Molecular profiling of radical prostatectomy tissue from patients with no sign of progression identifies ERG as the strongest independent predictor of recurrence
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Wusheng Yan1,2,*, Muhammad Jamal1,2,*, Shyh-Han Tan1,2,*, Yingjie Song1,2, Denise Young1,2, Yongmei Chen1,2, Shilpa Katta1,2, Kai Ying1,2, Lakshmi Ravindranath1,2, Tarah Woodle2, Indu Kohaar1,2, Jennifer Cullen1,2,3, Jacob Kagan4, Sudhir Srivastava4, Albert Dobi1,2,3, David G. McLeod1,2,3, Inger L. Rosner1,2,3, Isabell A. Sesterhenn5, Alagarsamy Srinivasan1,2, Shiv Srivastava1,2,3 and Gyorgy Petrovics1,2,3
1 Henry Jackson Foundation for the Advancement of Military Medicine (HJF), Bethesda, MD, USA
2 Center for Prostate Disease Research, Department of Surgery, Uniformed Services University of the Health Sciences and the Walter Reed National Military Medical Center, Bethesda, MD, USA
3 John P. Murtha Cancer Center, Walter Reed National Military Medical Center, Bethesda, MD, USA
4 Division of Cancer Prevention, National Cancer Institute, NIH, Bethesda, MD, USA
5 Joint Pathology Center, Silver Spring, MD, USA
* These authors contributed equally to this work
Keywords: prostate cancer; NanoString; prognostic biomarker; biochemical recurrence; ERG
Received: July 04, 2019 Accepted: October 19, 2019 Published: November 05, 2019
Background: As a major cause of morbidity and mortality among men, prostate cancer is a heterogenous disease, with a vast heterogeneity in the biology of the disease and in clinical outcome. While it often runs an indolent course, local progression or metastasis may eventually develop, even among patients considered “low risk” at diagnosis. Therefore, biomarkers that can discriminate aggressive from indolent disease at an early stage would greatly benefit patients. We hypothesized that tissue specimens from early stage prostate cancers may harbor predictive signatures for disease progression.
Methods: We used a cohort of radical prostatectomy patients with longitudinal follow-up, who had tumors with low grade and stage that revealed no signs of future disease progression at surgery. During the follow-up period, some patients either remained indolent (non-BCR) or progressed to biochemical recurrence (BCR). Total RNA was extracted from tumor, and adjacent normal epithelium of formalin-fixed-paraffin-embedded (FFPE) specimens. Differential gene expression in tumors, and in tumor versus normal tissues between BCR and non-BCR patients were analyzed by NanoString using a customized CodeSet of 151 probes.
Results: After controlling for false discovery rates, we identified a panel of eight genes (ERG, GGT1, HDAC1, KLK2, MYO6, PLA2G7, BICD1 and CACNAID) that distinguished BCR from non-BCR patients. We found a clear association of ERG expression with non-BCR, which was further corroborated by quantitative RT-PCR and immunohistochemistry assays.
Conclusions: Our results identified ERG as the strongest predictor for BCR and showed that potential prognostic prostate cancer biomarkers can be identified from FFPE tumor specimens.
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