Construction of a Novel Bladder Cancer Prognostic Risk Assessment Model Through Combined Single-Cell and Bulk RNA Sequencing Analysis
Objective The aim of this study was to develop a prognostic risk assessment model based on differential expression of core cell genes in bladder cancer.By validating its efficacy across multiple datasets,it aims to provide a new tool for clinical applica-tion in bladder cancer patients for prognostic risk assessment.Methods This research utilized a combination of single-cell and Bulk RNA sequencing data.We began by downloading and analyzing bladder cancer single-cell and microarray RNA datasets from the GEO database.Using bioinformatics methods,we identified differential gene expressions in core cells and conducted functional and pathway enrichment analyses.Based on these analyses,key genes significantly related to bladder cancer prognosis were selected using univari-ate and multivariate Cox regression methods,leading to the development of a prognostic risk assessment model.This model was further validated in the TCGA-BLCA dataset.Results Through comprehensive bioinformatics analysis,we identified 223 differentially ex-pressed genes in core cells.These genes play significant roles in the structure and function of the extracellular matrix.The constructed prognostic risk assessment model includes five independent prognostic-related genes(MFAP5,PDE4D,ISG15,ADAMTS1,and FGL2).Validation in the GEO and TCGA-BLCA datasets demonstrated the model's robust predictive power,offering a novel biologi-cal marker tool for the prognosis assessment of bladder cancer patients.Conclusion This study successfully developed a bladder canc-er prognostic risk assessment model based on five key gene markers,demonstrating strong predictive efficacy.The development of this model provides a new tool for biological research and clinical prognostic assessment of bladder cancer,aiding in a better understanding of the disease's biological characteristics and guiding personalized treatment for patients.
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