Construction and External Validation of a Ferroptosis-Related Gene Signature of Predictive Value for the Overall Survival in Bladder Cancer

Abstract

Purpose: To identify whether ferroptosis-related genes play predictive roles in bladder cancer patients and to develop a ferroptosis-related gene signature to predict overall survival outcomes.Materials and Methods: We downloaded the mRNA expression files and clinical data of 256 bladder samples (188 bladder tumour and 68 nontumour samples) from the GEO database and 430 bladder samples (411 bladder tumour and 19 nontumour samples) from the TCGA database. A multigene signature based on prognostic ferroptosis-related genes was constructed by least absolute shrinkage and selection operator Cox regression analysis in the GEO cohort. The TCGA cohort was used to validate the ferroptosis-related gene signature. Next, functional enrichment analysis, including both Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses, was performed to elucidate the mechanism underlying the signature. The ssGSEA scores of 16 immune cells and 13 immune-related pathway activities between the high-risk and low-risk groups were also analysed in our study.Results: Thirty-three (67.3%) ferroptosis-related genes were differentially expressed between bladder tumour samples and nontumour samples in the GEO cohort. The intersection of prognostic ferroptosis-related genes and differentially expressed genes identified four prognostic targets, including ALOX5, FANCD2, HMGCR and FADS2. The least absolute shrinkage and selection operator Cox regression successfully built a 4-gene signature: risk score value = esum (each gene’s normalized expression * each gene’s coefficient). Univariate and multivariate Cox regression analyses were performed in both the GEO and TCGA cohorts to test the independent prognostic value of the 4-gene risk signature. Multivariate Cox regression analysis in the GEO cohort identified age (p < 0.001), grade (p = 0.129) and risk score (p = 0.016) as independent prognostic predictors for overall survival. Multivariate Cox regression analysis in the TCGA cohort also identified age (p = 0.002), stage (p < 0.001) and risk score (p = 0.006) as independent prognostic predictors for overall survival. The type II IFN response was determined to be significantly weakened in the high-risk group in both the GEO and TCGA cohorts.Conclusion: We successfully built a ferroptosis-related gene signature of significant predictive value for bladder cancer. These results suggest a novel research direction for targeted therapy of bladder cancer in the future.

Identification of a Ferroptosis-Related Signature Model Including mRNAs and lncRNAs for Predicting Prognosis and Immune Activity in Hepatocellular Carcinoma

“…Besides, results from both difference in APC co-stimulation and co-inhibition appears contradictory in the immune microenvironment. However, we found the results are somewhat similar to the researches about ferroptosis-related signature in other cancers ( 6 , 89 – 91 ). Though the mechanisms illustrating tumor susceptibility to ferroptosis have been an intense area of research in past decades, the complex relationship between tumor immunity and ferroptosis remains elusive.…”

Identification of a Novel Ferroptosis-Related Gene Prognostic Signature in Bladder Cancer

“…Taken together, these findings strongly implied the great potential roles of ferroptosis in BLCA (Figure 10). Liu et al (20) previously constructed a FRG signature model to predict OS in BLCA. However, only 60 FRGs were included in their study compared to 149 FRGs in our study.…”

“…Liu et al ( 20 ) previously constructed a FRG signature model to predict OS in BLCA. However, only 60 FRGs were included in their study compared to 149 FRGs in our study.…”

Construction of a Novel Signature and Prediction of the Immune Landscape in Soft Tissue Sarcomas Based on N6-Methylandenosine-Related LncRNAs

“…To further evaluate the roles of m6A-related lncRNAs and facilitate the clinical applications of m6A-related lncRNAs as biomarkers and therapeutic targets in STS, we established a novel m6A-related lncRNA-based risk signature. Several studies have constructed risk signatures based on the expression of candidate genes in diverse cancers ( Li et al, 2017 ; Hong et al, 2020 ; Liu et al, 2021a ). The expression and coefficient of candidate genes were employed to calculate the risk scores, and patients with higher risk scores were suggested to have a worse prognosis.…”