Comprehensive analysis of the immunological implication and prognostic value of CXCR4 in non-small cell lung cancer

CXCR4 在非小细胞肺癌中的免疫学意义及预后价值的综合分析

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作者:Wei Guo #, Qilin Huai #, Bolun Zhou, Lei Guo, Li Sun, Xuemin Xue, Fengwei Tan, Qi Xue, Shugeng Gao, Jie He

Abstract

CXCR4 (C-X-C chemokine receptor type 4) is the most commonly expressed of all chemokine receptors in malignant tumors. However, studies on CXCR4 in non-small cell lung cancer (NSCLC) tumor immune microenvironment, including those determining its immune efficacy and prognostic potential, are still scarce. Therefore, in this study, we determined the ability of CXCR4 to predict immunotherapy response and prognosis in NSCLC using immunohistochemical staining and RT-PCR, respectively, in two independent cohorts from the National Cancer Center of China. We analyzed transcriptome sequencing data and clinical information from multiple public databases to assess immune cell infiltration in NSCLC and constructed immune risk prognostic signatures based on CXCR4-related immunomodulators. We found that immune cell infiltration is significant differences in NSCLC tissues and is moderately correlated with CXCR4 expression. High CXCR4 expression was significantly associated with poor prognosis in NSCLC patients and a higher response rate to immunotherapy. The ROC curve showed that CXCR4 expression exhibited excellent performance in predicting the efficacy of immunotherapy in NSCLC. We identified 30 CXCR4-related immunomodulators in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) and constructed immune prognostic signatures based on CXCR4-related immunomodulators and CXCR4-related mutant genes. The signature-based prognostic risk score showed good performance in predicting patient prognosis in both LUAD and LUSC; high risk scores were significantly associated with poor prognosis (P < 0.0001) and was established as an independent prognostic factor by multivariate Cox regression. We postulate that CXCR4 is a potential predictive marker of immunotherapy efficacy in NSCLC and should be used in clinical settings. Moreover, the constructed signatures may be valuable in predicting patient prognosis in NSCLC.

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