A novel gene signature combination improves the prediction of overall survival in urinary bladder cancer

Abstract

Objectives: Bladder carcinoma is a clinical heterogeneous disease, which is with significant variability of the prognosis and high risk of death. This revealed prominently the need to identify high-efficiency cancer characteristics to predict clinical prognosis.Methods: Gene expression profiles of 93 bladder tumor patients from Gene Expression Omnibus data sets was performed in this study, along with 408 bladder tumor patients retrieved from The Cancer Genome Atlas database. The relationship of gene signature and overall survival was analyzed in the training cohort (n = 46). The validation for that was performed in an internal validation cohort (n = 47) and an external validation cohort (n = 408).Results: Four genes (TMPRSS11E, SCEL, KRT78, TMEM185A) were identified by univariable and multivariable Cox regression analysis. According to a risk score on the bases on the four-gene signature, we grouped these patients in high-risk group and low-risk group with significantly different overall survival in the training series and successfully validated it in both the internal and external validation cohorts. Subsequent studies demonstrated that the four-gene expression risk score was independent of radical cystectomy stage, chemotherapy and lymph node status. Higher rates of FAT4 mutation and MACF1 mutation in bladder tumors with high risk score were found compared with tumors with low risk score. Gene set enrichment analysis revealed high-risk score was associated with some tumor progression and recurrence associated pathways.Conclusions: This four-gene risk score might have potential clinical implications in the selection of high-risk urinary bladder cancer patients for aggressive therapy. The selected four genes might become potential therapeutic targets and diagnostic markers for urinary bladder cancer.

Development of prognostic signature based on immune-related genes in muscle-invasive bladder cancer: bioinformatics analysis of TCGA database

“…Although several previous studies are focusing on distinct survival outcomes for differentially expressed genes [ 23 – 25 ], no genome-wide profiling studies of MIBC have been conducted. Until recently, the treatment of bladder cancer has made slow progress.…”

A Drosophila platform identifies a novel, personalized therapy for a patient with adenoid cystic carcinoma

“…FAT1, FAT3, and FAT4 are atypical cadherins and key regulators of cancer-relevant cellular processes including planar cell polarity and MST/HIPPO signaling, which regulates organ size. They are associated as tumor suppressors in a variety of tumors including ovarian, medullary thyroid, gastric, cervical, colorectal, bladder, and squamous cell carcinomas, as well as ACC ( Ho et al., 2013 ; Gao et al., 2014 ; Chen et al., 2019 ; Huang et al., 2019 ; Skuja et al., 2019 ; Malgundkar et al., 2020 ; Melis et al., 2020 ; Qu et al., 2020 ; Wang et al., 2020 ). Reducing these atypical cadherins by approximately 50% expression was therefore considered potentially impactful to our drug screening platform.…”

Development and validation of a molecular prognostic index of bladder cancer based on immunogenomic landscape analysis

“…As one of the important tumors that could benefit from immunotherapy, it is of great importance to explore the specific mechanism involved in immunotherapy of BCa [11,12]. Although there have been several prognostic models predicting the survival outcome of BCa demonstrated by previous study, few studies focus on the immune-related genes related to survival [13,14]. This study comprehensively utilized multiple online databases to identify prognostic differentially expressed IRGs that played a vital role in survival outcome in BCa patients and explored the associated mechanism.…”