Construction of Bladder Cancer Prognostic Model Based on Mast Cell-related Genes

Abstract

Abstract: Objective Analyzing the relationship between mast cell-related genes and bladder cancer prognosis, screening prognostic key genes, and constructing a bladder cancer prognosis model. Methods Utilizing bulk RNA-seq data from mast cells, differential gene expression analysis was conducted followed by KEGG and GO enrichment analyses as well as Gene Set Enrichment Analysis (GSEA). Mast cell characteristic genes within bladder cancer single cells RNA sequencing were obtained from the literature. After identifying overlapping genes, key prognostic genes were selected using Lasso regression and multivariable COX regression. Based on the risk score, patients were stratified into high-risk and low-risk groups. Finally, through univariable and multivariable COX regression analyses, in conjunction with risk scores and multiple independent prognostic factors, a nomogram was developed to predict the survival rate of bladder cancer patients. Results The prognostic model comprises five genes: WDR45B, EI24, NCOR1, VEGFA, and RNF19A, effectively stratifying patients into high-risk and low-risk groups. Patients in the high-risk group exhibit significantly poorer survival prognosis compared to those in the low-risk group. The model's efficacy was successfully validated using the GSE31864 dataset. Additionally, the forest plot, constructed by integrating T/N staging, risk score, and age, demonstrates excellent predictive performance for bladder cancer patient survival prognosis. Conclusion This study proposes a prognostic risk model based on five mast cell-related genes in bladder cancer patients. It can assist clinicians in evaluating prognosis and providing personalized treatment recommendations for bladder cancer patients.

Key words: mast cells, RNA sequencing, bladder cancer, LPS, prognostic risk model

CLC Number:

R392.3

MI Jun-hao, ZHOU Rong-bin, YANG Ri-rong. Construction of Bladder Cancer Prognostic Model Based on Mast Cell-related Genes[J]. ZHONGHUA YANGSHENG BAOJIAN, 2024, 42(12): 1-5.

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