Abstract 4599: Comprehensive molecular oncogenomic profiling & miRNA analysis of prostate cancer

Abstract

Background: Comprehensive molecular oncogenomic and microRNA (miRNA) profiling of tumors can provide tumor specific oncogenomic and miRNA signatures which can be useful to improve diagnostic accuracy, refine prognostic and predictive capabilities, and may serve as therapeutic targets. In prostate cancer (PCa) such a comprehensive analysis has not been reported. Design: DNA and RNA obtained from scant amounts of fresh frozen PCa tumor tissue samples (n=36) were profiled by (1) Mutation analysis: Sequenom Massarray & OncoCarta VI panel that profiles 238 common cancer mutations in 19 oncogenes (known predictors of response or resistance to targeted therapies);(2) Whole-genome gene expression Microarrays: Illumina Chip;(3) Single Nucleotide Polymorphisms (SNP) with genome-wide coverage:Illumina Omni microarrays. (4)miRNA analysis was done on RNA from FFPE PCa tumor tissues (n=126) using RT-PCR. Data was statistically analyzed & correlated with clinical & pathologic variables. Results: Massarray analysis identified a MET oncogene mutation, variant T992I, in a 49 year old patient with Gleason score 7 (4+3) tumor. Of the 47,224 genes analyzed by gene expression microarrays, 74 genes were significant predictors of high tumor grade by ordinal regression analysis (p<0.0001). TGIF1 was the most significant gene. Of the 731,442 SNP's analyzed, 638 significantly predicted high tumor grade by logistic regression analysis (p<0.0001). There was significant interaction between gene and SNPs in 531 SNP/gene pairs (p<0.05). Ingenuity Pathway analysis revealed the significant predictor genes (p<0.05) were involved in biological pathways for Gene Expression, Cell Cycle, Cancer,” “Inflammatory Response, Cell Death, Infection Mechanism & Cellular Assembly, Organization, Gene Expression, Cancer. P53 gene was found to be at the center hub of significant predicting pathways. Loss of miR-34a expression was found in PCa tissues consistent with the central role of p53. Conclusions: Using high throughput genomic profiling & miRNA analysis of small amounts of fresh-frozen and FFPE PCa tumor samples, we identified clinically relevant hot spot mutation in MET oncogene and several significant genes & SNPs to predict tumor grade. P53 gene is at the center hub of all significant pathways. Loss of miR-34a was consistent with p53 function in PCa. MET oncogene mutation is a novel finding, not previously reported in PCa against which small molecule inhibitors are under development. These molecular signatures may have a significant clinical impact on improving diagnostic and predictive capabilities & in designing targeted therapies to achieve the goal of personalized medicine. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4599. doi:1538-7445.AM2012-4599

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