Interleukin-6 as a Pan-Cancer Prognostic Inflammatory Biomarker: A Population-Based Study and Comprehensive Bioinformatics Analysis

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Abstract

Purpose: Interleukin-6 (IL-6) is a central factor linking inflammation to cancer. This study aimed to provide a comprehensive assessment of the prognostic value of IL-6 and its immunotherapeutic features using a population-based pan-cancer analysis and comprehensive bioinformatic analysis. Patients and Methods: In the cohort study, 540 patients were included to explore the prognostic value of serum IL-6 levels in cancer. The differential expression of IL-6 and its association with survival and immune cell infiltration were investigated using the TCGA database. The SangerBox database was used to analyze the correlation between IL-6 expression and immune checkpoint (ICP), tumor mutation burden (TMB), and microsatellite instability (MSI) in cancer. Genomic changes in the IL-6 levels were studied using the c-BioPortal database. The IL-6 co-expression network was analyzed using the LinkedOmics database. Results: Serum IL-6 is an independent prognostic factor for cancer, especially gastrointestinal cancers. Compared to other serum inflammatory markers, serum IL-6 is an optimal biomarker for cancer prognosis. A comprehensive bioinformatics analysis showed higher IL-6 expression in human cancers than in the paired normal tissues. The IL-6 expression is closely associated with prognosis, ICP, TMB, and MSI. In addition, it is also strongly correlated with tumor-infiltrating cells. IL-6 levels are significantly associated with the prognosis of stomach adenocarcinoma (STAD). The IL-6 co-expression network in STAD is mainly involved in regulating inflammatory pathways and cell communication. Conclusion: IL-6 is a potential prognostic and immune biomarker of cancer. Compared to other clinical inflammatory biomarkers, IL-6 demonstrates superior prognostic efficacy.

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Xie, H., Wei, L., Ruan, G., Zhang, H., & Shi, H. (2025). Interleukin-6 as a Pan-Cancer Prognostic Inflammatory Biomarker: A Population-Based Study and Comprehensive Bioinformatics Analysis. Journal of Inflammation Research , 18, 573–587. https://doi.org/10.2147/JIR.S484962

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