agents may interfere with transcription, by interacting, for example, with the promoter region. The compounds or agents may interfere with mRNA (e.g., by RNA interference, antisense technologies, etc.). The compounds or agents may interfere with pathways that are upstream or downstream of the biological activity of ncRNAs. In some embodiments, candidate compounds are antisense or interfering RNA agents (e.g., oligonucleotides) directed against ncRNAs. In other embodiments, candidate compounds are antibodies or small molecules that specifically bind to a ncRNAs regulator or expression products inhibit its biological function.
In one screening method, candidate compounds are evaluated for their ability to alter ncRNAs expression by contacting a compound with a cell expressing a ncRNA and then assaying for the effect of the candidate compounds on expression. In some embodiments, the effect of candidate compounds on expression of ncRNAs is assayed for by detecting the level ncRNA expressed by the cell. mRNA expression can be detected by any suitable method.
EXPERIMENTAL The following examples are provided in order to demonstrate and further illustrate certain preferred embodiments and aspects of the present invention and are not to be construed as limiting the scope thereof.
Example 1 A. Methods Methods Summary
All prostate tissue samples were obtained from the University of Michigan Specialized Program Of Research Excellence (S.P.O.R.E.) using an IRB-approved informed consent protocol. Next generation sequencing and library preparation was performed as previously described (Maher et al., Proc Natl Acad Sci USA 106 (30), 12353 (2009)). Uniquely mapping sequencing reads were aligned with TopHat and sequencing data for all samples was merged. Ab initio transcriptome assembly was performed by aligning sequences with TopHat and using uniquely mapped read positions to build transcripts with Cufflinks. Informatics approaches were used to refine the assembly and predict expressed transcriptional units. Unannotated transcripts were nominated based upon their absence in the UCSC, RefSeq, ENSEMBL, ENCODE, and Vega databases. Differential expression was determined using the Significance Analysis of Microarrays (SAM) algorithm (Tusher et al., Proc Natl Acad Sci USA 98 (9), 5116 (2001)) on log 2 mean expression in benign, cancer, and metastatic samples. Cancer outlier profile analysis (COPA) was performed as previously described (Tomlins et al., Science 310 (5748), 644 (2005)) with slight modifications. PCR experiments were performed according to standard protocols, and RACE was performed with the GeneRacer Kit (Invitrogen) according to manufacturer's instructions. ChIP-seq data was obtained from previously published data (Yu et al., Cancer Cell 17 (5), 443). siRNA knockdown was performed with custom siRNA oligos (Dharmacon) with Oligofectamine (Invitrogen). Transmembrane invasion assays were performed with Matrigel (BD Biosciences) and cell proliferation assays were performed by cell count with a Coulter counter. Urine analyses were performed as previously described (Laxman et al., Cancer Res 68 (3), 645 (2008)) with minor modifications.
Cell Lines and Tissues
The benign immortalized prostate cell line RWPE as well as PC3, Du145, LNCaP, VCaP, 22Rv1, CWR22, C4-2B, NCI-660, MDA PCa 2b, WPMY-1, and LAPC-4 prostate cell lines were obtained from the American Type Culture Collection (Manassas, Va.). Benign non-immortalized prostate epithelial cells (PrEC) and prostate smooth muscle cells (PrSMC) were obtained from Lonza (Basel, Switzerland). Cell lines were maintained using standard media and conditions. For androgen treatment experiments, LNCaP and VCaP cells were grown in androgen depleted media lacking phenol red and supplemented with 10% charcoal-stripped serum and 1% penicillin-streptomycin. After 48 hours, cells were treated with 5 nM methyltrienolone (R1881, NEN Life Science Products) or an equivalent volume of ethanol. Cells were harvested for RNA at 6, 24, and 48 hours post-treatment. Prostate tissues were obtained from the radical prostatectomy series and Rapid Autopsy Program at the University of Michigan tissue core. These programs are part of the University of Michigan Prostate Cancer Specialized Program Of Research Excellence (S.P.O.R.E.). All tissue samples were collected with informed consent under an Institutional Review Board (IRB) approved protocol at the University of Michigan.
PC3, Du145, LNCaP, 22Rv1, and CRW22 cells were grown in RPMI 1640 (Invitrogen) and supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin. LNCaP CDS parent cells were grown in RPMI 1640 lacking phenol red (Invitrogen) supplemented with 10% charcoal-dextran stripped FBS (Invitrogen) and 1% penicillin-streptomycin. LNCaP CDS 1, 2, and 3 are androgen-independent subclones derived from extended cell culture in androgendepleted media. VCaP and WPMY-1 cells were grown in DMEM (Invitrogen) and supplemented with 10% fetal bovine serum (FBS) with 1% penicillin-streptomycin. NCI-H660 cells were grown in RPMI 1640 supplemented with 0.005 mg/ml insulin, 0.01 mg/ml transferring, 30 nM sodium selenite, 10 nM hydrocortisone, 10 nM beta-estradiol, 5% FBS and an extra 2 mM of L-glutamine (for a final concentration of 4 mM). MDA PCa 2b cells were grown in F-12K medium (Invitrogen) supplemented with 20% FBS, 25 ng/ml cholera toxin, 10 ng/ml EGF, 0.005 mM phosphoethanolamine, 100 pg/ml hydrocortisone, 45 nM selenious acid, and 0.005 mg/ml insulin. LAPC-4 cells were grown in Iscove's media (Invitrogen) supplemented with 10% FBS and 1 nM R1881. C4-2B cells were grown in 80% DMEM supplemented with 20% F12, 5% FBS, 3 g/L NaCo3, 5 μg/ml insulin, 13.6 pg/ml triiodothyonine, 5 μg/ml transferrin, 0.25 μg/ml biotin, and 25 μg/ml adenine. PrEC cells were grown in PrEGM supplemented with 2 ml BPE, 0.5 ml hydrocortisone, 0.5 ml EGF, 0.5 ml epinephrine, 0.5 ml transferring, 0.5 ml insulin, 0.5 ml retinoic acid, and 0.5 ml triiodothyronine, as part of the PrEGM BulletKit (Lonza). PrSMC cells were grown in SmGM-2 media supplemented with 2 ml BPE, 0.5 ml hydrocortisone, 0.5 ml EGF, 0.5 ml epinephrine, 0.5 ml transferring, 0.5 ml insulin, 0.5 ml retinoic acid, and 0.5 ml triiodothyronine, as part of the SmGM-2 BulletKit (Lonza).
RNA-Seq Library Preparation.
Next generation sequencing of RNA was performed on 21 prostate cell lines, 20 benign adjacent prostates, 47 localized tumors, and 14 metastatic tumors according to Illumina's protocol using 2 μg of RNA. RNA integrity was measured using an Agilent 2100 Bioanalyzer, and only samples with a RIN score >7.0 were advanced for library generation. RNA was poly-A+ selected using the OligodT beads provided by Ilumina and fragmented with the Ambion Fragmentation Reagents kit (Ambion, Austin, Tex.). cDNA synthesis, end-repair, A-base addition, and ligation of the Illumina PCR adaptors (single read or paired-end where appropriate) were performed according to Illumina's protocol. Libraries were then size-selected for 250-300 bp cDNA fragments on a 3.5% agarose gel and PCR-amplified using Phusion DNA polymerase (Finnzymes) for 15-18 PCR cycles. PCR products were then purified on a 2% agarose gel and gel-extracted. Library quality was credentialed by assaying each library on an Agilent 2100 Bioanalyzer of product size and concentration. Libraries were sequenced as 36-45mers on an Illumina Genome Analyzer I or Genome Analyzer II flowcell according to Illumina's protocol. All single read samples were sequenced on a Genome Analyzer I, and all paired-end samples were sequenced on a Genome Analyzer II.
RNA Isolation and cDNA Synthesis
Total RNA was isolated using Trizol and an RNeasy Kit (Invitrogen) with DNase I digestion according to the manufacturer's instructions. RNA integrity was verified on an Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, Calif.). cDNA was synthesized from total RNA using Superscript III (Invitrogen) and random primers (Invitrogen).
Quantitative Real-Time PCR
Quantitative Real-time PCR (qPCR) was performed using Power SYBR Green Mastermix (Applied Biosystems, Foster City, Calif.) on an Applied Biosystems 7900HT Real-Time PCR System. All oligonucleotide primers were obtained from Integrated DNA Technologies (Coralville, Iowa) and are listed in Table 13. The housekeeping gene, GAPDH, was used as a loading control. Fold changes were calculated relative to GAPDH and normalized to the median value of the benign samples.
Reverse-Transcription PCR
Reverse-transcription PCR (RT-PCR) was performed for primer pairs using Platinum Taq High Fidelity polymerase (Invitrogen). PCR products were resolved on a 2% agarose gel. PCR products were either sequenced directly (if only a single product was observed) or appropriate gel products were extracted using a Gel Extraction kit (Qiagen) and cloned into pcr4-TOPO vectors (Invitrogen). PCR products were bidirectionally sequenced at the University of Michigan Sequencing Core using either gene-specific primers or M13 forward and reverse primers for cloned PCR products. All oligonucleotide primers were obtained from Integrated DNA Technologies (Coralville, Iowa) and are listed in Table 13.
RNA-Ligase-Mediated Rapid Amplification of cDNA Ends (RACE)
5′ and 3′ RACE was performed using the GeneRacer RLM-RACE kit (Invitrogen) according to the manufacturer's instructions. RACE PCR products were obtained using Platinum Taq High Fidelity polymerase (Invitrogen), the supplied GeneRacer primers, and appropriate gene-specific primers indicated in Table 13. RACEPCR products were separated on a 2% agarose gels. Gel products were extracted with a Gel Extraction kit (Qiagen), cloned into pcr4-TOPO vectors (Invitrogen), and sequenced bidirectionally using M13 forward and reverse primers at the University of Michigan Sequencing Core. At least three colonies were sequenced for every gel product that was purified.
Paired-End Next-Generation Sequencing of RNA
2 μg total RNA was selected for polyA+RNA using Sera-Mag oligo(dT) beads (Thermo Scientific), and paired-end next-generation sequencing libraries were prepared as previously described (Maher et al., supra) using Illumina-supplied universal adaptor oligos and PCR primers (Illumina). Samples were sequenced in a single lane on an Illumina Genome Analyzer II flowcell using previously described protocols (Maher et al., supra). 36-45 mer paired-end reads were according to the protocol provided by Illumina.
siRNA Knockdown Studies
Cells were plated in 100 mM plates at a desired concentration and transfected with 20 μM experimental siRNA oligos or non-targeting controls twice, at 12 hours and 36 hours post-plating. Knockdowns were performed with Oligofectamine and Optimem. Knockdown efficiency was determined by qPCR. 72 hours post-transfection, cells were trypsinized, counted with a Coulter counter, and diluted to 1 million cells/mL. For proliferation assays, 200,000 cells were plated in 24-well plates and grown in regular media. 48 and 96 hours post-plating, cells were harvested and counted using a Coulter counter. For invasion assays, Matrigel was diluted 1:4 in serum-free media and 100 μL of the diluted Matrigel was applied to a Boyden chamber transmembrane insert and allowed to settle overnight at 37° C. 200,000 cells suspended in serum-free media were applied per insert and 500 μL of serum-containing media was placed in the bottom of the Boyden (fetal bovine serum functioning as a chemoattractant). Cells were allowed to invade for 48 hours, at which time inserts were removed and noninvading cells and Matrigel were gently removed with a cotton swab. Invading cells were stained with crystal violet for 15 minutes and air-dried. For colorimetric assays, the inserts were treated with 200 μl of 10% acetic acid and the absorbance at 560 nm was measured using a spectrophotometer. For WST-1 assays, 20,000 cells were plated into 96-well plates and grown in 100 μL of serum-containing media. 48 and 96 hours post-plating, cells were measured for viability by adding 10 μL of WST-1 reagent to the cell media, incubating for 2 hours at 37° C. and measuring the absorbance at 450 nM using a spectrophotomer.
Urine qPCR
Urine samples were collected from 120 patients with informed consent following a digital rectal exam before either needle biopsy or radical prostatectomy at the University of Michigan with Institutional Review Board approval as described previously (Laxman et al., Cancer Res 68 (3), 645 (2008)). Isolation of RNA from urine and TransPlex whole transcriptome amplification were performed as described previously (Laxman et al., Neoplasia 8 (10), 885 (2006)). qPCR on urine samples was performed for KLK3 (PSA), TMPRSS2-ERG, GAPDH, PCA3, PCAT-1 and PCAT-14 using Power SYBR Mastermix (Applied Biosystems) as described above. Raw Ct values were extracted and normalized in the following manner. First, samples with GAPDH Ct values >25 or KLK3 Ct values >30 were removed from analysis to ensure sufficient prostate cell collection, leaving 108 samples for analysis. The GAPDH and KLK3 raw Ct values were average for each sample. ΔCt analysis was performed by measuring each value against the average of CtGAPDH and CtKLK3, and ΔCt values were normalized to the median ΔCt of the benign samples. Fold change was then calculated at 2-ΔCt. Samples were considered to be prostate cancer if histopathological analysis observed cancer or if the TMPRSS2-ERG transcript achieved a Ct value <37. Benign samples were defined as samples with normal histology and TMPRSS2-ERG transcript Ct values >37.
Statistical Analyses for Experimental Studies
All data are presented as means±s.e.m. All experimental assays were performed in duplicate or triplicate.
Bioinformatics Analyses
To achieve an ab initio prediction of the prostate cancer transcriptome existing publicly tools for mapping, assembly, and quantification of transcripts were supplemented with additional informatics filtering steps to enrich the results for the most robust transcript predictions (FIG. 6a). Transcripts were then identified and classified by comparing them against gene annotation databases (FIG. 6b). Details of the bioinformatics analyses are provided below.
Mapping Reads with TopHat
Reads were aligned using TopHat v1.0.13 (Feb. 5, 2010) (Trapnell et al., Bioinformatics 25, 1105-11 (2009)), a gapped aligner capable of discovering splice junctions ab initio. Briefly, TopHat aligns reads to the human genome using Bowtie (Langmead et al., Genome Biol 10, R25 (2009)) to determine a set of “coverage islands” that may represent putative exons. TopHat uses these exons as well as the presence of GT-AG genomic splicing motifs to build a second set of reference sequences spanning exon-exon junctions. The unmapped reads from the initial genome alignment step are then remapped against this splice junction reference to discover all the junction-spanning reads in the sample. TopHat outputs the reads that successfully map to either the genome or the splice junction reference in SAM format for further analysis. For this study a maximum intron size of 500 kb, corresponding to over 99.98% of RefSeq (Wheeler et al. Nucleic Acids Res 28, 10-4 (2000)) introns was used. For sequencing libraries the insert size was determined using an Agilent 2100 Bioanalyzer prior to data analysis, and it was found that this insert size agreed closely with software predictions. An insert size standard deviation of 20 bases was chosen in order to match the most common band size cut from gels during library preparation. In total, 1.723 billion fragments were generated from 201 lanes of sequencing on the Illumina Genome Analyzer and Illumina Genome Analyzer II. Reads were mapped to the human genome (hg18) downloaded from the UCSC genome browser website (Karolchik et al., Nucleic Acids Res 31, 51-4 (2003); Kent et al., Genome Res 12, 996-1006 (2002)). 1.418 billion unique alignments were obtained, including 114.4 million splice junctions for use in transcriptome assembly. Reads with multiple alignments with less than two mismatches were discarded.
Ab Initio Assembly and Quantification with Cufflinks
Aligned reads from TopHat were assembled into sample-specific transcriptomes with Cufflinks version 0.8.2 (Mar. 26, 2010) (Trapnell et al., Nat Biotechnol 28, 511-5). Cufflinks assembles exonic and splice-junction reads into transcripts using their alignment coordinates. To limit false positive assemblies a maximum intronic length of 300 kb, corresponding to the 99.93% percentile of known introns was used. After assembling transcripts, Cufflinks computes isoform-level abundances by finding a parsimonious allocation of reads to the transcripts within a locus. Transcripts with abundance less than 15% of the major transcript in the locus, and minor isoforms with abundance less than 5% of the major isoform were filtered. Default settings were used for the remaining parameters.
The Cufflinks assembly stage yielded a set of transcript annotations for each of the sequenced libraries. The transcripts were partitioned by chromosome and the Cuffcompare utility provided by Cufflinks was used to merge the transcripts into a combined set of annotations. The Cuffcompare program performs a union of all transcripts by merging transcripts that share all introns and exons. The 5′ and 3′ exons of transcripts were allowed to vary by up to 100 nt during the comparison process.
Distinguishing Transcripts from Background Signal
Cuffcompare reported a total of 8.25 million distinct transcripts. Manual inspection of these transcripts in known protein coding gene regions indicated that most of the transcripts were likely to be poor quality reconstructions of overlapping larger transcripts. Also, many of the transcripts were unspliced and had a total length smaller than the size selected fragment length of approximately ˜250 nt. Furthermore, many of these transcripts were only present in a single sample. A statistical classifier to predict transcripts over background signal was designed to identify highly recurrent transcripts that may be altered in prostate cancer. AceView (Thierry-Mieg et al. Genome Biol 7 Suppl 1, S12 1-14 (2006)) were used. For each transcript predicted by Cufflinks the following statistics were collected: length (bp), number of exons, recurrence (number of samples in which the transcript was predicted), 95th percentile of abundance (measured in Fragments per Kilobase per Million reads (FPKM)) across all samples, and uniqueness of genomic DNA harboring the transcript transcript (measured using the Rosetta uniqueness track from UCSC (Rhead et al. 2010. Nucleic Acids Res 38, D613-9). Using this information, recursive partitioning and regression trees in R (package rpart) were used to predict, for each transcript, whether its expression patterns and structural properties resembled those of annotated genes. Classification was performed independently for each chromosome in order to incorporate the effect of gene density variability on expression thresholds. Transcripts that were not classified as annotated genes were discarded, and the remainder were subjected to additional analysis and filtering steps. By examining the decision tree results it was observed that the 95th percentile of expression across all samples as well as the recurrence of each transcript were most frequently the best predictors of expressed versus background transcripts (FIG. 7).
Refinement of Transcript Fragments
The statistical classifier predicted a total 2.88 million (34.9%) transcript fragments as “expressed” transcripts. A program was developed to extend and merge intron-redundant transcripts to produce a minimum set of transcripts that describes the assemblies produced by Cufflinks. The merging step produced a total of 123,554 independent transcripts. Tanscript abundance levels were re-computed for these revised transcripts in Reads per Kilobase per Million (RPKM) units. These expression levels were used for the remainder of the study. Several additional filtering steps were used to isolate the most robust transcripts. First, transcripts with a total length less than 200 nt were discarded. Single exon transcripts with greater than 75% overlap to another longer transcript were also discarded. Transcripts that lacked a completely unambiguous genomic DNA stretch of at least 40 nt were also removed. Genomic uniqueness was measured using the Rosetta uniqueness track downloaded from the UCSC genome browser website. Transcripts that were not present in at least 5% of the cohort (>5 samples) at more than 5.0 RPKM were retained.
In certain instances transcripts were observed that were interrupted by poorly mappable genomic regions. Additionally, for low abundance genes fragmentation due to the lack of splice junction or paired-end read evidence needed to connect nearby fragments were observed. The difference in the Pearson correlation between expression of randomly chosen exons on the same transcript versus expression of spatially proximal exons on different transcripts was measured and it was found that in the cohort, a Pearson correlation >0.8 had a positive predictive value (PPV) of >95% for distinct exons to be part of the same transcript. Using this criteria, hierarchical agglomerative clustering to extend transcript fragments into larger transcriptional units was performed. Pairs of transcripts further than 100 kb apart, transcripts on opposite strands, and overlapping transcripts were not considered for clustering. Groups of correlated transcripts were merged, and introns <40 nt in length were removed.
Comparison with Gene Annotation Databases
The 44,534 transcripts produced by the bioinformatics pipeline were classified by comparison with a comprehensive list of “annotated” transcripts from UCSC, RefSeq, ENCODE, Vega, and Ensembl. First, transcripts corresponding to processed pseudogenes were separated. This was done to circumvent a known source of bias in the TopHat read aligner. TopHat maps reads to genomic DNA in its first step, predisposing exon-exon junction reads to align to their spliced retroposed pseudogene homologues. Next, transcripts with >1 bp of overlap with at least one annotated gene on the correct strand were designated “annotated”, and the remainder were deemed “unannotated”. Transcripts with no overlap with protein coding genes were subdivided into intronic, intergenic, or partially intronic antisense categories based on their relative genomic locations.
Informatics Filtering of Unspliced Pre-mRNA Isoforms
An increase in the percentage of intronic transcripts in the assembly relative to known intronic ncRNAs was observed. This led to the observation that in many cases unspliced pre mRNAs appear at sufficient levels to escape the filtering steps employed by Cufflinks during the assembly stage. Intronic and antisense transcripts that were correlated (Pearson correlation >0.5) to their overlapping protein coding genes were removed. This effectively removed transcripts within genes such as PCA3 and HPN that were obvious premRNA artifacts, while leaving truly novel intronic transcripts—such as those within FBXL7 and CDH13—intact. These steps produced a consensus set of 35,415 transcripts supporting long polyadenylated RNA molecules in human prostate tissues and cell lines. Per chromosome transcript counts closely mirrored known transcript databases (Table 2), indicating that the informatics procedures employed compensate well for gene density variability across chromosomes. Overall a similar number of transcripts as present in the either the RefSeq or UCSC databases (Wheeler et al. Nucleic Acids Res 28, 10-4 (2000)) were detected.
Coding Potential Analysis
To analyze coding potential, DNA sequences for each transcript were extracted and searched for open reading frames (ORFs) using the txCdsPredict program from the UCSC source tool set (Kent et al. Genome Res 12, 996-1006 (2002)). This program produces a score corresponding to the protein coding capacity of a given sequence, and scores >800 are ˜90% predictive of protein coding genes. This threshold was used to count transcripts with coding potential, and found only 5 of 6,641 unannotated genes with scores >800, compared with 1,669 of 25,414 protein coding transcripts. Additionally, it was observed that protein coding genes possess consistently longer ORFs than either unannotated or annotated ncRNA transcripts, indicating that the vast majority of the unannotated transcripts represent ncRNAs (FIG. 10).
Separation of Transcripts into Repetitive and Non-Repetitive Categories
To separate transcripts into “repeat” and “non-repeat” transcripts, the genomic DNA corresponding to the transcript exons was extracted and the fraction of repeat-masked nucleotides in each sequence were calculated. For the designation of repeat classes, RepMask 3.2.7 UCSC Genome Browser track (Kent, supra) was used. It was observed that transcripts enriched with repetitive DNA tended to be poorly conserved and lacked ChIP-seq marks of active chromatin (FIG. 12). Transcripts containing >25% repetitive DNA (FIG. 11) were separated for the purposes of the ChIP-seq and conservation analyses discussed below.
Conservation Analysis
The SiPhy package (Garber et al. Bioinformatics 25, i54-62 (2009)) was used to estimate the locate rate of variation (w) of all non-repetitive transcript exons across 29 placental mammals. The program was run as described on the SiPhy website.
ChIP-Seq Datasets
Published ChIP-Seq datasets for H3K4me1, H3K4me2, H3K4me3, Acetylated H3, Pan-H3, and H3K36me3 were used (Yu et al. Cancer Cell 17, 443-54). These data are publically available through the NCBI Geo Omnibus (GEO GSM353632). The raw ChIP-Seq data was analyzed using MACS34 (H3K4me1, H3K4me2, H3K4me3, Acetylated H3, and Pan-H3) or SICER35 (H3K36me3) peak finder programs using default settings. These peak finders were used based upon their preferential suitability to detect different types of histone modifications (Pepke et al., Nat Methods 6, S22-32 (2009)). The H3K4me3-H3K36me3 chromatin signature used to identify lincRNAs was determined from the peak coordinates by associating each H3K4me3 peak with the closest H3K36me3-enriched region up to a maximum of 10 kb away. The enhancer signature (H3K4me1 but not H3K4me3) was determined by subtracting the set of overlapping H3K4me3 peaks from the entire set of H3K4me1 peaks. These analyses were performed with the bx-python libraries distributed as part of the Galaxy bioinformatics infrastructure.
Differential Expression Analysis
To predict differentially expressed transcripts a matrix of log-transformed, normalized RPKM expression values was prepared by using the base 2 logarithm after adding 0.1 to all RPKM values. The data were first centered by subtracting the median expression of the benign samples for each transcript. The Significance Analysis of Microarrays (SAM) method (Tusher et al., Proc Natl Acad Sci USA 98, 5116-21 (2001)) with 250 permutations of the Tusher et al. S0 selection method was used to predict differentially expressed genes. A delta value corresponding to the 90th percentile FDR desired for individual analyses was used. The MultiExperiment Viewer application (Chu et al., Genome Biol 9, R118 (2008)) was used to run SAM and generate heatmaps. It was confirmed that the results matched expected results through comparison with microarrays and known prostate cancer biomarkers.
Outlier Analysis
A modified COPA analysis was performed on the 81 tissue samples in the cohort. RPKM expression values were used and shifted by 1.0 in order to avoid division by zero. The COPA analysis had the following steps (MacDonald & Ghosh, Bioinformatics 22, 2950-1 (2006); Tomlins et al. Science 310, 644-8 (2005)): 1) gene expression values were median centered, using the median expression value for the gene across the all samples in the cohort. This sets the gene's median to zero. 2) The median absolute deviation (MAD) was calculated for each gene, and then each gene expression value was scaled by its MAD. 3) The 80, 85, 90, 98 percentiles of the transformed expression values were calculated for each gene and the average of those four values was taken. Then, genes were rank ordered according to this “average percentile”, which generated a list of outliers genes arranged by importance. 4) Finally, genes showing an outlier profile in the benign samples were discarded. Six novel transcripts ranked as both outliers and differentially-expressed genes in the analyses. These six were manually classified either as differentially-expressed or outlier status based on what each individual's distribution across samples indicated.
Repeat Enrichment Analysis
To assess the enrichment of repetitive elements in the assembly, 100 random permutations of the transcript positions on the same chromosome and strand were generated. To mirror the original constraints used to nominate transcripts it was ensured that permuted transcript positions contained a uniquely mappable stretch of genomic DNA at least 50 nt long. To account for the effects of mappability difficulties, each exon was padded by ±0 bp, 50 bp, 100 bp, or 500 bp of additional genomic sequence before intersecting the exons with repeat elements in the RepeatMasker 3.2.7 database. It was observed that padding by more than 50 bp did not improve enrichment results and padded exons by ±50 bp in subsequent analyses and tests (Table 9). Finally, the Shapiro-Wilk test for normality was performed and it was verified that the number of matches to highly abundant repetitive element types was approximately normally distributed.
B. Results Prostate Cancer Transcriptome Sequencing
Transcriptome sequencing (RNA-Seq) was performed on 21 prostate cell lines, 20 benign adjacent prostates (benign), 47 localized tumors (PCA), and 14 metastatic tumors (MET). A total of 201 RNA-Seq libraries from this cohort were sequenced yielding a total of 1.41 billion mapped reads, with a median 4.70 million mapped reads per sample (Table 1 for sample information).
To analyze these data a method for ab initio transcriptome assembly to reconstruct transcripts and transcript abundance levels was used (FIG. 6 and Table 2) (Trapnell et al., Nat Biotechnol 28 (5), 511; Trapnell et al., Bioinformatics 25 (9), 1105 (2009)). Sample-specific transcriptomes were predicted and individual predication were merged into a consensus transcriptome and the most robust transcripts were retained (FIG. 7). The ab initio transcriptome assembly and subsequent refinement steps yielded 35,415 distinct transcriptional loci (see FIG. 8 for examples).
The assembled transcriptome was compared to the UCSC, Ensembl, Refseq, Vega, and ENCODE gene databases to identify and categorize transcripts. While the majority of the transcripts (77.3%) corresponded to annotated protein coding genes (72.1%) and noncoding RNAs (5.2%), a significant percentage (19.8%) lacked any overlap and were designated “unannotated” (FIG. 1a). These included partially intronic antisense (2.44%), totally intronic (12.1%), and intergenic transcripts (5.25%). These results agree with previous data indicating that large fractions of the transcriptome represent unannotated transcription (Birney et al., Nature 447 (7146), 799 (2007); Carninci et al., Science 309 (5740), 1559 (2005) and that significant percentages of genes may harbor related antisense transcripts (He et al., Science 322 (5909), 1855 (2008); Yelin et al., Nat Biotechnol 21 (4), 379 (2003)). Due to the added complexity of characterizing antisense or partially intronic transcripts without strand-specific RNA-Seq libraries, studies focused on totally intronic and intergenic transcripts.
Characterization of Novel Transcripts
Global characterization of novel transcripts corroborated previous reports that they are relatively poorly conserved and more lowly expressed than protein coding genes (Guttman et al., Nat Biotechnol 28 (5), 503; Guttman et al., Nature 458 (7235), 223 (2009)). Expression levels of unannotated prostate cancer transcripts were consistently higher than randomly permuted controls, but lower than annotated ncRNAs or protein coding genes (FIG. 1b). Unannotated transcripts also showed less overlap with known expressed sequence tags (ESTs) than protein-coding genes but more than randomly permuted controls (FIG. 5). Unannotated transcripts showed a clear but subtle increase in conservation over control genomic intervals (novel intergenic transcripts p=2.7×10-4±0.0002 for 0.4<ω<0.8; novel intronic transcripts p=2.6×10-5±0.0017 for 0<ω<0.4, FIG. 1c). Only a small subset of novel intronic transcripts showed increased conservation (FIG. 1c insert), but this conservation was quite profound. By contrast, a larger number of novel intergenic transcripts showed more mild increases in conservation. Finally, analysis of coding potential revealed that only 5 of 6,144 transcripts harbored a high quality open reading frame (ORF), indicating that the overwhelming majority of these transcripts represent ncRNAs (FIG. 10).
Next, published prostate cancer ChIP-Seq data for two prostate cell lines (Yu et al., Cancer Cell 17 (5), 443; VCaP and LNCaP was used in order to interrogate the overlap of unannotated transcripts with histone modifications supporting active transcription (H3K4me1, H3K4me2, H3K4me3, H3K36me3, Acetyl-H3 and RNA polymerase II, see Table 3). Because unannotated ncRNAs showed two clear subtypes, repeat-associated and non-repeats (FIG. 11 and discussed below), it was contemplated that these two subtypes may display distinct histone modifications as noted in previous research (Day et al., Genome Biol 11 (6), R69). Whereas non-repeat transcripts showed strong enrichment for hi stone marks of active transcription at their putative transcriptional start sites (TSSs), repeat-associated transcripts showed virtually no enrichment (FIG. 12), and for the remaining ChIP-Seq analyses non-repeat transcripts only were considered. In this set of unannotated transcripts, strong enrichment for histone modifications characterizing TSSs and active transcription, including H3K4me2, H3K4me3, Acetyl-H3 and RNA Polymerase II (FIG. 1d-g) but not H3K4me1 was observed, which characterizes enhancer regions (FIGS. 13 and 14). Intergenic ncRNAs performed much better in these analyses than intronic ncRNAs (FIG. 1d-g). To elucidate global changes in transcript abundance between prostate cancer and benign tissues, differential expression was performed analysis for all transcripts. 836 genes differentially-expressed between benign and PCA samples (FDR<0.01) were found, with protein-coding genes constituting 82.8% of all differentially-expressed genes (FIG. 1h and Table 4). This category contained the most significant transcripts, including numerous known prostate cancer genes such as AMACR32 and Hepsin (Dhanasekaran et al., Nature 412 (6849), 822 (2001)). Annotated ncRNAs represented 7.4% of differentially-expressed genes, including the ncRNA PCA334, which resides within an intron of the PRUNE2 gene and ranked #4 overall (12.2 fold change; adj. p<2×10-4, Wilcoxon rank sum test, Benjamini-Hochberg correction) (FIG. 8). Finally, 9.8% of differentially-expressed genes corresponded to unannotated ncRNAs, including 3.2% within gene introns and 6.6% in intergenic regions, indicating that these species contribute significantly to the complexity of the prostate cancer transcriptome.
Dysregulation of Unannotated Non-Coding RNAs
Recent reports of functional long intervening non-coding RNAs (Dhanasekaran et al., Nature 412 (6849), 822 (2001); Gupta et al., Nature 464 (7291), 1071; Rinn et al., Cell 129 (7), 1311 (2007); Guttman et al., Nature 458 (7235), 223 (2009)) (lincRNAs) in intergenic regions led to an exploration of intergenic ncRNAs further. A total of 1859 unannotated intergenic RNAs were found throughout the human genome. The present invention is not limited to a particular mechanism. Indeed, an understanding of the mechanism is not necessary to practice the present invention. Nonetheless it is contemplated that this is an underestimate due to the inability to detect small RNAs eliminated by the ˜250 bp size selection performed during RNA-Seq library generation (Methods). Overall, novel intergenic RNAs resided closer to protein-coding genes than protein-coding genes do to each other (the median distance to the nearest protein-coding gene is 4292 kb for novel genes and 8559 kb for protein-coding genes, FIG. 2a). For instance, if two protein-coding genes, Gene A and Gene B, are separated by the distance AB, then the furthest an unannotated ncRNA can be from both of them is 0.5*AB, which is exactly what was observed (4292/8559=0.501). Supporting this observation, 34.1% of unannotated transcripts are located ≧10 kb from the nearest protein-coding gene. As an example, the Chr15q arm was visualized using the Circos program. Eighty-nine novel intergenic transcripts were nominated across this chromosomal region, including several differentially-expressed loci centromeric to TLE3 (FIG. 2b) which were validated by PCR in prostate cancer cell lines (FIG. 15). A focused analysis of the 1859 novel intergenic RNAs yielded 106 that were differentially expressed in localized tumors (FDR<0.05; FIG. 2c). These Prostate Cancer Associated Transcripts (PCATs) were ranked according to their fold change in localized tumor versus benign tissue (Tables 5 and 6).
Similarly, performing a modified cancer outlier profile analysis (COPA) on the RNA-Seq dataset re-discovered numerous known prostate cancer outliers, such as ERG7, ETV17, SPINK135, and CRISP336,37, and nominated numerous unannotated ncRNAs as outliers (FIG. 2d and Tables 6 and 7). Merging the results from the differential expression and COPA analyses resulted in a set of 121 unannotated transcripts that accurately discriminated benign, localized tumor, and metastatic prostate samples by unsupervised clustering (FIG. 2c). These data provide evidence that PCATs serve as biomarkers for prostate cancer and novel prostate cancer subtypes. Clustering analyses using novel ncRNA outliers also provide disease subtypes (FIG. 16).
Confirmation and Tissue-Specificity of ncRNAs
Validation studies were performed on 14 unannotated expressed regions, including ones both included and not present in the list of differentially expressed transcripts. Reverse transcription PCR (RT-PCR) and quantitative real-time PCR (qPCR) experiments demonstrated a ˜78% (11/14) validation rate in predicted cell line models for both transcript identity and expression level (FIG. 17). Next, three transcripts (PCAT-109, PCAT-14, and PCAT-43) selectively upregulated in prostate cancer compared to normal prostate were examined. From the sequencing data, each genomic loci shows significantly increased expression in prostate cancer and metastases, except for PCAT-14, which appears absent in metastases (FIG. 3a-c). PCAT-109 also ranks as the #5 best outlier in prostate cancer, just ahead of ERG (FIG. 2d and Table 6). qPCR on a cohort of 14 benign prostates, 47 tumors, and 10 metastases confirmed expression of these transcripts (FIG. 3a-c). All three appear to be prostate-specific, with no expression seen in breast or lung cancer cell lines or in 19 normal tissue types (Table 8). This tissue specificity was not necessarily due to regulation by androgen signaling, as only PCAT-14 expression was induced by treatment of androgen responsive VCaP and LNCaP cells with the synthetic androgen R1881, consistent with previous data from this genomic locus (FIG. 18) (Tomlins et al., Nature 448 (7153), 595 (2007); Stavenhagen et al., Cell 55 (2), 247 (1988)). PCAT-14, but not PCAT-109 or PCAT-43, also showed differential expression when tested on a panel of matched tumor-normal samples, indicating that this transcript, which is comprised of an endogenous retrovirus in the HERV-K family (Bannert and Kurth, Proc Natl Acad Sci USA 101 Suppl 2, 14572 (2004)), can be used as a somatic marker for prostate cancer (FIG. 19). 5′ and 3′ rapid amplification of cDNA ends (RACE) at this locus revealed the presence of individual viral protein open reading frames (ORFs) and a transcript splicing together individual ORF 5′ untranslated region (UTR) sequences (FIG. 20). It was observed that the top-ranked intergenic ncRNA resided in the chromosome 8q24 gene desert nearby to the c-Myc oncogene. This ncRNA, termed PCAT-1, is located on the edge of the prostate cancer susceptibility region 240-43 (FIG. 4a) and is about 0.5 Mb away from c-Myc. This transcript is supported by clear peaks in H3K4me3, Acetyl-H3, and RNA polymerase II ChIP-Seq data (FIG. 4b). The exon-exon junction in cell lines was validated by RT-PCR and Sanger sequencing of the junction (FIG. 4c), and 5′ and 3′ RACE was performed to elucidate transcript structure (FIG. 4d). By this analysis, PCAT-1 is a mariner family transposase (Oosumi et al., Nature 378 (6558), 672 (1995); Robertson et al., Nat Genet 12 (4), 360 (1996)) interrupted by an Alu retrotransposon and regulated by a viral long terminal repeat (LTR) promoter region (FIG. 4d and FIG. 21). By qPCR, PCAT-1 expression is specific to prostate tissue, with striking upregulation in prostate cancers and metastases compared to benign prostate tissue (FIG. 4e). PCAT-1 ranks as the second best overall prostate cancer biomarker, just behind AMACR (Table 3), indicating that this transcript is a powerful discriminator of this disease. Matched tumor normal pairs similarly showed marked upregulation in the matched tumor samples (FIG. 4f). RNA interference (RNAi) was performed in VCaP cells using custom siRNAs targeting PCAT-1 sequences and no change in the cell proliferation or invasion upon PCAT-1 knockdown was observed (FIG. 22)
Selective Re-Expression of Repetitive Elements in Cancer
The presence of repetitive elements in PCAT-1 led to an exploration of repetitive elements. Repetitive elements, such as Alu and LINE-1 retrotransposons, are broadly known to be degenerate in humans (Oosumi et al, supra; Robertson et al., supra; Cordaux et al., Nat Rev Genet 10 (10), 691 (2009), with only ˜100 LINE-1 elements (out of 12 500,000) showing possible retrotransposon activity (Brouha et al., Proc Natl Acad Sci USA 100 (9), 5280 (2003)). While transcription of these elements is frequently repressed through DNA methylation and repressive chromatin modifications (Slotkin and Martienssen, Nat Rev Genet 8 (4), 272 (2007)), in cancer widespread hypomethylation has been reported (Cho et al., J Pathol 211 (3), 269 (2007); Chalitchagorn et al., Oncogene 23 (54), 8841 (2004); Yegnasubramanian et al., Cancer Res 68 (21), 8954 (2008)). Moreover, recent evidence indicates that these elements have functional roles in both normal biology (Kunarso et al., Nat Genet.) and cancer (Lin et al., Cell 139 (6), 1069 (2009)), even if their sequences have mutated away from their evolutionary ancestral sequence (Chow et al., Cell 141 (6), 956). To date, only RNA-Seq platforms enable discovery and quantification of specific transposable elements expressed in cancer. As described above, it was observed that >50% of unannotated exons in the assembly overlap with at least one repetitive element (FIG. 11). Since these elements pose mappability challenges when performing transcriptome assembly with unique reads, these loci typically appear as “mountain ranges” of expression, with uniquely mappable regions forming peaks of expression separated by unmappable “ravines” (FIGS. 23 and 24). PCR and Sanger sequencing experiments were performed to confirm that these transposable elements of low mappability are expressed as part of these loci (FIGS. 23 and 24). To probe this observation further, the exons from unannotated transcripts in the assembly, with the addition of the flanking 50, 100, or 500 bp of additional genomic sequence to the 5′ and 3′ end of the exons were generated, the overlap of these intervals with repetitive elements to randomly permuted genomic intervals of similar sizes was performed. A highly significant enrichment for repetitive elements in the dataset was observed (OR 2.82 (95% CI 2.68-2.97), p<10-100, Table 9). Examination of the individual repetitive element classes revealed a specific enrichment for SINE elements, particularly Alus (p≦2×10-16, Tables 10 and 11). A subset of LINE-1 and Alu transposable elements demonstrate marked differential expression in a subset of prostate cancer tumors (FIG. 25). One locus on chromosome 2 (also highlighted in FIG. 3b) is a 500+kb region with numerous expressed transposable elements (FIG. 26). This locus, termed Second Chromosome Locus Associated with Prostate-1 (SChLAP1), harbors transcripts that perform extremely well in outlier analyses for prostate cancer (Tables 6 and 7). PCAT-109, discussed above, is one outlier transcript in this region. Moreover, the SChLAP1 locus is highly associated with patients positive for ETS gene fusions (p<0.0001, Fisher's exact test, FIG. 27), whereas this association was not observed with other expressed repeats. A direct regulatory role for ERG on this region was not identified using siRNA-mediated knockdown of ERG in the VCaP cell line. These data indicate that the dysregulation of repeats in cancer is highly specific, and that this phenomenon associates with only a subset of tumors and metastases. Thus, the broad hypomethylation of repeat elements observed in cancer (Cho et al., J Pathol 211 (3), 269 (2007); Chalitchagorn et al., Oncogene 23 (54), 8841 (2004); Yegnasubramanian et al., Cancer Res 68 (21), 8954 (2008)) does not account for the high specificity of repeat expression.
Non-Invasive Detection of ncRNAs in Urine
Taken together, these data show an abundance of novel ncRNA biomarkers for prostate cancer, many of which appear to have tissue specificity. 77 urine sediments obtained from patients with prostate cancer and 31 control patients without known disease (Table 12 for sample details) were analyzed (Laxman et al., Cancer Res 68 (3), 645 (2008)). The control patients are defined as those lacking cancer histology upon prostate biopsy and lacking the TMPRSS2-ERG fusion transcript in urine sediment RNA (Laxman et al., supra). PCAT-1 and PCAT-14, as well as the known ncRNA biomarker PCA3, were selected for evaluation on this urine panel due to their biomarker status in patient tissue samples. qPCR analysis led to an observation of specificity in their ability to detect prostate cancer patients and not patients with normal prostates (FIG. 5a-c). In several cases, patients with ETS-negative prostate cancer that were misclassified as “benign” are clearly evident (FIGS. 5a and 5c). Moreover, PCAT-14 appears to perform almost as well as PCA3 as a urine biomarker, nearly achieving statistical significance (p=0.055, Fisher's exact test) despite the small number of patients used for this panel. It was next evaluated whether these unannotated ncRNAs identified a redundant set of patients that would also be identified by other urine tests, such as PCA3 or TMPRSS2-ERG transcripts. Comparing PCAT-1 and PCAT-14 expression in urine samples to PCA3 or to each other revealed that these ncRNAs identified distinct patient sets, indicating that a patient's urine typically harbors PCAT-1 or PCAT-14 transcripts but not both (FIG. 5d). Using the cut-offs displayed in FIG. 5a-c, a binary heatmap comparing these three ncRNAs with patients' TMPRSS2-ERG status was generated (FIG. 5e). The ncRNAs were able to detect additional ETS-negative patients with prostate cancer through this urine test, indicating that they have clinical utility as highly specific markers for prostate cancer using a multiplexed urine test. Combining PCAT-1, PCAT-14 and PCA3 into a single “non-coding RNA signature” generated a highly specific urine signature (p=0.0062, Fisher's exact test, FIG. 5f) that identifies a number of prostate cancer patients that is broadly comparable to the TMPRSS2-ERG fusion (33% vs. 45%).
FIG. 34 shows detection of prostate cancer RNAs in patient urine samples using qPCR. All RNA species were detectable in urine. FIG. 35 shows that multiplexing urine SChLAP-1 measurements with serum PSA improves prostate cancer risk stratification. Individually, SChLAP-1 is a predictor for prostate cancers with intermediate or high clinical risk of aggressiveness. Multiplexing this measurement with serum PSA improves upon serum PSA's ability to predict for more aggressive disease.
Additional Characterization Additional experiments were conducted related to PCAT-1 and SChLAP-1 region in prostate cancer. FIG. 29 demonstrates that PCAT-1 expression sensitizes prostate cancer cells to treatment with PARP-1 inhibitors. FIG. 30 demonstrates that PCAT-1 expression sensitizes prostate cells to radiation treatment.
FIG. 31 demonstrates that unannotated intergenic transcripts in SChLAP-1 differentiate prostate cancer and benign samples. FIG. 32 demonstrates that SChLAP-1 is required for prostate cancer cell invasion and proliferation. Prostate cell lines, but not non-prostate cells, showed a reduction in invasion by Boyden chamber assays. EZH2 and non-targeting siRNAs served as positive and negative controls, respectively. Deletion analysis of SChLAP-1 was performed. FIG. 33 shows that a regionessential for its function was identified.
ncRNAs in Lung, Breast, and Pancreatic Cancers
Analysis of the lung cancer transcriptome (FIG. 36) was performed. 38 lung cell lines were analyzed by RNA-Seq and then lncRNA transcripts were reconstructed. Unannotated transcripts accounted for 27% of all transcripts. Novel transcripts well more highly expressed than annotated ncRNAs but not protein-coding transcripts. An outlier analyses of 13 unannotated transcripts shows novel lncRNAs in subtypes of lung cancer cell lines. FIG. 37 shows discovery of M41 and ENST-75 ncRNAs in lung cancer. FIG. 38 shows that lncRNAs are drivers and biomarkers in lung cancer. FIG. 39 shows identification of cancer-associated lncRNAs in breast and pancreatic cancer. Three novel breast cancer lncRNAs were nominated from RNA-Seq data (TU0011194, TU0019356, and TU0024146. All show outlier expression patterns in breast cancer samples but not benign samples. Three novel pancreatic cancer lncRNAs were nominated from RNA-Seq data (TU0009141, TU0062051, and TU0021861). All show outlier expression patterns in pancreatic cancer samples but not benign samples.
TABLE 1
TopHat TopHat
Library ID Sample Name Type Sample Type Read Type Read Length Total Reads (x2 for PE) Mapped Reads Splice Junction Reads % Splice Diagnosis ETS status
ctp_42808AAXX_2 PWR-1E RNA-Seq CellLine paired_end 40 7363045 8367325 1091179 13.04% Benign Negative
mctp_30CYNAAXX_5 prEC RNA-Seq Cell Line single_read 40 3078462 955130 107311 11.24% Benign Negative
mctp_209ENAAXX_8 prEC RNA-Seq Cell Line single_read 30 3319066 871560 67610 7.76% Benign Negative
mctp_314T1AAXX_1 prEC RNA-Seq Cell Line paired_end 40 7748627 7443379 747751 10.05% Benign Negative
mctp_30351AAXX_7 prEC RNA-Seq Cell Line paired_end 40 5853459 9562343 892380 9.33% Benign Negative
mctp_314T1AAXX_2 PrSMC RNA-Seq Cell Line paired_end 40 8465529 8626281 935503 10.84% Benign Negative
mctp_20E5CAAXX_6 RWPE RNA-Seq Cell Line single_read 36 5300138 1693464 149383 8.82% Benign Negative
mctp_20E6CAAXX_7 RWPE RNA-Seq Cell Line single_read 36 5347764 1710762 250130 8.78% Benign Negative
mctp_20E6CAAXX_8 RWPE RNA-Seq Cell Line single_read 36 4778245 1539225 135996 8.84% Benign Negative
mctp_20F05AAXX_6 RWPE RNA-Seq Cell Line single_read 36 4833510 1565250 137416 8.78% Benign Negative
mctp_20F0BAAXX_7 RWPE RNA-Seq Cell Line single_read 36 5005497 1622033 143105 8.83% Benign Negative
mctp_20F0BAAXX_8 RWPE RNA-Seq Cell Line single_read 36 4955663 1607124 141358 8.80% Benign Negative
mctp_20F0GAAXX_7 RWPE RNA-Seq Cell Line single_read 36 4866138 1568635 130224 8.81% Benign Negative
mctp_20F0GAAXX_8 RWPE RNA-Seq Cell Line single_read 36 4809235 1550957 156049 8.77% Benign Negative
mctp_20F0GAAXX_6 RWPE RNA-Seq Cell Line single_read 36 4901167 1580424 138674 8.77% Benign Negative
mctp_4250BAAXX_3 WPMY-1 RNA-Seq Cell Line paired_end 40 7593911 8103303 1011035 12.48% Benign Negative
mctp_20F69AAXX_1 22Rv1 RNA-Seq Cell Line single_read 36 5301735 2345205 169257 7.22% Localized Negative
mctp_31401AAXX_6 22Rv1 RNA-Seq Cell Line paired_end 40 9214120 9500616 1063132 11.07% Localized Negative
mctp_429T4AAXX_5 CA-HPV.10 RNA-Seq Cell Line paired_end 40 13654861 14731620 1750416 11.88% Localized Negative
mctp_42974AAXX_7 CWR22 RNA-Seq Cell Line paired_end 40 13882984 14791235 1530790 10.35% Localized Negative
mctp_30DJDAAXX_2 VCaP RNA-Seq Cell Line single_read 45 8175900 1400658 167748 11.98% Metastatic ERG+
mctp_20CCAAAXX_7 VCaP RNA-Seq Cell Line single_read 36 5372814 981204 89660 9.14% Metastatic ERG+
mctp_20CCAAAXX_6 VCaP RNA-Seq Cell Line single_read 36 5210292 957549 86199 9.00% Metastatic ERG+
mctp_20CCAAAXX_4 VCaP RNA-Seq Cell Line single_read 36 5220542 956622 88342 9.23% Metastatic ERG+
mctp_20CCAAAXX_3 VCaP RNA-Seq Cell Line single_read 36 5405126 988972 96075 9.11% Metastatic ERG+
mctp_20CCAAAXX_2 VCaP RNA-Seq Cell Line single_read 36 5091526 938272 85147 9.07% Metastatic ERG+
mctp_20CCAAAXX_1 VCaP RNA-Seq Cell Line single_read 36 4273325 804080 72804 9.05% Metastatic ERG+
mctp_20E5CAAXX_1 VCaP RNA-Seq Cell Line single_read 36 4717324 861856 78164 9.07% Metastatic ERG+
mctp_20CCAAAXX_8 VCaP RNA-Seq Cell Line single_read 36 5024204 976214 85535 9.23% Metastatic ERG+
mctp_207D6AAXX_2 VCaP RNA-Seq Cell Line single_read 36 4491727 807997 73610 9.11% Metastatic ERG+
mctp_429T4AAXX_4 NCI-H660 RNA-Seq Cell Line paired_end 40 12322606 15104197 1377708 9.12% Metastatic ERG+
mctp_20FDGAAXX_4 LNCaP RNA-Seq Cell Line single_read 36 5109105 1430548 119570 8.35% Metastatic ETV1+
mctp_20F0GAAXX_1 LNCaP RNA-Seq Cell Line single_read 36 5015345 1402514 117293 8.36% Metastatic ETV1+
mctp_20F0GAAXX_3 LNCaP RNA-Seq Cell Line single_read 36 5106724 1426054 119462 8.57% Metastatic ETV1+
mctp_20F0GAAXX_2 LNCaP RNA-Seq Cell Line single_read 36 4990256 1398161 117850 8.43% Metastatic ETV1+
mctp_20E6CAAXX_2 LNCaP RNA-Seq Cell Line single_read 36 4593789 1370920 112874 8.30% Metastatic ETV1+
mctp_20E6CAAXX_3 LNCaP RNA-Seq Cell Line single_read 36 5432666 1510040 126177 5.96% Metastatic ETV1+
mctp_20E6CAAXX_4 LNCaP RNA-Seq Cell Line single_read 36 4553947 1501247 112409 3.62% Metastatic ETV1+
mctp_42PMUAAXX_6 LNCaP CDS2 RNA-Seq Cell Line paired_end 38 10714839 10272130 1057574 10.30% Metastatic Negative
mctp_42PMUAAXX_7 LNCaP CDS3 RNA-Seq Cell Line paired_end 38 5613473 9586206 973617 10.16% Metastatic Negative
mctp_42TA8AAXX_7 DU-145 RNA-Seq Cell Line paired_end 38 13804352 13651384 1372507 10.04% Metastatic Negative
mctp_42TA8AAXX_6 DU-145 RNA-Seq Cell Line paired_end 38 15785849 15918091 1570336 9.86% Metastatic Negative
mctp_42TA8AAXX_5 DU-145 RNA-Seq Cell Line paired_end 38 14197743 14950079 1485534 9.93% Metastatic Negative
mctp_42TA8AAXX_3 DU-145 RNA-Seq Cell Line paired_end 38 12152298 13047548 1320224 10.12% Metastatic Negative
mctp_42TA8AAXX_2 DU-145 RNA-Seq Cell Line paired_end 38 12583744 13715578 1384118 10.09% Metastatic Negative
mctp_42TA8AAXX_1 DU-145 RNA-Seq Cell Line paired_end 38 10944533 6437207 653992 10.16% Metastatic Negative
mctp_42TBDAAXX_8 DU-145 RNA-Seq Cell Line paired_end 38 9229144 10026773 1013731 10.11% Metastatic Negative
mctp_42PFAAAXX_6 LNCaP CD5 RNA-Seq Cell Line paired_end 38 12368574 9518829 966541 10.15% Metastatic Negative
parent
mctp_42PFAAAXX_5 LNCaP CDS1 RNA-Seq Cell Line paired_end 38 14489868 13995752 1611356 10.08% Metastatic Negative
mctp_20BC5AAXX_8 DU-145 RNA-Seq Cell Line single_read 36 5351406 1568641 235883 9.13% Metastatic Negative
mctp_20F69AAXX_2 DU-145 RNA-Seq Cell Line single_read 36 5069249 2437193 225574 9.25% Metastatic Negative
mctp_3001DAAXX_3 DU-145 RNA-Seq Cell Line single_read 45 8586532 4162580 498466 11.97% Metastatic Negative
mctp_429T4AAXX_3 LAPC-4 RNA-Seq Cell Line paired_end 40 14725826 16711055 1790200 10.71% Metastatic Negative
mctp_3064YAAXX_1 PC3 RNA-Seq Cell Line paired_end 40 10267396 10291560 1185473 11.52% Metastatic Negative
mctp_20F69AAXX_3 PC3 RNA-Seq Cell Line single_read 36 5364050 2547308 237597 8.33% Metastatic Negative
mctp_429T4AAXX_2 C4-2B RNA-Seq Cell Line paired_end 40 12754909 12823209 1591197 12.41% Metastatic Negative
mctp_429T4AAXX_6 MDA FCa 2b RNA-Seq Cell Line paired_end 40 13341323 14909946 1634544 10.96% Metastatic Negative
mctp_42808AAXX_4 WPE1-NB26 RNA-Seq Cell Line paired_end 40 10593920 9930521 1240048 12.49% Metastatic Negative
mctp_42848AAXX_4 PrBe10013 RNA-Seq Tissue paired_end 40 15313195 18040527 1435670 7.96% Benign Negative
mctp_30WUZAAXX_5 PrBe10013 RNA-Seq Tissue paired_end 38 9822744 12263152 927590 7.56% Benign Negative
mctp_42848AAXX_8 PrBe10014 RNA-Seq Tissue paired_end 40 11242542 9036870 715431 7.92% Benign Negative
mctp_42PFAAAXX_2 PrBe10014 RNA-Seq Tissue paired_end 38 6616551 6359875 471003 7.38% Benign Negative
mctp_30WUZAAXX_5 PrBe10014 RNA-Seq Tissue paired_end 38 3977109 4235690 321691 7.56% Benign Negative
mctp_42CUAAXX_7 PrBe10015 RNA-Seq Tissue paired_end 40 7584480 7927754 632270 7.90% Benign Negative
mctp_42NY4AAXX_2 PrBe10015 RNA-Seq Tissue paired_end 38 14331227 12877894 936438 7.27% Benign Negative
mctp_42543AAXX_1 PrBe10016 RNA-Seq Tissue paired_end 40 12122294 11750631 820710 6.98% Benign Negative
mctp_42NY9AAXX_3 PrBe10016 RNA-Seq Tissue paired_end 38 11809596 11367863 741980 6.53% Benign Negative
mctp_30WUZAAXX_7 PrBe10017 RNA-Seq Tissue paired_end 38 1859890 2156367 152020 7.05% Benign Negative
mctp_420JFAAXX_5 PrBe10017 RNA-Seq Tissue paired_end 40 14245213 14383797 1025161 7.13% Benign Negative
mctp_43830AAXX_5 PrBe10018 RNA-Seq Tissue paired_end 38 16816393 17002418 1465145 8.62% Benign Negative
mctp_42NY4AAXX_6 PrBe10018 RNA-Seq Tissue paired_end 38 15877894 16489882 1418434 8.60% Benign Negative
mctp_42D3MAAXX_5 aN10_6 RNA-Seq Tissue paired_end 40 10102958 11948284 938291 7.85% Benign Negative
mctp_3054YAAXX_2 aN11_1 RNA-Seq Tissue paired_end 40 9792955 10708088 843013 7.88% Benign Negative
mctp_42P6UAAXX_1 aN11_1 RNA-Seq Tissue paired_end 40 14658825 10917481 823116 7.54% Benign Negative
mctp_3040WAAXX_1 aN13_2 RNA-Seq Tissue paired_end 40 14755517 15347535 1174999 7.66% Benign Negative
mctp_42P6GAAXX_4 aN13_2 RNA-Seq Tissue paired_end 40 16107801 16070565 1231834 7.67% Benign Negative
mctp_3G54YAAXX_3 aN14_4 RNA-Seq Tissue paired_end 40 9282092 9526550 733492 7.70% Benign Negative
mctp_42P6UAAXX_2 aN14_4 RNA-Seq Tissue paired_end 40 12317092 11968962 894313 7.47% Benign Negative
mctp_30653AAXX_5 PrBe10002 RNA-Seq Tissue paired_end 40 10282216 3480927 190504 8.47% Benign Negative
mctp_30CVWAAXX_6 PrBe10002 RNA-Seq Tissue single_read 40 4389340 877146 39125 4.45% Benign Negative
mctp_3GCYWAAXX_7 PrBe10003 RNA-Seq Tissue single_read 40 4724195 382030 17102 4.48% Benign Negative
mctp_42P6UAAXX_5 aN15_3 RNA-Seq Tissue paired_end 40 14035929 10890695 928050 8.53% Benign Negative
mctp_3054YAAXX_7 aN15_3 RNA-Seq Tissue paired_end 40 8772663 8101379 714429 8.82% Benign Negative
mctp_30CM2AAXX_6 aN23 RNA-Seq Tissue single_read 35 6359089 2998000 171398 5.72% Benign Negative
mctp_30CM2AAXX_4 aN25 RNA-Seq Tissue single_read 35 5162304 2181784 100935 4.63% Benign Negative
mctp_30CM2AAXX_5 aN25 RNA-Seq Tissue single_read 35 5667482 2632682 123775 4.70% Benign Negative
mctp_30CM3AAXX_1 aN27 RNA-Seq Tissue single_read 35 4771661 1836620 93266 5.02% Benign Negative
mctp_30CM2AAXX_2 aN27 RNA-Seq Tissue single_read 35 5843509 2090978 103544 4.95% Benign Negative
mctp_30CM2AAXX_7 aN29 RNA-Seq Tissue single_read 35 5661652 1555510 87547 5.63% Benign Negative
mctp_30CM2AAXX_5 aN29 RNA-Seq Tissue single_read 35 5201944 1472975 83465 5.67% Benign Negative
mctp_ZCFCKAAXX_1 aN31 RNA-Seq Tissue single_read 36 4206556 1642681 122140 7.44% Benign Negative
mctp_ZCFCKAAXX_2 aN31 RNA-Seq Tissue single_read 35 3624043 1504320 107996 7.18% Benign Negative
mctp_ZCFCKAAXX_4 aN32 RNA-Seq Tissue single_read 36 4145596 1866001 118140 6.35% Benign Negative
mctp_ZCFCKAAXX_3 aN32 RNA-Seq Tissue single_read 36 4352455 1835242 115876 6.31% Benign Negative
mctp_ZCFCKAAXX_7 aN33 RNA-Seq Tissue single_read 35 5375947 2024782 122564 6.05% Benign Negative
mctp_ZCFCKAAXX_8 aN33 RNA-Seq Tissue single_read 35 3974268 1587869 96704 6.09% Benign Negative
mctp_42D3MAAXX_5 aT12_4 RNA-Seq Tissue paired_end 40 10323732 10700518 891873 8.34% Localized ERG+
mctp_42P6UAAXX_6 aT12_4 RNA-Seq Tissue paired_end 40 12591851 12687329 1035642 8.16% Localized ERG+
mctp_2GACMAAXX_7 aT54 RNA-Seq Tissue single_read 35 4951150 2395362 153160 6.39% Localized ERG+
mctp_3050WAAXX_3 aT5_5 RNA-Seq Tissue paired_end 40 14290078 15157910 1231918 6.13% Localized ERG+
mctp_20AGMAAXX_8 aT62 RNA-Seq Tissue single_read 35 5144018 2594526 146853 5.66% Localized ERG+
mctp_20G93AAXX_1 aT76 RNA-Seq Tissue single_read 30 4482645 2095390 77035 3.68% Localized ERG+
mctp_4203NAAXX_2 aT8_2 RNA-Seq Tissue paired_end 40 5949944 10269470 745408 7.26% Localized ERG+
mctp_42P6UAAXX_7 aT2_2 RNA-Seq Tissue paired_end 40 13165443 12758016 925564 7.25% Localized ERG+
mctp_2GACMAAXX_6 aT20 RNA-Seq Tissue single_read 35 4905934 2380289 168032 7.06% Localized ETV1+
mctp_30Y5NAAXX_6 aT52 RNA-Seq Tissue paired_end 34 9555248 11236237 579321 5.16% Localized ETV1+
mctp_20593AAXX_4 PrCa10001 RNA-Seq Tissue single_read 30 5073375 2003723 81777 4.05% Localized Negative
mctp_30CVWAAXX_2 PrCa10002 RNA-Seq Tissue single_read 40 3979845 1573898 142307 9.04% Localized Negative
mctp_20G95AAXX_7 PrCa10002 RNA-Seq Tissue single_read 30 5337734 2185509 134758 6.17% Localized Negative
mctp_30CW7AAXX_4 PrCa10003 RNA-Seq Tissue single_read 40 7245088 3325480 200975 6.04% Localized Negative
mctp_30CVWAAXX_1 PrCa10003 RNA-Seq Tissue single_read 40 2232676 996717 47049 4.72% Localized Negative
mctp_20G93AAXX_6 PrCa10003 RNA-Seq Tissue single_read 30 4209584 1860531 80219 4.29% Localized Negative
mctp_20G93AAXX_2 PrCa10004 RNA-Seq Tissue single_read 30 4877618 2429172 101279 4.17% Localized Negative
mctp_30CW2AAXX_3 PrCa10004 RNA-Seq Tissue single_read 40 8502651 4337032 261531 5.03% Localized Negative
mctp_20G93AAXX_1 PrCa10006 RNA-Seq Tissue single_read 30 4697349 2219408 86343 3.09% Localized Negative
mctp_30CW2AAXX_5 PrCa10006 RNA-Seq Tissue single_read 40 7780464 3825883 211003 5.52% Localized Negative
mctp_30WU2AAXX_6 PrCa10013 RNA-Seq Tissue paired_end 38 7094073 8465055 698526 8.25% Localized Negative
mctp_42FFAAAXX_3 PrCa10013 RNA-Seq Tissue paired_end 38 13129950 14850397 1205327 8.12% Localized Negative
mctp_42CJFAAXX_4 PrCa10013 RNA-Seq Tissue paired_end 40 11855634 13593367 1193752 8.78% Localized Negative
mctp_42603AAXX_5 PrCa10014 RNA-Seq Tissue paired_end 40 11559996 11278990 923485 8.19% Localized Negative
mctp_42808AAXX_1 PrCa10014 RNA-Seq Tissue paired_end 40 9629325 7576252 705179 9.31% Localized Negative
mctp_42CJ1AAXX_5 PrCa10014 RNA-Seq Tissue paired_end 40 15108424 17200396 1326961 7.71% Localized Negative
mctp_30WU2AAXX_1 PrCa10014 RNA-Seq Tissue paired_end 38 13033345 15792364 1122174 7.11% Localized Negative
mctp_42543AAXX_3 PrCa10015 RNA-Seq Tissue paired_end 40 14322439 14744516 1043963 7.08% Localized Negative
mctp_30WUJAAXX_4 PrCa10015 RNA-Seq Tissue paired_end 38 9081533 10010115 675880 6.75% Localized Negative
mctp_42NY4AAXX_4 PrCa10016 RNA-Seq Tissue paired_end 38 11879138 13526717 954576 7.06% Localized Negative
mctp_42843AAXX_6 PrCa10016 RNA-Seq Tissue paired_end 40 11883518 13459171 1027559 7.63% Localized Negative
mctp_42843AAXX_2 PrCa10017 RNA-Seq Tissue paired_end 40 7583235 7555611 622237 8.24% Localized Negative
mctp_429FAAAXX_1 PrCa10017 RNA-Seq Tissue paired_end 38 13554764 11318051 852274 7.53% Localized Negative
mctp_42NY4AAXX_5 PrCa10018 RNA-Seq Tissue paired_end 38 16107721 18636010 1471850 7.90% Localized Negative
mctp_42CJFAAXX_2 PrCa10018 RNA-Seq Tissue paired_end 40 12506692 14935573 1501243 8.71% Localized Negative
mctp_30V5NAAXX_4 PrCa10018 RNA-Seq Tissue paired_end 34 8565125 10521603 649435 6.17% Localized Negative
mctp_42CUAAXX_8 PrCa10019 RNA-Seq Tissue paired_end 40 14204491 12235106 884253 7.23% Localized Negative
mctp_42543AAXX_5 PrCa10021 RNA-Seq Tissue paired_end 40 14583654 15470222 1147556 7.42% Localized Negative
mctp_42CJFAAXX_1 PrCa10023 RNA-Seq Tissue paired_end 40 9473417 11040935 939157 8.51% Localized Negative
mctp_42CUAAXX_6 PrCa10024 RNA-Seq Tissue paired_end 40 5249645 5541745 432904 7.81% Localized Negative
mctp_42PF0AAXX_3 PrCa10024 RNA-Seq Tissue paired_end 38 8109134 7508966 541558 7.21% Localized Negative
mctp_42C16AAXX_3 PrCa10028 RNA-Seq Tissue paired_end 40 5344368 6256991 516414 6.25% Localized Negative
mctp_42T69AAXX_5 PrCa10030 RNA-Seq Tissue paired_end 38 17239720 18212019 1265021 6.95% Localized Negative
mctp_42T89AAXX_1 PrCa10031 RNA-Seq Tissue paired_end 38 17881940 19792732 1356072 5.85% Localized Negative
mctp_42T69AAXX_6 PrCa10032 RNA-Seq Tissue paired_end 38 16892184 18313947 1420306 7.75% Localized Negative
mctp_42T69AAXX_2 PrCa10033 RNA-Seq Tissue paired_end 38 10736010 7148288 460799 6.45% Localized Negative
mctp_42T89AAXX_7 PrCa10034 RNA-Seq Tissue paired_end 38 16494766 18616451 1416932 7.61% Localized Negative
mctp_42P0UAAXX_5 aT1_3 RNA-Seq Tissue paired_end 40 14031093 15128363 1089323 7.20% Localized Negative
mctp_302XWAAXX_2 aT1_3 RNA-Seq Tissue paired_end 40 14017921 15424771 1120415 7.26% Localized Negative
mctp_42543AAXX_7 aT38 RNA-Seq Tissue paired_end 40 14028075 14206815 1075647 7.57% Localized Negative
mctp_50V5NAAXX_3 aT38 RNA-Seq Tissue paired_end 34 9148041 10857079 634116 5.85% Localized Negative
mctp_42Y27AAXX_2 aT42 RNA-Seq Tissue paired_end 38 15907739 17336906 1111429 6.41% Localized Negative
mctp_30GJ0AAXX_5 aT41 RNA-Seq Tissue single_read 45 9446722 4597917 345881 7.52% Localized Negative
mctp_42Y2TAAXX_3 aT45 RNA-Seq Tissue paired_end 38 16395435 13748230 814457 5.92% Localized Negative
mctp_300JQAAXX_6 aT45 RNA-Seq Tissue single_read 45 9154922 3918914 273181 6.97% Localized Negative
mctp_32503AAXX_7 aT53 RNA-Seq Tissue paired_end 40 12164542 13040082 1055172 8.09% Localized Negative
mctp_20F66AAXX_6 aT56 RNA-Seq Tissue single_read 36 4655382 2002111 109234 5.46% Localized Negative
mctp_300WTAAXX_2 aT56 RNA-Seq Tissue single_read 40 7386627 3040283 189576 5.22% Localized Negative
mctp_20F85AAXX_1 aT56 RNA-Seq Tissue single_read 36 4894127 1958986 108306 5.50% Localized Negative
mctp_30U09AAXX_4 aT57 RNA-Seq Tissue paired_end 40 9490697 9403761 688415 7.52% Localized Negative
mctp_420JFAAXX_8 aT58 RNA-Seq Tissue paired_end 40 4160283 4703591 386748 8.22% Localized Negative
mctp_42500AAXX_5 aT61 RNA-Seq Tissue paired_end 40 10252280 10445106 718210 6.88% Localized Negative
mctp_20F66AAXX_7 aT56 RNA-Seq Tissue single_read 36 5016117 2455183 153987 6.27% Localized Negative
mctp_300W7AAXX_1 aT56 RNA-Seq Tissue single_read 40 8055624 3791022 268911 7.09% Localized Negative
mctp_20F85AAXX_2 aT56 RNA-Seq Tissue single_read 36 5184870 2368556 149558 6.51% Localized Negative
mctp_42P5UAAXX_8 aT6_1 RNA-Seq Tissue paired_end 40 936249 998194 76698 7.88% Localized Negative
mctp_420JFAAXX_7 aT6_1 RNA-Seq Tissue paired_end 40 9428987 7353536 524419 7.13% Localized Negative
mctp_42FFAAAXX_4 aT6_1 RNA-Seq Tissue paired_end 38 13242928 9178336 610189 6.65% Localized Negative
mctp_300W3AAXX_7 PrCa10007 RNA-Seq Tissue single_read 42 7909935 3246264 305730 8.36% Localized Negative
mctp_4203NAAXX_2 PrCa10025 RNA-Seq Tissue paired_end 40 8614803 9085984 903098 9.94% Localized Negative
mctp_4202NAAXX_1 PrCa10026 RNA-Seq Tissue paired_end 40 7781206 8539677 801237 9.38% Localized Negative
mctp_4203NAAXX_3 PrCa10027 RNA-Seq Tissue paired_end 40 10305382 11427244 1110643 9.72% Localized Negative
mctp_42T89AAXX_4 PrCa10029 RNA-Seq Tissue paired_end 38 8674521 9910831 734269 7.41% Localized Negative
mctp_42Y6WAAXX_6 PrCa10029 RNA-Seq Tissue paired_end 38 13229893 14068633 1060520 7.54% Localized Negative
mctp_3064YAAXX_4 ULM2927 RNA-Seq Tissue paired_end 40 9542506 8623117 638903 7.41% Localized Negative
mctp_4283YAAXX_4 aT47 RNA-Seq Tissue paired_end 40 7806523 7010780 354081 5.05% Localized Negative
mctp_2GF06AAXX_3 aM23 RNA-Seq Tissue single_read 36 4680305 2018538 116179 5.67% Metastatic ERG+
mctp_2GF66AAXX_4 aM23 RNA-Seq Tissue single_read 36 4913495 2187836 127972 5.85% Metastatic ERG+
mctp_20F69AAXX_4 aM28 RNA-Seq Tissue single_read 36 5374538 2103543 99339 4.51% Metastatic ERG+
mctp_20LV8AAXX_6 aM28 RNA-Seq Tissue single_read 30 5517555 2234529 79073 3.54% Metastatic ERG+
mctp_20LV8AAXX_7 aM28 RNA-Seq Tissue single_read 30 5548780 2250821 80015 3.55% Metastatic ERG+
mctp_20AGMAAXX_4 aM29 RNA-Seq Tissue single_read 36 4903432 1839767 73792 4.01% Metastatic ERG+
mctp_20FETAAXX_6 aM29 RNA-Seq Tissue single_read 36 5092573 1777721 73464 4.13% Metastatic ERG+
mctp_2074VAAXX_1 aM38 RNA-Seq Tissue single_read 36 5126432 2559949 150938 5.90% Metastatic ERG+
mctp_30CVMAAXX_4 aM38 RNA-Seq Tissue single_read 40 4759734 2287003 139731 6.11% Metastatic ERG+
mctp_30TVGAAXX_3 aM38 RNA-Seq Tissue paired_end 40 6778935 3689892 280553 7.60% Metastatic ERG+
mctp_43620AAXX_6 aM15 RNA-Seq Tissue paired_end 38 13825315 11684425 950874 8.14% Metastatic ERG+
mctp_3074VAAXX_3 aM15 RNA-Seq Tissue single_read 36 4744456 2087670 95102 4.56% Metastatic ERG+
mctp_3074VAAXX_5 aM37 RNA-Seq Tissue single_read 36 4509553 1941952 91631 4.72% Metastatic ETV1+
mctp_305KAAAXX_2 aM41 RNA-Seq Tissue single_read 36 4480735 1702019 74579 4.38% Metastatic ETV1+
mctp_20FETAAXX_8 aM41 RNA-Seq Tissue single_read 36 5372905 2091694 82686 4.03% Metastatic ETV1+
mctp_2074VAAXX_2 aM41 RNA-Seq Tissue single_read 36 5222746 2184030 88780 4.06% Metastatic ETV1+
mctp_3064VAAXX_6 ULM811239- RNA-Seq Tissue paired_end 40 9653726 10247077 1004315 9.80% Metastatic Negative
97
mctp_3064VAAXX_5 ULM82440-97 RNA-Seq Tissue paired_end 40 9822270 10358561 951893 9.19% Metastatic Negative
mctp_20E2PAAXX_7 aM11 RNA-Seq Tissue single_read 36 5201588 2333757 100570 4.65% Metastatic Negative
mctp_42CJFAAXX_6 aM20 RNA-Seq Tissue paired_end 40 9038499 8821509 572135 6.49% Metastatic Negative
mctp_20EXPAAXX_6 aM36 RNA-Seq Tissue single_read 36 5587558 2277795 104747 4.60% Metastatic Negative
mctp_30CW7AAXX_6 aM36 RNA-Seq Tissue single_read 40 9198611 3833469 193678 5.05% Metastatic Negative
mctp_307VGAAXX_1 aM36 RNA-Seq Tissue paired_end 40 7749518 2430500 141723 5.83% Metastatic Negative
mctp_205K4AAXX_1 aM36 RNA-Seq Tissue single_read 36 5097473 2217107 126224 5.69% Metastatic Negative
mctp_20E7PAAXX_2 aM39 RNA-Seq Tissue single_read 36 5516548 235217 113714 4.86% Metastatic Negative
mctp_307YGAAXX_5 aM39 RNA-Seq Tissue paired_end 40 6279578 3568922 236298 6.62% Metastatic Negative
mctp_20FETAAXX_7 aM39 RNA-Seq Tissue single_read 36 5354844 2117551 102001 4.82% Metastatic Negative
mctp_20E2PAAXX_8 aM43 RNA-Seq Tissue single_read 36 5497785 1680082 72729 4.33% Metastatic Negative
mctp_30CW7AAXX_7 aM43 RNA-Seq Tissue single_read 40 8489329 3952621 200213 5.07% Metastatic Negative
TOTAL 1723713421 1417627939 114448745 8.07%
TABLE 2
Merge
intron- Join Filter
Classification redundant Informatic transcript intronic UCSC
Chromosome Cuffcompare tree filter transcripts filters fragments pre-mRNA Canonical Refseq
chr1 759121 272072 12701 5030 4489 3652 2499 3334
chr2 581574 206281 9353 3224 2856 2361 1579 2023
chr3 518621 167071 5706 2917 2560 2053 1312 1816
chr4 329950 103113 5160 2019 1731 1444 977 1238
chr5 380613 126139 5833 2365 2067 1694 1104 1465
chr6 396848 145607 7580 2590 2309 1874 1370 1667
chr7 432152 134051 6432 2355 2132 1703 1326 1583
chr8 308935 97724 4226 1729 1529 1243 848 1210
chr9 359300 122626 4069 1937 1767 1402 1114 1272
chr10 354625 103512 3509 1672 1508 1226 998 1382
chr11 424606 165211 6909 2922 2640 2102 1566 2023
chr12 425280 138650 6872 2653 2373 1858 1233 1668
chr13 159649 68284 3616 1118 908 751 425 549
chr14 261497 123741 4842 1806 1619 1308 855 1102
chr15 291241 108058 5816 1884 1626 1321 1362 1127
chr16 364747 124182 3968 2002 1835 1386 1093 1311
chr17 473261 168469 5581 2780 2582 1950 1480 1907
chr18 144300 49112 2504 785 682 539 377 459
chr19 494738 189411 7209 3543 3239 2269 1668 2314
chr20 217223 70308 3059 1243 1158 907 659 926
chr21 113368 29728 939 495 436 354 306 427
chr22 223385 73509 2401 1156 1068 798 633 771
chrX 222743 94591 4997 1516 1349 1161 959 1841
chrY 15190 4039 272 81 71 59 148 254
Total 8253710 2885489 123554 49822 44534 35415 25921 33669
TABLE 3
# Uniquely
Peak mapped
Antibody Antibody Finder reads (in # Peaks
GEO ID File name Pubmed ID used vendor Used millions) Called
GSM353631 VCaP_regular_medium_H3K4me1 20478527 ab8895 Abcam MACS 6.96 23116
GSM353632 VCaP_regular_medium_H3K4me2 20478527 ab7766 Abcam MACS 5.97 74153
GSM353620 VCaP_regular_medium_H3K4me3 20478527 ab8580 Abcam MACS 10.95 30043
GSM353624 VCaP_regular_medium_H3K35me3 20478527 ab9050 Abcam SICER 9.91 29860
GSM353629 VCaP_regular_medium_Ace_H3 20478527 06-599 Millipore MACS 4.76 41971
GSM353622 VCaP_regular_medium_Pan_H3 20478527 ab1791 Abcam MACS 5.91 control
GSM353623 VCaP_regular_medium_Polil 20478527 ab817 Abcam MACS 6.88 16041
GSM353634 LNCaP_regular_medium_H3K4me1 20478527 ab8895 Abcam MACS 6.19 31109
GSM353635 LNCaP_regular_medium_H3K4me2 20478527 ab7765 Abcam MACS 6.14 62061
GSM353626 LNCaP_regular_medium_H3K4me3 20478527 ab8580 Abcam MACS 10.22 19638
GSM353627 LNCaP_regular_medium_H3K36me3 20478527 ab9050 Abcam SICER 9.15 24932
GSM353628 LNCaP_regular_medium_Ace_H3 20478527 06-599 Millipore MACS 4.76 33211
GSM353617 LNCaP_Ethl_Polil 20478527 ab817 Abcam MACS 1.36 8232
GSM353653 tissue_H3K4me3 20478527 ab8580 Abcam MACS 11.85 23750
TABLE 4
Fold
change SAM score
Category Type Name Interval (Unlogged) ((r)/(s + s0))
PROTEIN UPREG. TU_0084471_0 chr5: 33980375-34087770 12.75 7.71
NOVEL UPREG. TU_0099865_0 chr8: 128087842-128095202 7.07 7.41
PROTEIN UPREG. TU_0123088_0 chr2: 238147710-238169707 3.01 7.01
ncRNA UPREG. TU_0102832_0 chr9: 78569118-78593537 12.23 6.93
PROTEIN UPREG. TU_0078322_0 chr12: 32260254-32260805 4.52 6.82
ncRNA UPREG. TU_0101270_0 chr21: 41853044-41875166 9.82 6.79
PROTEIN UPREG. TU_0027326_0 chrX: 16874726-17077384 3.31 6.79
PROTEIN UPREG. TU_0092114_0 chr11: 60223535-60239968 7.48 6.65
PROTEIN UPREG. TU_0044448_0 chr13: 51509122-51537693 4.77 6.59
PROTEIN UPREG. TU_0023159_0 chr19: 40224450-40249318 3.69 6.56
PROTEIN UPREG. TU_0092116_0 chr11: 60238519-60239968 7.50 6.44
PROTEIN UPREG. TU_0123090_0 chr2: 238164428-238165452 3.57 6.24
ncRNA UPREG. TU_0046239_0 chr4: 1185645-1201937 5.19 6.22
PROTEIN UPREG. TU_0122750_0 chr2: 231610299-231625861 4.56 6.14
PROTEIN UPREG. TU_0082723_0 chr12: 120142512-120219979 3.26 6.13
PROTEIN UPREG. TU_0123089_0 chr2: 238164428-238165452 4.22 6.12
PROTEIN UPREG. TU_0101111_0 chr21: 36989329-37045253 4.04 6.04
PROTEIN UPREG. TU_0090152_0 chr11: 4965638-4969515 6.38 5.99
PROTEIN UPREG. TU_0101113_0 chr21: 36994126-37045253 3.76 5.98
PROTEIN UPREG. TU_0045026_0 chr13: 94660907-94668260 3.68 5.97
ncRNA UPREG. TU_0101274_0 chr21: 41869930-41870631 8.95 5.88
PROTEIN UPREG. TU_0046235_0 chr4: 1181913-1189142 4.28 5.87
NOVEL UPREG. TU_0054603_0 chr16: 82380933-82394836 7.25 5.84
PROTEIN UPREG. TU_0101308_0 chr21: 42605257-42608791 4.97 5.83
PROTEIN UPREG. TU_0084137_0 chr5: 13981150-13997615 3.91 5.80
PROTEIN UPREG. TU_0084127_0 chr5: 13882635-13892514 4.95 5.79
PROTEIN UPREG. TU_0101119_0 chr21: 37034016-37045253 3.56 5.78
PROTEIN UPREG. TU_0054919_0 chr16: 88188842-88191143 3.46 5.75
PROTEIN UPREG. TU_0120963_0 chr2: 172658361-172662549 27.56 5.66
PROTEIN UPREG. TU_0044977_0 chr13: 94524392-94621526 3.64 5.64
PROTEIN UPREG. TU_0052614_0 chr16: 20542057-20616514 6.65 5.63
NOVEL UPREG. TU_0084303_0 chr5: 15899476-15955226 7.46 5.61
PROTEIN UPREG. TU_0060406_0 chr1: 28134091-28158290 3.03 5.61
PROTEIN UPREG. TU_0060407_0 chr1: 28155047-28170460 2.41 5.60
ncRNA UPREG. TU_0103252_0 chr9: 96357168-96369978 5.00 5.58
PROTEIN UPREG. TU_0034719_0 chr14: 73490756-73555773 2.51 5.57
PROTEIN UPREG. TU_0070457_0 chr20: 2258975-2269890 6.49 5.56
NOVEL UPREG. TU_0114240_0 chr2: 1534883-1538193 5.25 5.54
PROTEIN UPREG. TU_0087676_0 chr5: 138643394-138648458 2.75 5.50
PROTEIN UPREG. TU_0084138_0 chr5: 13976388-13981285 4.09 5.48
ncRNA UPREG. TU_0046237_0 chr4: 1162036-1195088 4.29 5.47
ncRNA UPREG. TU_0060421_0 chr1: 28157480-28158290 3.12 5.44
PROTEIN UPREG. TU_0061436_0 chr1: 37954250-37957136 2.66 5.41
PROTEIN UPREG. TU_0044894_0 chr13: 94470096-94752898 2.85 5.38
PROTEIN UPREG. TU_0034720_0 chr14: 73486609-73503474 2.20 5.38
PROTEIN UPREG. TU_0090153_0 chr11: 4969009-4970186 7.37 5.34
PROTEIN UPREG. TU_0061432_0 chr1: 37954250-37958679 2.65 5.31
PROTEIN UPREG. TU_0090268_0 chr11: 6659768-6661138 1.76 5.30
PROTEIN UPREG. TU_0084120_0 chr5: 13743434-13864864 3.59 5.29
PROTEIN UPREG. TU_0045059_0 chr13: 94638351-94639152 2.93 5.28
ncRNA UPREG. TU_0075807_0 chr10: 101676895-101680049 2.61 5.27
PROTEIN UPREG. TU_0078285_0 chr12: 32150992-32421799 3.02 5.26
PROTEIN UPREG. TU_0103019_0 chr9: 87826642-87905011 2.77 5.22
PROTEIN UPREG. TU_0046244_0 chr4: 1185645-1216291 3.81 5.21
PROTEIN UPREG. TU_0075664_0 chr10: 98752046-98935267 4.15 5.20
PROTEIN UPREG. TU_0090949_0 chr11: 24475021-25059245 3.50 5.19
NOVEL UPREG. TU_0099864_0 chr8: 128094589-128103681 3.56 5.17
PROTEIN UPREG. TU_0030273_0 chrX: 106690714-106735138 3.52 5.15
PROTEIN UPREG. TU_0090128_0 chr11: 4656012-4675667 5.26 5.15
PROTEIN UPREG. TU_0017700_0 chr17: 51183394-51209728 2.05 5.13
ncRNA UPREG. TU_0018760_0 chr17: 71645643-71652049 6.41 5.08
PROTEIN UPREG. TU_0018765_0 chr17: 71652262-71747927 5.18 5.06
ncRNA UPREG. TU_0114235_0 chr2: 1521347-1608386 4.22 5.04
PROTEIN UPREG. TU_0084132_0 chr5: 13964466-13969509 4.30 5.03
NOVEL UPREG. TU_0049368_0 chr4: 106772318-106772770 3.40 5.03
PROTEIN UPREG. TU_0115204_0 chr2: 27175274-27195587 2.37 4.99
PROTEIN UPREG. TU_0115205_0 chr2: 27163593-27178264 2.49 4.98
PROTEIN UPREG. TU_0062449_0 chr1: 46418568-46424753 1.95 4.96
PROTEIN UPREG. TU_0072027_0 chr20: 35964872-36007156 3.91 4.95
ncRNA UPREG. TU_0086706_0 chr5: 116818427-116835522 2.91 4.92
PROTEIN UPREG. TU_0084136_0 chr5: 13972327-13976416 3.37 4.91
PROTEIN UPREG. TU_0042761_0 chr13: 23200813-23363662 3.54 4.90
PROTEIN UPREG. TU_0114168_0 chr15: 99658271-99847175 2.25 4.89
ncRNA UPREG. TU_0018764_0 chr17: 71650143-71652049 6.28 4.86
PROTEIN UPREG. TU_0085832_0 chr5: 76150810-76167055 3.84 4.86
NOVEL UPREG. TU_0090142_0 chr11: 4748677-4760303 12.08 4.86
PROTEIN UPREG. TU_0103018_0 chr9: 87745936-87851451 2.41 4.83
NOVEL UPREG. TU_0096472_0 chr11: 133844590-133862924 6.85 4.82
PROTEIN UPREG. TU_0029229_0 chrX: 70349443-70377690 2.34 4.81
NOVEL UPREG. TU_0084306_0 chr5: 15896315-15947088 5.37 4.78
PROTEIN UPREG. TU_0024934_0 chr19: 54352845-54407356 1.88 4.77
NOVEL UPREG. TU_0096473_0 chr11: 133844590-133862995 6.96 4.76
ncRNA UPREG. TU_0101131_0 chr21: 36994126-37041774 3.57 4.74
PROTEIN UPREG. TU_0008239_0 chr7: 7362390-7537552 3.00 4.73
PROTEIN UPREG. TU_0000022_0 chr6: 1567640-2190842 2.14 4.72
PROTEIN UPREG. TU_0065193_0 chr1: 145122471-145183544 2.72 4.72
PROTEIN UPREG. TU_0061439_0 chr1: 37954250-37971671 2.46 4.71
ncRNA UPREG. TU_0096470_0 chr11: 133841573-133850753 6.44 4.70
PROTEIN UPREG. TU_0046219_0 chr4: 993725-995193 3.90 4.69
NOVEL UPREG. TU_0078288_0 chr12: 32393283-32405731 2.47 4.67
PROTEIN UPREG. TU_0101115_0 chr21: 37000839-37005920 3.31 4.67
NOVEL UPREG. TU_0099884_0 chr8: 128301493-128307576 2.65 4.66
PROTEIN UPREG. TU_0008489_0 chr7: 23685881-23708938 1.70 4.64
PROTEIN UPREG. TU_0042767_0 chr13: 23186666-23204319 4.82 4.64
PROTEIN UPREG. TU_0061430_0 chr1: 37930752-37957012 2.30 4.64
PROTEIN UPREG. TU_0079451_0 chr12: 52696814-52736068 3.77 4.64
PROTEIN UPREG. TU_0069545_0 chr1: 226711356-226712534 2.36 4.63
PROTEIN UPREG. TU_0045837_0 chr13: 113151239-113151444 3.73 4.61
PROTEIN UPREG. TU_0101138_0 chr21: 36994126-37004010 3.54 4.61
PROTEIN UPREG. TU_0049362_0 chr4: 106693102-106771686 3.06 4.58
PROTEIN UPREG. TU_0055044_0 chr16: 88589437-88613428 2.23 4.55
PROTEIN UPREG. TU_0038605_0 chr3: 52689830-52704651 1.54 4.55
ncRNA UPREG. TU_0062653_0 chr1: 51756544-51799759 2.52 4.54
PROTEIN UPREG. TU_0080359_0 chr12: 63512292-63558861 1.87 4.53
PROTEIN UPREG. TU_0012481_0 chr7: 111155336-111217889 2.04 4.52
PROTEIN UPREG. TU_0076355_0 chr10: 115970327-115995953 10.34 4.52
PROTEIN UPREG. TU_0099892_0 chr8: 128817416-128822629 2.33 4.52
ncRNA UPREG. TU_0050484_0 chr1: 28706931-28707187 2.53 4.51
PROTEIN UPREG. TU_0046232_0 chr4: 1147069-1175181 2.75 4.50
PROTEIN UPREG. TU_0107858_0 chr22: 40664589-40673116 2.27 4.50
PROTEIN UPREG. TU_0042794_0 chr13: 23228589-23228839 3.47 4.49
PROTEIN UPREG. TU_0057850_0 chr1: 1523259-1525373 2.80 4.48
PROTEIN UPREG. TU_0023156_0 chr19: 40109515-40127909 2.56 4.48
PROTEIN UPREG. TU_0102821_0 chr9: 78263916-78312152 2.98 4.48
PROTEIN UPREG. TU_0081659_0 chr12: 108636297-108700791 2.90 4.47
PROTEIN UPREG. TU_0049370_0 chr4: 106776991-106847697 2.15 4.47
PROTEIN UPREG. TU_0047672_0 chr4: 41807710-41840313 2.51 4.47
PROTEIN UPREG. TU_0114959_0 chr2: 24865860-24869912 1.68 4.46
PROTEIN UPREG. TU_0037043_0 chr3: 13332730-13436812 1.77 4.46
PROTEIN UPREG. TU_0087443_0 chr5: 135237637-135247034 4.09 4.46
PROTEIN UPREG. TU_0086635_0 chr5: 114489075-114543909 2.02 4.43
PROTEIN UPREG. TU_0107859_0 chr22: 40664589-40665721 2.38 4.42
NOVEL UPREG. TU_0106548_0 chr22: 22209111-22212055 6.49 4.42
PROTEIN UPREG. TU_0067165_0 chr1: 160797907-160845907 1.81 4.40
PROTEIN UPREG. TU_0020146_0 chr19: 3728970-3737293 2.53 4.39
PROTEIN UPREG. TU_0107642_0 chr22: 39046992-39047479 1.69 4.38
PROTEIN UPREG. TU_0016185_0 chr17: 31415814-31422953 3.63 4.38
NOVEL UPREG. TU_0104717_0 chr9: 130697833-130698832 2.79 4.36
PROTEIN UPREG. TU_0052105_0 chr16: 4785874-4786488 2.99 4.36
PROTEIN UPREG. TU_0059663_0 chr1: 21795295-21850886 1.99 4.35
PROTEIN UPREG. TU_0108030_0 chr22: 43527117-43638770 1.74 4.34
PROTEIN UPREG. TU_0093781_0 chr11: 67151991-67154057 2.48 4.33
PROTEIN UPREG. TU_0086924_0 chr5: 126233852-126241807 2.89 4.32
PROTEIN UPREG. TU_0048191_0 chr4: 72423780-72424347 2.93 4.32
PROTEIN UPREG. TU_0034727_0 chr14: 73508223-73508442 2.29 4.32
PROTEIN UPREG. TU_0096297_0 chr11: 128342286-128353900 1.84 4.31
PROTEIN UPREG. TU_0007829_0 chr7: 3625233-4275129 4.39 4.30
PROTEIN UPREG. TU_0116252_0 chr2: 47449810-47467636 1.93 4.30
PROTEIN UPREG. TU_0115216_0 chr2: 27175274-27177799 2.02 4.27
PROTEIN UPREG. TU_0018409_0 chr17: 65013419-65049811 2.02 4.26
PROTEIN UPREG. TU_0099847_0 chr8: 126511614-126519830 2.75 4.25
PROTEIN UPREG. TU_0035152_0 chr14: 81062791-81063412 2.22 4.25
PROTEIN UPREG. TU_0040936_0 chr3: 155391785-155458293 2.10 4.25
PROTEIN UPREG. TU_0027558_0 chrX: 23595491-23614436 1.66 4.25
PROTEIN UPREG. TU_0076460_0 chr10: 121248954-121292235 1.66 4.24
PROTEIN UPREG. TU_0067170_0 chr1: 160826739-160826994 2.10 4.23
PROTEIN UPREG. TU_0103050_0 chr9: 89409681-89512477 2.30 4.23
PROTEIN UPREG. TU_0112868_0 chr15: 77390455-77402242 1.55 4.23
PROTEIN UPREG. TU_0090960_0 chr11: 25059388-25060757 3.35 4.23
PROTEIN UPREG. TU_0072165_0 chr20: 40142077-40204030 4.69 4.22
PROTEIN UPREG. TU_0044687_0 chr13: 74756644-74954891 2.04 4.21
ncRNA UPREG. TU_0096477_0 chr11: 133879414-133850753 4.43 4.21
PROTEIN UPREG. TU_0093947_0 chr11: 68208575-68215238 1.41 4.20
PROTEIN UPREG. TU_0103253_0 chr9: 96405246-96442373 1.69 4.20
PROTEIN UPREG. TU_0091863_0 chr11: 57008498-57039966 2.69 4.20
PROTEIN UPREG. TU_0106199_0 chr22: 18308042-18314411 3.94 4.20
NOVEL UPREG. TU_0090140_0 chr11: 4748163-4759145 6.33 4.20
PROTEIN UPREG. TU_0103051_0 chr9: 89302442-89409890 2.37 4.19
NOVEL UPREG. TU_0078290_0 chr12: 32394534-32410898 3.20 4.19
PROTEIN UPREG. TU_0029336_0 chrX: 70669659-70712461 1.70 4.18
PROTEIN UPREG. TU_0092155_0 chr11: 60871597-60886554 1.80 4.18
PROTEIN UPREG. TU_0095597_0 chr11: 114549577-114880335 1.75 4.18
PROTEIN UPREG. TU_0082724_0 chr12: 120230545-120274615 1.42 4.17
PROTEIN UPREG. TU_0079770_0 chr12: 55040666-55042824 4.25 4.16
PROTEIN UPREG. TU_0000263_0 chr6: 4060925-4080831 1.55 4.16
NOVEL UPREG. TU_0040394_0 chr3: 133418632-133441282 3.46 4.16
PROTEIN UPREG. TU_0066594_0 chr1: 154245443-154257363 1.40 4.15
PROTEIN UPREG. TU_0099852_0 chr8: 126515081-126519830 2.81 4.15
PROTEIN UPREG. TU_0100363_0 chr8: 144891741-144899598 2.24 4.14
PROTEIN UPREG. TU_0096461_0 chr11: 133751095-133757235 2.10 4.13
ncRNA UPREG. TU_0044488_0 chr13: 51641093-51641330 2.76 4.13
PROTEIN UPREG. TU_0048990_0 chr4: 95592056-95804933 2.30 4.13
NOVEL UPREG. TU_0078293_0 chr12: 32396393-32414822 2.90 4.13
PROTEIN UPREG. TU_0046201_0 chr4: 991841-1010686 2.57 4.12
PROTEIN UPREG. TU_0091866_0 chr11: 57008498-57010253 2.54 4.12
PROTEIN UPREG. TU_0011133_0 chr7: 94378726-94759741 1.77 4.12
PROTEIN UPREG. TU_0122941_0 chr2: 234410713-234427931 3.28 4.12
PROTEIN UPREG. TU_0084131_0 chr5: 13929889-13953380 2.62 4.12
NOVEL UPREG. TU_0084142_0 chr5: 14017046-14021379 3.59 4.11
PROTEIN UPREG. TU_0087955_0 chr5: 140931645-140931865 2.00 4.10
PROTEIN UPREG. TU_0085953_0 chr5: 79410392-79410908 3.35 4.10
PROTEIN UPREG. TU_0022288_0 chr19: 18357973-18360121 2.75 4.09
PROTEIN UPREG. TU_0085951_0 chr5: 79366959-79414885 3.01 4.09
PROTEIN UPREG. TU_0060849_0 chr1: 32572021-32574435 1.81 4.09
PROTEIN UPREG. TU_0087441_0 chr5: 134934290-134942617 2.74 4.09
PROTEIN UPREG. TU_0042725_0 chr13: 23148223-23200531 4.96 4.09
PROTEIN UPREG. TU_0039018_0 chr3: 66510805-66634168 1.69 4.08
PROTEIN UPREG. TU_0096299_0 chr11: 128340164-128347506 1.70 4.07
PROTEIN UPREG. TU_0022290_0 chr19: 18357973-18359195 2.64 4.07
PROTEIN UPREG. TU_0100684_0 chr8: 146190487-146191030 1.89 4.06
PROTEIN UPREG. TU_0042974_0 chr13: 26148671-26148967 2.81 4.06
NOVEL UPREG. TU_0084308_0 chr5: 15938753-15949124 4.09 4.06
NOVEL UPREG. TU_0082746_0 chr12: 120197102-120197416 4.97 4.06
PROTEIN UPREG. TU_0014355_0 chr17: 2650561-2887730 1.92 4.05
PROTEIN UPREG. TU_0114110_0 chr15: 99250537-99274351 2.01 4.05
PROTEIN UPREG. TU_0096341_0 chr11: 129534843-129585464 1.64 4.04
PROTEIN UPREG. TU_0052083_0 chr16: 4784094-4805339 2.71 4.04
NOVEL UPREG. TU_0078196_0 chr12: 32394534-32405549 2.92 4.04
PROTEIN UPREG. TU_0084126_0 chr5: 13892443-13903812 3.64 4.03
NOVEL UPREG. TU_0047312_0 chr4: 39217669-39222163 3.83 4.02
PROTEIN UPREG. TU_0008287_0 chr7: 8119340-8268973 1.65 4.02
PROTEIN UPREG. TU_0018937_0 chr17: 73714011-73714967 1.61 4.01
PROTEIN UPREG. TU_0048995_0 chr4: 95805027-95808417 2.47 4.00
PROTEIN UPREG. TU_0038694_0 chr3: 53810226-53855769 2.03 3.99
ncRNA UPREG. TU_0046233_0 chr4: 1202157-1232168 2.45 3.99
PROTEIN UPREG. TU_0019018_0 chr17: 75372094-75381243 2.25 3.98
PROTEIN UPREG. TU_0042326_0 chr3: 199123974-199125319 1.77 3.98
PROTEIN UPREG. TU_0099893_0 chr8: 128817416-128819105 2.23 3.98
PROTEIN UPREG. TU_0012491_0 chr7: 111304238-111362856 1.91 3.98
PROTEIN UPREG. TU_0112335_0 chr15: 70816880-70864494 1.71 3.97
PROTEIN UPREG. TU_0047964_0 chr4: 57020861-57038533 1.74 3.97
PROTEIN UPREG. TU_0052565_0 chr16: 19362784-19409995 1.98 3.96
NOVEL UPREG. TU_0042717_0 chr13: 23149908-23200198 4.95 3.96
PROTEIN UPREG. TU_0017374_0 chr17: 43380086-43404182 1.53 3.96
PROTEIN UPREG. TU_0071058_0 chr20: 20318209-20549154 2.02 3.96
PROTEIN UPREG. TU_0105741_0 chrY: 6971017-6998339 2.20 3.95
PROTEIN UPREG. TU_0018995_0 chr17: 74491566-74517485 1.64 3.94
PROTEIN UPREG. TU_0103055_0 chr9: 89512509-8913285 1.92 3.93
PROTEIN UPREG. TU_0041139_0 chr3: 171237964-171285906 1.91 3.93
PROTEIN UPREG. TU_0042325_0 chr3: 199124975-199143480 1.74 3.93
PROTEIN UPREG. TU_0020688_0 chr19: 8180084-8237335 1.60 3.93
PROTEIN UPREG. TU_0118314_0 chr2: 99086923-99100654 1.78 3.92
PROTEIN UPREG. TU_0017875_0 chr17: 54652767-54706896 2.33 3.92
PROTEIN UPREG. TU_0037277_0 chr3: 24134438-24511318 1.75 3.92
PROTEIN UPREG. TU_0047593_0 chr4: 40446539-40457235 1.90 3.91
PROTEIN UPREG. TU_0114108_0 chr15: 99235494-99274389 2.00 3.91
ncRNA UPREG. TU_0024530_0 chr19: 50889160-50909766 1.72 3.91
PROTEIN UPREG. TU_0008957_0 chr7: 38308886-38325338 2.62 3.91
PROTEIN UPREG. TU_0043122_0 chr13: 28981555-28989371 1.73 3.90
PROTEIN UPREG. TU_0076644_0 chr10: 127398227-127398596 2.06 3.90
PROTEIN UPREG. TU_0045423_0 chr13: 100053877-100125079 2.02 3.89
PROTEIN UPREG. TU_0045495_0 chr13: 107720446-107737194 2.06 3.88
PROTEIN UPREG. TU_0076648_0 chr10: 127412714-127442685 1.64 3.88
NOVEL UPREG. TU_0088857_0 chr5: 172259171-172275517 1.69 3.87
NOVEL UPREG. TU_0044453_0 chr13: 51505777-51524522 2.96 3.86
NOVEL UPREG. TU_0047330_0 chr4: 39217641-39222163 3.43 3.86
PROTEIN UPREG. TU_0100838_0 chr21: 30508275-30510244 2.43 3.86
NOVEL UPREG. TU_0106544_0 chr22: 22210421-22220506 4.27 3.85
ncRNA UPREG. TU_0100275_0 chr8: 144520506-144537551 2.11 3.85
PROTEIN UPREG. TU_0057466_0 chr18: 72853744-72866791 1.58 3.84
PROTEIN UPREG. TU_0040010_0 chr3: 126311839-126412928 2.16 3.84
PROTEIN UPREG. TU_0042800_0 chr13: 23360816-23370548 2.73 3.84
PROTEIN UPREG. TU_0117501_0 chr2: 74065748-74174193 1.71 3.83
PROTEIN UPREG. TU_0053389_0 chr16: 45673980-45701001 2.66 3.83
PROTEIN UPREG. TU_0087944_0 chr5: 140874777-140978925 1.47 3.83
PROTEIN UPREG. TU_0017393_0 chr17: 43389397-43390300 1.90 3.82
PROTEIN UPREG. TU_0008919_0 chr7: 38257158-38271020 1.93 3.82
PROTEIN UPREG. TU_0033383_0 chr14: 50259793-50367616 1.51 3.82
PROTEIN UPREG. TU_0049911_0 chr4: 139304784-139382952 2.48 3.82
PROTEIN UPREG. TU_0024366_0 chr19: 50100808-50104487 1.86 3.82
PROTEIN UPREG. TU_0070109_0 chr1: 243979271-244159914 1.56 3.81
PROTEIN UPREG. TU_0120975_0 chr2: 182104631-182107832 1.86 3.80
NOVEL UPREG. TU_0044933_0 chr13: 94755992-94760688 2.52 3.80
PROTEIN UPREG. TU_0103689_0 chr9: 111019219-111122750 1.75 3.80
PROTEIN UPREG. TU_0096460_0 chr11: 133734857-133786962 2.09 3.79
PROTEIN UPREG. TU_0071115_0 chr20: 24934888-24986948 1.48 3.79
PROTEIN UPREG. TU_0093783_0 chr11: 67153661-67153870 2.48 3.79
PROTEIN UPREG. TU_0047591_0 chr4: 40457999-40506655 1.79 3.79
PROTEIN UPREG. TU_0112336_0 chr15: 70830765-70838346 1.63 3.78
PROTEIN UPREG. TU_0066664_0 chr1: 154481433-154485049 2.29 3.78
PROTEIN UPREG. TU_0018812_0 chr17: 72119376-72151549 3.38 3.78
PROTEIN UPREG. TU_0110225_0 chr15: 48510091-48912722 3.60 3.78
ncRNA UPREG. TU_0054545_0 chr16: 79431010-79431852 10.26 3.78
PROTEIN UPREG. TU_0107643_0 chr22: 39072466-39093168 1.36 3.78
PROTEIN UPREG. TU_0025230_0 chr19: 55992773-56000199 1.86 3.78
PROTEIN UPREG. TU_0012480_0 chr7: 111153704-111155311 1.81 3.77
PROTEIN UPREG. TU_0070821_0 chr20: 8997167-9409281 1.64 3.77
PROTEIN UPREG. TU_0103873_0 chr9: 115151636-115178163 1.52 3.77
PROTEIN UPREG. TU_0018813_0 chr17: 72128611-72133119 3.56 3.76
NOVEL UPREG. TU_0112004_0 chr15: 67644390-67650387 3.56 3.76
PROTEIN UPREG. TU_0043118_0 chr13: 28981555-29067829 1.76 3.76
NOVEL UPREG. TU_0112003_0 chr15: 67645590-67775246 3.12 3.76
NOVEL UPREG. TU_0060446_0 chr1: 28438629-28450156 2.23 3.75
PROTEIN UPREG. TU_0122972_0 chr2: 236068012-236482693 1.69 3.75
NOVEL UPREG. TU_0106545_0 chr22: 22218478-22219162 3.99 3.74
PROTEIN UPREG. TU_0087283_0 chr5: 133753241-133766074 1.85 3.74
ncRNA UPREG. TU_0025312_0 chr19: 57059515-57145170 1.89 3.74
PROTEIN UPREG. TU_0079679_0 chr12: 54760142-54783545 1.58 3.73
PROTEIN UPREG. TU_0074564_0 chr10: 64241765-64246112 2.62 3.73
PROTEIN UPREG. TU_0106189_0 chr22: 18235213-18328816 1.82 3.73
PROTEIN UPREG. TU_0078994_0 chr12: 49412412-49428706 1.41 3.72
ncRNA UPREG. TU_0003229_0 chr6: 41598975-41621874 2.05 3.72
PROTEIN UPREG. TU_0040937_0 chr3: 155439710-155458293 1.96 3.72
PROTEIN UPREG. TU_0040093_0 chr3: 128830731-128874336 1.87 3.72
NOVEL UPREG. TU_0106542_0 chr22: 22211315-22220506 3.77 3.71
PROTEIN UPREG. TU_0019375_0 chr17: 77608812-77616980 1.63 3.71
PROTEIN UPREG. TU_0042563_0 chr13: 20264762-20334966 1.85 3.71
PROTEIN UPREG. TU_0103386_0 chr9: 9905734-99110148 1.89 3.71
PROTEIN UPREG. TU_0030004_0 chrX: 100534013-100534540 1.84 3.71
NOVEL UPREG. TU_0089906_0 chr11: 1042845-1045705 2.94 3.71
NOVEL UPREG. TU_0089014_0 chr5: 176014905-176015351 2.01 3.71
ncRNA UPREG. TU_0056173_0 chr18: 22523074-22537627 3.31 3.70
PROTEIN UPREG. TU_0052880_0 chr16: 28393117-28411069 1.48 3.70
PROTEIN UPREG. TU_0100355_0 chr8: 144884230-144910177 2.00 3.69
PROTEIN UPREG. TU_0096216_0 chr11: 125271293-125271517 2.08 3.69
PROTEIN UPREG. TU_0092161_0 chr11: 60884289-60892364 1.99 3.68
PROTEIN UPREG. TU_0086926_0 chr5: 126241953-126394149 2.27 3.68
NOVEL UPREG. TU_0088230_0 chr5: 148864170-148864752 1.94 3.68
ncRNA UPREG. TU_0099940_0 chr8: 129065546-129182684 1.61 3.68
PROTEIN UPREG. TU_0089017_0 chr5: 176222085-176240501 10.21 3.67
PROTEIN UPREG. TU_0078586_0 chr12: 46643629-46648944 1.47 3.67
PROTEIN UPREG. TU_0053467_0 chr16: 51028455-51138080 2.19 3.67
PROTEIN UPREG. TU_0089452_0 chr5: 179258704-179258997 1.62 3.67
PROTEIN UPREG. TU_0076329_0 chr10: 115501382-115531028 2.60 3.67
PROTEIN UPREG. TU_0047688_0 chr4: 42105164-42354144 1.68 3.67
PROTEIN UPREG. TU_0059142_0 chr1: 16203274-16206548 12.41 3.67
PROTEIN UPREG. TU_0116906_0 chr2: 63135968-63138462 2.81 3.66
PROTEIN UPREG. TU_0000154_0 chr6: 3063923-3099152 1.53 3.66
PROTEIN UPREG. TU_0088782_0 chr5: 170625426-170659593 1.78 3.66
NOVEL UPREG. TU_0089905_0 chr11: 1042845-1045705 2.77 3.66
PROTEIN UPREG. TU_0101704_0 chr9: 3265495-3516005 2.33 3.64
ncRNA UPREG. TU_0044897_0 chr13: 94746488-94760688 2.17 3.64
PROTEIN UPREG. TU_0071059_0 chr20: 20549245-20641260 2.39 3.64
ncRNA UPREG. TU_0046268_0 chr4: 1199698-1211108 1.93 3.63
PROTEIN UPREG. TU_0071601_0 chr20: 32827590-32828002 1.75 3.62
PROTEIN UPREG. TU_0100712_0 chr21: 15258179-15359100 2.14 3.62
PROTEIN UPREG. TU_0092156_0 chr11: 60885030-60893249 1.45 3.62
PROTEIN UPREG. TU_0091402_0 chr11: 46255779-46299542 1.71 3.62
PROTEIN UPREG. TU_0039018_0 chr3: 66376322-66514060 1.50 3.62
PROTEIN UPREG. TU_0100378_0 chr8: 144899799-144900640 2.00 3.62
NOVEL UPREG. TU_0112025_0 chr15: 67780574-67782345 3.42 3.62
PROTEIN UPREG. TU_0106031_0 chr22: 16336630-16412806 2.01 3.62
PROTEIN UPREG. TU_0050785_0 chr4: 174395360-174453821 2.36 3.61
PROTEIN UPREG. TU_0058834_0 chr1: 11768665-11783670 1.50 3.61
PROTEIN UPREG. TU_0039496_0 chr3: 106753939-106754201 1.99 3.61
ncRNA UPREG. TU_0098397_0 chr8: 69379259-69406175 2.73 3.61
PROTEIN UPREG. TU_0017847_0 chr17: 54188675-54413808 2.82 3.61
PROTEIN UPREG. TU_0108299_0 chr22: 49267227-49270226 2.03 3.60
PROTEIN UPREG. TU_0076846_0 chr10: 135042714-135056670 2.27 3.59
PROTEIN UPREG. TU_0096351_0 chr11: 129611827-129689996 1.61 3.59
PROTEIN UPREG. TU_0019298_0 chr17: 77242472-77300154 1.51 3.59
PROTEIN UPREG. TU_0057465_0 chr18: 72830973-7297379 1.56 3.59
PROTEIN UPREG. TU_0013475_0 chr7: 148137800-148212367 1.74 3.59
PROTEIN UPREG. TU_0001426_0 chr6: 28655044-28662198 2.56 3.59
NOVEL UPREG. TU_0106541_0 chr22: 22209111-22219162 4.02 3.58
PROTEIN UPREG. TU_0073803_0 chr10: 19005554-19007053 1.94 3.58
PROTEIN UPREG. TU_0040100_0 chr3: 129253916-129289610 1.39 3.58
PROTEIN UPREG. TU_0001431_0 chr6: 28978594-28999755 1.33 3.58
PROTEIN UPREG. TU_0076643_0 chr10: 127398227-127407663 1.73 3.57
PROTEIN UPREG. TU_0089137_0 chr5: 176814485-176815986 1.93 3.57
PROTEIN UPREG. TU_0098700_0 chr8: 82806988-82833618 1.76 3.57
PROTEIN UPREG. TU_0093785_0 chr11: 67186209-67198838 3.74 3.57
NOVEL UPREG. TU_0056168_0 chr18: 22477042-22477886 3.05 3.57
PROTEIN UPREG. TU_0067222_0 chr1: 164063363-164147501 1.63 3.57
PROTEIN UPREG. TU_0052172_0 chr16: 8799176-8799379 1.61 3.57
PROTEIN UPREG. TU_0008360_0 chr7: 16652301-16712672 1.46 3.57
PROTEIN UPREG. TU_0035610_0 chr14: 93580687-93582188 2.08 3.56
PROTEIN UPREG. TU_0000168_0 chr6: 3100128-3102765 2.10 3.56
PROTEIN UPREG. TU_0039649_0 chr3: 115160992-115164502 1.72 3.56
PROTEIN UPREG. TU_0052843_0 chr16: 27143818-27187607 1.42 3.56
NOVEL UPREG. TU_0024950_0 chr19: 54450100-54452968 2.11 3.55
PROTEIN UPREG. TU_0008504_0 chr7: 24656812-24693891 1.99 3.55
PROTEIN UPREG. TU_0061102_0 chr1: 35671678-35795597 1.44 3.55
PROTEIN UPREG. TU_0032890_0 chr14: 36736878-36788106 2.36 3.55
ncRNA UPREG. TU_0046241_0 chr4: 1158292-1167160 2.53 3.55
NOVEL UPREG. TU_0008499_0 chr7: 24236191-24236455 5.44 3.54
PROTEIN UPREG. TU_0100172_0 chr8: 142471307-142511866 1.78 3.54
NOVEL UPREG. TU_0086543_0 chr5: 110311813-110312092 1.53 3.53
PROTEIN UPREG. TU_0072450_0 chr20: 44619899-44747359 1.83 3.53
NOVEL UPREG. TU_0044931_0 chr13: 94755980-94759335 2.15 3.53
PROTEIN UPREG. TU_0093950_0 chr11: 68214746-68215218 1.49 3.53
PROTEIN UPREG. TU_0006239_0 chr6: 138649313-138671427 2.22 3.53
PROTEIN UPREG. TU_0065894_0 chr1: 150044684-150070988 1.54 3.52
PROTEIN UPREG. TU_0078675_0 chr12: 47602047-47602939 1.58 3.52
PROTEIN UPREG. TU_0052150_0 chr16: 8799176-8864674 1.42 3.52
NOVEL UPREG. TU_0112021_0 chr15: 67762926-67783593 2.66 3.52
PROTEIN UPREG. TU_0041581_0 chr3: 185450132-185459240 1.77 3.52
PROTEIN UPREG. TU_0017269_0 chr17: 42127174-42189979 1.59 3.52
PROTEIN UPREG. TU_0103138_0 chr9: 94055563-94056563 1.61 3.52
PROTEIN UPREG. TU_0078683_0 chr12: 47603989-47604485 1.69 3.52
PROTEIN UPREG. TU_0099209_0 chr11: 6453771-6453210 1.44 3.51
ncRNA UPREG. TU_0045193_0 chr13: 97851959-97852689 1.98 3.51
PROTEIN UPREG. TU_0050499_0 chr4: 156862572-156862939 1.82 3.51
PROTEIN UPREG. TU_0088025_0 chr5: 142130134-142254088 1.89 3.51
PROTEIN UPREG. TU_0052554_0 chr16: 19329285-19424714 1.78 3.51
PROTEIN UPREG. TU_0085653_0 chr5: 70918890-70990273 2.39 3.51
PROTEIN UPREG. TU_0101238_0 chr21: 41610494-41651888 1.89 3.50
PROTEIN UPREG. TU_0098689_0 chr8: 82355436-82355977 4.15 3.49
PROTEIN UPREG. TU_0100271_0 chr8: 144522379-144537551 1.93 3.49
PROTEIN UPREG. TU_0013258_0 chr7: 139750340-139773086 1.85 3.49
PROTEIN UPREG. TU_0122559_0 chr2: 224338108-224338327 2.32 3.49
PROTEIN UPREG. TU_0068947_0 chr1: 212567070-212567723 1.74 3.48
PROTEIN UPREG. TU_0101300_0 chr21: 42512421-42593934 1.60 3.48
PROTEIN UPREG. TU_0105268_0 chr9: 138238011-138277254 1.49 3.47
PROTEIN UPREG. TU_0080269_0 chr12: 62524730-62664317 2.05 3.47
PROTEIN UPREG. TU_0001992_0 chr6: 31939105-31955076 1.56 3.47
PROTEIN UPREG. TU_0018485_0 chr17: 70458432-70480451 1.58 3.47
ncRNA UPREG. TU_0050493_0 chr1: 28705947-28706605 1.60 2.46
PROTEIN UPREG. TU_0085975_0 chr5: 79478814-79495113 1.91 3.46
PROTEIN UPREG. TU_0018919_0 chr17: 73678343-73714970 1.48 3.46
ncRNA UPREG. TU_0054534_0 chr16: 79404014-79431652 9.85 3.46
PROTEIN UPREG. TU_0076107_0 chr10: 104454315-104488075 1.67 3.45
ncRNA UPREG. TU_0069658_0 chr1: 229724782-229731269 1.75 3.45
NOVEL UPREG. TU_0120387_0 chr2: 170267824-170281386 2.10 3.45
PROTEIN UPREG. TU_0015665_0 chr17: 24073407-24077926 1.52 3.45
ncRNA UPREG. TU_0070414_0 chr20: 1254059-1303172 1.68 3.45
NOVEL UPREG. TU_0072624_0 chr20: 47335522-47338977 1.65 3.45
PROTEIN UPREG. TU_0012495_0 chr7: 111373031-111411626 2.29 3.45
PROTEIN UPREG. TU_0076659_0 chr10: 127514501-127526128 1.31 3.45
PROTEIN UPREG. TU_0088525_0 chr5: 156625701-156755178 1.53 3.45
PROTEIN UPREG. TU_0046096_0 chr4: 759449-809939 2.01 3.44
ncRNA UPREG. TU_0074332_0 chr10: 43420869-43421283 1.52 3.44
PROTEIN UPREG. TU_0082983_0 chr12: 121778239-121779189 2.65 3.44
PROTEIN UPREG. TU_0008361_0 chr7: 16759923-16790805 1.58 3.44
PROTEIN UPREG. TU_0061443_0 chr1: 38032067-38039550 1.67 3.44
PROTEIN UPREG. TU_0042715_0 chr13: 23148223-23204319 3.68 3.43
ncRNA UPREG. TU_0119128_0 chr2: 118310197-118313068 1.62 3.43
PROTEIN UPREG. TU_0112349_0 chr15: 70834440-70835126 1.67 3.43
PROTEIN UPREG. TU_0027543_0 chrX: 21921233-21922374 2.48 3.43
PROTEIN UPREG. TU_0062582_0 chr1: 47489058-47552320 1.83 3.43
ncRNA UPREG. TU_0050791_0 chr4: 174322695-174323924 2.13 3.41
PROTEIN UPREG. TU_0048346_0 chr4: 77175264-77176185 2.48 3.41
NOVEL UPREG. TU_0093068_0 chr11: 64956616-64961189 2.13 3.41
PROTEIN UPREG. TU_0033869_0 chr14: 60248258-60260801 1.21 3.41
PROTEIN UPREG. TU_0000031_0 chr6: 2190031-2190908 2.44 3.41
PROTEIN UPREG. TU_0082131_0 chr12: 111151572-111152227 1.88 3.40
PROTEIN UPREG. TU_0038169_0 chr3: 49035494-49041923 1.35 3.40
NOVEL UPREG. TU_0044898_0 chr13: 94753009-94760688 2.11 3.40
PROTEIN UPREG. TU_0089144_0 chr5: 176814489-176815986 1.86 3.40
PROTEIN UPREG. TU_0094504_0 chr11: 74812477-74817273 2.40 3.40
PROTEIN UPREG. TU_0035633_0 chr14: 94304291-94305127 2.17 3.40
PROTEIN UPREG. TU_0085819_0 chr5: 75734806-76039614 1.64 3.40
PROTEIN UPREG. TU_0061431_0 chr1: 37961347-37973585 2.62 3.40
NOVEL UPREG. TU_0078299_0 chr12: 32290896-32292169 3.67 3.39
PROTEIN UPREG. TU_0004059_0 chr6: 52976378-53034598 1.65 3.39
PROTEIN UPREG. TU_0098927_0 chr8: 95722432-95788870 1.48 3.39
ncRNA UPREG. TU_0013886_0 chr7: 155957953-156090820 2.50 3.39
PROTEIN UPREG. TU_0068377_0 chr1: 201452418-201458956 1.84 3.39
NOVEL UPREG. TU_0101035_0 chr21: 35419563-36421930 1.84 3.39
PROTEIN UPREG. TU_0062957_0 chr1: 54089897-54128073 1.43 3.39
PROTEIN UPREG. TU_0099854_0 chr8: 127633901-127639897 1.65 3.38
PROTEIN UPREG. TU_0048743_0 chr4: 87924751-87955166 1.47 3.38
PROTEIN UPREG. TU_0086478_0 chr5: 102510255-102521832 1.95 3.38
PROTEIN UPREG. TU_0120565_0 chr2: 172672776-172675279 4.31 3.38
PROTEIN UPREG. TU_0122360_0 chr2: 219554051-219557439 2.92 3.38
PROTEIN UPREG. TU_0092154_0 chr11: 60857271-60874474 1.44 3.37
PROTEIN UPREG. TU_0015718_0 chr17: 24095069-24100305 1.64 3.37
PROTEIN UPREG. TU_0039284_0 chr3: 95208586-95249573 2.23 3.37
PROTEIN UPREG. TU_0082089_0 chr12: 111082307-111187476 1.44 3.37
PROTEIN UPREG. TU_0035148_0 chr14: 81009021-81069951 1.64 3.37
PROTEIN UPREG. TU_0054849_0 chr16: 87403253-87406669 1.47 3.37
PROTEIN UPREG. TU_0113376_0 chr15: 87432680-87545107 2.13 3.36
PROTEIN UPREG. TU_0019481_0 chr17: 77998514-77999441 1.55 3.36
PROTEIN UPREG. TU_0007004_0 chr6: 158396021-158440190 1.47 3.36
PROTEIN UPREG. TU_0092190_0 chr11: 60876795-60877493 1.85 3.36
ncRNA UPREG. TU_0001996_0 chr6: 31941546-31959679 1.43 3.36
NOVEL UPREG. TU_0066689_0 chr1: 154509233-154510967 1.61 3.36
PROTEIN UPREG. TU_0035151_0 chr14: 81015445-81021875 2.00 3.35
PROTEIN UPREG. TU_0092866_0 chr11: 63975211-63975675 3.20 3.35
PROTEIN UPREG. TU_0050482_0 chr4: 156807332-156877628 1.69 3.35
PROTEIN UPREG. TU_0022391_0 chr19: 19076718-19094443 1.60 3.35
PROTEIN UPREG. TU_0048729_0 chr4: 87734463-87924734 1.74 3.35
PROTEIN UPREG. TU_0103472_0 chr9: 100534124-100570357 1.61 3.35
PROTEIN UPREG. TU_0087465_0 chr5: 136431191-136431490 2.47 3.35
PROTEIN UPREG. TU_0058833_0 chr1: 11768665-11788581 1.45 3.34
PROTEIN DOWNREG. TU_0009047_0 chr7: 41967123-41970103 0.65 −3.35
PROTEIN DOWNREG. TU_0020039_0 chr19: 2948637-2980244 0.65 −3.36
PROTEIN DOWNREG. TU_0024046_0 chr19: 47194316-47201741 0.53 −3.36
PROTEIN DOWNREG. TU_0120035_0 chr2: 154042114-154043553 0.49 −3.36
PROTEIN DOWNREG. TU_0014542_0 chr17: 4790024-4790984 0.77 −3.36
PROTEIN DOWNREG. TU_0058703_0 chr1: 10457547-10613394 0.66 −3.37
NOVEL DOWNREG. TU_0084922_0 chr5: 44337219-44338127 0.51 −3.37
PROTEIN DOWNREG. TU_0067333_0 chr1: 167362572-167539064 0.68 −3.37
PROTEIN DOWNREG. TU_0030086_0 chrX: 101794939-101798995 0.64 −3.37
PROTEIN DOWNREG. TU_0031101_0 chrX: 134247418-134254372 0.69 −3.37
PROTEIN DOWNREG. TU_0063762_0 chr1: 87566944-87583813 0.66 −3.38
PROTEIN DOWNREG. TU_0107584_0 chr22: 38075931-38123808 0.66 −3.38
PROTEIN DOWNREG. TU_0102296_0 chr9: 34979701-34988409 0.57 −3.38
PROTEIN DOWNREG. TU_0038455_0 chr3: 51951847-51958668 0.65 −3.38
PROTEIN DOWNREG. TU_0062948_0 chr1: 53744574-53746867 0.46 −3.38
PROTEIN DOWNREG. TU_0092655_0 chr11: 63282470-63288729 0.73 −3.38
PROTEIN DOWNREG. TU_0035606_0 chr14: 93470258-93500717 0.58 −3.38
PROTEIN DOWNREG. TU_0055588_0 chr18: 10470831-10478699 0.58 −3.38
PROTEIN DOWNREG. TU_0056462_0 chr18: 41558112-41584622 0.49 −3.39
PROTEIN DOWNREG. TU_0002739_0 chr6: 35321958-35328561 0.55 −3.39
PROTEIN DOWNREG. TU_0030147_0 chrX: 102727067-102729284 0.65 −3.39
NOVEL DOWNREG. TU_0030209_0 chrX: 103250901-103253228 0.66 −3.39
ncRNA DOWNREG. TU_0068206_0 chr1: 200132176-200134973 0.60 −3.39
PROTEIN DOWNREG. TU_0081627_0 chr12: 108186419-108190411 0.63 −3.40
PROTEIN DOWNREG. TU_0068194_0 chr1: 200132176-200182322 0.59 −3.40
PROTEIN DOWNREG. TU_0049308_0 chr4: 104220026-104220361 0.46 −3.40
NOVEL DOWNREG. TU_0068431_0 chr1: 202350966-202363482 0.62 −3.40
PROTEIN DOWNREG. TU_0073506_0 chr10: 7630096-7723984 0.60 −3.40
PROTEIN DOWNREG. TU_0054695_0 chr16: 83411105-83499914 0.62 −3.40
PROTEIN DOWNREG. TU_0012556_0 chr7: 115934290-115935899 0.50 −3.41
PROTEIN DOWNREG. TU_0018647_0 chr17: 71259157-71294839 0.74 −3.41
NOVEL DOWNREG. TU_0030577_0 chrX: 118036531-118036860 0.43 −3.41
PROTEIN DOWNREG. TU_0089961_0 chr11: 2248339-2247566 0.52 −3.41
PROTEIN DOWNREG. TU_0000888_0 chr6: 19947236-19950403 0.56 −3.41
PROTEIN DOWNREG. TU_0002212_0 chr6: 32224073-32226328 0.56 −3.41
PROTEIN DOWNREG. TU_0024749_0 chr19: 52937559-52939100 0.58 −3.41
PROTEIN DOWNREG. TU_0101225_0 chr21: 40161189-40161418 0.52 −3.41
ncRNA DOWNREG. TU_0100030_0 chr8: 134653589-134655310 0.41 −3.41
PROTEIN DOWNREG. TU_0102256_0 chr9: 34356684-34366854 0.56 −3.41
PROTEIN DOWNREG. TU_0039040_0 chr3: 69107066-69108860 0.62 −3.42
ncRNA DOWNREG. TU_0115808_0 chr2: 37722515-37725828 0.61 −3.42
PROTEIN DOWNREG. TU_0115807_0 chr2: 37722515-37725828 0.61 −3.42
NOVEL DOWNREG. TU_0038811_0 chr3: 57890130-57890834 0.43 −3.43
PROTEIN DOWNREG. TU_0107000_0 chr22: 29790122-29830660 0.60 −3.43
PROTEIN DOWNREG. TU_0065126_0 chr1: 144274405-144279906 0.53 −3.43
PROTEIN DOWNREG. TU_0065093_0 chr1: 144167535-144181746 0.72 −3.43
PROTEIN DOWNREG. TU_0066887_0 chr1: 158352167-158379985 0.56 −3.44
PROTEIN DOWNREG. TU_0034681_0 chr14: 73248261-73250867 0.61 −3.44
PROTEIN DOWNREG. TU_0064872_0 chr1: 115373945-115394701 0.60 −3.44
PROTEIN DOWNREG. TU_0115146_0 chr2: 26806070-26809827 0.49 −3.44
PROTEIN DOWNREG. TU_0023552_0 chr19: 43433715-43439100 0.52 −3.44
PROTEIN DOWNREG. TU_0013056_0 chr2: 134269121-134269574 0.41 −3.44
PROTEIN DOWNREG. TU_0078015_0 chr12: 21809160-21817495 0.61 −3.45
PROTEIN DOWNREG. TU_0010849_0 chr7: 84462824-84464278 0.41 −3.45
PROTEIN DOWNREG. TU_0018278_0 chr17: 62235564-62237319 0.62 −3.45
PROTEIN DOWNREG. TU_0106896_0 chr22: 28206216-28217370 0.46 −3.46
PROTEIN DOWNREG. TU_0086308_0 chr5: 95158335-95154222 0.54 −3.46
PROTEIN DOWNREG. TU_0059500_0 chr1: 19842799-19857540 0.66 −3.46
PROTEIN DOWNREG. TU_0030156_0 chrX: 102749504-102752161 0.61 −3.46
PROTEIN DOWNREG. TU_0053209_0 chr16: 30815439-30839057 0.45 −3.46
PROTEIN DOWNREG. TU_0102372_0 chr9: 35672000-35681106 0.58 −3.46
PROTEIN DOWNREG. TU_0040491_0 chr3: 134947802-134980329 0.35 −3.46
PROTEIN DOWNREG. TU_0063025_0 chr1: 54832256-54849445 0.56 −3.46
PROTEIN DOWNREG. TU_0016741_0 chr17: 37808007-37818100 0.61 −3.47
PROTEIN DOWNREG. TU_0079872_0 chr12: 53272841-55276238 0.70 −3.47
NOVEL DOWNREG. TU_0072214_0 chr20: 42166331-42172501 0.45 −3.47
PROTEIN DOWNREG. TU_0069254_0 chr1: 223745864-223750945 0.54 −3.48
PROTEIN DOWNREG. TU_0014474_0 chr17: 4410320-4410614 0.34 −3.48
PROTEIN DOWNREG. TU_0002034_0 chr6: 31975375-31977685 0.61 −3.48
ncRNA DOWNREG. TU_0115805_0 chr2: 37722515-37727509 0.64 −3.48
PROTEIN DOWNREG. TU_0106487_0 chr22: 21742726-21797216 0.56 −3.48
PROTEIN DOWNREG. TU_0100880_0 chr21: 32808766-32809639 0.62 −3.48
PROTEIN DOWNREG. TU_0028960_0 chrX: 64873768-64873981 0.59 −3.48
PROTEIN DOWNREG. TU_0103717_0 chr9: 112675334-112676369 0.59 −3.48
PROTEIN DOWNREG. TU_0016732_0 chr17: 37807991-37828819 0.65 −3.48
PROTEIN DOWNREG. TU_0075573_0 chr10: 96987317-97040810 0.65 −3.48
PROTEIN DOWNREG. TU_0108979_0 chr15: 34659121-34889737 0.68 −3.48
PROTEIN DOWNREG. TU_0039868_0 chr3: 123526763-123543198 0.51 −3.48
PROTEIN DOWNREG. TU_0032236_0 chr14: 22885061-22893832 0.61 −3.48
PROTEIN DOWNREG. TU_0103902_0 chr9: 115957988-116128421 0.59 −3.49
PROTEIN DOWNREG. TU_0004251_0 chr6: 71069214-71069482 0.36 −3.49
PROTEIN DOWNREG. TU_0115344_0 chr2: 27568254-27571592 0.64 −3.49
NOVEL DOWNREG. TU_0094307_0 chr11: 7977293-7979927 0.69 −3.49
NOVEL DOWNREG. TU_0020914_0 chr19: 9718612-9721799 0.47 −3.49
PROTEIN DOWNREG. TU_0014009_0 chr7: 158513133-158630217 0.48 −3.50
PROTEIN DOWNREG. TU_0111467_0 chr15: 62817064-62854842 0.58 −3.50
NOVEL DOWNREG. TU_0088552_0 chr5: 157103352-157120455 0.64 −3.50
PROTEIN DOWNREG. TU_0016616_0 chr17: 36992038-37034423 0.44 −3.50
PROTEIN DOWNREG. TU_0109820_0 chr15: 41600571-41611159 0.56 −3.51
PROTEIN DOWNREG. TU_0083744_0 chr5: 236838-237985 0.50 −3.51
PROTEIN DOWNREG. TU_0038899_0 chr3: 58465926-58495812 0.58 −3.51
PROTEIN DOWNREG. TU_0018817_0 chr17: 72183287-72184800 0.61 −3.51
PROTEIN DOWNREG. TU_0096362_0 chr11: 129779777-129794214 0.56 −3.51
ncRNA DOWNREG. TU_0104765_0 chr9: 131134480-131144297 0.53 −3.51
PROTEIN DOWNREG. TU_0047809_0 chr4: 52581019-52582331 0.62 −3.52
PROTEIN DOWNREG. TU_0114638_0 chr2: 11804193-11884972 0.68 −3.52
PROTEIN DOWNREG. TU_0110215_0 chr15: 43246574-43254766 0.63 −3.52
PROTEIN DOWNREG. TU_0117024_0 chr2: 66515747-66653430 0.61 −3.52
PROTEIN DOWNREG. TU_0109004_0 chr15: 35178588-35180010 0.39 −3.53
PROTEIN DOWNREG. TU_0114005_0 chr15: 97462760-97493368 0.56 −3.53
PROTEIN DOWNREG. TU_0079534_0 chr12: 53260191-53268540 0.41 −3.53
PROTEIN DOWNREG. TU_0058435_0 chr1: 202366748-202385528 0.62 −3.53
PROTEIN DOWNREG. TU_0014730_0 chr17: 7034460-7061662 0.61 −3.53
PROTEIN DOWNREG. TU_0111099_0 chr15: 57738640-57756015 0.70 −3.54
PROTEIN DOWNREG. TU_0079355_0 chr12: 51906937-51912605 0.54 −3.54
PROTEIN DOWNREG. TU_0107389_0 chr22: 36670710-36671784 0.59 −3.54
PROTEIN DOWNREG. TU_0105434_0 chr9: 138991774-138996018 0.54 −3.54
ncRNA DOWNREG. TU_0122441_0 chr2: 220000172-220002664 0.38 −3.54
PROTEIN DOWNREG. TU_0074041_0 chr10: 29785041-30065975 0.64 −3.55
PROTEIN DOWNREG. TU_0114819_0 chr2: 23779564-23785016 0.65 −3.55
PROTEIN DOWNREG. TU_0013666_0 chr7: 150180552-150189309 0.34 −3.55
PROTEIN DOWNREG. TU_0036844_0 chr3: 9930678-9933062 0.54 −3.56
PROTEIN DOWNREG. TU_0014467_0 chr17: 4407802-4410614 0.49 −3.56
NOVEL DOWNREG. TU_0036397_0 chr14: 104617328-104624500 0.45 −3.56
PROTEIN DOWNREG. TU_0014721_0 chr17: 6882853-6884238 0.60 −3.57
PROTEIN DOWNREG. TU_0061867_0 chr1: 41618433-41621890 0.61 −3.57
PROTEIN DOWNREG. TU_0090901_0 chr11: 20061238-20099725 0.60 −3.57
PROTEIN DOWNREG. TU_0089503_0 chr5: 179949721-179951068 0.47 −3.57
NOVEL DOWNREG. TU_0112056_0 chr15: 69658838-69678469 0.46 −3.57
NOVEL DOWNREG. TU_0052454_0 chr16: 15702084-15702374 0.40 −3.57
PROTEIN DOWNREG. TU_0004248_0 chr6: 70983350-71069482 0.52 −3.57
PROTEIN DOWNREG. TU_0111118_0 chr15: 58426685-58428608 0.59 −3.58
PROTEIN DOWNREG. TU_0047256_0 chr4: 38781223-38804739 0.63 −3.58
PROTEIN DOWNREG. TU_0092308_0 chr11: 61395022-61326508 0.62 −3.58
PROTEIN DOWNREG. TU_0037381_0 chr3: 33159367-33165995 0.70 −3.59
PROTEIN DOWNREG. TU_0088765_0 chr5: 169737435-169749043 0.53 −3.60
PROTEIN DOWNREG. TU_0039072_0 chr3: 70098064-70100160 0.63 −3.60
NOVEL DOWNREG. TU_0112059_0 chr15: 69667695-69691724 0.41 −3.60
PROTEIN DOWNREG. TU_0030975_0 chrX: 130235170-130235814 0.49 −3.60
PROTEIN DOWNREG. TU_0038532_0 chr3: 52258212-52287726 0.77 −3.60
PROTEIN DOWNREG. TU_0014418_0 chr17: 3748115-3749717 0.39 −3.60
PROTEIN DOWNREG. TU_0001986_0 chr6: 31791087-31793378 0.48 −3.61
PROTEIN DOWNREG. TU_0111109_0 chr15: 58426685-58477514 0.66 −3.61
PROTEIN DOWNREG. TU_0064151_0 chr1: 98933515-98937074 0.46 −3.61
PROTEIN DOWNREG. TU_0111253_0 chr15: 61121812-61151157 0.63 −3.61
PROTEIN DOWNREG. TU_0058947_0 chr1: 13782811-13817026 0.61 −3.62
PROTEIN DOWNREG. TU_0031484_0 chrX: 151890690-151892673 0.59 −3.62
PROTEIN DOWNREG. TU_0076212_0 chr10: 105781059-105835687 0.47 −3.62
PROTEIN DOWNREG. TU_0062567_0 chr1: 47050692-47056967 0.47 −3.62
NOVEL DOWNREG. TU_0020667_0 chr19: 7888598-7889980 0.41 −3.62
PROTEIN DOWNREG. TU_0029358_0 chrX: 71263703-71268507 0.66 −3.63
PROTEIN DOWNREG. TU_0065339_0 chr1: 148457403-148475104 0.56 −3.63
PROTEIN DOWNREG. TU_0063765_0 chr1: 87583567-87587269 0.58 −3.63
NOVEL DOWNREG. TU_0036395_0 chr14: 104617328-104623671 0.53 −3.63
PROTEIN DOWNREG. TU_0103872_0 chr9: 115178483-115203441 0.59 −3.63
PROTEIN DOWNREG. TU_0050244_0 chr4: 148665059-148685558 0.63 −3.63
PROTEIN DOWNREG. TU_0031913_0 chr14: 20554755-20563715 0.64 −3.63
PROTEIN DOWNREG. TU_0065343_0 chr1: 148501147-148501585 0.37 −3.63
PROTEIN DOWNREG. TU_0084946_0 chr5: 50715235-50726033 0.60 −3.64
PROTEIN DOWNREG. TU_0090342_0 chr11: 8671475-8849482 0.64 −3.64
PROTEIN DOWNREG. TU_0120044_0 chr2: 155422693-155423038 0.26 −3.64
PROTEIN DOWNREG. TU_0023267_0 chr19: 40937280-40940189 0.52 −3.64
PROTEIN DOWNREG. TU_0023553_0 chr19: 43433715-43434071 0.51 −3.65
PROTEIN DOWNREG. TU_0115806_0 chr2: 37722515-37725663 0.60 −3.65
PROTEIN DOWNREG. TU_0085256_0 chr5: 59099679-59100724 0.53 −3.65
PROTEIN DOWNREG. TU_0038056_0 chr3: 48563574-48623119 0.68 −3.65
PROTEIN DOWNREG. TU_0022088_0 chr19: 16864768-16929718 0.55 −3.65
ncRNA DOWNREG. TU_0083408_0 chr12: 129197899-129212499 0.58 −3.65
PROTEIN DOWNREG. TU_0059155_0 chr1: 16397144-16405288 0.61 −3.65
PROTEIN DOWNREG. TU_0046595_0 chr4: 3264594-3411502 0.68 −3.65
PROTEIN DOWNREG. TU_0099476_0 chr8: 108331106-108578694 0.58 −3.66
PROTEIN DOWNREG. TU_0091498_0 chr11: 46834081-46849744 0.65 −3.66
PROTEIN DOWNREG. TU_0098389_0 chr8: 68586418-68699042 0.45 −3.66
PROTEIN DOWNREG. TU_0046627_0 chr4: 3735533-3740037 0.45 −3.67
NOVEL DOWNREG. TU_0103946_0 chr9: 116821701-116822181 0.48 −3.67
PROTEIN DOWNREG. TU_0008057_0 chr7: 5519816-5536775 0.62 −3.67
PROTEIN DOWNREG. TU_0100219_0 chr8: 143849604-143856276 0.59 −3.67
PROTEIN DOWNREG. TU_0087532_0 chr5: 137802544-137810548 0.53 −3.68
PROTEIN DOWNREG. TU_0066743_0 chr1: 154859563-154862200 0.43 −3.68
PROTEIN DOWNREG. TU_0052586_0 chr16: 19637116-19779369 0.64 −3.68
PROTEIN DOWNREG. TU_0075808_0 chr10: 88708340-88712998 0.51 −3.68
PROTEIN DOWNREG. TU_0032240_0 chr14: 22894093-22905632 0.57 −3.68
PROTEIN DOWNREG. TU_0046399_0 chr4: 2031053-2040569 0.44 −3.70
PROTEIN DOWNREG. TU_0081487_0 chr12: 104248577-104289423 0.56 −3.70
PROTEIN DOWNREG. TU_0096978_0 chr8: 22133174-22140355 0.47 −3.70
PROTEIN DOWNREG. TU_0054692_0 chr16: 83411105-83500616 0.62 −3.70
PROTEIN DOWNREG. TU_0067818_0 chr1: 180809414-180811333 0.72 −3.71
PROTEIN DOWNREG. TU_0098841_0 chr8: 92038228-92039575 0.39 −3.71
PROTEIN DOWNREG. TU_0121595_0 chr2: 202193170-202196672 0.62 −3.71
PROTEIN DOWNREG. TU_0023218_0 chr19: 40679964-40694184 0.55 −3.71
PROTEIN DOWNREG. TU_0112386_0 chr15: 71818130-71820041 0.55 −3.71
PROTEIN DOWNREG. TU_0024601_0 chr19: 51605296-51609005 0.56 −3.71
PROTEIN DOWNREG. TU_0055238_0 chr18: 2561572-2606627 0.59 −3.71
PROTEIN DOWNREG. TU_0085908_0 chr5: 78401241-78420780 0.52 −3.72
ncRNA DOWNREG. TU_0111315_0 chr15: 61676589-61681634 0.55 −3.72
PROTEIN DOWNREG. TU_0111311_0 chr15: 61676589-61681634 0.55 −3.72
PROTEIN DOWNREG. TU_0023241_0 chr19: 40856254-40861198 0.41 −3.72
PROTEIN DOWNREG. TU_0068139_0 chr1: 199127296-199147465 0.42 −3.72
ncRNA DOWNREG. TU_0102684_0 chr9: 70336502-70344481 0.56 −3.73
PROTEIN DOWNREG. TU_0068764_0 chr1: 207854842-207892483 0.49 −3.73
PROTEIN DOWNREG. TU_0053636_0 chr16: 55846971-55853340 0.58 −3.74
PROTEIN DOWNREG. TU_0084025_0 chr5: 6501949-6545706 0.54 −3.74
NOVEL DOWNREG. TU_0032151_0 chr14: 22508055-22508830 0.58 −3.74
PROTEIN DOWNREG. TU_0014680_0 chr17: 6295379-6305574 0.62 −3.74
PROTEIN DOWNREG. TU_0076124_0 chr10: 104619299-104651033 0.60 −3.75
PROTEIN DOWNREG. TU_0085198_0 chr5: 58300638-58305429 0.60 −3.75
PROTEIN DOWNREG. TU_0102686_0 chr9: 70337677-70344573 0.55 −3.76
PROTEIN DOWNREG. TU_0112385_0 chr15: 71818130-71831566 0.54 −3.76
PROTEIN DOWNREG. TU_0100875_0 chr21: 32705500-32809639 0.61 −3.78
PROTEIN DOWNREG. TU_0065928_0 chr1: 151800274-151855449 0.49 −3.78
PROTEIN DOWNREG. TU_0063298_0 chr1: 62474433-62474872 0.36 −3.78
PROTEIN DOWNREG. TU_0100851_0 chr21: 32604246-32608457 0.62 −3.79
PROTEIN DOWNREG. TU_0101015_0 chr21: 35010830-35012376 0.55 −3.79
ncRNA DOWNREG. TU_0031086_0 chrX: 133993992-133995935 0.73 −3.79
PROTEIN DOWNREG. TU_0068759_0 chr1: 207669209-207672813 0.45 −3.79
NOVEL DOWNREG. TU_0069253_0 chr1: 223741202-223745600 0.62 −3.79
PROTEIN DOWNREG. TU_0020150_0 chr19: 3877291-3879097 0.52 −3.79
ncRNA DOWNREG. TU_0084069_0 chr5: 9599340-9603383 0.50 −3.80
PROTEIN DOWNREG. TU_0016922_0 chr17: 38430856-38435173 0.51 −3.80
PROTEIN DOWNREG. TU_0013053_0 chr7: 134114695-134305949 0.56 −3.81
PROTEIN DOWNREG. TU_0017406_0 chr17: 43458534-43470076 0.58 −3.81
PROTEIN DOWNREG. TU_0014681_0 chr17: 6295379-6305877 0.50 −3.81
PROTEIN DOWNREG. TU_0058447_0 chr1: 9040090-9052233 0.36 −3.81
PROTEIN DOWNREG. TU_0055624_0 chr18: 11872611-11875972 0.64 −3.82
PROTEIN DOWNREG. TU_0003717_0 chr6: 43381215-43381963 0.49 −3.82
NOVEL DOWNREG. TU_0016578_0 chr17: 35881203-35884855 0.52 −3.82
PROTEIN DOWNREG. TU_0101224_0 chr21: 40161189-40223184 0.50 −3.82
PROTEIN DOWNREG. TU_0064871_0 chr1: 115391459-115433611 0.59 −3.83
PROTEIN DOWNREG. TU_0097462_0 chr8: 37773618-37822041 0.55 −3.83
PROTEIN DOWNREG. TU_0066742_0 chr1: 154860755-154862200 0.42 −3.83
PROTEIN DOWNREG. TU_0090638_0 chr11: 14242208-14246823 0.55 −3.83
PROTEIN DOWNREG. TU_0046626_0 chr4: 3735533-3740037 0.46 −3.83
PROTEIN DOWNREG. TU_0024608_0 chr19: 51842682-51856041 0.53 −3.83
PROTEIN DOWNREG. TU_0071146_0 chr20: 25381375-25432639 0.58 −3.84
PROTEIN DOWNREG. TU_0080097_0 chr12: 56301840-56307003 0.56 −3.85
PROTEIN DOWNREG. TU_0062615_0 chr1: 48974664-48997227 0.51 −3.85
PROTEIN DOWNREG. TU_0013669_0 chr7: 150272983-150305963 0.52 −3.86
PROTEIN DOWNREG. TU_0102682_0 chr9: 70197177-70337519 0.56 −3.86
PROTEIN DOWNREG. TU_0104855_0 chr9: 131689287-131691419 0.64 −3.86
PROTEIN DOWNREG. TU_0116336_0 chr2: 48677181-48685259 0.65 −3.86
PROTEIN DOWNREG. TU_0116619_0 chr2: 60532630-60533546 0.47 −3.87
PROTEIN DOWNREG. TU_0034452_0 chr14: 69415893-69568826 0.48 −3.87
PROTEIN DOWNREG. TU_0067213_0 chr1: 163086189-163087684 0.59 −3.87
PROTEIN DOWNREG. TU_0065337_0 chr1: 148457403-148475119 0.56 −3.87
NOVEL DOWNREG. TU_0062461_0 chr1: 46461750-46463004 0.51 −3.88
PROTEIN DOWNREG. TU_0080098_0 chr12: 56302807-56307707 0.56 −3.88
PROTEIN DOWNREG. TU_0034421_0 chr14: 68410559-68412495 0.62 −3.88
PROTEIN DOWNREG. TU_0016601_0 chr17: 36911114-36928728 0.39 −3.88
PROTEIN DOWNREG. TU_0079221_0 chr12: 51194638-51200498 0.43 −3.89
PROTEIN DOWNREG. TU_0112752_0 chr15: 76184009-76210733 0.55 −3.90
PROTEIN DOWNREG. TU_0028410_0 chrX: 48910899-48929704 0.68 −3.91
PROTEIN DOWNREG. TU_0076498_0 chr10: 123227854-123347940 0.55 −3.92
NOVEL DOWNREG. TU_0093208_0 chr11: 65396931-65397655 0.45 −3.92
PROTEIN DOWNREG. TU_0078129_0 chr12: 27016771-27017190 0.47 −3.92
PROTEIN DOWNREG. TU_0064620_0 chr1: 111962071-112059304 0.61 −3.92
PROTEIN DOWNREG. TU_0005224_0 chr6: 107917248-108088034 0.60 −3.93
PROTEIN DOWNREG. TU_0023668_0 chr19: 44114820-44158190 0.56 −3.93
PROTEIN DOWNREG. TU_0041856_0 chr3: 190990156-191097717 0.44 −3.93
PROTEIN DOWNREG. TU_0107364_0 chr22: 36658502-36671784 0.62 −3.93
PROTEIN DOWNREG. TU_0079224_0 chr12: 51194638-51199100 0.43 −3.94
PROTEIN DOWNREG. TU_0027357_0 chrX: 17728093-17737982 0.57 −3.94
PROTEIN DOWNREG. TU_0071013_0 chr20: 19141491-19652034 0.55 −3.95
PROTEIN DOWNREG. TU_0060281_0 chr1: 27204050-27211524 0.48 −3.95
PROTEIN DOWNREG. TU_0096007_0 chr11: 119487208-119514087 0.45 −3.95
PROTEIN DOWNREG. TU_0058810_0 chr1: 11631005-11637486 0.50 −3.95
ncRNA DOWNREG. TU_0102668_0 chr9: 67902293-67904671 0.52 −3.96
PROTEIN DOWNREG. TU_0103126_0 chr9: 93524079-93559558 0.55 −3.96
PROTEIN DOWNREG. TU_0098384_0 chr8: 68508843-68581618 0.43 −3.96
NOVEL DOWNREG. TU_0084058_0 chr5: 9602147-9603383 0.49 −3.96
ncRNA DOWNREG. TU_0018887_0 chr17: 73068191-73068659 0.29 −3.97
PROTEIN DOWNREG. TU_0020916_0 chr19: 9720305-9727203 0.55 −3.97
PROTEIN DOWNREG. TU_0018819_0 chr17: 72184340-72195820 0.59 −3.97
NOVEL DOWNREG. TU_0042081_0 chr3: 197374550-197376798 0.46 −3.97
PROTEIN DOWNREG. TU_0065864_0 chr1: 149850009-149852238 0.46 −3.98
PROTEIN DOWNREG. TU_0111301_0 chr15: 61676589-51684028 0.54 −3.98
PROTEIN DOWNREG. TU_0073443_0 chr10: 5556713-3558609 0.43 −3.99
PROTEIN DOWNREG. TU_0030581_0 chrX: 118096546-118104692 0.38 −3.99
PROTEIN DOWNREG. TU_0039780_0 chr3: 120843508-120866813 0.55 −4.00
PROTEIN DOWNREG. TU_0081660_0 chr12: 108705678-108718771 0.50 −4.00
PROTEIN DOWNREG. TU_0046397_0 chr4: 2032569-2050090 0.46 −4.00
PROTEIN DOWNREG. TU_0122440_0 chr2: 219991398-219999705 0.53 −4.01
PROTEIN DOWNREG. TU_0011534_0 chr7: 99083477-99096154 0.36 −4.01
PROTEIN DOWNREG. TU_0047206_0 chr4: 37815997-37817190 0.59 −4.02
PROTEIN DOWNREG. TU_0017005_0 chr17: 39308253-39337366 0.52 −4.02
PROTEIN DOWNREG. TU_0052436_0 chr16: 15704489-15858435 0.54 −4.03
PROTEIN DOWNREG. TU_0014761_0 chr17: 7128572-7131411 0.46 −4.03
PROTEIN DOWNREG. TU_0080075_0 chr12: 56290183-56301803 0.53 −4.03
PROTEIN DOWNREG. TU_0089295_0 chr5: 177597111-177621358 0.48 −4.03
PROTEIN DOWNREG. TU_0062594_0 chr16: 19775320-19780719 0.60 −4.03
PROTEIN DOWNREG. TU_0068168_0 chr1: 199700556-199742901 0.61 −4.04
ncRNA DOWNREG. TU_0102657_0 chr9: 67902293-67908869 0.54 −4.04
PROTEIN DOWNREG. TU_0003729_0 chr6: 43525496-43528789 0.55 −4.04
PROTEIN DOWNREG. TU_0071246_0 chr20: 29913077-29921837 0.42 −4.05
NOVEL DOWNREG. TU_0050224_0 chr4: 147115887-147190781 0.25 −4.06
PROTEIN DOWNREG. TU_0110166_0 chr15: 43172154-43198892 0.49 −4.07
PROTEIN DOWNREG. TU_0030085_0 chrX: 101782933-101800062 0.56 −4.07
PROTEIN DOWNREG. TU_0021042_0 chr19: 10435466-10441506 0.61 −4.08
PROTEIN DOWNREG. TU_0097463_0 chr8: 37812227-37826549 0.58 −4.08
PROTEIN DOWNREG. TU_0101681_0 chr9: 734412-736069 0.67 −4.08
PROTEIN DOWNREG. TU_0030157_0 chrX: 102750729-102751737 0.44 −4.09
NOVEL DOWNREG. TU_0098190_0 chr8: 61704765-61708199 0.40 −4.09
PROTEIN DOWNREG. TU_0062947_0 chr1: 53744955-53838542 0.42 −4.09
PROTEIN DOWNREG. TU_0078008_0 chr12: 21679541-21702042 0.57 −4.09
PROTEIN DOWNREG. TU_0017582_0 chr17: 45858594-45907395 0.54 −4.09
PROTEIN DOWNREG. TU_0000021_0 chr6: 1555144-1559122 0.53 −4.09
PROTEIN DOWNREG. TU_0031424_0 chrX: 149432223-149433104 0.47 −4.10
PROTEIN DOWNREG. TU_0065603_0 chr1: 149275738-149286201 0.42 −4.10
PROTEIN DOWNREG. TU_0037859_0 chr3: 45240966-45242817 0.49 −4.11
PROTEIN DOWNREG. TU_0102271_0 chr9: 34511045-34512853 0.50 −4.11
PROTEIN DOWNREG. TU_0035605_0 chr14: 93254401-93273368 0.49 −4.11
PROTEIN DOWNREG. TU_0064621_0 chr1: 112047963-112062396 0.54 −4.11
ncRNA DOWNREG. TU_0031098_0 chrX: 134057388-134058604 0.47 −4.11
PROTEIN DOWNREG. TU_0018799_0 chr17: 72061371-72080938 0.61 −4.11
PROTEIN DOWNREG. TU_0011129_0 chr7: 94135058-94136943 0.41 −4.11
NOVEL DOWNREG. TU_0036396_0 chr14: 104617328-104619095 0.41 −4.12
PROTEIN DOWNREG. TU_0086255_0 chr5: 92944260-92956054 0.57 −4.12
ncRNA DOWNREG. TU_0074501_0 chr10: 60429298-60431091 0.42 −4.12
PROTEIN DOWNREG. TU_0073757_0 chr10: 17672547-17699461 0.56 −4.13
PROTEIN DOWNREG. TU_0015457_0 chr17: 19581898-19587356 0.45 −4.13
PROTEIN DOWNREG. TU_0122402_0 chr2: 219821926-219824741 0.61 −4.13
PROTEIN DOWNREG. TU_0116618_0 chr2: 60532830-60633902 0.49 −4.13
PROTEIN DOWNREG. TU_0029963_0 chrX: 100220537-100238005 0.51 −4.15
PROTEIN DOWNREG. TU_0028949_0 chrX: 64804077-64878518 0.61 −4.15
PROTEIN DOWNREG. TU_0088443_0 chr5: 154178336-154210363 0.57 −4.16
PROTEIN DOWNREG. TU_0107371_0 chr22: 36668731-36671784 0.56 −4.17
PROTEIN DOWNREG. TU_0016830_0 chr17: 38070906-38071660 0.57 −4.17
PROTEIN DOWNREG. TU_0016596_0 chr17: 36923524-36946925 0.50 −4.17
PROTEIN DOWNREG. TU_0014764_0 chr17: 7131441-7134452 0.45 −4.18
PROTEIN DOWNREG. TU_0070473_0 chr20: 2621571-2702522 0.60 −4.18
PROTEIN DOWNREG. TU_0065602_0 chr1: 149282206-149286718 0.40 −4.19
PROTEIN DOWNREG. TU_0105435_0 chr9: 138997874-138999099 0.37 −4.19
PROTEIN DOWNREG. TU_0015445_0 chr17: 19415396-19422913 0.46 −4.20
PROTEIN DOWNREG. TU_0019012_0 chr17: 74597027-74990278 0.42 −4.21
PROTEIN DOWNREG. TU_0048538_0 chr4: 81336928-81344460 0.41 −4.22
PROTEIN DOWNREG. TU_0098385_0 chr8: 68508843-68509111 0.41 −4.22
PROTEIN DOWNREG. TU_0076499_0 chr10: 123227854-123248042 0.53 −4.23
PROTEIN DOWNREG. TU_0117482_0 chr2: 73973507-74000287 0.56 −4.23
PROTEIN DOWNREG. TU_0114778_0 chr2: 20264034-20288661 0.45 −4.24
PROTEIN DOWNREG. TU_0018316_0 chr17: 33917848-33935788 0.53 −4.25
PROTEIN DOWNREG. TU_0071893_0 chr20: 34603301-34611746 0.59 −4.25
PROTEIN DOWNREG. TU_0073523_0 chr10: 8136827-8157157 0.44 −4.26
PROTEIN DOWNREG. TU_0064500_0 chr1: 110061334-110079791 0.42 −4.27
PROTEIN DOWNREG. TU_0065862_0 chr1: 149850009-149852444 0.41 −4.27
PROTEIN DOWNREG. TU_0030064_0 chrX: 101268429-101269091 0.44 −4.28
PROTEIN DOWNREG. TU_0060278_0 chr1: 27192773-27200190 0.51 −4.28
PROTEIN DOWNREG. TU_0000013_0 chr6: 1257191-1259972 0.36 −4.29
PROTEIN DOWNREG. TU_0120707_0 chr2: 176665581-176669190 0.46 −4.31
PROTEIN DOWNREG. TU_0016744_0 chr17: 37790368-37809206 0.54 −4.31
PROTEIN DOWNREG. TU_0016827_0 chr17: 38065830-38071660 0.63 −4.31
PROTEIN DOWNREG. TU_0056190_0 chr18: 26824024-26842486 0.43 −4.33
PROTEIN DOWNREG. TU_0096964_0 chr8: 22027917-22043914 0.47 −4.35
PROTEIN DOWNREG. TU_0030062_0 chrX: 101267701-101269091 0.41 −4.36
ncRNA DOWNREG. TU_0120711_0 chr2: 176690351-176696560 0.49 −4.36
PROTEIN DOWNREG. TU_0011537_0 chr7: 99085728-99111736 0.39 −4.39
PROTEIN DOWNREG. TU_0107366_0 chr22: 36668731-36673469 0.54 −4.39
PROTEIN DOWNREG. TU_0065341_0 chr1: 148496551-148500610 0.35 −4.39
PROTEIN DOWNREG. TU_0015076_0 chr17: 12510065-12612990 0.50 −4.40
PROTEIN DOWNREG. TU_0087752_0 chr5: 139206352-139211418 0.44 −4.40
PROTEIN DOWNREG. TU_0108990_0 chr15: 34970176-35180015 0.51 −4.41
PROTEIN DOWNREG. TU_0062566_0 chr1: 47037330-47057598 0.43 −4.42
PROTEIN DOWNREG. TU_0018825_0 chr17: 72192513-72192794 0.47 −4.43
PROTEIN DOWNREG. TU_0002566_0 chr6: 33797424-33798978 0.37 −4.44
PROTEIN DOWNREG. TU_0074074_0 chr10: 29814868-29815135 0.26 −4.44
PROTEIN DOWNREG. TU_0110179_0 chr15: 43196205-43235205 0.43 −4.46
PROTEIN DOWNREG. TU_0082372_0 chr12: 116130336-116130610 0.41 −4.47
ncRNA DOWNREG. TU_0102658_0 chr9: 67902293-67908683 0.46 −4.48
PROTEIN DOWNREG. TU_0024160_0 chr19: 48777171-48778386 0.51 −4.49
PROTEIN DOWNREG. TU_0031081_0 chrX: 133993992-134013925 0.64 −4.49
PROTEIN DOWNREG. TU_0015447_0 chr17: 19421649-19423000 0.46 −4.50
PROTEIN DOWNREG. TU_0016834_0 chr17: 38072130-38072515 0.54 −4.50
PROTEIN DOWNREG. TU_0120709_0 chr2: 176677352-176697902 0.49 −4.50
PROTEIN DOWNREG. TU_0041205_0 chr3: 171619688-171634575 0.48 −4.53
PROTEIN DOWNREG. TU_0110178_0 chr15: 43196270-43241274 0.43 −4.54
PROTEIN DOWNREG. TU_0064473_0 chr1: 110000292-110079791 0.51 −4.58
ncRNA DOWNREG. TU_0120715_0 chr2: 176692475-176697902 0.50 −4.58
PROTEIN DOWNREG. TU_0110180_0 chr15: 43196205-43243358 0.43 −4.63
PROTEIN DOWNREG. TU_0024922_0 chr19: 54253368-54259943 0.42 −4.64
ncRNA DOWNREG. TU_0115816_0 chr2: 38109039-38116939 0.32 −4.64
ncRNA DOWNREG. TU_0067289_0 chr1: 166307141-166318970 0.48 −4.69
NOVEL DOWNREG. TU_0095765_0 chr11: 117640504-117642734 0.36 −4.69
PROTEIN DOWNREG. TU_0058445_0 chr1: 9017797-9040122 0.33 −4.70
PROTEIN DOWNREG. TU_0047068_0 chr4: 23402764-23403824 0.41 −4.72
PROTEIN DOWNREG. TU_0016882_0 chr17: 38260060-38263683 0.51 −4.82
NOVEL DOWNREG. TU_0098382_0 chr8: 68494189-68495887 0.29 −4.83
PROTEIN DOWNREG. TU_0110177_0 chr15: 43196768-43245735 0.47 −4.86
PROTEIN DOWNREG. TU_0089598_0 chr11: 303980-310982 0.35 −4.87
PROTEIN DOWNREG. TU_0107527_0 chr22: 37740155-37746215 0.44 −4.88
PROTEIN DOWNREG. TU_0107528_0 chr22: 37741248-37746215 0.43 −4.90
PROTEIN DOWNREG. TU_0032311_0 chr14: 23612588-23617134 0.32 −5.04
TABLE 5
Fold change
Expected score Observed (PCA vs q-value
PCAT ID Gene Chromosomal Location (dExp) score (d) Benign (%)
PCAT-1 TU_0099865_0 chr8: 128087842-128095202 −2.2654014 5.444088 6.9071784 0
PCAT-2 TU_0090142_0 chr11: 4748677-4760303 −2.4408573 4.6781354 11.39658 0
PCAT-3 TU_0054603_0 chr16: 82380933-82394836 −2.1786723 4.4612455 5.8916535 0
PCAT-4 TU_0090140_0 chr11: 4748163-4759145 −2.1153426 4.4345 7.1933164 0
PCAT-5 TU_0078288_0 chr12: 32393283-32405731 −1.9164219 4.312603 3.5655262 0
PCAT-6 TU_0099864_0 chr6: 128094589-128103681 −1.7214081 4.265536 3.8937242 0
PCAT-7 TU_0084308_0 chr5: 15938753-15949124 −1.9636476 4.124071 4.747601 0
PCAT-8 TU_0084303_0 chr5: 15899476-15955226 −2.0245786 4.0520086 7.1035967 0
PCAT-9 TU_0082746_0 chr12: 120197102-120197416 −1.861408 3.7551165 5.1431665 0
PCAT-10 TU_0078296_0 chr12: 32394534-32405549 −1.5944241 3.6902914 3.034359 0
PCAT-11 TU_0078290_0 chr12: 32394534-32410898 −1.5337954 3.675318 3.1572607 0
PCAT-12 TU_0002597_0 chr6: 34335202-34338521 −1.6263148 3.6469774 3.352418 0
PCAT-13 TU_0049368_0 chr4: 106772318-106772770 −1.6894234 3.6079373 2.8299546 0
PCAT-14 TU_0106548_0 chr22: 22209111-22212055 −1.939075 3.591358 5.962547 0
PCAT-15 TU_0078293_0 chr12: 32396393-32414822 −1.5212961 3.5705945 2.9213174 0
PCAT-16 TU_0099884_0 chr8: 128301493-128307576 −1.4445064 3.5658643 2.516981 0
PCAT-17 TU_0112014_0 chr15: 67722165-67739990 −1.6326295 3.562463 3.694224 0
PCAT-18 TU_0084306_0 chr5: 15896315-15947088 −1.845 3.5603588 5.746707 0
PCAT-19 TU_0114240_0 chr2: 1534883-1538193 −1.6870209 3.5233572 4.339847 0
PCAT-20 TU_0008499_0 chr7: 24236191-24236455 −1.8302058 3.5071697 6.6821446 0
PCAT-21 TU_0078299_0 chr12: 32290896-32292169 −1.7297353 3.506232 3.2923684 0
PCAT-22 TU_0000033_0 chr6: 1619606-1668581 −1.7680657 3.434188 2.2470818 0
PCAT-23 TU_0096472_0 chr11: 133844590-133862924 −1.8782617 3.410355 5.9854193 0
PCAT-24 TU_0114259_0 chr2: 1606782-1607314 −1.6662377 3.3919659 5.060926 0
PCAT-25 TU_0096473_0 chr11: 133844590-133862995 −1.8963361 3.3859823 6.1071715 0
PCAT-26 TU_0100361_0 chr8: 144914456-144930753 −1.6521469 3.3805158 3.8420231 0
PCAT-27 TU_0040394_0 chr3: 133418632-133441282 −1.6208398 3.3201025 2.9724674 0
PCAT-28 TU_0043432_0 chr13: 34032994-34050503 −1.6739471 3.2037551 3.2093527 0
PCAT-29 TU_0112020_0 chr15: 67764259-67801825 −1.5603316 3.1967351 3.593551 0
PCAT-30 TU_0042717_0 chr13: 23149908-23200198 −2.0654948 3.1685438 4.9699407 0
PCAT-31 TU_0078292_0 chr12: 32290485-32406307 −1.4503003 3.151879 2.8911364 0
PCAT-32 TU_0084146_0 chr5: 14025126-14062770 −1.6452767 3.1257985 2.6190455 0
PCAT-33 TU_0056168_0 chr18: 22477042-22477666 −1.5381516 3.0557241 3.1951044 0
PCAT-34 TU_0040383_0 chr3: 133360541-133429262 −1.5558791 3.0416508 3.7478442 0
PCAT-35 TU_0112025_0 chr15: 67780574-87782345 −1.6815377 3.0412362 3.433415 0
PCAT-36 TU_0041688_0 chr3: 186741299-186741933 −1.4749297 3.0062308 2.543468 0
PCAT-37 TU_0103642_0 chr9: 109187089-109187455 −1.7387192 2.998956 6.6124363 0
PCAT-38 TU_0040375_0 chr3: 133280694-133394609 −1.5469999 2.9753568 3.9068055 0
PCAT-39 TU_0047312_0 chr4: 39217669-39222163 −1.6388936 2.9124916 3.6121209 0
PCAT-40 TU_0106545_0 chr22: 22218478-22219162 −1.7586497 2.889856 3.7357745 0
PCAT-41 TU_0054541_0 chr16: 79408800-79435066 −1.7485934 2.8699164 6.647557 0
PCAT-42 TU_0060446_0 chr1: 28438629-28450156 −1.4880521 2.857332 1.9824111 0
PCAT-43 TU_0072907_0 chr20: 55759486-55771563 −1.5254781 2.7966201 2.812179 0
PCAT-44 TU_0043403_0 chr13: 33844637-33845921 −1.5793877 2.7919009 3.6403422 0
PCAT-45 TU_0038678_0 chr3: 53515951-53517078 −1.7047809 2.7858517 3.6908987 0
PCAT-46 TU_0101706_0 chr9: 3408690-3415374 −1.4780945 2.7822099 3.3066912 0
PCAT-47 TU_0101709_0 chr9: 3411967-3415374 −1.4652373 2.7622206 3.1886175 0
PCAT-48 TU_0106544_0 chr22: 22210421-22220506 −1.6153399 2.7578135 3.7418716 0
PCAT-49 TU_0046121_0 chr4: 766363-766599 −1.5697786 2.7573307 1.485532 0
PCAT-50 TU_0106542_0 chr22: 22211315-22220506 −1.6098742 2.755721 3.3781004 0
PCAT-51 TU_0106541_0 chr22: 22209111-22219162 −1.6593723 2.7341027 3.664146 0
PCAT-52 TU_0044453_0 chr13: 51505777-51524522 −1.3416 2.732019 2.536953 0
PCAT-53 TU_0104717_0 chr9: 130697833-130698832 −1.2938 2.7219732 2.3344588 0
PCAT-54 TU_0089014_0 chr5: 176014905-176015351 −1.3967873 2.7047238 1.7803582 0
PCAT-55 TU_0108452_0 chr15: 19344745-19362916 −1.5839852 2.6759455 1.8484153 0
PCAT-56 TU_0112003_0 chr15: 67645590-67775246 −1.4386703 2.668052 3.045022 0
PCAT-57 TU_0078286_0 chr12: 32395588-32405731 −1.3580605 2.6660874 2.6121044 0
PCAT-58 TU_0078303_0 chr12: 32274210-32274530 −1.5020599 2.65866 3.3306372 0
PCAT-59 TU_0112004_0 chr15: 67644390-67650387 −1.5175762 2.6509888 2.9933636 0
PCAT-60 TU_0071087_0 chr20: 21428679-21429454 −1.4916688 2.649109 4.6481714 0
PCAT-61 TU_0072906_0 chr20: 55759768-55770657 −1.5059631 2.645004 2.95756 0
PCAT-62 TU_0054240_0 chr16: 70155175-70173873 −1.4715649 2.6437716 3.5309577 0
PCAT-63 TU_0047330_0 chr4: 39217641-39222163 −1.5139307 2.6277235 3.0695639 0
PCAT-64 TU_0055435_0 chr18: 6715938-6719172 −1.6048826 2.6173768 2.9221427 0
PCAT-65 TU_0079791_0 chr12: 54971063-54971481 −1.4415668 2.6010823 2.0141602 0
PCAT-66 TU_0043411_0 chr13: 33918267-33926769 −1.495064 2.5991623 3.3860362 0
PCAT-67 TU_0056121_0 chr18: 20196762-20197522 −1.2526748 2.5938754 1.7191441 0
PCAT-68 TU_0043412_0 chr13: 33918267-33935946 −1.5891836 2.590199 4.2804046 0
PCAT-69 TU_0065837_0 chr1: 149791252-149795934 −1.3852053 2.5882297 2.9343975 0
PCAT-70 TU_0043401_0 chr13: 33825711-33845275 −1.5994886 2.5853698 4.3461533 0
PCAT-71 TU_0006463_0 chr6: 144659819-144660143 −1.4985942 2.5744107 2.2007995 0
PCAT-72 TU_0048506_0 chr4: 80329017-80348259 −1.5744382 2.5690413 2.8022916 0
PCAT-73 TU_0084140_0 chr5: 14003669-14054874 −1.4040573 2.5472755 2.5979335 0
PCAT-74 TU_0082982_0 chr12: 121776584-121777370 −1.5293782 2.5458217 2.6197503 0
PCAT-75 TU_0013212_0 chr7: 138990883-139001515 −1.2296493 2.544434 1.6879753 0
PCAT-76 TU_0072912_0 chr20: 55779532-55780817 −1.4302964 2.5406737 3.8653345 0
PCAT-77 TU_0112281_0 chr15: 70586704-70590792 −1.4590155 2.5375097 2.4288568 0
PCAT-78 TU_0048767_0 chr4: 88120066-88124880 −1.3735119 2.5323946 2.233308 0
PCAT-79 TU_0108455_0 chr15: 19358326-19365341 −1.5651321 2.5261333 1.9462687 0
PCAT-80 TU_0091997_0 chr11: 58560356-58573012 −1.3149309 2.5185204 2.1176686 0
PCAT-81 TU_0121655_0 chr2: 202985284-202998634 −1.4014161 2.476237 2.2194188 0.859614
PCAT-82 TU_0071798_0 chr20: 33775260-33778511 −1.3356665 2.4645917 1.6566333 0.850371
PCAT-83 TU_0049200_0 chr4: 102469973-102476087 −1.3222212 2.456723 1.9456172 0.841324
PCAT-84 TU_0121714_0 chr2: 203295212-203314868 −1.3457565 2.4496663 1.7624274 0.832468
PCAT-85 TU_0098937_0 chr8: 95748751-95751321 −1.4532137 2.42248 2.2326834 0.823797
PCAT-86 TU_0108453_0 chr15: 19356996-19364013 −1.8033699 2.4094539 3.839975 0.767811
PCAT-87 TU_0114170_0 chr15: 99659312-99669199 −1.4358851 2.4062114 2.1252658 0.768711
PCAT-88 TU_0089906_0 chr11: 1042845-1045705 −1.3899238 2.401665 2.6390955 0.767811
PCAT-89 TU_0001559_0 chr6: 30283700-30286011 −1.3517065 2.3987799 1.5110766 0.767811
PCAT-90 TU_0050557_0 chr4: 159976338-160016453 −1.17525 2.398688 2.0524442 0.767811
PCAT-91 TU_0078294_0 chr12: 32395632-32413064 −1.4560982 2.3969867 2.1863208 0.767811
PCAT-92 TU_0044933_0 chr13: 94755992-94760688 −1.2905197 2.3965187 2.189938 0.767811
PCAT-93 TU_0017730_0 chr17: 52346638-52346880 −1.4169512 2.3874657 1.4708191 0.760428
PCAT-94 TU_0039020_0 chr3: 66578329-66607777 −1.2662895 2.3720088 1.7112709 0.712473
PCAT-95 TU_0049213_0 chr4: 102461960-102476087 −1.2725139 2.3671806 1.8876821 0.712473
PCAT-96 TU_0093070_0 chr11: 64945809-64961189 −1.2954472 2.3645105 1.9128969 0.712473
PCAT-97 TU_0051063_0 chr4: 187244297-187244767 1.8922831 −2.8485844 0.50983155 0.732264
PCAT-98 TU_0098190_0 chr8: 61704765-61708199 1.9825526 −2.8612607 0.4027831 0.732264
PCAT-99 TU_0038811_0 chr3: 57890130-57890834 1.9620296 −2.8837616 0.44431657 0.732264
PCAT-100 TU_0020914_0 chr19: 9718612-9721799 1.6433232 −2.9243097 0.50623006 0.732264
PCAT-101 TU_0112056_0 chr15: 69658838-69678469 1.837821 −3.0355222 0.46161976 0
PCAT-102 TU_0036396_0 chr14: 104617328-104619095 1.849786 −3.1192882 0.45514825 0
PCAT-103 TU_0095765_0 chr11: 117640504-117642734 2.1002219 −3.2632742 0.38160667 0
PCAT-104 TU_0050224_0 chr4: 147115887-147190781 2.1981242 −3.2975357 0.28569755 0
PCAT-105 TU_0112059_0 chr15: 69667695-69691724 1.8148681 −3.3816626 0.43667468 0
PCAT-106 TU_0098382_0 chr8: 68494189-68495887 2.5413978 −4.0586042 0.30793378 0
TABLE 6
Median Maximum
Expression Expression
PCAT ID Gene Chromosomal Location Outlier Score (RPKM) (RPKM)
PCAT-107 TU_0029004_0 chrX: 66691350-66692032 130.7349145 1 90.921
PCAT-108 TU_0054542_0 chr16: 79420131-79423590 127.0430957 5.60998 135.85
PCAT-109 TU_0120899_0 chr2: 180689090-180696402 123.5416436 1.0525222 94.6932
PCAT-110 TU_0054540_0 chr16: 79419351-79423673 119.090847 4.161985 94.4461
PCAT-111 TU_0120918_0 chr2: 181297540-181400892 112.710111 1.4533705 92.1795
PCAT-112 TU_0054538_0 chr16: 79408946-79450819 98.01851659 1.830343 93.1207
PCAT-113 TU_0059541_0 chr1: 20685471-20686432 68.3572507 1.783109 1375.15
PCAT-114 TU_0120924_0 chr2: 181331111-181427485 63.95455962 1.3891845 365.202
PCAT-115 TU_0074308_0 chr10: 42652247-42653596 60.91841567 1.393607 65.7712
PCAT-116 TU_0049192_0 chr4: 102257900-102306678 59.24997694 1.3854525 69.2423
PCAT-117 TU_0054537_0 chr16: 79406933-79430041 58.04481977 1.8534395 42.751
PCAT-118 TU_0120900_0 chr2: 180926864-180985967 55.8438747 1 67.6582
PCAT-119 TU_0114527_0 chr2: 10858318-10858530 54.76455104 1.2969775 35.0059
PCAT-120 TU_0120923_0 chr2: 181328093-181419226 52.9793227 1.2821 232.556
PCAT-121 TU_0049231_0 chr4: 102257900-102259695 52.77001947 1.34042 67.6276
TABLE 7
Median Maximum
Outlier Expression Expression
Rank Gene Chromosomal location Score (RPKM) (RPKM)
1 CRISP3 chr6: 49803053-49813070 294.56446 1.5414775 478.812
2 SPINK1 chr5: 147184335-147191453 177.19518 2.484455 624.733
3 TU_0029004_0 chrX: 66691350-66692032 130.73491 1 90.921
4 TU_0054542_0 chr16: 79420131-79423590 127.0431 5.60998 135.85
5 TU_0120899_0 chr2: 180689090-180696402 123.54164 1.0525222 94.6932
6 ERG chr21: 38673821-38792298 119.446 3.421615 178.826
7 TU_0054540_0 chr16: 79419351-79423673 119.09085 4.161985 94.4461
8 ERG chr21: 38673821-38792298 117.60294 3.470755 176.186
9 ERG chr21: 38673821-38955574 117.26408 3.385695 170.663
10 ERG chr21: 38673821-38955574 116.33448 3.40077 170.443
11 TU_0120918_0 chr2: 181297540-181400892 112.71011 1.4533705 92.1795
12 C7orf68 chr7: 127883119-127885708 105.18504 6.835525 336.148
13 CSRP3 chr11: 19160153-19180106 101.12947 1 148.45
14 C7orf68 chr7: 127883119-127885708 100.63202 7.08303 337.76
15 COL2A1 chr12: 46653014-46684552 99.166329 1.2285615 96.0977
16 C1orf64 chr1: 16203317-16205771 98.085922 3.62012 252.013
17 TU_0054538_0 chr16: 79408946-79450819 98.018517 1.830343 93.1207
18 COL2A1 chr12: 46653014-46684552 97.347905 1.2416035 94.6672
19 CSRP3 chr11: 19160153-19180165 96.730187 1 141.963
20 COL9A2 chr1: 40538749-40555526 74.408443 19.24815 570.961
21 PLA2G7 chr6: 46780012-46811389 69.521175 10.83567 97.8331
22 AGT chr1: 228904891-228916959 69.319886 4.797365 189.281
23 TU_0059541_0 chr1: 20685471-20686432 68.357251 1.783109 1375.15
24 ETV1 chr7: 13897382-13992664 68.218569 1.932797 138.519
25 ETV1 chr7: 13897382-13992664 67.723331 1.9899945 142.406
26 ETV1 chr7: 13897382-13992664 67.680571 1.9915925 143.632
27 PLA2G7 chr6: 46780011-46811110 67.089039 10.62 95.3551
28 ETV1 chr7: 13897382-13997390 66.381191 2.097225 143.975
29 ETV1 chr7: 13897382-13997575 65.563724 2.074935 141.069
30 MUC6 chr11: 1002823-1026706 64.7328 1.466194 351.862
31 TU_0120924_0 chr2: 181331111-181427485 63.95456 1.3891845 365.202
32 ETV1 chr7: 13897382-13996167 63.929225 2.05648 135.131
33 ETV1 chr7: 13897382-13996167 62.424072 2.03086 131.644
34 TU_0074308_0 chr10: 42652247-42653596 60.918416 1.393607 65.7712
35 TU_0049192_0 chr4: 102257900-102306678 59.249977 1.3854525 69.2423
36 TU_0054537_0 chr16: 79406933-79430041 58.04482 1.8534395 42.751
37 RGL3 chr19: 11365731-11391018 57.528689 7.660035 91.2238
38 RGL3 chr19: 11365731-11391018 57.393056 7.6327 90.6937
39 TMEM45B chr11: 129190950-129235108 55.887845 4.87695 60.0414
40 TU_0120900_0 chr2: 180926864-180985967 55.843875 1 67.6582
41 PTK6 chr20: 61630219-61639151 55.101291 3.420545 114.116
42 TU_0114527_0 chr2: 10858318-10858530 54.764551 1.2969775 35.0059
43 TU_0112020_0 chr15: 67764259-67801825 53.882769 2.0281615 88.99
44 TU_0120923_0 chr2: 181328093-181419226 52.979323 1.2821 232.556
45 TU_0049231_0 chr4: 102257900-102259695 52.770019 1.34042 67.6276
46 MON1B chr16: 75782336-75791044 51.717027 26.00355 187.807
47 TU_0054541_0 chr16: 79408800-79435066 50.445248 1.7164375 32.5832
48 TU_0087466_0 chr5: 136779809-136798173 50.285169 1.2738505 42.0309
49 DLX1 chr2: 172658453-172662647 50.048039 2.088625 43.0035
50 TU_0108209_0 chr22: 46493579-46531245 47.753833 1.0491419 26.6643
51 DLX1 chr2: 172658453-172662647 47.159314 1.9682735 38.4705
52 SMC4 chr3: 161600123-161635435 47.127047 4.581655 63.2353
53 SMC4 chr3: 161601040-161635435 46.967013 4.442065 61.2756
54 TU_0102399_0 chr9: 35759438-35761676 46.664973 6.44675 179.711
55 TU_0029005_0 chrX: 66690414-66704178 46.155567 1.0870047 38.3022
56 C15orf48 chr15: 43510054-43512939 45.732195 19.02125 223.42
57 C15orf48 chr15: 43510054-43512939 45.549287 21.28355 248.097
58 EFNA3 chr1: 153317971-153326638 44.993943 3.68358 70.5016
59 TU_0043412_0 chr13: 33918267-33935946 44.506741 1.311142 15.1968
60 TU_0069093_0 chr1: 220878648-220886461 42.645673 1.443496 160.898
61 UGT1A6 chr2: 234265059-234346684 42.500058 1.937622 45.753
62 TU_0057051_0 chr18: 54524352-54598419 42.108622 2.418785 56.0712
63 AMH chr19: 2200112-2203072 41.744334 2.16026 91.244
64 TU_0120908_0 chr2: 181147971-181168431 41.650097 1.0750564 48.7957
65 TU_0099873_0 chr8: 128138926-128140075 41.420293 1.51101 38.7353
66 HN1 chr17: 70642938-70662369 40.495209 16.35625 110.208
67 TU_0022570_0 chr19: 20341299-20343938 39.984803 2.912835 98.5739
68 TU_0098937_0 chr8: 95748751-95751321 39.740546 1.4422495 51.5935
69 TU_0040375_0 chr3: 133280694-133394609 39.664781 2.149005 90.9787
70 HN1 chr17: 70642938-70662370 39.655603 16.34725 109.587
71 TU_0120929_0 chr2: 181328093-181423017 39.419483 1.2116475 189.765
72 TU_0112004_0 chr15: 67644390-67650387 39.300923 6.10665 76.723
73 TU_0108439_0 chr15: 19293567-19296333 39.131646 1 27.7534
74 HN1 chr17: 70642938-70662369 39.00893 15.53595 103.782
75 SULT1C2 chr2: 108271526-108292803 39.007062 1.2259165 91.5617
76 STX19 chr3: 95215904-95230144 38.954223 4.521255 46.0375
77 TU_0030420_0 chrX: 112642982-112685485 38.715477 1.0890785 62.9419
78 TU_0099875_0 chr8: 128138047-128140075 38.489447 1.393413 35.8984
79 UBE2T chr1: 200567408-200577717 38.387515 3.070345 85.9738
80 SULT1C2 chr2: 108271526-108292803 37.817555 1.215033 88.0858
81 TU_0049429_0 chr4: 109263508-109272353 37.794245 1.09915225 29.1838
82 STMN1 chr1: 26099193-26105955 37.319869 14.3784 187.062
83 UGT1A1 chr2: 234333657-234346684 37.267194 1.660554 35.9476
84 LRRN1 chr3: 3816120-3864387 37.229013 3.8912 137.117
85 TU_0086631_0 chr5: 113806149-113806936 36.896806 1.0501165 29.6561
86 ORM2 chr9: 116131889-116135357 36.878688 3.614505 120.139
87 TU_0084060_0 chr5: 7932238-7932523 36.807599 1 23.1979
88 TU_0098644_0 chr8: 81204784-81207034 36.779294 1.6013735 64.9663
89 ACSM1 chr16: 20542059-20610079 36.280896 13.3707 317.077
90 STMN1 chr1: 26099193-26105231 35.882914 12.73275 164.721
91 STMN1 chr1: 26099193-26105580 35.823453 14.31935 185.329
92 TU_0120914_0 chr2: 181265370-181266053 35.551458 1.053468 30.7074
93 UGT1A7 chr2: 234255322-234346684 35.073998 1.667349 33.4378
94 TU_0087462_0 chr5: 136386339-136403134 34.992335 1.4450115 27.1703
95 UGT1A3 chr2: 234302511-234346684 34.952247 1.6889365 33.4202
96 UGT1A5 chr2: 234286376-234346684 34.950003 1.6639345 33.2718
97 FOXD1 chr5: 72777840-72780108 34.875512 1.2373575 10.80944
98 ADM chr11: 10283217-10285499 34.855767 11.83635 276.194
99 PPFIA4 chr1: 201286933-201314487 34.769924 1.566044 43.9812
100 UGT1A10 chr2: 234209861-234346690 34.738527 1.652799 32.7318
101 UGT1A4 chr2: 234292176-234346684 34.663597 1.655824 32.9264
102 UGT1A9 chr2: 234245282-234346690 34.648086 1.655272 32.852
103 TU_0090142_0 chr11: 4748677-4760303 34.517072 1.6226305 51.3411
104 TU_0082746_0 chr12: 120197102-120197416 34.499713 2.531095 59.9026
105 UGT1A8 chr2: 234191029-234346684 34.433379 1.6498025 32.5849
106 TU_0112207_0 chr15: 70278422-70286121 34.308752 10.40266 112.274
107 LOC145837 chr15: 67641112-67650833 34.291574 7.59729 74.8194
108 TU_0050712_0 chr4: 170217424-170228463 34.23107 1.504313 65.5606
109 TU_0043410_0 chr13: 33929484-33944669 34.112491 1.393529 24.8401
110 SNHG1 chr11: 62376035-62379936 33.971989 33.74365 270.512
111 MUC1 chr1: 153424923-153429324 33.838228 16.3238 664.278
112 MUC1 chr1: 153424923-153429324 33.823147 15.8436 644.44
113 TU_0099871_0 chr8: 128138047-128143500 33.697285 1.412872 33.2958
114 TU_0040383_0 chr3: 133360541-133429262 33.548813 2.553955 85.8384
115 MUC1 chr1: 153424923-153429324 33.495501 15.91355 627.622
116 TU_0049202_0 chr4: 102257900-102304755 33.391066 1.5555505 39.7522
117 TU_0120913_0 chr2: 181254530-181266950 33.188328 1 43.8515
118 B4GALNT4 chr11: 359794-372116 33.176248 6.3749 80.9639
119 TU_0100059_0 chr8: 141258835-141260573 33.169029 1.3615865 44.8943
120 TOP2A chr17: 35798321-35827695 33.132056 1.9725825 34.1032
121 MUC1 chr1: 153424923-153429324 33.081326 15.9539 632.042
122 TU_0001265_0 chr6: 27081719-27082291 33.045746 1.3381905 100.5401
123 C7orf53 chr7: 111908143-111918171 33.024251 2.820945 32.2465
124 SLC45A2 chr5: 33980477-34020537 32.952911 2.012104 54.8589
125 TU_0099869_0 chr8: 128138047-128225937 32.928048 1.308804 30.4667
126 UGT1A6 chr2: 234266250-234346690 32.918772 1.662221 31.4671
127 TU_0120917_0 chr2: 181265370-181266950 32.796137 1.0771403 36.3557
128 CACNA1D chr3: 53504070-53821532 32.608994 4.51306 44.9904
129 UBE2C chr20: 43874661-43879003 32.456813 1.6391285 58.398
130 ALDOC chr17: 23924259-23928078 32.455953 14.98415 228.812
131 MUC1 chr1: 153424923-153429324 32.44845 15.5895 599.062
132 MMP11 chr22: 22445035-22456503 32.411555 3.257735 73.9158
133 TU_0084303_0 chr5: 15899476-15955226 32.39036 2.21168 14.4385
134 CACNA1D chr3: 53504070-53821532 32.381439 4.484655 44.6867
135 UBE2C chr20: 43874661-43879003 32.358151 1.705223 57.8559
136 CACNA1D chr3: 53504070-53821532 32.353332 4.463805 44.2455
137 FGFRL1 chr4: 995609-1010686 32.275762 26.0133 450.449
138 FGFRL1 chr4: 996251-1010686 32.075261 27.0148 468.809
139 FGFRL1 chr4: 995759-1010686 32.069901 26.92945 467.246
140 MUC1 chr1: 153424923-153429324 32.011017 15.3218 586.058
141 TU_0099922_0 chr8: 128979617-128981414 31.833339 3.32544 32.6893
142 TU_0001173_0 chr6: 26385234-26386052 31.823293 2.339595 71.3388
143 MUC1 chr1: 153424923-153429324 31.781267 15.22945 587.582
144 TMEM178 chr2: 39746141-39798605 31.614406 13.40605 182.08
145 UBE2C chr20: 43874661-43879003 31.37539 1.7154185 58.1531
146 KCNC2 chr12: 73720162-73889778 31.294059 1.8783795 104.225
147 MAGEC2 chrX: 141117794-141120742 31.286618 1 34.1099
148 SERHL2 chr22: 41279868-41300332 31.131788 3.670135 61.9969
149 KCNC2 chr12: 73720162-73889778 31.126593 1.868714 108.199
150 GRAMD4 chr22: 45401321-45454352 31.063732 5.977725 79.8338
Table 8 shows the number of cancer-associated lncRNAs nominated for four major cancer types. The number validated is indicated in the column on the right. This table reflects ongoing efforts.
TABLE 8
# of cancer-specific # validated
lncRNAs nominated to date
Prostate cancer 121 11
Breast cancer 6 6
Lung cancer 36 32
Pancreatic cancer 34 0
All publications, patents, patent applications and accession numbers mentioned in the above specification are herein incorporated by reference in their entirety. Although the invention has been described in connection with specific embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications and variations of the described compositions and methods of the invention will be apparent to those of ordinary skill in the art and are intended to be within the scope of the following claims.
