Identification of an 11-Autophagy-Related-Gene Signature as Promising Prognostic Biomarker for Bladder Cancer Patients

Abstract

Background: Survival rates for highly invasive bladder cancer (BC) patients have been very low, with a 5-year survival rate of 6%. Accurate prediction of tumor progression and survival is important for diagnosis and therapeutic decisions for BC patients. Our study aims to develop an autophagy-related-gene (ARG) signature that helps to predict the survival of BC patients. Methods: RNA-seq data of 403 BC patients were retrieved from The Cancer Genome Atlas Urothelial Bladder Carcinoma (TCGA-BLCA) database. Univariate Cox regression analysis was performed to identify overall survival (OS)-related ARGs. The Lasso Cox regression model was applied to establish an ARG signature in the TCGA training cohort (N = 203). The performance of the 11-gene ARG signature was further evaluated in a training cohort and an independent validation cohort (N = 200) using Kaplan-Meier OS curve analysis, receiver operating characteristic (ROC) analysis, as well as univariate and multivariate Cox regression analysis. Results: Our study identified an 11-gene ARG signature that is significantly associated with OS, including APOL1, ATG4B, BAG1, CASP3, DRAM1, ITGA3, KLHL24, P4HB, PRKCD, ULK2, and WDR45. The ARGs-derived high-risk bladder cancer patients exhibited significantly poor OS in both training and validation cohorts. The prognostic model showed good predictive efficacy, with the area under the ROC curve (AUCs) for 1-year, 3-year, and 5-year overall survival of 0.702 (0.695), 0.744 (0.640), and 0.794 (0.658) in the training and validation cohorts, respectively. A prognostic nomogram, which included the ARGs-derived risk factor, age and stage for eventual clinical translation, was established. Conclusion: We identified a novel ARG signature for risk-stratification and robust prediction of overall survival for BC patients.

Prediction of immune infiltration and prognosis for patients with urothelial bladder cancer based on the DNA damage repair-related genes signature

“…Zhou et al also established a 11-gene signature based on autophagy for prognosis prediction in BLCA, which exhibited an even better efficacy in survival prediction. Nevertheless, a same defect still existed in this study that the inner mechanism explanation lacked [ 40 ]. More recently, ferroptosis has been identified as a novel iron-dependent cell death regulatory mechanism and has also been applied as a prognostic modality in BLCA.…”

An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer

“…F. Tang et al developed a seven-gene signature in order to predict the BCa patient prognosis, succeeding AUC values of 0.711/0.714/0.711 and 0.608/0.680/0.638 for the years one, three, and five in the training and test sets, respectively [ 130 ]. Additionally, C. Zhou suggested an 11-autophagy-related gene signature to predict the prognosis of BCa patients, showing a predictive efficiency for 1/3/5-year of 0.702/0.744/0.794 and 0.695/0.640/0.658 in the training and validation cohorts, respectively [ 131 ]. Moreover, F. Xu developed a six-gene prognostic signature for BCa, showing AUC values for cancer-specific survival of 3/5 years of 0.96/0.967, 0.744/0.748, and 0.576/0.606 for the training set (GSE32894) and the test sets (GSE13507 and TCGA-BCa), respectively [ 132 ].…”

Identification and Validation of Autophagy-Related Genes in Necrotizing Enterocolitis

“…Thus, as an autophagy-related gene, HIF-1a plays a vital role in the progression of NEC. ITGA3 belongs to the integrin family of cell surface receptors and is related to autophagy in various cancers, such as head and neck squamous cell carcinoma, bladder cancer, osteosarcoma, and glioblastoma ( 32 – 35 ).…”