Construction of a prediction model for prognosis of bladder cancer based on the expression of ion channel-related genes.
10.3724/zdxbyxb-2023-0051
- Author:
Dianfeng ZHANG
1
;
Guicao YIN
2
;
Shengqi ZHENG
2
;
Qiu CHEN
2
;
Yifan LI
3
Author Information
1. Department of Urology, Xuchang Central Hospital of Henan Province, Xuchang 461000, Henan Province, China. dianfeng720@163.com.
2. Department of Urology, the Affiliated Hospital of Yangzhou University, Yangzhou 225000, Jiangsu Province, China.
3. Department of Urology, the Affiliated Hospital of Yangzhou University, Yangzhou 225000, Jiangsu Province, China. yfli@bjmu.edu.cn.
- Publication Type:Journal Article
- Keywords:
Bladder cancer;
Gene;
Ion channel;
Prognosis;
Risk assessment
- MeSH:
Humans;
Female;
Prognosis;
Urinary Bladder Neoplasms/genetics*;
Urinary Bladder;
Ion Channels;
Breast Neoplasms
- From:
Journal of Zhejiang University. Medical sciences
2023;52(4):499-509
- CountryChina
- Language:English
-
Abstract:
OBJECTIVES:To construct a prediction model for the prognosis of bladder cancer patients based on the expression of ion channel-related genes (ICRGs).
METHODS:ICRGs were obtained from the existing researches. The clinical information and the expression of ICRGs 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 qRT-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 risk score. Immune cell infiltration was compared between the two groups. Kaplan-Meier survival curve and receiver operating characteristic (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.
RESULTS:By comparing the expression levels of ICRGs in bladder cancer tissues and normal bladder tissues, 73 differentially expressed ICRGs were dentified, 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 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 ICRGs-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 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.
CONCLUSIONS:The study shows the potential value of ICRGs in the prognostic risk assessment of bladder cancer patients. The constructed prognostic nomogram based on ICRGs risk score has high accuracy in predicting the prognosis of bladder cancer patients.
