A prognostic model for bladder cancer based on cytoskeleton-related genes

Abstract

A typical cancerous growth in the urinary tract, bladder cancer (BLCA) has a dismal survival rate and a poor chance of being cured. The main cause of tumor death is tumor metastasis, cell migration is crucial in tumor metastasis, and cell-directed movement requires the involvement of the cytoskeleton, so it is said that the cytoskeleton is tightly related to tumor invasion and metastasis. Nevertheless, the expression of genes associated with the cytoskeleton and their prognostic significance in BLCA remain unknown. Differential expression of 546 genes involved in the cytoskeleton was analyzed in BLCA versus normal bladder tissues. According to the outcomes of this analysis of differentially expressed genes (DEGs), all BLCA cases doing NMF clustering analysis could be classified into two molecular subtypes and were subjected to survival analysis. Using the TCGA dataset to screen out genes with drastically differing expression levels, a cytoskeleton-associated gene prediction model for bladder cancer was constructed, and 11 genes were assigned risk formulae using the least absolute shrinkage and selection operator (LASSO) Cox regression approach. We divided all TCGA cohort patients with BLCA into low-risk groups and high-risk groups categories based on the average risk score in the middle, then analyzed survival data and ROC curves separately for each risk category. An external validation dataset (GSM340668) was used to verify the accuracy of the model. Columnar line plots were created to predict the prognostic outcome of bladder cancer cases. Significant enrichment pathways for cytoskeleton-associated genes in bladder cancer samples were explored by GSEA enrichment analysis. In addition, immune infiltration studies were conducted to help us better understand and observe the degree of bladder cancer immune cell infiltration. An independent prognostic analysis of risk score (RS) was done and proven to be a significant predictor of outcome for bladder cancer. Following this, we looked at the connection between risk score, clinical characteristics, and immune cells, and found that they are all interconnected. In conclusion, cytoskeleton-related genes have an important predictive value for bladder cancer, and the prognostic model we constructed may enable personalized treatment of bladder cancer.