The landscape of prognostic outlier genes in high-risk prostate cancer

Shuang G. Zhao, Joseph R. Evans, Vishal Kothari, Grace Sun, Ashley Larm, Victor Mondine, Edward M. Schaeffer, Ashley E. Ross, Eric A. Klein, Robert B. Den, Adam P. Dicker, Robert Jeffrey Karnes, Nicholas Erho, Paul L. Nguyen, Elai Davicioni, Felix Y. Feng

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

Purpose: There is a clear need to improve risk stratification and to identify novel therapeutic targets in aggressive prostate cancer. The goal of this study was to investigate genes with outlier expression with prognostic association in high-risk prostate cancer patients as potential biomarkers and drug targets. Experimental Design:Weinterrogated microarray gene expression data from prostatectomy samples from 545 high-risk prostate cancer patients with long-term follow-up (mean 13.4 years). Three independent clinical datasets totaling an additional 545 patients were used for validation. Novel prognostic outlier genes were interrogated for impact on oncogenic phenotypes in vitro using siRNA-based knockdown. Association with clinical outcomes and comparison with existing prognostic instruments was assessed with multivariable models using a prognostic outlier score. Results: Analysis of the discovery cohort identified 20 prognostic outlier genes. Three top prognostic outlier genes were novel prostate cancer genes; NVL, SMC4, or SQLE knockdown reduced migration and/or invasion and outlier expression was significantly associated with poor prognosis. Increased prognostic outlier score was significantly associated with poor prognosis independent of standard clinicopathologic variables. Finally, the prognostic outlier score prognostic association is independent of, and adds to existing genomic and clinical tools for prognostication in prostate cancer (Decipher, the cell-cycle progression signature, and CAPRA-S). Conclusions: To our knowledge, this study represents the first unbiased high-throughput investigation of prognostic outlier genes in prostate cancer and demonstrates the potential biomarker and therapeutic importance of this previously unstudied class of cancer genes.

Original languageEnglish (US)
Pages (from-to)1777-1786
Number of pages10
JournalClinical Cancer Research
Volume22
Issue number7
DOIs
StatePublished - Apr 1 2016

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Prostatic Neoplasms
Genes
Neoplasm Genes
Biomarkers
Prostatectomy
Small Interfering RNA
Cell Cycle
Cohort Studies
Research Design
Phenotype
Gene Expression
Therapeutics
Pharmaceutical Preparations

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

Cite this

Zhao, S. G., Evans, J. R., Kothari, V., Sun, G., Larm, A., Mondine, V., ... Feng, F. Y. (2016). The landscape of prognostic outlier genes in high-risk prostate cancer. Clinical Cancer Research, 22(7), 1777-1786. https://doi.org/10.1158/1078-0432.CCR-15-1250

The landscape of prognostic outlier genes in high-risk prostate cancer. / Zhao, Shuang G.; Evans, Joseph R.; Kothari, Vishal; Sun, Grace; Larm, Ashley; Mondine, Victor; Schaeffer, Edward M.; Ross, Ashley E.; Klein, Eric A.; Den, Robert B.; Dicker, Adam P.; Karnes, Robert Jeffrey; Erho, Nicholas; Nguyen, Paul L.; Davicioni, Elai; Feng, Felix Y.

In: Clinical Cancer Research, Vol. 22, No. 7, 01.04.2016, p. 1777-1786.

Research output: Contribution to journalArticle

Zhao, SG, Evans, JR, Kothari, V, Sun, G, Larm, A, Mondine, V, Schaeffer, EM, Ross, AE, Klein, EA, Den, RB, Dicker, AP, Karnes, RJ, Erho, N, Nguyen, PL, Davicioni, E & Feng, FY 2016, 'The landscape of prognostic outlier genes in high-risk prostate cancer', Clinical Cancer Research, vol. 22, no. 7, pp. 1777-1786. https://doi.org/10.1158/1078-0432.CCR-15-1250
Zhao SG, Evans JR, Kothari V, Sun G, Larm A, Mondine V et al. The landscape of prognostic outlier genes in high-risk prostate cancer. Clinical Cancer Research. 2016 Apr 1;22(7):1777-1786. https://doi.org/10.1158/1078-0432.CCR-15-1250
Zhao, Shuang G. ; Evans, Joseph R. ; Kothari, Vishal ; Sun, Grace ; Larm, Ashley ; Mondine, Victor ; Schaeffer, Edward M. ; Ross, Ashley E. ; Klein, Eric A. ; Den, Robert B. ; Dicker, Adam P. ; Karnes, Robert Jeffrey ; Erho, Nicholas ; Nguyen, Paul L. ; Davicioni, Elai ; Feng, Felix Y. / The landscape of prognostic outlier genes in high-risk prostate cancer. In: Clinical Cancer Research. 2016 ; Vol. 22, No. 7. pp. 1777-1786.
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AU - Evans, Joseph R.

AU - Kothari, Vishal

AU - Sun, Grace

AU - Larm, Ashley

AU - Mondine, Victor

AU - Schaeffer, Edward M.

AU - Ross, Ashley E.

AU - Klein, Eric A.

AU - Den, Robert B.

AU - Dicker, Adam P.

AU - Karnes, Robert Jeffrey

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AU - Nguyen, Paul L.

AU - Davicioni, Elai

AU - Feng, Felix Y.

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N2 - Purpose: There is a clear need to improve risk stratification and to identify novel therapeutic targets in aggressive prostate cancer. The goal of this study was to investigate genes with outlier expression with prognostic association in high-risk prostate cancer patients as potential biomarkers and drug targets. Experimental Design:Weinterrogated microarray gene expression data from prostatectomy samples from 545 high-risk prostate cancer patients with long-term follow-up (mean 13.4 years). Three independent clinical datasets totaling an additional 545 patients were used for validation. Novel prognostic outlier genes were interrogated for impact on oncogenic phenotypes in vitro using siRNA-based knockdown. Association with clinical outcomes and comparison with existing prognostic instruments was assessed with multivariable models using a prognostic outlier score. Results: Analysis of the discovery cohort identified 20 prognostic outlier genes. Three top prognostic outlier genes were novel prostate cancer genes; NVL, SMC4, or SQLE knockdown reduced migration and/or invasion and outlier expression was significantly associated with poor prognosis. Increased prognostic outlier score was significantly associated with poor prognosis independent of standard clinicopathologic variables. Finally, the prognostic outlier score prognostic association is independent of, and adds to existing genomic and clinical tools for prognostication in prostate cancer (Decipher, the cell-cycle progression signature, and CAPRA-S). Conclusions: To our knowledge, this study represents the first unbiased high-throughput investigation of prognostic outlier genes in prostate cancer and demonstrates the potential biomarker and therapeutic importance of this previously unstudied class of cancer genes.

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