ABERRANT MITOCHONDRIAL DNA, ASSOCIATED FUSION TRANSCRIPTS AND HYBRIDIZATION PROBES THEREFOR

The present invention provides novel mitochondrial fusion transcripts and the parent mutated mtDNA molecules that are useful for predicting, diagnosing and/or monitoring cancer. Hybridization probes complementary thereto for use in the methods of the invention are also provided.

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Description
CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Division of U.S. application Ser. No. 14/627,755, filed Feb. 20, 2015, now U.S. Pat. No. ______, issued ______, which is a Continuation of U.S. application Ser. No. 12/935,181, filed Jan. 17, 2011, now abandoned, which is a national entry of PCT Application No. PCT/CA2009/000351, filed Mar. 27, 2009, which claims priority under 35 U.S.C. § 119(e) from U.S. Provisional Application No. 61/040,616, filed Mar. 28, 2008. Each of the aforementioned applications is incorporated by reference herein as if set forth in its entirety.

FIELD OF THE INVENTION

The present invention relates to the field of mitochondrial genomics. In one aspect, the invention relates to the identification and use of mitochondrial genome fusion transcripts and probes that hybridize thereto.

BACKGROUND OF THE INVENTION

Mitochondrial Genome

The mitochondrial genome is a compact yet critical sequence of nucleic acids. Mitochondrial DNA, or “mtDNA”, comprises a small genome of 16,569 nucleic acid base pairs (bp) (Anderson et al., 1981; Andrews et al., 1999) in contrast to the immense nuclear genome of 3.3 billion bp (haploid). Its genetic complement is substantially smaller than that of its nuclear cell mate (0.0005%). However, individual cells carry anywhere from 103 to 104 mitochondria depending on specific cellular functions (Singh and Modica-Napolitano 2002). Communication or chemical signalling routinely occurs between the nuclear and mitochondrial genomes (Sherratt et al., 1997). Moreover, specific nuclear components are responsible for the maintenance and integrity of mitochondrial sequences (Croteau et al., 1999). All mtDNA genomes in a given individual are identical due to the clonal expansion of mitochondria within the ovum, once fertilization has occurred. However mutagenic events can induce sequence diversity reflected as somatic mutations. These mutations may accumulate in different tissues throughout the body in a condition known as heteroplasmy.

Mitochondrial Proteome

About 3,000 nuclear genes are required to construct, operate and maintain mitochondria, with only thirty-seven of these coded by the mitochondrial genome, indicating heavy mitochondrial dependence on nuclear loci. The mitochondrial genome codes for a complement of 24 genes, including 2 rRNAs and 22 tRNAs that ensure correct translation of the remaining 13 genes which are vital to electron transport (see FIG. 1). The mitochondrial genome is dependent on seventy nuclear encoded proteins to accomplish the oxidation and reduction reactions necessary for this vital function, in addition to the thirteen polypeptides supplied by the mitochondrial genome. Both nuclear and mitochondrial proteins form complexes spanning the inner mitochondrial membrane and collectively generate 80-90% of the chemical fuel adenosine triphosphate, or ATP, required for cellular metabolism. In addition to energy production, mitochondria play a central role in other metabolic pathways as well. A critical function of the mitochondria is mediation of cell death, or apoptosis (see Green and Kroemer, 2005). Essentially, there are signal pathways which permeabilize the outer mitochondrial membrane, or in addition, the inner mitochondrial membrane as well. When particular mitochondrial proteins are released into the cytosol, non-reversible cell death is set in motion. This process highlights the multi-functional role that some mitochondrial proteins have. These multi-tasking proteins suggest that there are other mitochondrial proteins as well which may have alternate functions.

Mitochondrial Fusion Transcriptome

The mitochondrial genome is unusual in that it is a circular, intron-less DNA molecule. The genome is interspersed with repeat motifs which flank specific lengths of sequences. Sequences between these repeats are prone to deletion under circumstances which are not well understood. Given the number of repeats in the mitochondrial genome, there are many possible deletions. The best known example is the 4977 “common deletion.” This deletion has been associated with several purported conditions and diseases and is thought to increase in frequency with aging (Dai et al., 2004; Ro et al., 2003; Barron et al., 2001; Lewis et al., 2000; Muller-Hocker, 1998; Porteous et al., 1998) (FIG. 4). The current thinking in the field of mitochondrial genomics is that mitochondrial deletions are merely deleterious by-products of damage to the mitochondrial genome by such agents as reactive oxygen species and UVR. (Krishnan et al 2008, Nature Genetics). Further, though it is recognized that high levels of mtDNA deletions can have severe consequences on the cell's ability to produce energy in the form of ATP as a result of missing gene sequences necessary for cellular respiration, it is not anticipated that these deleted mitochondrial molecules may be a component of downstream pathways, have an intended functional role, and possibly may be more aptly viewed as alternate natural forms of the recognized genes of the mitochondria as has been anticipated by the Applicant.

The sequence dynamics of mtDNA are important diagnostic tools. Mutations in mtDNA are often preliminary indicators of developing disease. For example, it has been demonstrated that point mutations in the mitochondrial genome are characteristic of tumour foci in the prostate. This trend also extends to normal appearing tissue both adjacent to and distant from tumour tissue (Parr et al. 2006). This suggests that mitochondrial mutations occur early in the malignant transformation pathway.

For example, the frequency of a 3.4 kb mitochondrial deletion has excellent utility in discriminating between benign and malignant prostate tissues (Maki et al. 2008).

Mitochondrial fusion transcripts have been reported previously in the literature, first in soybeans (Morgens et al. 1984) and then later in two patients with Kearns-Sayre Syndrome, a rare neuromuscular disorder (Nakase et al 1990). Importantly, these transcripts were not found to have (or investigated regarding) association with any human cancers.

SUMMARY OF THE INVENTION

An object of the present invention to provide aberrant mitochondrial DNA, associated fusion transcripts and hybridization probes therefor.

In accordance with an aspect of the invention, there is provided an isolated mitochondrial fusion transcript associated with cancer.

In accordance with an aspect of the invention, there is provided a mitochondrial fusion protein corresponding to the above fusion transcript, having a sequence as set forth in any one of SEQ ID NOs: 34 to 49 and 52.

In accordance with another aspect of the invention, there is provided an isolated mtDNA encoding a fusion transcript of the invention.

In accordance with another aspect of the invention, there is provided a hybridization probe having a nucleic acid sequence complementary to at least a portion of a mitochondrial fusion transcript or an mtDNA of the invention.

In accordance with another aspect of the invention, there is provided a method of detecting a cancer in a mammal, the method comprising assaying a tissue sample from the mammal for the presence of at least one mitochondrial fusion transcript associated with cancer by hybridizing the sample with at least one hybridization probe having a nucleic acid sequence complementary to at least a portion of a mitochondrial fusion transcript according to the invention.

In accordance with another aspect of the invention, there is provided a method of detecting a cancer in a mammal, the method comprising assaying a tissue sample from the mammal for the presence of at least one aberrant mtDNA associated with cancer by hybridizing the sample with at least one hybridization probe having a nucleic acid sequence complementary to at least a portion of an mtDNA according to the invention.

In accordance with another aspect of the invention, there is provided a kit for conducting an assay for detecting the presence of a cancer in a mammal, said kit comprising at least one hybridization probe complementary to at least a portion of a fusion transcript or an mtDNA of the invention.

In accordance with another aspect of the invention, there is provided a screening tool comprised of a microarray having 10's, 100's, or 1000's of mitochondrial fusion transcripts for identification of those associated with cancer.

In accordance with another aspect of the invention, there is provided a screening tool comprised of a microarray having 10's, 100's, or 1000's of mitochondrial DNAs corresponding to mitochondrial fusion transcripts for identification of those associated with cancer.

In accordance with another aspect of the invention, there is provided a screening tool comprised of a multiplexed branched DNA assay having 10's, 100's, or 1000's of mitochondrial fusion transcripts for identification of those associated with cancer.

In accordance with another aspect of the invention, there is provided a screening tool comprised of a multiplexed branched DNA assay having 10's, 100's, or 1000's of mitochondrial DNAs corresponding to mitochondrial fusion transcripts for identification of those associated with cancer.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments of the invention will now be described by way of example only with reference to the appended drawings wherein:

FIG. 1 is an illustration showing mitochondrial coding genes.

FIG. 2 shows polyadenalated fusion transcripts in prostate samples invoked by the loss of the 3.4 kb deletion.

FIG. 3 shows polyadenalated fusion transcripts in prostate samples invoked by the loss of the 4977 kb common deletion.

FIG. 4 shows polyadenalated fusion transcripts in breast samples invoked by the loss of the 3.4 kb segment from the mtgenome.

FIGS. 5A and 5B show an example of a mitochondrial DNA region before and after splicing of genes.

FIGS. 6A to 6BB illustrate the results for transcripts 2, 3, 8, 9, 10, 11 and 12 of the invention in the identification of colorectal cancer tumours.

FIGS. 7A to 7P illustrate the results for transcripts 6, 8, 10 and 20 of the invention in the identification of lung cancer tumours.

FIGS. 8A to 8BB illustrate the results for transcripts 6, 10, 11, 14, 15, 16 and 20 of the invention in the identification of melanomas.

FIGS. 9A to 9NN illustrate the results for transcripts 1, 2, 3, 6, 11, 12, 15 and 20 of the invention in the identification of ovarian cancer.

FIGS. 10A to 10K illustrate the results for transcripts 2, 3, 4, 11, 12, 13, 15, 16 and 20 of the invention in the identification of testicular cancer.

FIGS. 11A to 11I illustrate the results for transcripts 2, 3, 4, 11, 12, 13, 15, 16 and 20 of the invention in the identification of testicular cancer.

FIGS. 12A to 12E illustrate the results for transcripts 2, 3, 4, 11, 12, 13, 15, 16 and 20 of the invention in the identification of testicular cancer.

FIGS. 13A to 13I illustrate the results for transcripts 2, 3, 4, 11, 12, 13, 15, 16 and 20 of the invention in the identification of testicular cancer.

FIGS. 14A to 14I illustrate the results for transcripts 2, 3, 4, 11, 12, 13, 15, 16 and 20 of the invention in the identification of testicular cancer.

FIGS. 15A to 15N illustrate the results for transcripts 2, 3, 4, 11, 12, 13, 15, 16 and 20 of the invention in the identification of testicular cancer.

FIGS. 16A to 16E illustrate the results for transcripts 2, 3, 4, 11, 12, 13, 15, 16 and 20 of the invention in the identification of testicular cancer.

FIGS. 17A to 17J illustrate the results for transcripts 2, 3, 4, 11, 12, 13, 15, 16 and 20 of the invention in the identification of testicular cancer.

FIGS. 18A to 18I illustrate the results for transcripts 2, 3, 4, 11, 12, 13, 15, 16 and 20 of the invention in the identification of testicular cancer.

 DETAILED DESCRIPTION OF THE INVENTION

The present invention provides novel mitochondrial fusion transcripts and the parent mutated mtDNA molecules that are useful for predicting, diagnosing and/or monitoring cancer. The invention further provides hybridization probes for the detection of fusion transcripts and associated mtDNA molecules and the use of such probes.

Definitions

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

As used herein, “aberration” or “mutation” encompasses any modification in the wild type mitochondrial DNA sequence that results in a fusion transcript and includes, without limitation, insertions, translocations, deletions, duplications, recombinations, rearrangements or combinations thereof.

As defined herein, “biological sample” refers to a tissue or bodily fluid containing cells from which a molecule of interest can be obtained. For example, the biological sample can be derived from tissue such as prostate, breast, colorectal, lung and skin, or from blood, saliva, cerebral spinal fluid, sputa, urine, mucous, synovial fluid, peritoneal fluid, amniotic fluid and the like. The biological sample may be a surgical specimen or a biopsy specimen. The biological sample can be used either directly as obtained from the source or following a pre-treatment to modify the character of the sample. Thus, the biological sample can be pre-treated prior to use by, for example, preparing plasma or serum from blood, disrupting cells, preparing liquids from solid materials, diluting viscous fluids, filtering liquids, distilling liquids, concentrating liquids, inactivating interfering components, adding reagents, and the like.

A “continuous” transcript is a fusion transcript that keeps the reading frame from the beginning to the end of both spliced genes. An “end” transcript is a fusion transcript that results in a premature termination codon before the original termination codon of a second spliced gene.

As used herein, “mitochondrial DNA” or “mtDNA” is DNA present in mitochondria.

As used herein, the expression “mitochondrial fusion transcript” or “fusion transcript” refers to an RNA transcription product produced as a result of the transcription of a mutated mitochondrial DNA sequence wherein such mutations may comprise mitochondrial deletions and other large-scale mitochondrial DNA rearrangements.

Computer Analysis and Sequence Targeting

As discussed above, mitochondrial fusion transcripts have been reported in soybeans (Morgens et al. 1984) and in humans suffering from a rare neuromuscular disorder (Nakase et al 1990). Fusion transcripts associated with human cancer have not, however, been described.

Using the knowledge gained from mapping the large-scale deletions of the human mitochondrial genome associated with cancer, the observation of high frequencies of these deletions, and the evidence in another organism and another disease type of trancriptionally active mutated mtDNA molecules, Applicant hypothesized that such deletions may have importance beyond the DNA molecule and the damage and repair processes as it relates to cancer. To test this hypothesis computer analysis of the mitochondrial genome was conducted, specific for repeat elements, which suggested many potential deletion sites. Following this initial step identifying unique repeats in the mitochondrial sequence having non-adjacent or non-tandem locations, a filter was then applied to identify those repeats that upon initiating a deletion event in the DNA molecule would then likely reclose or religate to produce a fused DNA sequence having an open reading frame (ORF). A subset of 18 molecules were then selected for targetting to investigate whether: 1) they existed in the natural biological state of humans and 2) they had relevance to malignancy. Results from these investigations are described hereinafter.

Genomic Mutations

Mitochondrial DNA (mtDNA) dynamics are an important diagnostic tool. Mutations in mtDNA are often preliminary indicators of developing disease and behave as biomarkers indicative of risk factors associated with disease onset. According to the present invention, large-scale rearrangement mutations in the mitochondrial genome result in the generation of fusion transcripts associated with cancer. Thus, the use of mtDNA encoding such transcripts and probes directed thereto for the detection, diagnosis and monitoring of cancer is provided.

One of skill in the art will appreciate that the mtDNA molecules for use in the methods of the present invention may be derived through the isolation of naturally-occurring mutants or may be based on the complementary sequence of any of the fusion transcripts described herein. Exemplary mtDNA sequences and fusion transcripts are disclosed in Applicant's U.S. priority application No. 61/040,616, herein incorporated in its entirety by reference.

Detection of Mutant Genomic Sequences

Mutant mtDNA sequences according to the present invention may comprise any modification that results in the generation of a fusion transcript. Non-limiting examples of such modifications include insertions, translocations, deletions, duplications, recombinations, rearrangements or combinations thereof. While the modification or change can vary greatly in size from only a few bases to several kilobases, preferably the modification results in a substantive deletion or other large-scale genomic aberration.

Extraction of DNA to detect the presence of such mutations may take place using art-recognized methods, followed by amplification of all or a region of the mitochondrial genome, and may include sequencing of the mitochondrial genome, as described in Current Protocols in Molecular Biology. Alternatively, crude tissue homogenates may be used as well as techniques not requiring amplification of specific fragments of interest.

The step of detecting the mutations can be selected from any technique as is known to those skilled in the art. For example, analyzing mtDNA can comprise selection of targets by branching DNA, sequencing the mtDNA, amplifying mtDNA by PCR, Southern, Northern, Western South-Western blot hybridizations, denaturing HPLC, hybridization to microarrays, biochips or gene chips, molecular marker analysis, biosensors, melting temperature profiling or a combination of any of the above.

Any suitable means to sequence mitochondrial DNA may be used. Preferably, mtDNA is amplified by PCR prior to sequencing. The method of PCR is well known in the art and may be performed as described in Mullis and Faloona, 1987, Methods Enzymol., 155: 335. PCR products can be sequenced directly or cloned into a vector which is then placed into a bacterial host. Examples of DNA sequencing methods are found in Brumley, R. L. Jr. and Smith, L. M., 1991, Rapid DNA sequencing by horizontal ultrathin gel electrophoresis, Nucleic Acids Res. 19:4121-4126 and Luckey, J. A., et al, 1993, High speed DNA sequencing by capillary gel electrophoresis, Methods Enzymol. 218: 154-172. The combined use of PCR and sequencing of mtDNA is described in Hopgood, R., et al, 1992, Strategies for automated sequencing of human mtDNA directly from PCR products, Biotechniques 13:82-92 and Tanaka, M. et al, 1996, Automated sequencing of mtDNA, Methods Enzymol. 264: 407-421.

Methods of selecting appropriate sequences for preparing various primers are also known in the art. For example, the primer can be prepared using conventional solid-phase synthesis using commercially available equipment, such as that available from Applied Biosystems USA Inc. (Foster City, Calif.), DuPont, (Wilmington, Del.), or Milligen (Bedford, Mass.).

According to an aspect of the invention, to determine candidate genomic sequences, a junction point of a sequence deletion is first identified. Sequence deletions are primarily identified by direct and indirect repetitive elements which flank the sequence to be deleted at the 5′ and 3′ end. The removal of a section of the nucleotides from the genome followed by the ligation of the genome results in the creation of a novel junction point.

Upon identification of the junction point, the nucleotides of the genes flanking the junction point are determined in order to identify a spliced gene. Typically the spliced gene comprises the initiation codon from the first gene and the termination codon of the second gene, and may be expressed as a continuous transcript, i.e. one that keeps the reading frame from the beginning to the end of both spliced genes. It is also possible that alternate initiation or termination codons contained within the gene sequences may be used as is evidenced by SEQ ID No:2 and SEQ ID No: 17 disclosed herein. Some known mitochondrial deletions discovered to have an open reading frame (ORF) when the rearranged sequences are rejoined at the splice site are provided in Table 1.

Exemplary mtDNA molecules for use in the methods of the present invention, which have been verified to exist in the lab, are provided below. These mtDNAs are based on modifications of the known mitochondrial genome (SEQ ID NO: 1) and have been assigned a fusion or “FUS” designation, wherein A:B represents the junction point between the last mitochondrial nucleotide of the first spliced gene and the first mitochondrial nucleotide of the second spliced gene. The identification of the spliced genes is provided in parentheses followed by the corresponding sequence identifier. Where provided below, (AltMet) and (OrigMet) refer to alternate and original translation start sites, respectively.

    • FUS 8469:13447 (AltMet) (ATP synthase FO subunit 8 to NADH dehydrogenase subunit) (SEQ ID No: 2)
    • FUS 10744:14124 (NADH dehydrogenase subunit 4L (ND4L) to NADH dehydrogenase subunit 5 (ND5)) (SEQ ID No: 3)
    • FUS 7974:15496 (Cytochrome c oxidase subunit II (COII) to Cytochrome b (Cytb)) (SEQ ID No: 4)
    • FUS 7992:15730 (Cytochrome c oxidase subunit II (COII) to Cytochrome b (Cytb)) (SEQ ID No: 5)
    • FUS 8210:15339 (Cytochrome c oxidase subunit II (COII) to Cytochrome b (Cytb)) (SEQ ID No: 6)
    • FUS 8828:14896 (ATP synthase FO subunit 6 (ATPase6) to Cytochrome b (Cytb)) (SEQ ID No: 7)
    • FUS 10665:14856 (NADH dehydrogenase subunit 4L (ND4L) to Cytochrome b (Cytb)) (SEQ ID No: 8)
    • FUS 6075:13799 (Cytochrome c oxidase subunit I (COI) to NADH dehydrogenase subunit 5 (ND5)) (SEQ ID No: 9)
    • FUS 6325:13989 (Cytochrome c oxidase subunit I (COI) to NADH dehydrogenase subunit 5 (ND5)) (SEQ ID No: 10)
    • FUS 7438:13476 (Cytochrome c oxidase subunit I (COI) to NADH dehydrogenase subunit 5 (ND5)) (SEQ ID No: 11)
    • FUS 7775:13532 (Cytochrome c oxidase subunit II (COII) to NADH dehydrogenase subunit 5 (ND5)) (SEQ ID No: 12)
    • FUS 8213:13991 (Cytochrome c oxidase subunit II (COII) to NADH dehydrogenase subunit 5 (ND5)) (SEQ ID No: 13)
    • FUS 9191:12909 (ATP synthase FO subunit 6 (ATPase6) to NADH dehydrogenase subunit 5 (ND5)) (SEQ ID No: 14)
    • FUS 9574:12972 (Cytochrome c oxidase subunit III (COIII) to NADH dehydrogenase subunit 5 (ND5)) (SEQ ID No: 15)
    • FUS 10367:12829 (NADH dehydrogenase subunit 3 (ND3) to NADH dehydrogenase subunit 5 (ND5)) (SEQ ID No: 16)
    • FUS 8469:13447 (OrigMet) (ATP synthase FO subunit 8 to NADH dehydrogenase subunit) (SEQ ID No: 17)
    • FUS 9144:13816 ((ATP synthase FO subunit 6 (ATPase6) to NADH dehydrogenase subunit 5 (ND5)) (SEQ ID No: 51)

The present invention also provides the use of variants or fragments of these sequences for predicting, diagnosing and/or monitoring cancer.

“Variant”, as used herein, refers to a nucleic acid differing from a mtDNA sequence of the present invention, but retaining essential properties thereof. Generally, variants are overall closely similar, and, in many regions, identical to a select mtDNA sequence. Specifically, the variants of the present invention comprise at least one of the nucleotides of the junction point of the spliced genes, and may further comprise one or more nucleotides adjacent thereto. In one embodiment of the invention, the variant sequence is at least 80%, 85%, 90%, 95%, 96%, 97%, 98% or 99% identical to any one of the mtDNA sequences of the invention, or the complementary strand thereto.

In the present invention, “fragment” refers to a short nucleic acid sequence which is a portion of that contained in the disclosed genomic sequences, or the complementary strand thereto. This portion includes at least one of the nucleotides comprising the junction point of the spliced genes, and may further comprise one or more nucleotides adjacent thereto. The fragments of the invention are preferably at least about 15 nt, and more preferably at least about 20 nt, still more preferably at least about 30 nt, and even more preferably, at least about 40 nt, at least about 50 nt, at least about 75 nt, or at least about 150 nt in length. A fragment “at least 20 nt in length,” for example, is intended to include 20 or more contiguous bases of any one of the mtDNA sequences listed above. In this context “about” includes the particularly recited value, a value larger or smaller by several (5, 4, 3, 2, or 1) nucleotides, at either terminus or at both termini. These fragments have uses that include, but are not limited to, as diagnostic probes and primers as discussed herein. Of course, larger fragments (e.g., 50, 150, 500, 600, 2000 nucleotides) are also contemplated.

Thus, in specific embodiments of the invention, the mtDNA sequences are selected from the group consisting of:

SEQ ID NO: 2 (FUS 8469:13447; AltMet)

SEQ ID NO: 3 (FUS 10744:14124)

SEQ ID NO: 4 (FUS 7974:15496)

SEQ ID NO: 5 (FUS 7992:15730)

SEQ ID NO: 6 (FUS 8210:15339)

SEQ ID NO: 7 (FUS 8828:14896)

SEQ ID NO: 8 (FUS 10665:14856)

SEQ ID NO: 9 (FUS 6075:13799)

SEQ ID NO: 10 (FUS 6325:13989)

SEQ ID NO: 11 (FUS 7438:13476)

SEQ ID NO: 12 (FUS 7775:13532)

SEQ ID NO: 13 (FUS 8213:13991)

SEQ ID NO: 14 (FUS 9191:12909)

SEQ ID NO: 15 (FUS 9574:12972)

SEQ ID NO: 16 (FUS 10367:12829)

SEQ ID NO: 17 (FUS 8469:13447; OrigMet)

SEQ ID NO: 51 (FUS 9144:13816), and

fragments or variants thereof.

Probes

Another aspect of the invention is to provide a hybridization probe capable of recognizing an aberrant mtDNA sequence of the invention. As used herein, the term “probe” refers to an oligonucleotide which forms a duplex structure with a sequence in the target nucleic acid, due to complementarity of at least one sequence in the probe with a sequence in the target region. The probe may be labeled, according to methods known in the art.

Once aberrant mtDNA associated with a particular disease is identified, hybridization of mtDNA to, for example, an array of oligonucleotides can be used to identify particular mutations, however, any known method of hybridization may be used.

As with the primers of the present invention, probes may be generated directly against exemplary mtDNA fusion molecules of the invention, or to a fragment or variant thereof. For instance, the sequences set forth in SEQ ID NOs: 2-17 and 51 and those disclosed in Table 1 can be used to design primers or probes that will detect a nucleic acid sequence comprising a fusion sequence of interest. As would be understood by those of skill in the art, primers or probes which hybridize to these nucleic acid molecules may do so under highly stringent hybridization conditions or lower stringency conditions, such conditions known to those skilled in the art and found, for example, in Current Protocols in Molecular Biology (John Wiley & Sons, New York (1989)), 6.3.1-6.3.6.

In specific embodiments of the invention, the probes of the invention contain a sequence complementary to at least a portion of the aberrant mtDNA comprising the junction point of the spliced genes. This portion includes at least one of the nucleotides involved in the junction point A:B, and may further comprise one or more nucleotides adjacent thereto. In this regard, the present invention encompasses any suitable targeting mechanism that will select an mtDNA molecule using the nucleotides involved and/or adjacent to the junction point A:B.

Various types of probes known in the art are contemplated by the present invention. For example, the probe may be a hybridization probe, the binding of which to a target nucleotide sequence can be detected using a general DNA binding dye such as ethidium bromide, SYBR® Green, SYBR® Gold and the like. Alternatively, the probe can incorporate one or more detectable labels. Detectable labels are molecules or moieties a property or characteristic of which can be detected directly or indirectly and are chosen such that the ability of the probe to hybridize with its target sequence is not affected. Methods of labelling nucleic acid sequences are well-known in the art (see, for example, Ausubel et al., (1997 & updates) Current Protocols in Molecular Biology, Wiley & Sons, New York).

Labels suitable for use with the probes of the present invention include those that can be directly detected, such as radioisotopes, fluorophores, chemiluminophores, enzymes, colloidal particles, fluorescent microparticles, and the like. One skilled in the art will understand that directly detectable labels may require additional components, such as substrates, triggering reagents, light, and the like to enable detection of the label. The present invention also contemplates the use of labels that are detected indirectly.

The probes of the invention are preferably at least about 15 nt, and more preferably at least about 20 nt, still more preferably at least about 30 nt, and even more preferably, at least about 40 nt, at least about 50 nt, at least about 75 nt, or at least about 150 nt in length. A probe of “at least 20 nt in length,” for example, is intended to include 20 or more contiguous bases that are complementary to an mtDNA sequence of the invention. Of course, larger probes (e.g., 50, 150, 500, 600, 2000 nucleotides) may be preferable.

The probes of the invention will also hybridize to nucleic acid molecules in biological samples, thereby enabling the methods of the invention. Accordingly, in one aspect of the invention, there is provided a hybridization probe for use in the detection of cancer, wherein the probe is complementary to at least a portion of an aberrant mtDNA molecule. In another aspect the present invention provides probes and a use of (or a method of using) such probes for the detection of colorectal cancer, lung cancer, breast cancer, ovarian cancer, testicular, cancer, prostate cancer and/or melanoma skin cancer.

Assays

Measuring the level of aberrant mtDNA in a biological sample can determine the presence of one or more cancers in a subject. The present invention, therefore, encompasses methods for predicting, diagnosing or monitoring cancer, comprising obtaining one or more biological samples, extracting mtDNA from the samples, and assaying the samples for aberrant mtDNA by: quantifying the amount of one or more aberrant mtDNA sequences in the sample and comparing the quantity detected with a reference value. As would be understood by those of skill in the art, the reference value is based on whether the method seeks to predict, diagnose or monitor cancer. Accordingly, the reference value may relate to mtDNA data collected from one or more known non-cancerous biological samples, from one or more known cancerous biological samples, and/or from one or more biological samples taken over time.

In one aspect, the invention provides a method of detecting cancer in a mammal, the method comprising assaying a tissue sample from the mammal for the presence of an aberrant mitochondrial DNA described above. The present invention also provides for methods comprising assaying a tissue sample from the mammal by hybridizing the sample with at least one hybridization probe. The probe may be generated against a mutant mitochondrial DNA sequence of the invention as described herein.

In another aspect, the invention provides a method as above, wherein the assay comprises:

a) conducting a hybridization reaction using at least one of the probes to allow the at least one probe to hybridize to a complementary aberrant mitochondrial DNA sequence;

b) quantifying the amount of the at least one aberrant mitochondrial DNA sequence in the sample by quantifying the amount of the mitochondrial DNA hybridized to the at least one probe; and,

c) comparing the amount of the mitochondrial DNA in the sample to at least one known reference value.

Also included in the present invention are methods for predicting, diagnosing or monitoring cancer comprising diagnostic imaging assays as described below. The diagnostic assays of the invention can be readily adapted for high-throughput. High-throughput assays provide the advantage of processing many samples simultaneously and significantly decrease the time required to screen a large number of samples. The present invention, therefore, contemplates the use of the nucleotides of the present invention in high-throughput screening or assays to detect and/or quantitate target nucleotide sequences in a plurality of test samples.

Fusion Transcripts

The present invention further provides the identification of fusion transcripts and associated hybridization probes useful in methods for predicting, diagnosing and/or monitoring cancer. One of skill in the art will appreciate that such molecules may be derived through the isolation of naturally-occurring transcripts or, alternatively, by the recombinant expression of mtDNAs isolated according to the methods of the invention. As discussed, such mtDNAs typically comprise a spliced gene having the initiation codon from the first gene and the termination codon of the second gene. Accordingly, fusion transcripts derived therefrom comprise a junction point associated with the spliced genes.

Detection of Fusion Transcripts

Naturally occurring fusion transcripts can be extracted from a biological sample and identified according to any suitable method known in the art, or may be conducted according to the methods described in the examples. In one embodiment of the invention, stable polyadenylated fusion transcripts are identified using Oligo(dT) primers that target transcripts with poly-A tails, followed by RT-PCR using primer pairs designed against the target transcript.

The following exemplary fusion transcripts were detected using such methods and found useful in predicting, diagnosing and/or monitoring cancer as indicated in the examples. Likewise, fusion transcripts derived from the ORF sequences identified in Table 1 may be useful in predicting, diagnosing and/or monitoring cancer according to the assays and methods of the present invention.

SEQ ID NO: 18 (Transcripts 1;8469:13447; AltMet)

SEQ ID NO: 19 (Transcript 2;10744:14124)

SEQ ID NO: 20 (Transcript 3;7974:15496)

SEQ ID NO: 21 (Transcript 4;7992:15730)

SEQ ID NO: 22 (Transcript 5; 8210:15339)

SEQ ID NO: 23 (Transcript 6;8828:14896)

SEQ ID NO: 24 (Transcript 7;10665:14856)

SEQ ID NO: 25 (Transcript 8;6075:13799)

SEQ ID NO: 26 (Transcript 9;6325:13989)

SEQ ID NO: 27 (Transcript 10;7438:13476)

SEQ ID NO: 28 (Transcript 11;7775:13532)

SEQ ID NO: 29 (Transcript 12;8213:13991)

SEQ ID NO: 30 (Transcript 14;9191:12909)

SEQ ID NO: 31 (Transcript 15;9574:12972)

SEQ ID NO: 32 (Transcript 16;10367:12829)

SEQ ID NO: 33 (Transcript 20; 8469:13447; OrigMet)

SEQ ID NO: 50 (Transcript 13; 9144:13816)

Further, fusion transcripts of like character to those described herein are contemplated for use in the field of clinical oncology.

Fusion transcripts can also be produced by recombinant techniques known in the art. Typically this involves transformation (including transfection, transduction, or infection) of a suitable host cell with an expression vector comprising an mtDNA sequence of interest.

Variants or fragments of the fusion transcripts identified herein are also provided. Such sequences may adhere to the size limitations and percent identities described above with respect to genomic variants and fragments, or as determined suitable by a skilled technician.

In addition, putative protein sequences corresponding to transcripts 1-16 and 20 are listed below. These sequences, which encode hypothetical fusion proteins, are provided as a further embodiment of the present invention.

SEQ ID NO: 34 (Transcripts 1)

SEQ ID NO: 35 (Transcript 2)

SEQ ID NO: 36 (Transcript 3)

SEQ ID NO: 37 (Transcript 4)

SEQ ID NO: 38 (Transcript 5)

SEQ ID NO: 39 (Transcript 6)

SEQ ID NO: 40 (Transcript 7)

SEQ ID NO: 41 (Transcript 8)

SEQ ID NO: 42 (Transcript 9)

SEQ ID NO: 43 (Transcript 10)

SEQ ID NO: 44 (Transcript 11)

SEQ ID NO: 45 (Transcript 12)

SEQ ID NO: 46 (Transcript 14)

SEQ ID NO: 47 (Transcript 15)

SEQ ID NO: 48 (Transcript 16)

SEQ ID NO: 49 (Transcripts 20)

SEQ ID NO: 52 (Transcript 13)

Probes

Once a fusion transcript has been characterized, primers or probes can be developed to target the transcript in a biological sample. Such primers and probes may be prepared using any known method (as described above) or as set out in the examples provided below. A probe may, for example, be generated for the fusion transcript, and detection technologies, such as QuantiGene 2.0™ by Panomics™, used to detect the presence of the transcript in a sample. Primers and probes may be generated directly against exemplary fusion transcripts of the invention, or to a fragment or variant thereof. For instance, the sequences set forth in SEQ ID NOs: 18-33 and 50 as well as those disclosed in Table 1 can be used to design probes that will detect a nucleic acid sequence comprising a fusion sequence of interest.

As would be understood by those skilled in the art, probes designed to hybridize to the fusion transcripts of the invention contain a sequence complementary to at least a portion of the transcript expressing the junction point of the spliced genes. This portion includes at least one of the nucleotides complementary to the expressed junction point, and may further comprise one or more complementary nucleotides adjacent thereto. In this regard, the present invention encompasses any suitable targeting mechanism that will select a fusion transcript that uses the nucleotides involved and adjacent to the junction point of the spliced genes.

Various types of probes and methods of labelling known in the art are contemplated for the preparation of transcript probes. Such types and methods have been described above with respect to the detection of genomic sequences. The transcript probes of the invention are preferably at least about 15 nt, and more preferably at least about 20 nt, still more preferably at least about 30 nt, and even more preferably, at least about 40 nt, at least about 50 nt, at least about 75 nt, or at least about 150 nt in length. A probe of “at least 20 nt in length,” for example, is intended to include 20 or more contiguous bases that are complementary to an mtDNA sequence of the invention. Of course, larger probes (e.g., 50, 150, 500, 600, 2000 nucleotides) may be preferable.

In one aspect, the invention provides a hybridization probe for use in the detection of cancer, wherein the probe is complementary to at least a portion of a mitochondrial fusion transcript provided above.

In another aspect, the present invention provides probes and a use of (or a method of using) such probes for the detection of colorectal cancer, lung cancer, breast cancer, ovarian cancer, testicular cancer, prostate cancer or melanoma skin cancer.

Assays

Measuring the level of mitochondrial fusion transcripts in a biological sample can determine the presence of one or more cancers in a subject. The present invention, therefore, provides methods for predicting, diagnosing or monitoring cancer, comprising obtaining one or more biological samples, extracting mitochondrial RNA from the samples, and assaying the samples for fusion transcripts by: quantifying the amount of one or more fusion transcripts in the sample and comparing the quantity detected with a reference value. As would be understood by those of skill in the art, the reference value is based on whether the method seeks to predict, diagnose or monitor cancer. Accordingly, the reference value may relate to transcript data collected from one or more known non-cancerous biological samples, from one or more known cancerous biological samples, and/or from one or more biological samples taken over time.

In one aspect, the invention provides a method of detecting a cancer in a mammal, the method comprising assaying a tissue sample from said mammal for the presence of at least one fusion transcript of the invention by hybridizing said sample with at least one hybridization probe having a nucleic acid sequence complementary to at least a portion of the mitochondrial fusion transcript.

In another aspect, the invention provides a method as above, wherein the assay comprises:

a) conducting a hybridization reaction using at least one of the above-noted probes to allow the at least one probe to hybridize to a complementary mitochondrial fusion transcript;

b) quantifying the amount of the at least one mitochondrial fusion transcript in the sample by quantifying the amount of the transcript hybridized to the at least one probe; and,

c) comparing the amount of the mitochondrial fusion transcript in the sample to at least one known reference value.

As discussed above, the diagnostic assays of the invention may also comprise diagnostic methods and screening tools as described herein and can be readily adapted for high-throughput. The present invention, therefore, contemplates the use of the fusion transcripts and associated probes of the present invention in high-throughput screening or assays to detect and/or quantitate target nucleotide sequences in a plurality of test samples.

Diagnostic Methods and Screening Tools

Methods and screening tools for diagnosing specific diseases or identifying specific mitochondrial mutations are also herein contemplated. Any known method of hybridization may be used to carry out such methods including, without limitation, probe/primer based technologies such as branched DNA and qPCR, both single-plex and multi-plex. Array technology, which has oligonucleotide probes matching the wild type or mutated region, and a control probe, may also be used. Commercially available arrays such as microarrays or gene chips are suitable. These arrays contain thousands of matched and control pairs of probes on a slide or microchip, and are capable of sequencing the entire genome very quickly. Review articles describing the use of microarrays in genome and DNA sequence analysis are available on-line.

Screening tools designed to identify targets which are relevant to a given biological condition may include specific arrangements of nucleic acids associated with a particular disease or disorder. Thus, in accordance with one embodiment of the invention, there is provided a screening tool comprised of a microarray having 10's, 100's, or 1000's of mitochondrial fusion transcripts for identification of those associated with one or more cancers. In accordance with another embodiment, there is provided a screening tool comprised of a microarray having 10's, 100's, or 1000's of mitochondrial DNAs corresponding to mitochondrial fusion transcripts for identification of those associated with one or more cancers. In a further embodiment, there is provided a screening tool comprised of a multiplexed branched DNA assay having 10's, 100's, or 1000's of mitochondrial fusion transcripts for identification of those associated with one or more cancers. In yet another embodiment of the invention, there is provided a screening tool comprised of a multiplexed branched DNA assay having 10's, 100's, or 1000's of mitochondrial DNAs corresponding to mitochondrial fusion transcripts for identification of those associated with one or more cancers.

Approaches useful in the field of clinical oncology are also herein contemplated and may include such diagnostic imaging techniques as Positron Emission Tomography (PET), contrast Magnetic Resonance Imaging (MRI) or the like. These diagnostic methods are well known to those of skill in the art and are useful in the diagnosis and prognosis of cancer.

Diagnostic Monitoring

The methods of the present invention may further comprise the step of recommending a monitoring regime or course of therapy based on the outcome of one or more assays. This allows clinicians to practice personalized medicine; e.g. cancer therapy, by monitoring the progression of the patient's cancer (such as by recognizing when an initial or subsequent mutation occurs) or treatment (such as by recognizing when a mutation is stabilized).

With knowledge of the boundaries of the sequence variation in hand, the information can be used to diagnose a pre-cancerous condition or existing cancer condition. Further, by quantitating the amount of aberrant mtDNA in successive samples over time, the progression of a cancer condition can be monitored. For example, data provided by assaying the patient's tissues at one point in time to detect a first set of mutations from wild-type could be compared against data provided from a subsequent assay, to determine if changes in the aberration have occurred.

Where a mutation is found in an individual who has not yet developed symptoms of cancer, the mutation may be indicative of a genetic susceptibility to develop a cancer condition. A determination of susceptibility to disease or diagnosis of its presence can further be evaluated on a qualitative basis based on information concerning the prevalence, if any, of the cancer condition in the patient's family history and the presence of other risk factors, such as exposure to environmental factors and whether the patient's cells also carry a mutation of another sort.

Biological Sample

The present invention provides for diagnostic tests which involve obtaining or collecting one or more biological samples. In the context of the present invention, “biological sample” refers to a tissue or bodily fluid containing cells from which mtDNA and mtRNA can be obtained. For example, the biological sample can be derived from tissue including, but not limited to, skin, lung, breast, prostate, nervous, muscle, heart, stomach, colon, rectal tissue and the like; or from blood, saliva, cerebral spinal fluid, sputa, urine, mucous, synovial fluid, peritoneal fluid, amniotic fluid and the like. The biological sample may be obtained from a cancerous or non-cancerous tissue and may be, but is not limited to, a surgical specimen or a biopsy specimen.

The biological sample can be used either directly as obtained from the source or following a pre-treatment to modify the character of the sample. Thus, the biological sample can be pre-treated prior to use by, for example, preparing plasma or serum from blood, disrupting cells, preparing liquids from solid materials, diluting viscous fluids, filtering liquids, distilling liquids, concentrating liquids, inactivating interfering components, adding reagents, and the like.

One skilled in the art will understand that more than one sample type may be assayed at a single time (i.e. for the detection of more than one cancer). Furthermore, where a course of collections are required, for example, for the monitoring of cancer over time, a given sample may be diagnosed alone or together with other samples taken throughout a test period. In this regard, biological samples may be taken once only, or at regular intervals such as biweekly, monthly, semi-annually or annually.

Kits

The present invention provides diagnostic/screening kits for detecting cancer in a clinical environment. Such kits may include one or more sampling means, in combination with one or more probes according to the present invention.

The kits can optionally include reagents required to conduct a diagnostic assay, such as buffers, salts, detection reagents, and the like. Other components, such as buffers and solutions for the isolation and/or treatment of a biological sample, may also be included in the kit. One or more of the components of the kit may be lyophilised and the kit may further comprise reagents suitable for the reconstitution of the lyophilised components.

Where appropriate, the kit may also contain reaction vessels, mixing vessels and other components that facilitate the preparation of the test sample. The kit may also optionally include instructions for use, which may be provided in paper form or in computer-readable form, such as a disc, CD, DVD or the like.

In one embodiment of the invention there is provided a kit for diagnosing cancer comprising sampling means and a hybridization probe of the invention.

Various aspects of the invention will be described by illustration using the following examples. The examples provided herein serve only to illustrate certain specific embodiments of the invention and are not intended to limit the scope of the invention in any way.

EXAMPLES Example 1: Detection of Mitochondrial Fusion Transcripts

The mitochondrial 4977 “common deletion” and a 3.4 kb deletion previously identified by the present Applicant in PCT application no. PCT/CA2007/001711 (the entire contents of which are incorporated by reference) result in unique open reading frames having active transcripts as identified by oligo-dT selection in prostate tissue (FIGS. 2 and 3). Examination of breast tissue samples also reveals the presence of a stable polyadenylated fusion transcript resulting from the 3.4 kb deletion (FIG. 4).

Reverse Transcriptase-PCR Protocol for Deletion Transcript Detection

RNA Isolation cDNA Synthesis

Total RNA was isolated from snap frozen prostate and breast tissue samples (both malignant and normal samples adjacent to tumours) using the Aurum™ Total RNA Fatty and Fibrous Tissue kit (Bio-Rad, Hercules, Calif.) following the manufacturer's instructions. Since in this experiment, genomic DNA contamination was to be avoided, a DNase I treatment step was included, using methods as commonly known in the art. RNA quantity and quality were determined with an ND-1000 spectrophotometer (NanoDrop® technologies). From a starting material of about 100 g, total RNA concentrations varied from 100-1000 ng/ul with a 260/280 ratio between 1.89-2.10. RNA concentrations were adjusted to 100 ng/ul and 2 ul of each template were used for first strand DNA synthesis with SuperScript™ First-Strand Synthesis System for RT-PCR (Invitrogen) following the manufacturer's instructions. In order to identify stable polyadenylated fusion transcripts, Oligo(dT) primers that target transcripts with poly-A tails were used.

PCR

Real time PCR was performed using 5 ul of each cDNA template with the iQ™ SYBR® Green Supermix (Bio-Rad, Hercules, Calif.) on DNA Engine Opticon® 2 Continuous Fluorescence Detection System (Bio-Rad, Hercules, Calif.). The primer pairs targeting the 4977 bp deletion are; 8416F 5′-CCTTACACTATTCCTCATCAC-3′ (SEQ ID NO: 53), 13637R 5′-TGACCTGTTAGGGTGAGAAG-3′ (SEQ ID NO: 54), and those for the 3.4 kb deletion are; ND4LF 5′-TCGCTCACACCTCATATCCTC-3′ (SEQ ID NO: 55), ND5R 5′-TGTGATTAGGAGTAGGGTTAGG-3′ (SEQ ID NO: 56). The reaction cocktail included: 2× SYBR® Green Supermix (100 mM KCL, 40 mM Tris-HCl, pH 8.4, 0.4 mM of each dNTP [dATP, dCTP, dGTP, and dTTP], iTaq™ DNA polymerase, 50 units/ml, 6 mM MgCl2, SYBR® Green 1, 20 nM flourescein, and stabilizers), 250 nM each of primers, and ddH2O. PCR cycling parameters were as follows; (1) 95° C. for 2 min, (2) 95° C. for 30 sec, (3) 55° C. (for the 4977 bp deletion) and 63° C. (for the 3.4 kb deletion) for 30 sec, (4) 72° C. for 45 sec, (5) plate read, followed by 39 cycles of steps 3 to 5, and final incubation at 4° C. Apart from cycling threshold and melting curve analysis, samples were run on agarose gels for specific visualization of amplification products (see FIGS. 2 to 4).

FIG. 2 is an agarose gel showing polyadenalated fusion transcripts in prostate samples invoked by the loss of 3.4 kb from the mitochondrial genome. Legend for FIG. 2: B-blank, Lanes 1-6 transcripts detected in cDNA; lanes 7-12 no reverse transcriptase (RT) controls for samples in lanes 1-6.

FIG. 3 shows polyadenalated fusion transcripts in prostate samples invoked by the loss of the 4977 kb common deletion. Legend for FIG. 3: B-blank, Lanes 1-6 transcripts detected in cDNA; lanes 7-12 no RT controls for samples in lanes 1-6.

FIG. 4 shows polyadenalated fusion transcripts in breast samples invoked by the loss of 3.4 kb from the mtgenome. Legend for FIG. 4: Lanes 2-8 transcripts from breast cDNAs; lane 9 negative (water) control; lanes 10 and 11, negative, no RT, controls for samples in lanes 2 and 3.

These results demonstrate the existence of stable mitochondrial fusion transcripts.

Example 2: Identification and Targeting of Fusion Products

Various hybridization probes were designed to detect, and further demonstrate the presence of novel transcripts resulting from mutated mitochondrial genomes, such as the 3.4 kb deletion. For this purpose, a single-plex branched DNA platform for quantitative gene expression analysis (QuantiGene 2.0™, Panomics™) was utilized. The specific deletions and sequences listed in this example are based on their relative positions with the entire mtDNA genome, which is recited in SEQ ID NO: 1. The nucleic acid sequences of the four transcript to which the probes were designed in this example are identified herein as follows: Transcript 1 (SEQ ID NO: 18), Transcript 2 (SEQ ID NO: 19), Transcript 3 (SEQ ID NO: 20) and Transcript 4 (SEQ ID NO: 21).

An example of a continuous transcript from the 3.4 kb mitochondrial genome deletion occurs with the genes ND4L (NADH dehydrogenase subunit 4L) and ND5 (NADH dehydrogenase subunit 5). A probe having a complementary sequence to SEQ ID NO: 19, was used to detect transcript 2. The repetitive elements occur at positions 10745-10754 in ND4L and 14124-14133 in ND5.

The 3.4 kb deletion results in the removal of the 3′ end of ND4L, the full ND4 gene, tRNA histidine, tRNA serine2, tRNA leucine2, and the majority of the 5′ end of ND5 (see FIG. 5a), resulting in a gene splice of ND4L and ND5 with a junction point of 10744 (ND4L):14124 (ND5) (FIG. 5b). SEQ ID NO: 3 is the complementary DNA sequence to the RNA transcript (SEQ ID NO: 19) detected in the manner described above.

Similarly, transcript 1 is a fusion transcript between ATPase 8 and ND5 associated with positions 8469:13447 (SEQ ID NO: 18). Transcripts 3 and 4 (SEQ ID NO: 20 and SEQ ID NO: 21, respectively) are fusion transcripts between COII and Cytb associated with nucleotide positions 7974:15496 and 7992:15730 respectively. Table 3 provides a summary of the relationships between the various sequences used in this example. Table 3 includes the detected fusion transcript and the DNA sequence complementary to the fusion transcript detected.

Example 3: Application to Prostate Cancer

Using the four fusion transcripts, i.e. transcripts 1 to 4, discussed above, two prostate tissue samples from one patient were analyzed to assess the quantitative difference of the novel predicted fusion transcripts. The results of the experiment are provided in Table 2 below, wherein “Homog 1” refers to the homogenate of frozen prostate tumour tissue from a patient and “Homog 2” refers to the homogenate of frozen normal prostate tissue adjacent to the tumour of the patient. These samples were processed according to the manufacturer's protocol (QuantiGene® Sample Processing Kit for Fresh or Frozen Animal Tissues; and QuantiGene® 2.0 Reagent System User Manual) starting with 25.8 mg of Homog 1 and 28.9 mg of Homog 2 (the assay setup is shown in Tables 5a and 5b).

Clearly demonstrated is an increased presence of mitochondrial fusion transcripts in prostate cancer tissue compared to normal adjacent prostate tissue. The fusion transcript is present in the normal tissue, although at much lower levels. The relative luminescence units (RLU) generated by hybridization of a probe to a target transcript are directly proportional to the abundance of each transcript. Table 2 also indicates the coefficients of variation, CV, expressed as a percentage, of the readings taken for the samples. The CV comprises the Standard deviation divided by the average of the values. The significance of such stably transcribed mitochondrial gene products in cancer tissue has implications in disease evolution and progression.

Example 4: Application to Breast Cancer

Using the same protocol from Example 3 but focusing only on Transcript 2, the novel fusion transcript associated with the 3.4 kb mtgenome deletion, analyses were conducted on two samples of breast tumour tissue and two samples of tumour-free tissues adjacent to those tumours, as well as three samples of prostate tumour tissue, one sample comprising adjacent tumour-free tissue. Results for this example are provided in Table 4. The prostate tumour tissue sample having a corresponding normal tissue section demonstrated a similar pattern to the prostate sample analyzed in Example 3 in that the tumour tissue had approximately 2 times the amount of the fusion transcript than did the normal adjacent tissue. The breast tumour samples demonstrated a marked increase in the fusion transcript levels when compared to the adjacent non-tumour tissues. A 1:100 dilution of the homogenate was used for this analysis as it performed most reproducibly in the experiment cited in Example 3.

Thus, the above discussed results illustrate the application of the transcripts of the invention in the detection of tumours of both prostate and breast tissue.

Example 5: Application to Colorectal Cancer

This study sought to determine the effectiveness of several transcripts of the invention in detecting colorectal cancer. A total of 19 samples were prepared comprising nine control (benign) tissue samples (samples 1 to 9) and ten tumour (malignant) tissue samples (samples 10 to 19). The samples were homogenized according to the manufacturer's recommendations (Quantigene® Sample Processing Kit for Fresh or Frozen Animal Tissues; and Quantigene 2.0 Reagent System User Manual). Seven target transcripts and one housekeeper transcript were prepared in the manner as outlined above in previous examples. The characteristics of the transcripts are summarized as follows:

TABLE 7 Characteristics of Breast Cancer Transcripts Transcript ID Junction Site Gene Junction 2 10744:14124  ND4L:ND5 3 7974:15496 COII:Cytb 10 7438:13476 COI:ND5 11 7775:13532 COII:ND5 12 8213:13991 COII:ND5 Peptidylpropyl isomerase B (PPIB) N/A N/A (“housekeeper”)

It is noted that transcripts 2 and 3 are the same as those discussed above with respect to Examples 3 and 4.

Homogenates were prepared using approximately 25 mg of tissue from OCT blocks and diluted 1:1 for transcripts 2 and 4, and 1:8 for transcripts 10 and 11. The quantity of the transcripts was measured in Relative Luminenscence Units RLU on a Glomax™ Multi Detection System (Promega). All samples were assayed in triplicate for each transcript. Background measurements (no template) were done in triplicate as well. The analysis accounted for background by subtracting the lower limit from the RLU values for the samples. Input RNA was accounted for by using the formula log2 a RLU−log2 h RLU where a is the target fusion transcript and h is the housekeeper transcript.

The analysis of the data comprised the following steps:

a) Establish CV's (coefficients of variation) for triplicate assays; acceptable if 15%.

b) Establish average RLU value for triplicate assays of target fusion transcript (a) and housekeeper transcript (h).

c) Establish lower limit from triplicate value of background RLU (I).

d) Subtract lower limit (I) from (a).

e) Calculate log2 a RLU−log 2 h RLU.

Summary of Results:

The results of the above analysis are illustrated in FIGS. 6a to 6g, which comprise plots of the log2 a RLU−log 2 h RLU against sample number. Also illustrated are the respective ROC (Receiver Operating Characteristic) curves determined from the results for each transcript.

Transcript 2:

There exists a statistically significant difference between the means (p<0.10) of the normal and malignant groups (p>0.09), using a cutoff value of 3.6129 as demonstrated by the ROC curve results in a sensitivity of 60% and specificity of 89% and the area under the curve is 0.73 indicating fair test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 3:

There exists a statistically significant difference between the means (p<0.05) of the normal and malignant groups (p=0.03), using a cutoff value of 4.0813 as demonstrated by the ROC curve results in a sensitivity of 60% and specificity of 78% and the area under the curve is 0.79 indicating fair to good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 8:

There exists a statistically significant difference between the means (p<0.1) of the normal and malignant groups (p=0.06). Using a cutoff value of −6.0975 as demonstrated by the ROC curve results in a sensitivity of 60% and specificity of 89% and the area under the curve is 0.76 indicating fair test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 9:

There exists a statistically significant difference between the means (p<0.1) of the normal and malignant groups (p=0.06). Using a cutoff value of −7.5555 as demonstrated by the ROC curve results in a sensitivity of 60% and specificity of 89% and the area under the curve is 0.76 indicating fair to good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 10:

There is a statistically significant difference between the means (100.01) of the normal and malignant groups (p=0.01). Using a cutoff value of −3.8272 as demonstrated by the ROC curve results in a sensitivity of 90% and specificity of 67% and the area under the curve is 0.84, indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 11:

There exists a statistically significant difference between the means (p<0.1) of the normal and malignant groups (p=0.06), using a cutoff value of 3.1753 as demonstrated by the ROC curve results in a sensitivity of 70% and specificity of 78% and the area under the curve is 0.76 indicating fair to good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 12:

There exists a statistically significant difference between the means (p<0.1) of the normal and malignant groups (p=0.06), using a cut-off value of 3.2626 as demonstrated by the ROC curve results in a sensitivity of 70% and specificity of 78% and the area under the curve is 0.76 indicating fair to good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Conclusions:

The above results illustrate the utility of transcripts 2, 3, 8, 9, 10, 11, and 12 in the detection of colorectal cancer and in distinguishing malignant from normal colorectal tissue. As indicated above, transcripts 2 and 3 were also found to have utility in the detection of prostate cancer. Transcript 2 was also found to have utility in the detection of breast cancer. Transcript 11 was also found to have utility in the detection of melanoma skin cancer. Transcript 10 was also found to have utility in the detection of lung cancer and melanoma. Transcript 8 was also found to have utility in the detection of lung cancer. Any of the 7 transcripts listed may be used individually or in combination as a tool for the detection of characterization of colorectal cancer in a clinical setting.

Example 6: Application to Lung Cancer

This study sought to determine the effectiveness of several transcripts of the invention in the detection of lung cancer. As in Example 5, nine control (benign) tissue samples (samples 1 to 9) and ten tumour (malignant) tissue samples (samples 10 to 19) were homogenized according to the manufacturer's recommendations (Quantigene® Sample Processing Kit for Fresh or Frozen Animal Tissues; and Quantigene 2.0 Reagent System User Manual). Homogenates were diluted 1:8 and the quantity of 4 target transcripts and 1 housekeeper transcript was measured in Relative Luminenscence Units RLU on a Glomax™ Multi Detection System (Promega). All samples were assayed in triplicate for each transcript. Background measurements (no template) were done in triplicate as well.

The following transcripts were prepared for this example:

TABLE 8 Characteristics of Lung Cancer Transcripts Transcript ID Junction Site Gene Junction 6 8828:14896 ATPase6:Cytb 8 6075:13799 COI:ND5 10 7438:13476 COI:ND5 20 8469:13447 ATPase8:ND5 Peptidylpropyl isomerase B (PPIB) N/A N/A (“housekeeper”)

The tissue samples used in this example had the following characteristics:

TABLE 9 Characteristics of Lung Cancer Samples Sample Malignant Comments (source of tissue) 1 NO interstitial lung disease 2 NO emphysema 3 NO aneurysm 4 NO bronchopneumonia, COPD 5 NO malignant neoplasm in liver, origin unknown, calcified granulomas in lung 6 NO 12 hours post mortem, mild emphysema 7 NO 12 hours post mortem, large B cell lymphoma, pulmonary edema, pneumonia 8 NO pneumonia, edema, alveolar damage 9 NO congestion and edema 10 YES adenocarcinoma, non-small cell 11 YES small cell 12 YES squamous cell carcinoma, NSC, emphysema 13 YES adenocarcinoma, lung cancer, nsc, metastatic 14 YES squamous cell carcinoma, non-small cell 15 YES mixed squamous and adenocarcinoma 16 YES non-small cell carcinoma, squamous 17 YES small cell carcinoma 18 YES adenocarcinoma, lung cancer, nsc 19 YES adenocarcinoma, lung cancer, nsc, metastatic

The analysis of data was performed according to the method described in Example 5. The results are illustrated in FIGS. 7a, 7b, 7c and 7d.

Summary of Results:

Transcript 6:

There exists a statistically significant difference between the means (p<0.1) of the normal (benign) and malignant groups (p=0.06), using a cutoff value of −6.5691 as demonstrated by the ROC curve results in a sensitivity of 80% and specificity of 71% and the area under the curve is 0.77, indicating fair test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 8:

The difference between the means of the normal and malignant groups is statistically significant, p<0.05 (p=0.02). Using a cutoff value of −9.6166 as demonstrated by the ROC curve results in a sensitivity of 90% and specificity of 86% and the area under the curve is 0.86 indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 10:

The difference between the means of the normal and malignant groups is statistically significant, p≤0.01 (p=0.01). Using a cutoff value of −10.6717 as demonstrated by the ROC curve results in a sensitivity of 90% and specificity of 86% and the area under the curve is 0.89 indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 20:

The difference between the means of the normal and malignant groups is statistically significant, p≤0.1 (p=0.1). Using a cutoff value of 2.5071 as demonstrated by the ROC curve results in a sensitivity of 70% and specificity of 71% and the area under the curve is 0.74 indicating fair test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Conclusions:

The results from example 6 illustrate the utility of transcripts 6, 8, 10, and 20 of the invention in the detection of lung cancer tumours and the distinction between malignant and normal lung tissues. Any of these three transcripts may be used for the detection or characterization of lung cancer in a clinical setting.

Example 7: Application to Melanoma

This study sought to determine the effectiveness of several transcripts of the invention in the detection of melanomas. In this study a total of 14 samples were used, comprising five control (benign) tissue samples and nine malignant tissue samples. All samples were formalin fixed, paraffin embedded (FFPE). The FFPE tissue samples were sectioned into tubes and homogenized according to the manufacturer's recommendations (Quantigene® 2.0 Sample Processing Kit for FFPE Samples; and Quantigene 2.0 Reagent System User Manual) such that each sample approximated 20 microns prior to homogenization. Homogenates were diluted 1:4 and the quantity of 7 target transcripts and 1 housekeeper transcript was measured in Relative Luminenscence Units RLU on a Glomax™ Multi Detection System (Promega). All samples were assayed in triplicate for each transcript. Background measurements (no template) were done in triplicate as well.

The 14 tissue samples used in this example had the following characteristics:

TABLE 10 Characteristics of Melanoma Cancer Samples Sample Malignant Comments (source of tissue) 1 NO breast reduction tissue (skin) 2 NO breast reduction tissue (skin) 3 NO breast reduction tissue (skin) 4 NO breast reduction tissue (skin) 5 NO breast reduction tissue (skin) 6 YES lentigo maligna, (melanoma in situ) invasive melanoma not present 7 YES invasive malignant melanoma 8 YES nodular melanoma, pT3b, associated features of lentigo maligna 9 YES residual superficial spreading invasive malignant melanoma, Clark's level II 10 YES superficial spreading malignant melanoma, Clark's Level II 11 YES nodular malignant melanoma, Clark's level IV 12 YES superficial spreading malignant melanoma in situ, no evidence of invasion 13 YES superficial spreading malignant melanoma, Clark's level II, focally present vertical phase 14 YES superficial spreading malignant melanoma in situ, Clark's level I

The following transcripts were prepared for this example:

TABLE 11 Characteristics of Melanoma Cancer Transcripts Transcript ID Junction Site GeneJunction 6 8828:4896  ATPase6:Cytb 10 7438:13476 COI:ND5 11 7775:13532 COII:ND5 14 9191:12909 ATPase6:ND5 15 9574:12972 COIII:ND5 16 10367:12829  ND3:ND5 20 8469:13447 ATPase8:ND5 Peptidylpropyl isomerase B (PPIB) N/A N/A (“housekeeper”)

As indicated, transcripts 10 and 11 were also used in Example 5. The analysis of data was performed according to the method described in Example 5. The results are illustrated in FIGS. 8a-8g.

Summary of Results:

Transcript 6:

There exists a statistically significant difference between the means (p≤0.01) of the normal and malignant groups (p=0.01). Further, using a cutoff value of −5.9531 as demonstrated by the ROC curve results in a sensitivity of 89% and specificity of 80% and the area under the curve is 0.96, indicating very good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 10:

There exists a statistically significant difference between the means (p≤0.05) of the normal and malignant groups (p=0.05), using a cutoff value of −4.7572 as demonstrated by the ROC curve results in a sensitivity of 89% and specificity of 40% and the area under the curve is 0.82, indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 11:

There exists a statistically significant difference between the means (p<0.05) of the normal and malignant groups (p=0.02). Further, using a cutoff value of 1.6762 as demonstrated by the ROC curve results in a sensitivity of 78% and specificity of 100% and the area under the curve is 0.89, indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 14:

There exists a statistically significant difference between the means (p≤0.05) of the normal and malignant groups (p=0.05). Further, using a cutoff value of −4.9118 as demonstrated by the ROC curve results in a sensitivity of 89% and specificity of 60% and the area under the curve is 0.82, indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 15:

There exists a statistically significant difference between the means (p<0.1) of the normal and malignant groups (p=0.07), using a cutoff value of −7.3107 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 67% and the area under the curve is 0.80, indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 16:

There exists a statistically significant difference between the means (p<0.05) of the normal and malignant groups (p=0.03). Further, using a cutoff value of −10.5963 as demonstrated by the ROC curve results in a sensitivity of 89% and specificity of 80% and the area under the curve is 0.878, indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 20:

There exists a statistically significant difference between the means (p<0.05) of the normal and malignant groups (p=0.04). Further, using a cutoff value of −8.3543 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 80% and the area under the curve is 0.89, indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Conclusions:

The results from example 7 illustrate the utility of transcripts 6, 10, 11, 14, 15, 16 and 20 of the invention in the detection of malignant melanomas. As indicated above, transcripts 10 and 11 were also found have utility in detecting colorectal cancer while transcript 6 has utility in the detection of lung cancer. A transcript summary by disease is provided at Table 6.

Example 8: Application to Ovarian Cancer

This study sought to determine the effectiveness of several transcripts of the invention in detecting ovarian cancer. A total of 20 samples were prepared comprising ten control (benign) tissue samples (samples 1 to 10) and ten tumour (malignant) tissue samples (samples 11 to 20). The samples were homogenized according to the manufacturer's recommendations (Quantigene® Sample Processing Kit for Fresh or Frozen Animal Tissues; and Quantigene 2.0 Reagent System User Manual). Eight target transcripts and one housekeeper transcript were prepared in the manner as outlined above in previous examples.

The 20 tissue samples used in this example had the following characteristics:

TABLE 12 Characteristics of Ovarian Cancer Samples Sample Diagnosis Comments 1 Normal follicular cyst 2 Normal fibroma 3 Normal No pathological change in ovaries 4 Normal follicular cysts 5 Normal cellular fibroma 6 Normal benign follicular and simple cysts 7 Normal leiomyomata, corpora albicantia 8 Normal copora albicantia and an epithelial inclusions cysts 9 Normal corpora albicantia 10 Normal corpora albicantia, surface inclusion cysts, follicullar cysts 11 Malignant high grade poorly differentiated papillary serous carcinoma involving omentum 12 Malignant endometrioid adenocarcinoma, well to moderately differentiated with focal serous differentiation 13 Malignant papillary serous carcinoma 14 Malignant mixed epithelial carcinoma predominantly papillary serous carcinoma 15 Malignant High grade: serous carcinoma, papillary and solid growth patterns 16 Malignant High Grade (3/3) Papillary serous carcinoma 17 Malignant papillary serous carcinoma, high nuclear grade 18 Malignant Papillary serous cystadenocarcinomas Grade: III 19 Malignant poorly differentiated papillary serous carcinoma 20 Malignant Well-differentiated adnocarcinoma, Endometrioid type, Grade 1

The characteristics of the transcripts are summarized as follows:

TABLE 13 Characteristics of Ovarian Cancer Transcripts Transcript ID Junction Site Gene Junction 1 8469:13447 ATPase8:ND5 2 10744:14124  ND4L:ND5 3 7974:15496 COII:Cytb 6 8828:14896 ATPase6:Cytb 11 7775:13532 COII:ND5 12 8213:13991 COII:ND5 15 9574:12972 COIII:ND5 20 8469:13447 ATPase8:ND5 Ribosomal Protein Large PO (LRP) N/A N/A Housekeeper

It is noted that transcripts 1, 2, 3, 6, 11, 12, 15 and 20 are the same as those discussed above with respect to Examples 3-7.

Homogenates were prepared using approximately 25 mg of frozen tissue and diluted 1:4. The quantity of the transcripts was measured in Relative Luminenscence Units RLU on a Glomax™ Multi Detection System (Promega). All samples were assayed in triplicate for each transcript. Background measurements (no template) were done in triplicate as well. The analysis accounted for background by subtracting the lower limit from the RLU values for the samples. Input RNA was accounted for by using the formula log2 a RLU−log2 h RLU where a is the target fusion transcript and h is the housekeeper transcript.

The analysis of the data comprised the following steps:

a) Establish CV's (coefficients of variation) for triplicate assays; acceptable if 15%.

b) Establish average RLU value for triplicate assays of target fusion transcript (a) and housekeeper transcript (h).

c) Establish lower limit from triplicate value of background RLU (I).

d) Subtract lower limit (I) from (a).

e) Calculate log2 a RLU−log 2 h RLU.

Summary of Results:

The results of the above analysis are illustrated in FIGS. 9a to 9h, which comprise plots of the log2 a RLU−log 2 h RLU against sample number. Also illustrated are the respective ROC (Receiver Operating Characteristic) curves determined from the results for each transcript.

Transcript 1:

There exists a statistically significant difference between the means (p<0.05) of the normal and malignant groups (p=0.002). Using a cutoff value of −11.1503 as demonstrated by the ROC curve results in a sensitivity of 90% and specificity of 80% and the area under the curve is 0.91 indicating very good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 2:

There exists a statistically significant difference between the means (p<0.01) of the normal and malignant groups (p=0.001). Using a cutoff value of 0.6962 as demonstrated by the ROC curve results in a sensitivity of 90% and specificity of 100% and the area under the curve is 0.96 indicating very good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 3:

There exists a statistically significant difference between the means (p<0.01) of the normal and malignant groups (p=0.000). Using a cutoff value of 0.6754 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 100% and the area under the curve is 1.00 indicating excellent test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 6:

There exists a statistically significant difference between the means (p<0.01) of the normal and malignant groups (p=0.007). Using a cutoff value of −9.6479 as demonstrated by the ROC curve results in a sensitivity of 90% and specificity of 70% and the area under the curve is 0.86 indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 11:

There is a statistically significant difference between the means (p<0.01) of the normal and malignant groups (p=0.000). Using a cutoff value of −1.3794 demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 90% and the area under the curve is 0.99, indicating excellent test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 12:

There exists a statistically significant difference between the means (p<0.01) of the normal and malignant groups (p=0.001). Using a cutoff value of −1.2379 as demonstrated by the ROC curve results in a sensitivity of 90% and specificity of 100% and the area under the curve is 0.96 indicating excellent test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 15:

There exists a statistically significant difference between the means (p<0.05) of the normal and malignant groups (p=0.023). Using a cut-off value of −8.6926 as demonstrated by the ROC curve results in a sensitivity of 70% and specificity of 80% and the area under the curve is 0.80 indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 20:

There exists a statistically significant difference between the means (p<0.01) of the normal and malignant groups (p=0.000). Using a cut-off value of 0.6521 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 100% and the area under the curve is 0.76 indicating fair to good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Conclusions:

The above results illustrate the utility of transcripts 1, 2, 3, 6, 11, 12, 15, and 20 in the detection of ovarian cancer and in distinguishing malignant from normal ovarian tissue. Transcripts 1, 2 and 3 were also found to have utility in the detection of prostate cancer. Transcript 6 was also found to have utility in the detection of melanoma and lung cancer. Transcript 11 was also found to have utility in the detection of melanoma skin cancer, colorectal cancer and testicular cancer. Transcript 12 was also found to have utility in the detection of colorectal cancer and testicular cancer. Transcript 15 was also found to have utility in the detection of melanoma and testicular cancer. Transcript 20 was also found to have utility in the detection of colorectal cancer, melanoma, and testicular cancer. Any of the 8 transcripts listed may be used individually or in combination as a tool for the detection or characterization of ovarian cancer in a clinical setting.

Example 9: Application to Testicular Cancer

This study sought to determine the effectiveness of several transcripts of the invention in detecting testicular cancer. A total of 17 samples were prepared comprising eight control (benign) tissue samples (samples 1 to 8) and 9 tumour (malignant) tissue samples (samples 9 to 17), 5 of the malignant samples were non-seminomas (samples 9-13) and 4 were seminomas (samples 14-17). The samples were homogenized according to the manufacturer's recommendations (Quantigene® Sample Processing Kit for Fresh or Frozen Animal Tissues; and Quantigene 2.0 Reagent System User Manual). 10 target transcripts and one housekeeper transcript were prepared in the manner as outlined above in previous examples.

The 17 tissue samples used in this example had the following characteristics:

TABLE 14 Characteristics of Testicular Cancer Samples General Stratified Sample Diagnosis Malignant Diagnosis 1 Benign Benign 2 Benign Benign 3 Benign Benign 4 Benign Benign 5 Benign Benign 6 Benign Benign 7 Benign Benign 8 Benign Benign 9 Malignant Non-Seminoma 10 Malignant Non-Seminoma 11 Malignant Non-Seminoma 12 Malignant Non-Seminoma 13 Malignant Non-Seminoma 14 Malignant Seminoma 15 Malignant Seminoma 16 Malignant Seminoma 17 Malignant Seminoma

The characteristics of the transcripts are summarized as follows:

TABLE 15 Characteristics of Testicular Cancer Transcripts Transcript ID Junction Site Gene Junction 2 10744:14124  ND4L:ND5 3 7974:15496 COII:Cytb 4 7992:15730 COII:Cytb 11 7775:13532 COII:ND5 12 8213:13991 COII:ND5 13 9144:13816 ATPase6:ND5 15 9574:12972 COIII:ND5 16 10367:12829  ND3:ND5 20 8469:13447 ATPase8:ND5 Peptidylpropyl isomerase B (PPIB) N/A N/A

It is noted that transcripts 2, 3, 4, 7, 11, 12, 15, 16 and 20 are the same as those discussed above with respect to Examples 3-8.

Homogenates were prepared using approximately 25 mg of frozen tissue and diluted 1:4. The quantity of the transcripts was measured in Relative Luminenscence Units RLU on a Glomax™ Multi Detection System (Promega). All samples were assayed in triplicate for each transcript. Background measurements (no template) were done in triplicate as well. The analysis accounted for background by subtracting the lower limit from the RLU values for the samples. Input RNA was accounted for by using the formula log2 a RLU−log2 h RLU where a is the target fusion transcript and h is the housekeeper transcript.

The analysis of the data comprised the following steps:

a) Establish CV's (coefficients of variation) for triplicate assays; acceptable if 15%.

b) Establish average RLU value for triplicate assays of target fusion transcript (a) and housekeeper transcript (h).

c) Establish lower limit from triplicate value of background RLU (I).

d) Subtract lower limit (I) from (a).

e) Calculate log2 a RLU−log 2 h RLU.

Summary of Results:

The results of the above analysis are illustrated in FIGS. 10 to 18, which comprise plots of the log2 a RLU−log 2 h RLU against sample number. Also illustrated are the respective ROC (Receiver Operating Characteristic) curves determined from the results for each transcript.

While some transcripts distinguish between benign and malignant testicular tissue, others demonstrate distinction between the tumour subtypes of seminoma and non-seminoma and/or benign testicular tissue. It is therefore anticipated that combining transcripts from each class will facilitate not only detection of testicular cancer but also classification into subtype of seminoma or non-seminomas.

Transcript 2:

There exists a statistically significant difference between the means (p<0.05) of the normal group and the malignant seminomas (p=0.02). Using a cutoff value of 1.5621 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 100% and the area under the curve is 1.00 indicating excellent test accuracy. There also exists a statistically significant difference between the means (p<0.05) of the malignant seminomas and the malignant non-seminomas (p=0.024). Using a cutoff value of 2.1006 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 80% and the area under the curve is 0.90 indicating excellent test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 3:

There exists a statistically significant difference between the means (p<0.05) of the normal group and the malignant seminomas (p=0.018). Using a cutoff value of 0.969 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 87.5% and the area under the curve is 0.969 indicating excellent accuracy. There also exists a statistically significant difference between the means (p<0.05) of the malignant seminomas and the malignant non-seminomas (p=0.017). Using a cutoff value of 1.8181 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 80% and the area under the curve is 0.9 indicating excellent test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 4:

There exists a statistically significant difference between the means (p<0.05) of the normal and malignant groups (p=0.034). Using a cutoff value of −9.7628 as demonstrated by the ROC curve results in a sensitivity of 67% and specificity of 100% and the area under the curve is 0.833 indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 11:

There exists a statistically significant difference between the means (p<0.05) of the normal group and the malignant seminomas (p=0.016). Using a cutoff value of 0.732 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 100% and the area under the curve is 1.00 indicating excellent test accuracy. There also exists a statistically significant difference between the means (p<0.05) of the malignant seminomas and the malignant non-seminomas (p=0.016). Using a cutoff value of 0.9884 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 80% and the area under the curve is 0.90 indicating excellent test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 12:

There exists a statistically significant difference between the means (p<0.1) of the normal group and the malignant seminomas (p=0.056). Using a cutoff value of 1.5361 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 87.5% and the area under the curve is 0.969 indicating excellent test accuracy. There also exists a statistically significant difference between the means (p<0.05) of the malignant seminomas and the malignant non-seminomas (p=0.044). Using a cutoff value of 1.6039 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 80% and the area under the curve is 0.9 indicating excellent test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 13:

There exists a statistically significant difference between the means (p<0.05) of the normal group and the malignant group (p=0.019). Using a cutoff value of −9.8751 as demonstrated by the ROC curve results in a sensitivity of 87.5% and specificity of 78% and the area under the curve is 0.875 indicating very good test accuracy. There also exists a statistically significant difference between the means (p<0.01) of the malignant non-seminomas and the benign group (p=0.000). Using a cutoff value of −13.9519 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 87.5% and the area under the curve is 0.975 indicating excellent test accuracy. There also exists a statistically significant difference between the means (p<0.01) of the malignant seminomas and the malignant non-seminomas (p=0.001). Using a cutoff value of −15.8501 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 100% and the area under the curve is 1.00 indicating excellent test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 15:

There exists a statistically significant difference between the means (p<0.1) of the normal and malignant groups (p=0.065). Using a cut-off value of −5.4916 as demonstrated by the ROC curve results in a sensitivity of 75% and specificity of 89% and the area under the curve is 0.833 indicating good test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 16:

There exists a statistically significant difference between the means (p<0.05) of the normal and malignant groups including both seminomas and non-seminomas (p=0.037). Using a cut-off value of −6.448 as demonstrated by the ROC curve results in a sensitivity of 89% and specificity of 75% and the area under the curve is 0.806 indicating good test accuracy. There also exists a statistically significant difference between the means (p<0.05) of the normal and malignant seminomas (p=0.037). Using a cut-off value of −7.4575 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 87.5% and the area under the curve is 0.938 indicating excellent test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Transcript 20:

There exists a statistically significant difference between the means (p<0.01) of the normal group and the malignant seminomas (p=0.006). Using a cutoff value of 1.8364 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 100% and the area under the curve is 1.00 indicating excellent test accuracy. There also exists a statistically significant difference between the means (p<0.01) of the malignant seminomas and the malignant non-seminomas (p=0.004). Using a cutoff value of 1.6065 as demonstrated by the ROC curve results in a sensitivity of 100% and specificity of 100% and the area under the curve is 1.00 indicating excellent test accuracy. The threshold value chosen may be adjusted to increase either the specificity or sensitivity of the test for a particular application.

Conclusions:

The above results illustrate the utility of transcripts 2, 3, 4, 11, 12, 13, 15, 16, and 20 in the detection of testicular cancer, and testicular cancer subtypes, and in distinguishing malignant from normal testicular tissue. Transcript 2 was also found to have utility in the detection of prostate, breast, colorectal and ovarian cancer. Transcript 3 was also found to have utility in the detection of prostate, breast, melanoma, colorectal, and ovarian cancers. Transcript 4 was also found to have utility in the detection of prostate and colorectal cancers. Transcript 11 was also found to have utility in the detection of colorectal, melanoma, and ovarian cancers. Transcript 12 was also found to have utility in the detection of colorectal and ovarian cancers. Transcript 15 was also found to have utility in the detection of melanoma and ovarian cancers. Transcript 16 was also found to have utility in the detection of melanoma skin cancer. Transcript 20 was also found to have utility in the detection of colorectal cancer, melanoma, and ovarian cancer. Any of the 9 transcripts listed may be used individually or in combination as a tool for the detection or characterization of testicular cancer in a clinical setting.

In one aspect, the invention provides a kit for conducting an assay for determining the presence of cancer in a tissue sample. The kit includes the required reagents for conducting the assay as described above. In particular, the kit includes one or more containers containing one or more hybridization probes corresponding to transcripts 1 to 17, and 20 described above. As will be understood, the reagents for conducting the assay may include any necessary buffers, salts, detection reagents etc. Further, the kit may include any necessary sample collection devices, containers etc. for obtaining the needed tissue samples, reagents or materials to prepare the tissue samples for example by homogenization or nucleic acid extraction, and for conducting the subject assay or assays. The kit may also include control tissues or samples to establish or validate acceptable values for diseased or non-diseased tissues.

Although the invention has been described with reference to certain specific embodiments, various modifications thereof will be apparent to those skilled in the art without departing from the spirit and scope of the invention as outlined in the claims appended hereto. All documents (articles, manuals, patent applications etc) referred to in the present application are incorporated herein in their entirety by reference.

BIBLIOGRAPHY

The following references, amongst others, were cited in the foregoing description. The entire contents of these references are incorporated herein by way of reference thereto.

Author Journal Title Volume Date Anderson et al Nature Sequence and Organization of the Human 290(5806): 457- 1981 Mitochondrial Genome 65 Andrews et al Nat Genet Reanalysis and revision of the Cambridge 23(2): 147 1999 reference sequence for human mitochondrial DNA. Modica- Expert Rev Mitochondria as targets for detection and 4: 1-19 2002 Napolitano et al Mol Med treatment of cancer Sherratt et al Clin Sci (Lond) Mitochondrial DNA defects: a widening 92(3): 225-35 1997 clinical spectrum of disorders. Croteau et al Mutat Res Mitochondrial DNA repair pathways. 434(3): 137-48 1999 Green and J Clin Invest Pharmacological manipulation of cell death: 115(10): 2610- 2005 Kroemer clinical applications in sight? 2617 Dai et al Acta Correlation of cochlear blood supply with 24(2): 130-6 2004 Otolaryngol mitochondrial DNA common deletion in presbyacusis. Ro et al Muscle Nerve Deleted 4977-bp mitochondrial DNA 28(6): 737-43 2003 mutation is associated with sporadic amyotrophic lateral sclerosis: a hospital- based case-control study. Barron et al Invest Mitochondrial abnormalities in ageing 42(12): 3016-22 2001 Ophthalmol macular photoreceptors. Vis Sci Lewis et al J Pathol Detection of damage to the mitochondrial 191(3): 274-81 2000 genome in the oncocytic cells of Warthin's tumour. Muller-Hocker Mod Pathol The common 4977 base pair deletion of 11(3): 295-301. 1998 et al mitochondrial DNA preferentially accumulates in the cardiac conduction system of patients with Kearns-Sayre syndrome. Porteous et al Eur J Biochem Bioenergetic consequences of accumulating 257(1): 192-201 1998 the common 4977-bp mitochondrial DNA deletion. Parr et al J Mol Diagn Somatic mitochondrial DNA mutations in 8(3): 312-9. 2006 prostate cancer and normal appearing adjacent glands in comparison to age- matched prostate samples without malignant histology. Maki et al Am J Clin Mitochondrial genome deletion aids in the 129(1): 57-66 2008 Pathol identification of false- and true-negative prostate needle core biopsy specimens. Nakase et al Am J Hum Transcription and translation of deleted 46(3): 418-27. 1990 Genet mitochondrial genomes in Kearns-Sayre syndrome: implications for pathogenesis. Libura et al Blood Therapy-related acute myeloid leukemia- 105(5): 2124-31 2005 like MLL rearrangements are induced by etoposide in primary human CD34+ cells and remain stable after clonal expansion. Meyer et al Proc Natl Diagnostic tool for the identification of MLL 102(2): 449-54 2005 Acad Sci rearrangements including unknown partner USA genes. Eguchi et al Genes MLL chimeric protein activation renders 45(8): 754-60 2006 Chromosomes cells vulnerable to chromosomal damage: Cancer an explanation for the very short latency of infant leukemia. Hayashi et al Proc Natl Introduction of disease-related 88: 10614- 1991 Acad Sci mitochondrial DNA deletions into HeLa cells 10618 USA lacking mitochondrial DNA results in mitochondrial dysfunction

TABLE 1 Known mitochondrial deletions having an ORF Deletion Deletion Repeat Number of Junction (nt:nt) Size (bp) Location (nt/nt) Repeats References COX I - ND5 6075:13799 −7723 6076-6084/13799- D, 9/9 Mita, S., Rizzuto, R., Moraes, C. T., Shanske, S., Arnaudo, E., Fabrizi, 13807 G. M., Koga, Y., DiMauro, S., Schon, E. A. (1990) “Recombination via flanking direct repeats is a major cause of large-scale deletions of human mitochondrial DNA” Nucleic Acids Research 18(3): 561-567 6238:14103 −7864 6235-6238/14099- D, 4/4 Blok, R. B., Thorburn, D.R., Thompson, G. N., Dahl, H. H. (1995) “A 14102 topoisomerase II cleavage site is associated with a novel mitochondrial DNA deletion” Human Genetics 95 (1): 75-81 6325:13989 −7663 6326-6341/13889- D, 16/17 Larsson, N. G., Holme, E., Kristiansson, B., Oldfors, A., Tulinius, M. 14004 (1990) “Progressive increase of the mutated mitochondrial DNA fraction in Kearns-Sayre syndrome” Pediatric Research 28 (2): 131- 136 Larsson, N. G., Holme, E. (1992) “Multiple short direct repeats associated with single mtDNA deletions ” Biochimica et Biophysica Acta 1139(4): 311-314 6330:13994 −7663 6331-6341/13994- D, 11/11 Mita, S., Rizzuto, R., Moraes, C. T., Shanske, S., Arnaudo, E., Fabrizi, 14004 G. M., Koga, Y., DiMauro, S., Schon, E.A. (1990) “Recombination via flanking direct repeats is a major cause of large-scale deletions of human mitochondrial DNA” Nucleic Acids Research 18(3): 561-567 COX II - ND5 7829:14135 −6305 7824-7829/14129- D, 6/6 Bet, L., Moggio, M., Comi, G. P., Mariani, C., Prelle, A., Checcarelli, N., 14134 Bordoni, A., Bresolin, N., Scarpini, E., Scarlato, G. (1994) “Multiple sclerosis and mitochondrial myopathy: an unusual combination of diseases” Journal of Neurology 241 (8): 511-516 8213:13991 −5777 8214-8220/13991- D, 7/7 Hinokio, Y., Suzuki, S., Komatu, K., Ohtomo, M., Onoda, M., 13997 Matsumoto, M., Hirai, S., Sato, Y., Akai, H., Abe, K., Toyota, T. (1995) “A new mitochondrial DNA deletion associated with diabetic amyotrophy, diabetic myoatrophy and diabetic fatty liver” Muscle and Nerve 3 (9): S142-149 ATPase - ND5 8631:13513 −4881 8625-8631/13506- D, 7/7 Zhang, C., Baumer, A., Mackay, I. R., Linnane, A. W., Nagley, P. (1995) 13512 “Unusual pattern of mitochondrial DNA deletions in skeletal muscle of an adult human with chronic fatigue syndrome” Human Molecular Genetics 4 (4): 751 -754 9144:13816 −4671 9137-9144/13808- D, 8/8 Ota, Y., Tanaka, M., Sato, W., Ohno, K., Yamamoto, T., Maehara, M., 13815 Negoro, T., Watanabe, K., Awaya, S., Ozawa, T. (1991) “Detection of platelet mitochondrial DNA deletions in Kearns-Sayre syndrome” Investigative Ophthalmology and Visual Science 32 (10): 2667-2675 9191:12909 −3717 9189-9191/12906- D, 3/3 Tanaka, M., Sato, W., Ohno, K., Yamamoto, T., Ozawa, T. (1989) 12908 “Direct sequencing of mitochondrial DNA in myopathic patients” Biochemical and Biophysical Research Communications 164 ( ): 156- 163 COX III - ND5 10190:13753  −3562 10191-10190/13753- D, 8/8 Rotig, A., Bourgeron, T., Chretien. D., Rustin, P., Munnich, A. (1995) 13760 “Spectrum of mitochondrial DNA rearrangements in the Pearson marrow-pancreas syndrome” Human Molecular Genetics 4 (8): 1327- 1330 Rotig, A., Cormier, Y., Kol, F., Mize, C. E., Souslubray, J. M., Veerman, A., Pearson, H. A., Munnich, A. (1991) “Site-specific deletions of the mitochondrial genome in Pearson marrow-pancreas syndrome” Genomics 10 (2): 502-504 10067:12029  −2461 10365-10367/12825- D, 3/3 Kapsa, R., Thompson, G. N., Thorburn, D. R., Dahl, H. H., Marzuki, G., 12828 Byrna, E., Blair, R. B. (1984) “A novel mtDNA deletion in an infant with Pearson syndrome” Journal of Inherited Metabolic Disease 17 (5): 521- 526 ND4L - ND5 10744:14124  −3378 10745-10754/14124- D, 9/10 Cormier-Daire, V., Bonnefont, J. P., Rustin, P., Maurage, C., Ogler, H., 14133 Schmitz, J., Ricour, C., Saudubray, J. M., Munnich, A., Rotig, A. (1984) “Mitochondrial DNA, rearrangements with onset as chronic diarrhea with villous atrophy” Journal of Pediatrics 124 (1): 53-70 ND4 - ND5 11232:13980  −2747 1324-11242/13981- D, 9/9 Rotig, A., Cormier, V., Roll, F., Mize, C. E., Saudubray, J. M., Veerman, 13989 A., Pearson, H. A., Munnich, A. (1991) “Site-specific deletions of the mitochondrial genome in Pearson marrow-pancreas syndrome” Genomics 10 (2): 502-504 Rotig, A., Cormier, Y., Blanche, S., Bonnefont, J. P., Ledeist, F., Romero, N., Schmitz, J., Rustin, P., Fischer, A., Saudubray, J. M. (1990) “Pearson's marrow-pancreas syndrome. A multi-system mitochondrial disorder in infancy” Journal of Clinical Investigation 86 ( ): 1601-1608 Cormier, V., Rotig, A., Quartino, A. R., Forni, G. L., Cerane, R., Maier, M., Saudubray, J. M., Munnich, A. (1990) “Widespread multitissue deletions of the mitochondrial genome in Pearson marrow-pancreas syndrome” Journal of Pediatrics 117 (4): 599-602 Awata, T., Matsumata, T., Iwamoto, Y., Matsuda, A., Kuzuya, T., Saito, T. (1993) “Japanese case of diabetes mellitus and deafness with mutations in mitochondrial tRNALeu(UUR) gene [letter]” Lancet 341 (8855): 1281-1282

TABLE 2 Prostate Cancer Detection with Novel Mitochondrial Fusion Transcripts Homog Homog Homog Homog Homog Homog Homog Homog RNA 1 2 RNA 1 2 RNA 1 2 RNA 1 2 Transcript Tran- Tran- Tran- Tran- Tran- Tran- Tran- Tran- Tran- Tran- Tran- Tran- script script script script script script script script script script script script 1 1 1 2 2 2 3 3 3 4 4 4 1 2 3 4 5 6 7 8 9 10 11 12 No dilution A 2957 353 233 144838 75374 17192 348424 333189 213844 509 565 207 Replicate A B 3174 475 298 202793 100062 31750 320877 278137 210265 401 676 250 1:10 dilution C 1041 262 114 106195 98403 36191 238467 248677 123497 181 486 168 Replicate C D 1040 272 176 120308 116930 50323 239231 262520 129778 153 467 149 1:100 dilution E 318 170 110 25155 64823 27725 100345 164606 85287 72 265 119 Replicate E F 287 150 109 23500 50524 24629 100856 178527 84731 83 251 120 1:1000 dilution G 100 76 123 3002 12960 252 29203 102309 137 31 143 66 Replicate G H 94 83 91 1263 5796 285 29092 97257 96 45 110 94 % CV A 5.0 20.9 17.3 23.6 19.9 42.1 5.8 12.7 1.2 16.9 12.7 13.3 % CV C 0.1 2.5 30.1 8.8 12.2 23.1 0.2 3.8 3.5 12.0 2.8 8.3 % CV E 7.1 9.0 0.6 4.8 17.5 8.4 0.4 5.7 0.5 9.8 3.8 0.6 % CV G 4.7 6.0 20.8 57.7 54.0 8.8 0.3 3.6 25.0 27.0 18.2 24.9 * unit results in table are RLU (relative luminescence units); Data read on Glorunner ™. % CV = Coefficient of variation (as %). Legend: Homog = homogenate. Homog 1: Prostate tumour tissue sample from patient; Homog 2: Histologically normal tissue adjacent to tumour from patient. RNA: Control: Total RNA from prostate tissue (Ambion p/n 7988).

TABLE 3 Deletion/Transcript/DNA Complement DNA sequence with deletion complementary Deletion RNA transcript to RNA transcript Transcript No. ATP synthase F0 subunit 8 to NADH SEQ ID NO: 18 SEQ ID NO: 2 1 dehydrogenase subunit mitochondrial positions 8366-14148 (with reference to SEQ ID NO: 1). NADH dehydrogenase subunit 4L SEQ ID NO: 19 SEQ ID NO: 3 2 (ND4L) to NADH dehydrogenase subunit 5 (ND5); Mitochondrial positions 10470- 14148 (with reference to SEQ ID NO: 1) Cytochrome c oxidase subunit II (COII) to SEQ ID NO: 20 SEQ ID NO: 4 3 Cytochrome b (Cytb); Mitochondrial positions 7586-15887 (with reference to SEQ ID NO: 1) Cytochrome c oxidase subunit II (COII) to SEQ ID NO: 21 SEQ ID NO: 5 4 Cytochrome b (Cytb); Mitochondrial positions 7586-15887 (with reference to SEQ ID NO: 1)

TABLE 4 Breast and Prostate Cancer Detection Normal Normal Normal Adjacent Breast adjacent Breast Adjacent Prostate Prostate Prostate to Prostate Tumour Breast Tumour to Breast Tumour Tumour Tumour Tumour 1 Tumour 1 2 Tumour 2 3 4 5 5 1 2 3 4 5 6 7 8 1:100 dilution E 68920 2971 49108 1245 46723 56679 99836 35504 1:100 dilution F 92409 3017 60637 1512 53940 56155 100582 44221 replicate G 420 3 31 6 26 25 44 23 H 518 3 4 5 5 3 4 2 % CV 20.6 1.1 14.9 13.7 10.1 0.7 0.5 15.5
    • unit results in table are RLU (relative luminescence units)
    • background G1, H1
    • empty well G2-G8, H2-H8

TABLE 5a Assay Conditions Template for the assay RNA Homogen 1 Homogen 2 RNA Homogen 1 Homogen 2 Transcript 1 Transcript 1 Transcript 1 Transcript 2 Transcript 2 Transcript 2 1 2 3 4 5 6 A RNA Homog 1 Homog 2 RNA Homog 1 Homog 2 B Dil 1 Dil 1 Dil 1 Dil 1 Dil 1 Dil 1 C RNA Homog 1 Homo 2 RNA Homog 1 Homog 2 D Dil 2 Dil 2 Dil 2 Dil 2 Dil 2 Dil 2 E RNA Homog 1 Homog 2 RNA Homog 1 Homog 2 F Dil 3 Dil 3 Dil 3 Dil 3 Dil 3 Dil 3 G RNA Homog 1 Transcript 1 RNA Homog 1 Transcript 1 H Dil 4 Dil 4 Background Dil 4 Dil 4 Background RNA Homogen 1 Homogen 2 RNA Homogen 1 Homogen 2 Transcript 3 Transcript 3 Transcript 3 Transcript 4 Transcript 4 Transcript 4 7 8 9 10 11 12 A RNA Homog 1 Homog 2 RNA Homog 1 Homog 2 B Dil 1 Dil 1 Dil 1 Dil 1 Dil 1 Dil 1 C RNA Homog 1 Homog 2 RNA Homog 1 Homog 2 D Dil 2 Dil 2 Dil 2 Dil 2 Dil 2 Dil 2 E RNA Homog 1 Homog 2 RNA Homog 1 Homog 2 F Dil 3 Dil 3 Dil 3 Dil 3 Dil 3 Dil 3 G RNA Homog 1 Transcript 1 RNA Homog 1 Transcript 1 H Dil 4 Dil 4 Background Dil 4 Dil 4 Background Homogenate1- Used 26 mg of tissue to homogenize in 700 ul H soln with Proteinase K (PK). Used Qiagen TissueRuptor. Used 40 ul homogenate supernatant, 20, 10 and 5 ul for dilution Homogenate1 = Tumour tissue from the tumorous Prostate Homogenate2- Used 29 mg of tissue to homogenize in 700 ul H soln with PK. Used Qiagen TissueRuptor. Used 40 ul homogenate supernatant, 20, 10 and 5 ul for dilution Homogenate2 = Normal tissue from the tumorous Prostate RNA dilution was made as below. RNA was from Prostate Normal from Ambion. Assay was done in duplicates.

TABLE 5b RNA dilution RNA Dilution ng/ul Dil 1 3000 1:3 dil Dil 2 1000 Serial dil Dil 3 333 Dil 4 111

TABLE 6 Transcript Summary by Disease Mela- Pros- Colo- noma Testi- tate Breast rectal Skin Lung Ovarian cular Probe Cancer Cancer Cancer Cancer Cancer Cancer Cancer 1 • • 2 • • • • • 3 • • • • 4 • • 5 6 • • • 7 8 • • 9 • 10 • • • 11 • • • • 12 • • • 13 • 14 • 15 • • • 16 • • 17 20 • • • •

Claims

1. An isolated mitochondrial fusion transcript associated with cancer, wherein the transcript has the nucleic acid sequence as set forth in any one of SEQ ID NOs:18 to 33 or 50.

2. An isolated mitochondrial DNA (mtDNA) molecule having a nucleic acid sequence encoding the fusion transcript of claim 1.

3. The isolated mtDNA of claim 2, wherein the mtDNA has the nucleic acid sequence as set forth in any one of SEQ ID NOs: 2-17 or 51.

4. A mitochondrial fusion protein, wherein the fusion protein is a translation product of the fusion transcript of claim 1.

5. The mitochondrial fusion protein of claim 4, wherein the fusion protein has the amino acid sequence as set forth in any one of SEQ ID NOs: 34 to 49 and 52.

6. A hybridization probe having a nucleic acid sequence complementary to a portion of the mitochondrial fusion transcript of claim 1.

7. The hybridization probe of claim 6, wherein the portion of the mitochondrial fusion transcript comprises an expressed sequence of mtDNA corresponding to a junction point resulting from a deletion of nucleotides of the human mtDNA genome.

8. The hybridization probe of claim 7, wherein the probe has a length of at least about 15 nucleotides, at least about 20 nucleotides, at least about 30 nucleotides, at least about 40 nucleotides, at least about 50 nucleotides, at least about 75 nucleotides, or at least about 150 nucleotides.

9. A kit for diagnosing cancer or for detecting the fusion transcript of claim 1, wherein the kit comprises the hybridization probe of claim 6.

10. The kit of claim 9, wherein the cancer is prostate cancer, testicular cancer, ovarian cancer, breast cancer, colorectal cancer, lung cancer, melanoma skin cancer or combinations thereof.

11. A method of detecting a cancer in a mammal, the method comprising assaying a tissue sample from the mammal for the presence of:

(i) a mitochondrial fusion transcript having the nucleic acid sequence as set forth in any one of SEQ ID NOs:18 to 33 or 50;
(ii) an mtDNA molecule encoding the fusion transcript of (i);
(iii) an mtDNA molecule having the nucleic acid sequence as set forth in any one of SEQ ID NOs: 2-17 or 51;
(iv) a fusion protein comprising a translation product of the fusion transcript of (i); or
(v) a fusion protein having the amino acid sequence as set forth in any one of SEQ ID NOs: 34 to 49 and 52.

12. The method of claim 11, wherein the method comprises hybridizing the tissue sample with at least one hybridization probe having a nucleic acid sequence complementary to at least a portion of the mitochondrial fusion transcript of (i), the mtDNA of (ii) or the mtDNA of (iii).

13. The method of claim 12, wherein the portion of the mitochondrial fusion transcript comprises an expressed sequence of mtDNA corresponding to a junction point resulting from a deletion of nucleotides of the human mtDNA genome.

14. The method of claim 12, wherein the assay comprises:

a) conducting a hybridization reaction using at least one of said probes to allow said at least one probe to hybridize to a complementary sequence of the mitochondrial fusion transcript or the mtDNA; and,
b) quantifying the amount of the mitochondrial fusion transcript or the mtDNA in said sample by quantifying the amount of said transcript or mtDNA hybridized to the at least one probe.

15. The method of claim 14, wherein the step of quantifying is carried out using diagnostic imaging technology, branched DNA technology, or PCR.

16. The method of claim 11, wherein the cancer is prostate cancer, testicular cancer, ovarian cancer, breast cancer, colorectal cancer, lung cancer, melanoma skin cancer or combinations thereof.

Patent History
Publication number: 20190382846
Type: Application
Filed: Apr 17, 2019
Publication Date: Dec 19, 2019
Inventors: Ryan Parr (Thunder Bay), Brian Reguly (Thunder Bay), Gabriel Dakubo (Thunder Bay), Jennifer Creed (Broomsfield, CO), Kerry Robinson (Thunder Bay)
Application Number: 16/386,381
Classifications
International Classification: C12Q 1/6886 (20060101); C07K 14/47 (20060101);