Characterization of 1577 primary prostate cancers reveals novel biological and clinicopathologic insights into molecular subtypes

Scott A. Tomlins, Mohammed Alshalalfa, Elai Davicioni, Nicholas Erho, Kasra Yousefi, Shuang Zhao, Zaid Haddad, Robert B. Den, Adam P. Dicker, Bruce J. Trock, Angelo M. Demarzo, Ashley E. Ross, Edward M. Schaeffer, Eric A. Klein, Cristina Magi-Galluzzi, Robert Jeffrey Karnes, Robert Brian Jenkins, Felix Y. Feng

Research output: Contribution to journalArticle

71 Citations (Scopus)

Abstract

Background Prostate cancer (PCa) molecular subtypes have been defined by essentially mutually exclusive events, including ETS gene fusions (most commonly involving ERG) and SPINK1 overexpression. Clinical assessment may aid in disease stratification, complementing available prognostic tests. Objective To determine the analytical validity and clinicopatholgic associations of microarray-based molecular subtyping. Design, setting, and participants We analyzed Affymetrix GeneChip expression profiles for 1577 patients from eight radical prostatectomy cohorts, including 1351 cases assessed using the Decipher prognostic assay (GenomeDx Biosciences, San Diego, CA, USA) performed in a laboratory with Clinical Laboratory Improvements Amendment certification. A microarray-based (m-) random forest ERG classification model was trained and validated. Outlier expression analysis was used to predict other mutually exclusive non-ERG ETS gene rearrangements (ETS<sup>+</sup>) or SPINK1 overexpression (SPINK1<sup>+</sup>). Outcome measurements Associations with clinical features and outcomes by multivariate logistic regression analysis and receiver operating curves. Results and limitations The m-ERG classifier showed 95% accuracy in an independent validation subset (155 samples). Across cohorts, 45% of PCas were classified as m-ERG<sup>+</sup>, 9% as m-ETS<sup>+</sup>, 8% as m-SPINK1<sup>+</sup>, and 38% as triple negative (m-ERG<sup>-</sup>/m-ETS<sup>-</sup>/m-SPINK1<sup>-</sup>). Gene expression profiling supports three underlying molecularly defined groups: m-ERG<sup>+</sup>, m-ETS<sup>+</sup>, and m-SPINK1<sup>+</sup>/triple negative. On multivariate analysis, m-ERG<sup>+</sup> tumors were associated with lower preoperative serum prostate-specific antigen and Gleason scores, but greater extraprostatic extension (p < 0.001). m-ETS<sup>+</sup> tumors were associated with seminal vesicle invasion (p = 0.01), while m-SPINK1<sup>+</sup>/triple negative tumors had higher Gleason scores and were more frequent in Black/African American patients (p < 0.001). Clinical outcomes were not significantly different among subtypes. Conclusions A clinically available prognostic test (Decipher) can also assess PCa molecular subtypes, obviating the need for additional testing. Clinicopathologic differences were found among subtypes based on global expression patterns. Patient summary Molecular subtyping of prostate cancer can be achieved using extra data generated from a clinical-grade, genome-wide expression-profiling prognostic assay (Decipher). Transcriptomic and clinical analysis support three distinct molecular subtypes: (1) m-ERG<sup>+</sup>, (2) m-ETS<sup>+</sup>, and (3) m-SPINK1<sup>+</sup>/triple negative (m-ERG<sup>-</sup>/m-ETS<sup>-</sup>/m-SPINK1<sup>-</sup>). Incorporation of subtyping into a clinically available assay may facilitate additional applications beyond routine prognosis.

Original languageEnglish (US)
Pages (from-to)555-567
Number of pages13
JournalEuropean Urology
Volume68
Issue number4
DOIs
StatePublished - Oct 1 2015

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Prostatic Neoplasms
Neoplasm Grading
Neoplasms
Seminal Vesicles
Gene Rearrangement
Gene Fusion
Certification
Gene Expression Profiling
Prostate-Specific Antigen
Prostatectomy
African Americans
Multivariate Analysis
Logistic Models
Regression Analysis
Serum
Forests

Keywords

  • ERG
  • ETS
  • Microarray
  • Prognosis
  • Prostate cancer
  • SPINK1

ASJC Scopus subject areas

  • Urology

Cite this

Characterization of 1577 primary prostate cancers reveals novel biological and clinicopathologic insights into molecular subtypes. / Tomlins, Scott A.; Alshalalfa, Mohammed; Davicioni, Elai; Erho, Nicholas; Yousefi, Kasra; Zhao, Shuang; Haddad, Zaid; Den, Robert B.; Dicker, Adam P.; Trock, Bruce J.; Demarzo, Angelo M.; Ross, Ashley E.; Schaeffer, Edward M.; Klein, Eric A.; Magi-Galluzzi, Cristina; Karnes, Robert Jeffrey; Jenkins, Robert Brian; Feng, Felix Y.

In: European Urology, Vol. 68, No. 4, 01.10.2015, p. 555-567.

Research output: Contribution to journalArticle

Tomlins, SA, Alshalalfa, M, Davicioni, E, Erho, N, Yousefi, K, Zhao, S, Haddad, Z, Den, RB, Dicker, AP, Trock, BJ, Demarzo, AM, Ross, AE, Schaeffer, EM, Klein, EA, Magi-Galluzzi, C, Karnes, RJ, Jenkins, RB & Feng, FY 2015, 'Characterization of 1577 primary prostate cancers reveals novel biological and clinicopathologic insights into molecular subtypes', European Urology, vol. 68, no. 4, pp. 555-567. https://doi.org/10.1016/j.eururo.2015.04.033
Tomlins, Scott A. ; Alshalalfa, Mohammed ; Davicioni, Elai ; Erho, Nicholas ; Yousefi, Kasra ; Zhao, Shuang ; Haddad, Zaid ; Den, Robert B. ; Dicker, Adam P. ; Trock, Bruce J. ; Demarzo, Angelo M. ; Ross, Ashley E. ; Schaeffer, Edward M. ; Klein, Eric A. ; Magi-Galluzzi, Cristina ; Karnes, Robert Jeffrey ; Jenkins, Robert Brian ; Feng, Felix Y. / Characterization of 1577 primary prostate cancers reveals novel biological and clinicopathologic insights into molecular subtypes. In: European Urology. 2015 ; Vol. 68, No. 4. pp. 555-567.
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abstract = "Background Prostate cancer (PCa) molecular subtypes have been defined by essentially mutually exclusive events, including ETS gene fusions (most commonly involving ERG) and SPINK1 overexpression. Clinical assessment may aid in disease stratification, complementing available prognostic tests. Objective To determine the analytical validity and clinicopatholgic associations of microarray-based molecular subtyping. Design, setting, and participants We analyzed Affymetrix GeneChip expression profiles for 1577 patients from eight radical prostatectomy cohorts, including 1351 cases assessed using the Decipher prognostic assay (GenomeDx Biosciences, San Diego, CA, USA) performed in a laboratory with Clinical Laboratory Improvements Amendment certification. A microarray-based (m-) random forest ERG classification model was trained and validated. Outlier expression analysis was used to predict other mutually exclusive non-ERG ETS gene rearrangements (ETS+) or SPINK1 overexpression (SPINK1+). Outcome measurements Associations with clinical features and outcomes by multivariate logistic regression analysis and receiver operating curves. Results and limitations The m-ERG classifier showed 95{\%} accuracy in an independent validation subset (155 samples). Across cohorts, 45{\%} of PCas were classified as m-ERG+, 9{\%} as m-ETS+, 8{\%} as m-SPINK1+, and 38{\%} as triple negative (m-ERG-/m-ETS-/m-SPINK1-). Gene expression profiling supports three underlying molecularly defined groups: m-ERG+, m-ETS+, and m-SPINK1+/triple negative. On multivariate analysis, m-ERG+ tumors were associated with lower preoperative serum prostate-specific antigen and Gleason scores, but greater extraprostatic extension (p < 0.001). m-ETS+ tumors were associated with seminal vesicle invasion (p = 0.01), while m-SPINK1+/triple negative tumors had higher Gleason scores and were more frequent in Black/African American patients (p < 0.001). Clinical outcomes were not significantly different among subtypes. Conclusions A clinically available prognostic test (Decipher) can also assess PCa molecular subtypes, obviating the need for additional testing. Clinicopathologic differences were found among subtypes based on global expression patterns. Patient summary Molecular subtyping of prostate cancer can be achieved using extra data generated from a clinical-grade, genome-wide expression-profiling prognostic assay (Decipher). Transcriptomic and clinical analysis support three distinct molecular subtypes: (1) m-ERG+, (2) m-ETS+, and (3) m-SPINK1+/triple negative (m-ERG-/m-ETS-/m-SPINK1-). Incorporation of subtyping into a clinically available assay may facilitate additional applications beyond routine prognosis.",
keywords = "ERG, ETS, Microarray, Prognosis, Prostate cancer, SPINK1",
author = "Tomlins, {Scott A.} and Mohammed Alshalalfa and Elai Davicioni and Nicholas Erho and Kasra Yousefi and Shuang Zhao and Zaid Haddad and Den, {Robert B.} and Dicker, {Adam P.} and Trock, {Bruce J.} and Demarzo, {Angelo M.} and Ross, {Ashley E.} and Schaeffer, {Edward M.} and Klein, {Eric A.} and Cristina Magi-Galluzzi and Karnes, {Robert Jeffrey} and Jenkins, {Robert Brian} and Feng, {Felix Y.}",
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TY - JOUR

T1 - Characterization of 1577 primary prostate cancers reveals novel biological and clinicopathologic insights into molecular subtypes

AU - Tomlins, Scott A.

AU - Alshalalfa, Mohammed

AU - Davicioni, Elai

AU - Erho, Nicholas

AU - Yousefi, Kasra

AU - Zhao, Shuang

AU - Haddad, Zaid

AU - Den, Robert B.

AU - Dicker, Adam P.

AU - Trock, Bruce J.

AU - Demarzo, Angelo M.

AU - Ross, Ashley E.

AU - Schaeffer, Edward M.

AU - Klein, Eric A.

AU - Magi-Galluzzi, Cristina

AU - Karnes, Robert Jeffrey

AU - Jenkins, Robert Brian

AU - Feng, Felix Y.

PY - 2015/10/1

Y1 - 2015/10/1

N2 - Background Prostate cancer (PCa) molecular subtypes have been defined by essentially mutually exclusive events, including ETS gene fusions (most commonly involving ERG) and SPINK1 overexpression. Clinical assessment may aid in disease stratification, complementing available prognostic tests. Objective To determine the analytical validity and clinicopatholgic associations of microarray-based molecular subtyping. Design, setting, and participants We analyzed Affymetrix GeneChip expression profiles for 1577 patients from eight radical prostatectomy cohorts, including 1351 cases assessed using the Decipher prognostic assay (GenomeDx Biosciences, San Diego, CA, USA) performed in a laboratory with Clinical Laboratory Improvements Amendment certification. A microarray-based (m-) random forest ERG classification model was trained and validated. Outlier expression analysis was used to predict other mutually exclusive non-ERG ETS gene rearrangements (ETS+) or SPINK1 overexpression (SPINK1+). Outcome measurements Associations with clinical features and outcomes by multivariate logistic regression analysis and receiver operating curves. Results and limitations The m-ERG classifier showed 95% accuracy in an independent validation subset (155 samples). Across cohorts, 45% of PCas were classified as m-ERG+, 9% as m-ETS+, 8% as m-SPINK1+, and 38% as triple negative (m-ERG-/m-ETS-/m-SPINK1-). Gene expression profiling supports three underlying molecularly defined groups: m-ERG+, m-ETS+, and m-SPINK1+/triple negative. On multivariate analysis, m-ERG+ tumors were associated with lower preoperative serum prostate-specific antigen and Gleason scores, but greater extraprostatic extension (p < 0.001). m-ETS+ tumors were associated with seminal vesicle invasion (p = 0.01), while m-SPINK1+/triple negative tumors had higher Gleason scores and were more frequent in Black/African American patients (p < 0.001). Clinical outcomes were not significantly different among subtypes. Conclusions A clinically available prognostic test (Decipher) can also assess PCa molecular subtypes, obviating the need for additional testing. Clinicopathologic differences were found among subtypes based on global expression patterns. Patient summary Molecular subtyping of prostate cancer can be achieved using extra data generated from a clinical-grade, genome-wide expression-profiling prognostic assay (Decipher). Transcriptomic and clinical analysis support three distinct molecular subtypes: (1) m-ERG+, (2) m-ETS+, and (3) m-SPINK1+/triple negative (m-ERG-/m-ETS-/m-SPINK1-). Incorporation of subtyping into a clinically available assay may facilitate additional applications beyond routine prognosis.

AB - Background Prostate cancer (PCa) molecular subtypes have been defined by essentially mutually exclusive events, including ETS gene fusions (most commonly involving ERG) and SPINK1 overexpression. Clinical assessment may aid in disease stratification, complementing available prognostic tests. Objective To determine the analytical validity and clinicopatholgic associations of microarray-based molecular subtyping. Design, setting, and participants We analyzed Affymetrix GeneChip expression profiles for 1577 patients from eight radical prostatectomy cohorts, including 1351 cases assessed using the Decipher prognostic assay (GenomeDx Biosciences, San Diego, CA, USA) performed in a laboratory with Clinical Laboratory Improvements Amendment certification. A microarray-based (m-) random forest ERG classification model was trained and validated. Outlier expression analysis was used to predict other mutually exclusive non-ERG ETS gene rearrangements (ETS+) or SPINK1 overexpression (SPINK1+). Outcome measurements Associations with clinical features and outcomes by multivariate logistic regression analysis and receiver operating curves. Results and limitations The m-ERG classifier showed 95% accuracy in an independent validation subset (155 samples). Across cohorts, 45% of PCas were classified as m-ERG+, 9% as m-ETS+, 8% as m-SPINK1+, and 38% as triple negative (m-ERG-/m-ETS-/m-SPINK1-). Gene expression profiling supports three underlying molecularly defined groups: m-ERG+, m-ETS+, and m-SPINK1+/triple negative. On multivariate analysis, m-ERG+ tumors were associated with lower preoperative serum prostate-specific antigen and Gleason scores, but greater extraprostatic extension (p < 0.001). m-ETS+ tumors were associated with seminal vesicle invasion (p = 0.01), while m-SPINK1+/triple negative tumors had higher Gleason scores and were more frequent in Black/African American patients (p < 0.001). Clinical outcomes were not significantly different among subtypes. Conclusions A clinically available prognostic test (Decipher) can also assess PCa molecular subtypes, obviating the need for additional testing. Clinicopathologic differences were found among subtypes based on global expression patterns. Patient summary Molecular subtyping of prostate cancer can be achieved using extra data generated from a clinical-grade, genome-wide expression-profiling prognostic assay (Decipher). Transcriptomic and clinical analysis support three distinct molecular subtypes: (1) m-ERG+, (2) m-ETS+, and (3) m-SPINK1+/triple negative (m-ERG-/m-ETS-/m-SPINK1-). Incorporation of subtyping into a clinically available assay may facilitate additional applications beyond routine prognosis.

KW - ERG

KW - ETS

KW - Microarray

KW - Prognosis

KW - Prostate cancer

KW - SPINK1

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