Comprehensive Prostate Cancer Characterization by Genomic and Transcriptomic Prof

Weill Medical Coll Of Cornell Univ, New York NY

Investigators

Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): Approximately 55% of prostate cancers (PCA) harbor cancer specific gene fusions. This represents an important opportunity to develop a non-invasive highly specific test for the early detection of PCA. Implementation of a urine assay to detect the TMPRSS2-ERG gene fusion is already underway, demonstrating a high specificity. A logical next step in biomarker development is the exploration of novel cancer specific gene fusions and somatic alterations. The overall goal of this proposal is to discover and validate PCA specific biomarkers that can be non- invasively detected in the urine. We have taken a Systems Biology approach integrating state-of-the-art RNA-sequencing (RNA-seq) and DNA 6.0 single nucleotide polymorphism (SNP) arrays with novel computational approaches for analysis. In Aim 1, we will identify novel gene fusions with RNA-seq and in Aim 2 we will determine somatic copy number alterations (gains and losses) associated with altered gene transcript expression as determined by RNA-seq from Aim 1. We will use 100 frozen PCA samples and 25 paired benign prostate tissues in the discovery step of Phase 1 for initial discovery of PCA specific biomarkers. The PCA samples will be equally divided based Gleason Score (tumor grade), 6 (3+3), 7 (3+4), 7(4+3), and 8-10. We will also attempt to balance for age at time of biopsy, PSA levels, and tumor stage (organ confined (pT2) versus extraprostatic extension (pT3). Tumors will be evaluated for known ETS gene fusions (e.g., TMPRSS2- ERG, SLC45A3-ETV1, etc.). We will also attempt to balance samples based on known fusions versus no fusions based on the current knowledge of gene fusions. The verification step of Phase 1 will occur using FISH for the novel gene fusions and immunohistochemisty (IHC) and/or FISH for somatic alterations to determine PCA specificity on tissue microarrays with over 200 PCA samples and 400 benign tissues. We will also explore PCA specificity in 100 urine samples collected from men with and without PCA using a rigorous EDRN Protocol on local samples. RT-PCR assays for fusion genes and over or under expression of somatically altered genes will be tested using mRNA for PSA as an internal control. The biostatistical group will supervise all steps of the analysis and help prioritize the lead candidates in conjunction with the computational biology group. We anticipate nominating 20 candidates from each biomarker category per year and will hand off 5-10 for formal Phase 2 validation by the EDRN Clinical Validation Center of Harvard/Michigan/Weil Cornel (outside the scope of this application). Discoveries made in this proposal will be strong candidates for clinical validation as part of the Early Detection Research Network PCA program. This study will also generate important insight into the molecular biology of PCA, which has broad implications in understanding disease progression and identifying potential drug targets. Finally, the computational tools and dataset will be important resources for the research community at large.