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

Abstract

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.

Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma

“…Autophagy-, EMT-, and immune-related gene signatures have been extensively reported in cancer [9,10,28]. However, few studies have analyzed CSC expression profiles to construct a risk prediction model.…”

“…Several previous studies have attempted to build risk prediction models by assessing critical biological processes associated with cancer, such as autophagy, epithelial-mesenchymal transition (EMT), and DNA damage-repair pathway [8][9][10]. Similarly, cancer stem cells (CSCs), a small population of cancer cells (account only 0.2%-0.8% in PDAC) with self-renewal and multilineage differentiation capacities, have become promising therapeutic targets in PDAC treatment.…”

Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma

“…Autophagy-, EMT-, and immune-related gene signatures of cancers have been extensively reported [9,10,28]. However, few studies have analysed CSC expression pro les to construct a risk prediction model.…”

“…Several previous studies have attempted to build risk prediction models by assessing critical biological processes associated with cancer, such as autophagy, epithelial-mesenchymal transition (EMT), and the DNA damage-repair pathway [8][9][10]. Similarly, cancer stem cells (CSCs), a small population of cancer cells (accounting for only 0.2%-0.8% of PDAC cells) with self-renewal and multilineage differentiation capacities, have become promising therapeutic targets in PDAC treatment.…”

A stemness-related seven-gene signature for predicting prognosis and treatment response in muscle invasive bladder cancer

“…Abudurexiti et almade a meta-analysis of published gene signature studies in BC patients and collected 274 candidate genes to develop a 12-gene signature to predict OS in MIBC patients[16]. Cao et al developed a seven-gene signature related with epithelial-mesenchymal transition (EMT) process, which could stratify patients into different risk groups with distinct prognosis[17]. Jiang et al analyzed genes associated with immune cells infiltration in MIBC and developed a nine-gene signature which could distinguish patients with different prognoses and immunotherapeutic response[18].…”