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Molecular profiling of radical prostatectomy tissue from patients with no sign of progression identifies ERG as the strongest independent predictor of recurrence

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 pa...

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Autores principales: Yan, Wusheng, Jamal, Muhammad, Tan, Shyh-Han, Song, Yingjie, Young, Denise, Chen, Yongmei, Katta, Shilpa, Ying, Kai, Ravindranath, Lakshmi, Woodle, Tarah, Kohaar, Indu, Cullen, Jennifer, Kagan, Jacob, Srivastava, Sudhir, Dobi, Albert, McLeod, David G., Rosner, Inger L., Sesterhenn, Isabell A., Srinivasan, Alagarsamy, Srivastava, Shiv, Petrovics, Gyorgy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6849651/
https://www.ncbi.nlm.nih.gov/pubmed/31741711
http://dx.doi.org/10.18632/oncotarget.27294
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author Yan, Wusheng
Jamal, Muhammad
Tan, Shyh-Han
Song, Yingjie
Young, Denise
Chen, Yongmei
Katta, Shilpa
Ying, Kai
Ravindranath, Lakshmi
Woodle, Tarah
Kohaar, Indu
Cullen, Jennifer
Kagan, Jacob
Srivastava, Sudhir
Dobi, Albert
McLeod, David G.
Rosner, Inger L.
Sesterhenn, Isabell A.
Srinivasan, Alagarsamy
Srivastava, Shiv
Petrovics, Gyorgy
author_facet Yan, Wusheng
Jamal, Muhammad
Tan, Shyh-Han
Song, Yingjie
Young, Denise
Chen, Yongmei
Katta, Shilpa
Ying, Kai
Ravindranath, Lakshmi
Woodle, Tarah
Kohaar, Indu
Cullen, Jennifer
Kagan, Jacob
Srivastava, Sudhir
Dobi, Albert
McLeod, David G.
Rosner, Inger L.
Sesterhenn, Isabell A.
Srinivasan, Alagarsamy
Srivastava, Shiv
Petrovics, Gyorgy
author_sort Yan, Wusheng
collection PubMed
description 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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spelling pubmed-68496512019-11-18 Molecular profiling of radical prostatectomy tissue from patients with no sign of progression identifies ERG as the strongest independent predictor of recurrence Yan, Wusheng Jamal, Muhammad Tan, Shyh-Han Song, Yingjie Young, Denise Chen, Yongmei Katta, Shilpa Ying, Kai Ravindranath, Lakshmi Woodle, Tarah Kohaar, Indu Cullen, Jennifer Kagan, Jacob Srivastava, Sudhir Dobi, Albert McLeod, David G. Rosner, Inger L. Sesterhenn, Isabell A. Srinivasan, Alagarsamy Srivastava, Shiv Petrovics, Gyorgy Oncotarget Research Paper 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. Impact Journals LLC 2019-11-05 /pmc/articles/PMC6849651/ /pubmed/31741711 http://dx.doi.org/10.18632/oncotarget.27294 Text en http://creativecommons.org/licenses/by/3.0/ Copyright: Yan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Yan, Wusheng
Jamal, Muhammad
Tan, Shyh-Han
Song, Yingjie
Young, Denise
Chen, Yongmei
Katta, Shilpa
Ying, Kai
Ravindranath, Lakshmi
Woodle, Tarah
Kohaar, Indu
Cullen, Jennifer
Kagan, Jacob
Srivastava, Sudhir
Dobi, Albert
McLeod, David G.
Rosner, Inger L.
Sesterhenn, Isabell A.
Srinivasan, Alagarsamy
Srivastava, Shiv
Petrovics, Gyorgy
Molecular profiling of radical prostatectomy tissue from patients with no sign of progression identifies ERG as the strongest independent predictor of recurrence
title Molecular profiling of radical prostatectomy tissue from patients with no sign of progression identifies ERG as the strongest independent predictor of recurrence
title_full Molecular profiling of radical prostatectomy tissue from patients with no sign of progression identifies ERG as the strongest independent predictor of recurrence
title_fullStr Molecular profiling of radical prostatectomy tissue from patients with no sign of progression identifies ERG as the strongest independent predictor of recurrence
title_full_unstemmed Molecular profiling of radical prostatectomy tissue from patients with no sign of progression identifies ERG as the strongest independent predictor of recurrence
title_short Molecular profiling of radical prostatectomy tissue from patients with no sign of progression identifies ERG as the strongest independent predictor of recurrence
title_sort molecular profiling of radical prostatectomy tissue from patients with no sign of progression identifies erg as the strongest independent predictor of recurrence
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6849651/
https://www.ncbi.nlm.nih.gov/pubmed/31741711
http://dx.doi.org/10.18632/oncotarget.27294
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