Development and External Validation of a Novel 12-Gene Signature for Prediction of Overall Survival in Muscle-Invasive Bladder Cancer.

Purpose: We aimed to develop and validate a novel gene signature from published data and improve the prediction of survival in muscle-invasive bladder cancer (MIBC). Methods: We searched the published gene signatures associated with the overall survival (OS) of MIBC and compiled all 274 genes to develop a novel gene signature. RNAseq data of TOGA (the Cancer Genome Atlas) bladder cohort were downloaded. All genes were included in a univariate Cox hazard ratio model. We then used a reduced multivariate Cox regression model, which included only genes achieving P < 0.05 in the univariate model. A total of 172 patients at Fudan University Shanghai Cancer Center (FUSCC) and 61 patients from GEO datasets were used as an external validation set. Results: A total of 327 patients in the TOGA cohort were enrolled. We identified 274 genes from eight published papers on the OS of MIBC. Using the TCGA database, we identified 12 genes that correlated with OS (P < 0.05 in both univariate and multivariate analyses). By integrating these genes with the RT-qPCR data in our validation dataset and GEO datasets, we confirmed that the power for predicting OS of the 12-gene panel (AUC of 0.741 and 0.727, respectively) was higher than just clinical data (including gender, age, T stage, grade, and N stage) alone in the TCGA and FUSCC cohort (AUC of 0.667 and 0.631, respectively). Additionally, upon combining the clinical data and 12-gene panel together, the AUC increased to 0.768, 0.757, and 0.88 in the TOGA, FUSCC and GSE13507 cohorts, respectively. Conclusions: Applying published gene signatures and TCGA data, we successfully built and externally validated a novel 12-gene signature for the survival of MIBC.