A Novel 3 chemotactic activity-related gene signature for Predicting prognosis of bladder Cancer

Abstract

Abstract Background Bladder cancer is one of the most common malignant tumors of the urinary system. Both cancer and stromal cells, including bladder cancer, express chemokines and their corresponding receptors. Their altered expression controls angiogenesis, cancer cell proliferation, metastasis, and immune cell recruitment and activation in a variety of malignancies. Therefore, it is necessary to investigate the association between chemotactic activity-related genes and the prognosis of bladder cancer patients. Methods Download the The Cancer Genome Atlas (TCGA) database's expression profiles for chemotactic activity-related genes and clinical information. Create a prognostic model by using the univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) regression model. Additionally, the validation cohort for the GSE13507 and GSE48276 datasets is used to verify the signature's predictive power. Results We identified 3 chemotactic activity-related genes related to BLCA patients’ overall survival (OS) and established a prognostic model based on their expression. According on the findings of the LASSO regression analysis, patients were split into high-risk and low-risk groups during the study. The survival time of the low-risk group was significantly longer than that of the high-risk group (P < 0.001). The riskscore and clinical prognostic indicators were combined to create a nomogram, which demonstrated strong predictive capacity in the training and validation groups. Conclusions With the use of CXCL12, ACKR3, and CXCL10, we have created a chemotactic activity-related predictive model in this study that may aid doctors in making conclusions regarding BLCA patients and provide useful information for tailored management.