Construction of a prediction model for prognosis of bladder cancer based on the expression of ion channel-related genes.

Abstract

To construct a prediction model for the prognosis of bladder cancer patients based on the expression of ion channel-related genes (ICRG). The clinical information and the expression of ICRG mRNA in breast cancer patients were obtained from the Cancer Genome Atlas database. Cox regression analysis, minimum absolute shrinkage and selection operator regression analysis were used to screen breast cancer prognosis related genes, which were verified by immunohistochemistry and real-time fluorescence quantitative PCR. The risk scoring equation for predicting the prognosis of patients with bladder cancer was constructed, and the patients were divided into high-risk group and low-risk group according to the median of risk score. The immune cell infiltration abundance was compared between the two groups. Kaplan-Meier survival curve and receiver operating characteristic curve (ROC curve) were used to evaluate the accuracy and clinical application value of the risk scoring equation. The factors related to the prognosis of bladder cancer patients were analyzed by univariate and multivariate Cox regression, and a nomogram for predicting the prognosis of bladder cancer patients was constructed. By comparing the expression levels of ICRG in bladder cancer tissues and normal bladder tissues, 73 differentially expressed ICRGs were screened out, of which 11 were related to the prognosis of bladder cancer patients. Kaplan-Meier survival curve suggested that the risk score based on these 11 genes was negatively correlated with the prognosis of patients. The area under the ROC curve (AUC) of the risk score for predicting the prognosis of patients at 1, 3 and 5 year was 0.634, 0.665 and 0.712, respectively. Stratified analysis showed that the ICRG-based risk score performed well in predicting the prognosis of patients with American Joint Committee on Cancer (AJCC) stage Ⅲ-Ⅳ bladder cancer (P<0.05), while it had a poor value in predicting the prognosis of patients with AJCC stage Ⅰ-Ⅱ (P>0.05). There were significant differences in the infiltration levels of plasma cells, activated natural killer cells, resting mast cells and M2 macrophages between the high-risk group and the low-risk group. Cox regression analysis showed that risk score, smoking, age and AJCC stage were independently associated with the prognosis of patients with bladder cancer (P<0.05). The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1-, 3-and 5-year overall survival rate of bladder cancer patients. The study shows the potential value of ICRG in the prognostic risk assessment of bladder cancer patients. The constructed prognostic nomogram based on ICRG risk score has high accuracy in predicting the prognosis of bladder cancer patients.