Using Necroptosis-Associated Genes To Predict The Immune Microenvironment And Prognosis Of Bladder Urothelial Carcinoma

Author:

Liu Yi-jiang1,Yang Cui1,Li Yan-ling1,Xu Jia-jia1,Chen Min-wei1,Liu Shi-xiao1,Wang Xue-qi1,Zheng Xiang-hui2,Luo Ping1,Zhang Zheng-hao1,Li Run-jing1,Li Rui1,Shan Zhong-gui1

Affiliation:

1. The First Affiliated Hospital of Xiamen University, Xiamen University

2. The Third Clinical Medical College,Fujian Medical University

Abstract

Abstract PURPOSE Bladder urothelial carcinoma (BLCA), the most common urinary tract malignancy, has a high recurrence rate and poor survival at late stages. Necroptosis, a form of programmed cell death, is involved in cancer development and progression, but its function in BLCA prognosis remains unclear. This study sought to investigate the role of necroptosis in the development and prognosis of BLCA. METHODS Clinical information and RNA expression matrix data were obtained from the databases. Survival analysis was performed to obtain survival- and necroptosis-related genes and identify any that overlapped. Consensus clustering analysis was used to create different subgroups by combining the overlapping gene expression matrix and clinical information. The tumor immune microenvironment and immune status of the different subgroups were determined using ESTIMATE, MCPcounter, and ssGSEA analysis. We performed differential analysis on the gene expression matrix of molecular subpopulations to find and screen out differentially expressed genes (DEGs). GO, KEGG, GSVA, and GSEA analyses were used to elucidate the underlying mechanisms of the DEGs. Lasso Cox regression analysis was used to build a prognostic risk model and perform a pan-cancer analysis of the screened genes. The results were used to define potential roles for these genes in other cancers and assess the efficacy of the risk model. RESULTS Cluster analysis identified two subgroups, C1 and C2, with significantly different survival rates. ESTIMATE, MCPcounter, and ssGSEA analyses showed that high immune scores, tumor purity, and immune status were associated with poorer prognoses. GO and KEGG functional enrichment analyses indicated that DEGs were mainly focused on tumor proliferation, invasion, and immunity and GSEA analysis suggested that necroptosis may affect Toll-like receptor signaling pathways, MAPK cascade regulation of leukocyte trafficking, and cytokine-cytokine receptor interaction pathways. Lasso Cox regression analysis was used to model the prognostic risk while screening for representative necroptosis-associated genes, ANXA1, ATAD3A, and TRPC6, with high potential for survival prediction in BLCA patients. The pan-cancer analysis indicated that the three representative genes were also differentially expressed in other cancer types. CONCLUSION Expression of necroptosis-related genes such as ANXA1, ATAD3A, and TRPC6 correlate with the immune microenvironment of BLCA patients and have the potential for use in disease prognostics.

Publisher

Research Square Platform LLC

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