Novel RB1-Loss Transcriptomic Signature Is Associated with Poor Clinical Outcomes across Cancer Types

Clin Cancer Res. 2019 Jul 15;25(14):4290-4299. doi: 10.1158/1078-0432.CCR-19-0404. Epub 2019 Apr 22.


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 = 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 = 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 = 0.008) and gene body hypomethylation (P = 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 = 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 = 0.03) and of shorter overall survival in mCRPC (P = 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.See related commentary by Choudhury and Beltran, p. 4199.

MeSH terms

  • Biomarkers, Tumor
  • Disease Progression
  • Humans
  • Male
  • Neoplasms*
  • Prognosis
  • Transcriptome*


  • Biomarkers, Tumor