Abstract 226: Verification of prostate cancer genomics biomarker candidates at protein level using PRISM-SRM
Authors: Wang Hui , Gao Yuqian , Schepmoes Athena , Petrovics Gyorgy , Cullen Jennifer , Fillmore Thomas , Shi Tujin , Qian Wei-Jun , Smith Richard , Weaver Brandi , Leach Robin , Thompson Ian , Srivastava Sudhir , Kagan Jacob , Dobi Albert , Rodland Karin , Srivastava Shiv , Liu Tao 
Published: July 2017

Mass spectrometry (MS) based targeted proteomics such as selected reaction monitoring (SRM) provides an antibody-independent strategy for sensitive, specific and multiplexed verification of genomics biomarker candidates at the protein level. In order to identify a panel of proteins with the potential to discriminate between aggressive and indolent forms of prostate cancer and predict prostate cancer progression, we have selected 52 protein candidates from existing prostate cancer genomics data sets and validated cancer drivers, and performed quantitative proteomics analysis in tumor and control tissue samples using the highly sensitive PRISM (high-pressure, high-resolution separations coupled with intelligent selection and multiplexing)-SRM approach. PRISM-SRM assays have been developed for the 52 prostate cancer biomarker candidates including: prostate cancer prognosis associated genes, prostate cancer associated genes that were up-regulated in transcriptomics studies, and other cancer-related genes (including the ERG or ETV1 isoforms). Two sets of tissue samples were analyzed using PRISM-SRM with heavy isotope-labeled synthetic peptides as internal standards: 1) 10 high Gleason-score (7-9) primary prostate tumors and 10 benign prostatic hyperplasia (BPH) tissues (OCT-embedded specimens); and 2) 10 primary tumors from patients showing metastatic progression, 10 primary tumors from patients who showed biochemical recurrence (BCR), and 10 primary tumors from patients with no BCR or metastatic progression after more than ten years of follow-up after radical prostatectomy (FFPE whole mount prostate specimens). Overall, PRISM-SRM analyses of all the patient tissue samples enabled the detection of 48 out of 52 biomarker candidates, suggesting extremely low level of expression of the remaining 6 genes (HXC6, OSTP, TWST1, and ERG8); in comparison regular LC-SRM can only detect 21 of these candidates at the protein level. In the 10 high Gleason-score tumors and 10 BPH controls, 13 proteins were found differentially abundant with P&lt;0.05. In the 10X10X10 FFPE sample analysis, there were three proteins discriminating between “metastatic progression” and “no progression” tumors, one protein discriminated between BCR and “no progression” tumors, and four proteins discriminated between metastatic progression and BCR tumors (P&lt;0.05). These promising biomarker candidates will be further evaluated, individually and in panels, in independent, larger cohort for their potential prognostic applications. In summary, PRISM-SRM provides a highly sensitive method for quantification and rapid screening of multiple potential biomarker candidates at the protein level. This approach holds great potential for rapidly translating genomics-based discovery candidates into protein-based biomarkers.

Citation Format: Hui Wang, Yuqian Gao, Athena Schepmoes, Gyorgy Petrovics, Jennifer Cullen, Thomas Fillmore, Tujin Shi, Wei-Jun Qian, Richard Smith, Brandi Weaver, Robin Leach, Ian Thompson, Sudhir Srivastava, Jacob Kagan, Albert Dobi, Karin Rodland, Shiv Srivastava, Tao Liu. Verification of prostate cancer genomics biomarker candidates at protein level using PRISM-SRM [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 226. doi:10.1158/1538-7445.AM2017-226