Prognostic value and underlying mechanism of autophagy-related genes in bladder cancer

Abstract

Bladder cancer (BLCA) is the most common malignancy whose early diagnosis can ensure a better prognosis. However, the predictive accuracy of commonly used predictors, including patients’ general condition, histological grade, and pathological stage, is insufficient to identify the patients who need invasive treatment. Autophagy is regarded as a vital factor in maintaining mitochondrial function and energy homeostasis in cancer cells. Whether autophagy-related genes (ARGs) can predict the prognosis of BLCA patients deserves to be investigated. Based on BLCA data retrieved from the Cancer Genome Atlas and ARGs list obtained from the Human Autophagy Database website, we identified prognosis-related differentially expressed ARGs (PDEARGs) through Wilcox text and constructed a PDEARGs-based prognostic model through multivariate Cox regression analysis. The predictive accuracy, independent forecasting capability, and the correlation between present model and clinical variables or tumor microenvironment were evaluated through R software. Enrichment analysis of PDEARGs was performed to explore the underlying mechanism, and a systematic prognostic signature with nomogram was constructed by integrating clinical variables and the aforementioned PDEARGs-based model. We found that the risk score generated by PDEARGs-based model could effectively reflect deteriorated clinical variables and tumor-promoting microenvironment. Additionally, several immune-related gene ontology terms were significantly enriched by PDEARGs, which might provide insights for present model and propose potential therapeutic targets for BLCA patients. Finally, a systematic prognostic signature with promoted clinical utility and predictive accuracy was constructed to assist clinician decision. PDEARGs are valuable prognostic predictors and potential therapeutic targets for BLCA patients.

Establishment of a risk score model for bladder urothelial carcinoma based on energy metabolism‐related genes and their relationships with immune infiltration

“…Previous researchers have constructed a prediction model for BLCA prognosis based on the TCGA-BLCA dataset. For example, Peng et al [35] developed a prognostic model based on five autophagy-related genes, and its AUC value was 0.724. Zhang et al [36] constructed a prognostic model based on five pyroptosisrelated genes, and the AUCs of the 5-gene model for 1-, 3-, and 5-year OS were 0.667, 0.632, and 0.637, respectively.…”

“…For example, Peng et al . [ 35 ] developed a prognostic model based on five autophagy‐related genes, and its AUC value was 0.724. Zhang et al .…”

Functional investigation and two-sample Mendelian randomization study of bladder cancer-related genes: focus on gender differences

“…As for the causes of gender differences in bladder cancer incidence, the current study indicated that the higher incidence among men may be due to their more frequent exposure to toxic substances, smoking, long-term drinking, and other reasons, but there are few studies on genetic differences in males and females. Currently, there are several reports on the role of immune cell in ltration-related genes [19], pyroptosis-related genes [20], and autophagy-related genes [21], in the development of bladder cancer.…”