Novel Rb1-loss transcriptomic signature is associated with poor clinical outcomes across cancer types

William S. Chen, Mohammed Alshalalfa, Shuang G. Zhao, Yang Liu, Brandon A. Mahal, David A. Quigley, Ting Wei, Elai Davicioni, Timothy R. Rebbeck, Philip W. Kantoff, Christopher A. Maher, Karen E. Knudsen, Eric J. Small, Paul L. Nguyen, Felix Y. Feng

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Purpose: Rb-pathway disruption is of great clinical interest, as it has been shown to predict outcomes in multiple cancers. We sought to develop a transcriptomic signature for detecting biallelic RB1 loss (RBS) that could be used to assess the clinical implications of RB1 loss on a pan-cancer scale. Experimental Design: We utilized data from the Cancer Cell Line Encyclopedia (N ¼ 995) to develop the first pan-cancer transcriptomic signature for predicting biallelic RB1 loss (RBS). Model accuracy was validated using The Cancer Genome Atlas (TCGA) Pan-Cancer dataset (N ¼ 11,007). RBS was then used to assess the clinical relevance of biallelic RB1 loss in TCGA Pan-Cancer and in an additional metastatic castration-resistant prostate cancer (mCRPC) cohort. Results: RBS outperformed the leading existing signature for detecting RB1 biallelic loss across all cancer types in TCGA Pan-Cancer (AUC, 0.89 vs. 0.66). High RBS (RB1 biallelic loss) was associated with promoter hypermethylation (P ¼ 0.008) and gene body hypomethylation (P ¼ 0.002), suggesting RBS could detect epigenetic gene silencing. TCGA Pan-Cancer clinical analyses revealed that high RBS was associated with short progression-free (P < 0.00001), overall (P ¼ 0.0004), and disease-specific (P < 0.00001) survival. On multivariable analyses, high RBS was predictive of shorter progression-free survival in TCGA Pan-Cancer (P ¼ 0.03) and of shorter overall survival in mCRPC (P ¼ 0.004) independently of the number of DNA alterations in RB1. Conclusions: Our study provides the first validated tool to assess RB1 biallelic loss across cancer types based on gene expression. RBS can be useful for analyzing datasets with or without DNA-sequencing results to investigate the emerging prognostic and treatment implications of Rb-pathway disruption.

Original languageEnglish
Pages (from-to)4290-4299
Number of pages10
JournalClinical Cancer Research
Volume25
Issue number14
DOIs
StatePublished - 2019

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