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, R. Jeffrey Karnes, John T. Wei, Eric A. Klein, Robert B. Jenkins, Arul M. Chinnaiyan, Felix Y. Feng*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

196 Scopus citations


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
Issue number13
StatePublished - 2014

ASJC Scopus subject areas

  • Oncology


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