Identification of immune-related cervical cancer prognostic biomarkers and construction of prognostic model based on tumor microenvironment

基于肿瘤微环境的宫颈癌免疫相关预后生物标志物鉴定及预后模型构建

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Abstract

OBJECTIVE: Tumor microenvironment (TME) and the expression of immune-related genes (IRGs) are closely related to the development of cervical cancer (CC). This study aims to explore some IRGs as prognostic biomarkers for CC patients based on TME. METHODS: The abundance of tumor-infiltrating immune cells in CC samples was assessed using single-sample gene set enrichment analysis (ssGSEA). Thus, two immune-related groups are generated according to the immune status. The differentially expressed genes were discovered based on the grouping. Then, univariate Cox and LASSO regression analyses were performed using the R package glmnet. Five IRG prognostic signatures (HLA-DMA, DMBT1, CXCR6, CX3CL1, and SEMA3A) were established after that. The protein expression of some genes was verified by immunohistochemistry (IHC). RESULTS: The signature of the five IRGs was identified to be an independent prognostic indicator for the overall survival in CC patients. A prognostic risk model was also constructed. CC patients were classified into high- and low-risk groups based on the median risk score. The survival time of patients in the high-risk group was shorter than that of those in the low-risk group. The five genes remarkably related to prognosis were screened, among which HLA-DMA, CXCR6, and CX3CL1 were the protective factors, whereas DMBT1 and SEMA3A were the risk factors. GO and KEGG enrichment analyses showed that the biomarkers of the five IRGs were enriched in the receptor-ligand interaction and chemokine signaling pathway. Moreover, CXCR6 expression was significantly correlated with immune cell infiltration among the five hub genes. IHC results demonstrated that the expression of SEMA3A protein level was increased, and CX3CL1 protein level was decreased in cervical cancer tissue. CONCLUSION: Immune-related prognostic biomarkers in CC include HLA-DMA, DMBT1, CXCR6, CX3CL1, and SEMA3A. The risk score for the five genes is more accurate than that for other clinical risk factors in predicting prognosis at 3 and 5 years. The higher the risk score is, the worse the prognosis of CC patients is. Five prognostic biomarkers may participate in regulating TME through chemokine-mediated signaling pathways and receptor-ligand interactions. These findings provide new insights into the immunotherapy of CC.

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