Gene

Survival analysis

Statistics

Cancer

Internal medicine

Oncology

Stage (stratigraphy)

Gene expression

Paleontology

Multivariate statistics

Univariate

Metastasis

Gene signature

Bladder cancer

Mathematics

Nomogram

Multivariate analysis

Proportional hazards model

Genetics

Medicine

Epithelial–mesenchymal transition

Biology

Journal of Cellular and Molecular Medicine

The transition from non–muscle‐invasive bladder cancer (NMIBC) to muscle‐invasive bladder cancer (MIBC) is detrimental to bladder cancer (BLCA) patients. Here, we aimed to study the underlying mechanism of the subtype transition. Gene set variation analysis (GSVA) revealed the epithelial‐mesenchymal transition (EMT) signalling pathway with the most positive correlation in this transition. Then, we built a LASSO Cox regression model of an EMT‐related gene signature in BLCA. The patients with high risk scores had significantly worse overall survival (OS) and disease‐free survival (DFS) than those with low risk scores. The EMT‐related gene signature also performed favourably in the accuracy of prognosis and in the subtype survival analysis. Univariate and multivariate Cox regression analyses demonstrated that the EMT‐related gene signature, pathological N stage and age were independent prognostic factors for predicting survival in BLCA patients. Furthermore, the predictive nomogram model was able to effectively predict the outcome of BLCA patients by appropriately stratifying the risk score. In conclusion, we developed a novel EMT‐related gene signature that has tumour‐promoting effects, acts as a negative independent prognostic factor and might facilitate personalized counselling and treatment in BLCA.

An EMT‐related gene signature for the prognosis of human bladder cancer