Abstract: Methods to compute gestational age and time to delivery utilizing temporal alignment methods and applications thereof are described. Generally, systems utilize analyte measurements collected at one or more time points to determine a gestational age and time to delivery, which can be used as a basis to perform interventions and treat individuals. Computational models trained utilizing temporal alignment of analyte measurements can be used to determine gestational age and time to delivery.

Abstract: Through genomic analysis a 12-gene signature comprising up-regulated genes and down-regulated genes has been identified that is highly predictive of metastasis and overall survival in human patients with HCC. Another aspect of the disclosure methods of determining the metastatic status of an hepatocellular carcinoma of a patient, comprising obtaining a first differential gene expression profile from a carcinoma sample from a subject having an hepatocellular carcinoma and creating a report summarizing the normalized data obtained by the first gene expression analysis and including a determination of the metastatic status of the hepatic carcinoma.

Abstract: Through genomic analysis a 12-gene signature comprising up-regulated genes and down-regulated genes has been identified that is highly predictive of metastasis and overall survival in human patients with HCC. Another aspect of the disclosure methods of determining the metastatic status of an hepatocellular carcinoma of a patient, comprising obtaining a first differential gene expression profile from a carcinoma sample from a subject having an hepatocellular carcinoma and creating a report summarizing the normalized data obtained by the first gene expression analysis and including a determination of the metastatic status of the hepatic carcinoma.

Abstract: Assays, methods and kits for predicting survival outcome in a subject having diffuse large B-cell lymphoma (DLBCL) and for measuring a subject's response to DLBCL therapy involve specific miRNAs that are prognostic biomarkers for prediction of outcome of DLBCL patients. Expression of miRNAs miR-18a, miR-181a and miR-222 is associated with response to therapy and outcome of patients with DLBCL. Measurement of these miRs can be used to identify patients' outcomes in the clinic and allow tailoring of patient-specific therapy.

Abstract: Methods are provided for determining whether a patient treated with an anti-proliferative agent is susceptible to toxicity. In practicing the subject methods, an expression profile for the transcriptional response to a therapy is obtained from the patient and compared to a reference profile to determine whether the patient is susceptible to toxicity. In addition, reagents and kits thereof that find use in practicing the subject methods are provided.

Abstract: Microarrays can measure the expression of thousands of genes and thus identify changes in expression between different biological states. Methods are needed to determine the significance of these changes, while accounting for the enormous number of genes. We describe a new method, Significance Analysis of Microarrays (SAM), that assigns a score to each gene based on the change in gene expression relative to the standard deviation of repeated measurements. For genes with scores greater than an adjustable threshold, SAM uses permutations of the repeated measurements to estimate the percentage of such genes identified by chance, the false discovery rate (FDR). When the transcriptional response of human cells to ionizing radiation was measured by microarrays, SAM identified 34 genes that changed at least 1.5-fold with an estimated FDR of 12%, compared to FDRs of 60% and 84% using conventional methods of analysis. Of the 34 genes, 19 were involved in cell cycle regulation, and 3 in apoptosis.

Abstract: Methods and kits for classifying patients having diffuse large B-cell lymphoma (DLBCL) based upon expression of a plurality of genes are disclosed. Real-time quantitative RT-PCR can be used to measure expression values. Correlating expression values of the plurality of genes in a tumor sample from the patient to reference expression values obtained from DLBCL patients can stratify patients in the classification groups. The methods and kits can be used to predict overall patient survival.

Abstract: The present invention provides methods for diagnosing cancers, such as prostate cancer. Also, methods for evaluating the prostate cancer state of a patient are described herein. These methods involve the detection, analysis, and classification of biological patterns in biological samples. The biological patterns are obtained using, for example, mass spectrometry systems, antibody based techniques, or nucleic acid based techniques. The present invention also includes therapeutic and prophylactic agents that target the biomarkers described herein. Also, the present invention provides methods for the treatment of prostate cancer using the markers described herein or agents that mimic the properties of these markers.

Abstract: Methods and kits for classifying patients having diffuse large B-cell lymphoma (DLBCL) based upon expression of a plurality of genes are disclosed. Real-time quantitative RT-PCR can be used to measure expression values. Correlating expression values of the plurality of genes in a tumor sample from the patient to reference expression values obtained from DLBCL patients can stratify patients in the classification groups. The methods and kits can be used to predict overall patient survival.

Abstract: Methods are provided for determining whether a patient treated with an anti-proliferative agent is susceptible to toxicity. In practicing the subject methods, an expression profile for the transcriptional response to a therapy is obtained from the patient and compared to a reference profile to determine whether the patient is susceptible to toxicity. In addition, reagents and kits thereof that find use in practicing the subject methods are provided.

Abstract: Microarrays can measure the expression of thousands of genes and thus identify changes in expression between different biological states. Methods are needed to determine the significance of these changes, while accounting for the enormous number of genes. We describe a new method, Significance Analysis of Microarrays (SAM), that assigns a score to each gene based on the change in gene expression relative to the standard deviation of repeated measurements. For genes with scores greater than an adjustable threshold, SAM uses permutations of the repeated measurements to estimate the percentage of such genes identified by chance, the false discovery rate (FDR). When the transcriptional response of human cells to ionizing radiation was measured by microarrays, SAM identified 34 genes that changed at least 1.5-fold with an estimated FDR of 12%, compared to FDRs of 60% and 84% using conventional methods of analysis. Of the 34 genes, 19 were involved in cell cycle regulation, and 3 in apoptosis.