Identifying Chemokine System-Related Phenotype to Predict Immune Feature in Pan-Cancer and Prognostic Signature for Lung Adenocarcinoma

识别趋化因子系统相关表型以预测泛癌的免疫特征和肺腺癌的预后特征

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Abstract

BACKGROUND: The chemokine system modulates tumor cell characteristics and influences immune cell function. This research investigates the roles of chemokines and their receptors (CaCRs) across multiple cancers and establishes a reliable CaCRs-based prognostic model for lung adenocarcinoma (LUAD). METHODS: Gene expression data were sourced from the UCSC-Xena platform and the GEO database. The chemokine score was calculated using the ssGSEA algorithm. A CaCRs-based prognostic signature was constructed and validated for LUAD. Expression levels of signature genes in lung cancer tissues were verified. RESULTS: Dysregulation of CaCRs expression was observed in multiple cancers. The chemokine score has shown prognostic features in various tumors. In the LUAD cohort, a seven-gene signature of CaCRs (CCR2, CCR4, CCR6, XCR1, CCL20, CXCL17, and XCL2) was constructed as a prognostic model, identifying a poorer prognosis for high-risk groups. mRNA levels of CCR2, CCR4, CCR6, and XCR1 were significantly reduced in lung cancer tissues compared to adjacent normal tissues, while CCL20 was markedly overexpressed in tumor tissues. Furthermore, CCL20 promoted A549 cell proliferation via the MAPK pathway, with JNK inhibitors effectively blocking CCL20-induced proliferation. CONCLUSION: This study highlights the substantial role of CaCRs in immunity and prognosis. The identified seven-gene signature of CaCRs provides a new prognostic tool for LUAD.

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