Prognostic Implications of Immune-Related Gene Pairs Signatures in Bladder Cancer

Abstract

Compelling evidence indicates that immune function is correlated with the prognosis of bladder cancer (BC). Here, we aimed to develop a clinically translatable immune-related gene pairs (IRGPs) prognostic signature to estimate the overall survival (OS) of bladder cancer. From the 251 prognostic-related IRGPs, 37 prognostic-related IRGPs were identified using LASSO regression. We identified IRGPs with the potential to be prognostic markers. The established risk scores divided BC patients into high and low risk score groups, and the survival analysis showed that risk score was related to OS in the TCGA-training set ( p < 0.001 ; HR = 7.5 [5.3, 10]). ROC curve analysis showed that the AUC for the 1-year, 3-year, and 5-year follow-up was 0.820, 0.883, and 0.879, respectively. The model was verified in the TCGA-testing set and external dataset GSE13507. Multivariate analysis showed that risk score was an independent prognostic predictor in patients with BC. In addition, significant differences were found in gene mutations, copy number variations, and gene expression levels in patients with BC between the high and low risk score groups. Gene set enrichment analysis showed that, in the high-risk score group, multiple immune-related pathways were inhibited, and multiple mesenchymal phenotype-related pathways were activated. Immune infiltration analysis revealed that immune cells associated with poor prognosis of BC were upregulated in the high-risk score group, whereas immune cells associated with a better prognosis of BC were downregulated in the high-risk score group. Other immunoregulatory genes were also differentially expressed between high and low risk score groups. A 37 IRGPs-based risk score signature is presented in this study. This signature can efficiently classify BC patients into high and low risk score groups. This signature can be exploited to select high-risk BC patients for more targeted treatment.

Construction of a prognostic assessment model for colon cancer patients based on immune-related genes and exploration of related immune characteristics

“…The increasing number of research reveals that immune-related genes can be used to diagnose cancer stage and prognosis. Immune-related gene pairs have been proved to become effective biomarkers for predicting the prognosis of gastric, breast and bladder cancer patients, providing assistance in identifying immunotherapy response of patients (Mu et al, 2021;Xiong et al, 2021;Zhao et al, 2021). Although several prognostic markers of colon cancer based on immune-related genes have been established, there is a lack of a more comprehensive indicator to predict patient survival and immunotherapy response.…”

Molecular genetic and clinical characteristic analysis of primary signet ring cell carcinoma of urinary bladder identified by a novel OR2L5 mutation

“…Primary signet ring cell carcinoma (SRCC) is a rare bladder adenocarcinoma. Histologically, SRCC is classified under mucinous adenocarcinoma and represents 0.24%–2% of primary epithelial urinary bladder cancers 1,2 . According to the World Health Organization, these are tumors in which more than 50% of the tumor's pathophysiology is composed of mucin located extracellularly and malignant epithelial cells that form individual cells, clusters, or layers 3,4 .…”

“…Histologically, SRCC is classified under mucinous adenocarcinoma and represents 0.24%–2% of primary epithelial urinary bladder cancers. 1 , 2 According to the World Health Organization, these are tumors in which more than 50% of the tumor's pathophysiology is composed of mucin located extracellularly and malignant epithelial cells that form individual cells, clusters, or layers. 3 , 4 Mucosal epithelial cells secrete mucin, which is a high molecular weight glycoprotein consisting of oligosaccharides linked to a core protein as a lubricant to protect themselves from infections and irritants.…”

A Novel Immune-Related Prognostic Model Based on Chemosensitivity Predicts the Outcome of Ovarian Cancer

“…Analyzing the matching values of the gene expression values has higher accuracy than those constructed with a single marker since eliminating the inherent biological heterogeneity of the tumor and the technical bias caused by the sequencing platform (14). In this study, we constructed a gene pairs prognostic model associated with immunity and chemosensitivity, which was evaluated by survival rate, immune checkpoints, and the response to chemo agents.…”