RNA biomarkers associated with metastatic progression in prostate cancer

A multi-institutional high-throughput analysis of SChLAP1

John R. Prensner, Shuang Zhao, Nicholas Erho, Matthew Schipper, Matthew K. Iyer, Saravana M. Dhanasekaran, Cristina Magi-Galluzzi, Rohit Mehra, Anirban Sahu, Javed Siddiqui, Elai Davicioni, Robert B. Den, Adam P. Dicker, Robert Jeffrey Karnes, John T. Wei, Eric A. Klein, Robert Brian Jenkins, Arul M. Chinnaiyan, Felix Y. Feng

Research output: Contribution to journalArticle

123 Citations (Scopus)

Abstract

Background: Improved clinical predictors for disease progression are needed for localised prostate cancer, since only a subset of patients develop recurrent or refractory disease after first-line treatment. Therefore, we undertook an unbiased analysis to identify RNA biomarkers associated with metastatic progression after prostatectomy. Methods: Prostate cancer samples from patients treated with radical prostatectomy at three academic institutions were analysed for gene expression by a high-density Affymetrix GeneChip platform, encompassing more than 1 million genomic loci. In a discovery cohort, all protein-coding genes and known long non-coding RNAs were ranked by fold change in expression between tumours that subsequently metastasised versus those that did not. The top ranked gene was then validated for its prognostic value for metastatic progression in three additional independent cohorts. 95% of the gene expression assays were done in a Clinical Laboratory Improvements Amendments certified laboratory facility. All genes were assessed for their ability to predict metastatic progression by receiver-operating-curve area-under-the-curve analyses. Multivariate analyses were done for the primary endpoint of metastatic progression, with variables including Gleason score, preoperative prostate-specific antigen concentration, seminal vesicle invasion, surgical margin status, extracapsular extension, lymph node invasion, and expression of the highest ranked gene. Findings: 1008 patients were included in the study: 545 in the discovery cohort and 463 in the validation cohorts. The long non-coding RNA SChLAP1 was identified as the highest-ranked overexpressed gene in cancers with metastatic progression. Validation in three independent cohorts confirmed the prognostic value of SChLAP1 for metastatic progression. On multivariate modelling, SChLAP1 expression (high vs low) independently predicted metastasis within 10 years (odds ratio [OR] 2.;45, 95% CI 1.;70-3.;53; p<0.;0001). The only other variable that independently predicted metastasis within 10 years was Gleason score (8-10 vs 5-7; OR 2.;14, 95% CI 1.;77-2.;58; p<0.;0001). Interpretation: We identified and validated high SChLAP1 expression as significantly prognostic for metastatic disease progression of prostate cancer. Our findings suggest that further development of SChLAP1 as a potential biomarker, for treatment intensification in aggressive prostate cancer, warrants future study.

Original languageEnglish (US)
Pages (from-to)1469-1480
Number of pages12
JournalThe Lancet Oncology
Volume15
Issue number13
DOIs
StatePublished - 2014

Fingerprint

Prostatic Neoplasms
Biomarkers
Long Noncoding RNA
RNA
Neoplasm Grading
Prostatectomy
Disease Progression
Odds Ratio
Neoplasm Metastasis
Genes
Gene Expression
Seminal Vesicles
Neoplasm Genes
Prostate-Specific Antigen
Area Under Curve
Multivariate Analysis
Lymph Nodes
Therapeutics
Neoplasms
Proteins

ASJC Scopus subject areas

  • Oncology
  • Medicine(all)

Cite this

Prensner, J. R., Zhao, S., Erho, N., Schipper, M., Iyer, M. K., Dhanasekaran, S. M., ... Feng, F. Y. (2014). RNA biomarkers associated with metastatic progression in prostate cancer: A multi-institutional high-throughput analysis of SChLAP1. The Lancet Oncology, 15(13), 1469-1480. https://doi.org/10.1016/S1470-2045(14)71113-1

RNA biomarkers associated with metastatic progression in prostate cancer : A multi-institutional high-throughput analysis of SChLAP1. / Prensner, John R.; Zhao, Shuang; Erho, Nicholas; Schipper, Matthew; Iyer, Matthew K.; Dhanasekaran, Saravana M.; Magi-Galluzzi, Cristina; Mehra, Rohit; Sahu, Anirban; Siddiqui, Javed; Davicioni, Elai; Den, Robert B.; Dicker, Adam P.; Karnes, Robert Jeffrey; Wei, John T.; Klein, Eric A.; Jenkins, Robert Brian; Chinnaiyan, Arul M.; Feng, Felix Y.

In: The Lancet Oncology, Vol. 15, No. 13, 2014, p. 1469-1480.

Research output: Contribution to journalArticle

Prensner, JR, Zhao, S, Erho, N, Schipper, M, Iyer, MK, Dhanasekaran, SM, Magi-Galluzzi, C, Mehra, R, Sahu, A, Siddiqui, J, Davicioni, E, Den, RB, Dicker, AP, Karnes, RJ, Wei, JT, Klein, EA, Jenkins, RB, Chinnaiyan, AM & Feng, FY 2014, 'RNA biomarkers associated with metastatic progression in prostate cancer: A multi-institutional high-throughput analysis of SChLAP1', The Lancet Oncology, vol. 15, no. 13, pp. 1469-1480. https://doi.org/10.1016/S1470-2045(14)71113-1
Prensner, John R. ; Zhao, Shuang ; Erho, Nicholas ; Schipper, Matthew ; Iyer, Matthew K. ; Dhanasekaran, Saravana M. ; Magi-Galluzzi, Cristina ; Mehra, Rohit ; Sahu, Anirban ; Siddiqui, Javed ; Davicioni, Elai ; Den, Robert B. ; Dicker, Adam P. ; Karnes, Robert Jeffrey ; Wei, John T. ; Klein, Eric A. ; Jenkins, Robert Brian ; Chinnaiyan, Arul M. ; Feng, Felix Y. / RNA biomarkers associated with metastatic progression in prostate cancer : A multi-institutional high-throughput analysis of SChLAP1. In: The Lancet Oncology. 2014 ; Vol. 15, No. 13. pp. 1469-1480.
@article{f0d5c48b2f6945bc9d87b72111fbcba3,
title = "RNA biomarkers associated with metastatic progression in prostate cancer: A multi-institutional high-throughput analysis of SChLAP1",
abstract = "Background: Improved clinical predictors for disease progression are needed for localised prostate cancer, since only a subset of patients develop recurrent or refractory disease after first-line treatment. Therefore, we undertook an unbiased analysis to identify RNA biomarkers associated with metastatic progression after prostatectomy. Methods: Prostate cancer samples from patients treated with radical prostatectomy at three academic institutions were analysed for gene expression by a high-density Affymetrix GeneChip platform, encompassing more than 1 million genomic loci. In a discovery cohort, all protein-coding genes and known long non-coding RNAs were ranked by fold change in expression between tumours that subsequently metastasised versus those that did not. The top ranked gene was then validated for its prognostic value for metastatic progression in three additional independent cohorts. 95{\%} of the gene expression assays were done in a Clinical Laboratory Improvements Amendments certified laboratory facility. All genes were assessed for their ability to predict metastatic progression by receiver-operating-curve area-under-the-curve analyses. Multivariate analyses were done for the primary endpoint of metastatic progression, with variables including Gleason score, preoperative prostate-specific antigen concentration, seminal vesicle invasion, surgical margin status, extracapsular extension, lymph node invasion, and expression of the highest ranked gene. Findings: 1008 patients were included in the study: 545 in the discovery cohort and 463 in the validation cohorts. The long non-coding RNA SChLAP1 was identified as the highest-ranked overexpressed gene in cancers with metastatic progression. Validation in three independent cohorts confirmed the prognostic value of SChLAP1 for metastatic progression. On multivariate modelling, SChLAP1 expression (high vs low) independently predicted metastasis within 10 years (odds ratio [OR] 2.;45, 95{\%} CI 1.;70-3.;53; p<0.;0001). The only other variable that independently predicted metastasis within 10 years was Gleason score (8-10 vs 5-7; OR 2.;14, 95{\%} CI 1.;77-2.;58; p<0.;0001). Interpretation: We identified and validated high SChLAP1 expression as significantly prognostic for metastatic disease progression of prostate cancer. Our findings suggest that further development of SChLAP1 as a potential biomarker, for treatment intensification in aggressive prostate cancer, warrants future study.",
author = "Prensner, {John R.} and Shuang Zhao and Nicholas Erho and Matthew Schipper and Iyer, {Matthew K.} and Dhanasekaran, {Saravana M.} and Cristina Magi-Galluzzi and Rohit Mehra and Anirban Sahu and Javed Siddiqui and Elai Davicioni and Den, {Robert B.} and Dicker, {Adam P.} and Karnes, {Robert Jeffrey} and Wei, {John T.} and Klein, {Eric A.} and Jenkins, {Robert Brian} and Chinnaiyan, {Arul M.} and Feng, {Felix Y.}",
year = "2014",
doi = "10.1016/S1470-2045(14)71113-1",
language = "English (US)",
volume = "15",
pages = "1469--1480",
journal = "The Lancet Oncology",
issn = "1470-2045",
publisher = "Lancet Publishing Group",
number = "13",

}

TY - JOUR

T1 - RNA biomarkers associated with metastatic progression in prostate cancer

T2 - A multi-institutional high-throughput analysis of SChLAP1

AU - Prensner, John R.

AU - Zhao, Shuang

AU - Erho, Nicholas

AU - Schipper, Matthew

AU - Iyer, Matthew K.

AU - Dhanasekaran, Saravana M.

AU - Magi-Galluzzi, Cristina

AU - Mehra, Rohit

AU - Sahu, Anirban

AU - Siddiqui, Javed

AU - Davicioni, Elai

AU - Den, Robert B.

AU - Dicker, Adam P.

AU - Karnes, Robert Jeffrey

AU - Wei, John T.

AU - Klein, Eric A.

AU - Jenkins, Robert Brian

AU - Chinnaiyan, Arul M.

AU - Feng, Felix Y.

PY - 2014

Y1 - 2014

N2 - Background: Improved clinical predictors for disease progression are needed for localised prostate cancer, since only a subset of patients develop recurrent or refractory disease after first-line treatment. Therefore, we undertook an unbiased analysis to identify RNA biomarkers associated with metastatic progression after prostatectomy. Methods: Prostate cancer samples from patients treated with radical prostatectomy at three academic institutions were analysed for gene expression by a high-density Affymetrix GeneChip platform, encompassing more than 1 million genomic loci. In a discovery cohort, all protein-coding genes and known long non-coding RNAs were ranked by fold change in expression between tumours that subsequently metastasised versus those that did not. The top ranked gene was then validated for its prognostic value for metastatic progression in three additional independent cohorts. 95% of the gene expression assays were done in a Clinical Laboratory Improvements Amendments certified laboratory facility. All genes were assessed for their ability to predict metastatic progression by receiver-operating-curve area-under-the-curve analyses. Multivariate analyses were done for the primary endpoint of metastatic progression, with variables including Gleason score, preoperative prostate-specific antigen concentration, seminal vesicle invasion, surgical margin status, extracapsular extension, lymph node invasion, and expression of the highest ranked gene. Findings: 1008 patients were included in the study: 545 in the discovery cohort and 463 in the validation cohorts. The long non-coding RNA SChLAP1 was identified as the highest-ranked overexpressed gene in cancers with metastatic progression. Validation in three independent cohorts confirmed the prognostic value of SChLAP1 for metastatic progression. On multivariate modelling, SChLAP1 expression (high vs low) independently predicted metastasis within 10 years (odds ratio [OR] 2.;45, 95% CI 1.;70-3.;53; p<0.;0001). The only other variable that independently predicted metastasis within 10 years was Gleason score (8-10 vs 5-7; OR 2.;14, 95% CI 1.;77-2.;58; p<0.;0001). Interpretation: We identified and validated high SChLAP1 expression as significantly prognostic for metastatic disease progression of prostate cancer. Our findings suggest that further development of SChLAP1 as a potential biomarker, for treatment intensification in aggressive prostate cancer, warrants future study.

AB - Background: Improved clinical predictors for disease progression are needed for localised prostate cancer, since only a subset of patients develop recurrent or refractory disease after first-line treatment. Therefore, we undertook an unbiased analysis to identify RNA biomarkers associated with metastatic progression after prostatectomy. Methods: Prostate cancer samples from patients treated with radical prostatectomy at three academic institutions were analysed for gene expression by a high-density Affymetrix GeneChip platform, encompassing more than 1 million genomic loci. In a discovery cohort, all protein-coding genes and known long non-coding RNAs were ranked by fold change in expression between tumours that subsequently metastasised versus those that did not. The top ranked gene was then validated for its prognostic value for metastatic progression in three additional independent cohorts. 95% of the gene expression assays were done in a Clinical Laboratory Improvements Amendments certified laboratory facility. All genes were assessed for their ability to predict metastatic progression by receiver-operating-curve area-under-the-curve analyses. Multivariate analyses were done for the primary endpoint of metastatic progression, with variables including Gleason score, preoperative prostate-specific antigen concentration, seminal vesicle invasion, surgical margin status, extracapsular extension, lymph node invasion, and expression of the highest ranked gene. Findings: 1008 patients were included in the study: 545 in the discovery cohort and 463 in the validation cohorts. The long non-coding RNA SChLAP1 was identified as the highest-ranked overexpressed gene in cancers with metastatic progression. Validation in three independent cohorts confirmed the prognostic value of SChLAP1 for metastatic progression. On multivariate modelling, SChLAP1 expression (high vs low) independently predicted metastasis within 10 years (odds ratio [OR] 2.;45, 95% CI 1.;70-3.;53; p<0.;0001). The only other variable that independently predicted metastasis within 10 years was Gleason score (8-10 vs 5-7; OR 2.;14, 95% CI 1.;77-2.;58; p<0.;0001). Interpretation: We identified and validated high SChLAP1 expression as significantly prognostic for metastatic disease progression of prostate cancer. Our findings suggest that further development of SChLAP1 as a potential biomarker, for treatment intensification in aggressive prostate cancer, warrants future study.

UR - http://www.scopus.com/inward/record.url?scp=84925231126&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84925231126&partnerID=8YFLogxK

U2 - 10.1016/S1470-2045(14)71113-1

DO - 10.1016/S1470-2045(14)71113-1

M3 - Article

VL - 15

SP - 1469

EP - 1480

JO - The Lancet Oncology

JF - The Lancet Oncology

SN - 1470-2045

IS - 13

ER -