Exploration and validation of the effects of robust co-expressed immune-related genes on immune infiltration patterns and prognosis in laryngeal cancer.

Int Immunopharmacol

Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, China; State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, China. Electronic address:

Published: August 2020

Objectives: Laryngeal cancer is a common malignant tumor that originates from the larynx, yet its molecular mechanisms have not been thoroughly explored. The purpose of this study was to identify and evaluate immune-related genes in laryngeal cancer through gene co-expression networks, which may serve as biomarkers for its immunotherapy.

Methods: We applied ESTIMATE to evaluate the immune-infiltration landscape of tumor microenvironment. The co-expression networks were constructed by weighted gene co expression network analysis (WGCNA) and compared with the existing human immune related genes (IRGs) to determine the co-expressed IRGs. GSVA combined with CIBERSORT and ssGSEA illustrated the correlation of hub genes and immune infiltration patterns. TIDE algorithm and Subclass mapping evaluated the function of hub genes in predicting immune function and immunotherapeutic sensitivity. The pRRophetic was employed in the sensitivity prediction of chemotherapeutic drugs.

Results: A total of 23 co-expressed IRGs were identified and showed robust expression characteristics. These genes were significantly related to immune infiltration patterns, immune function and sensitivity prediction of immunotherapy and chemotherapeutic drugs for laryngeal cancer patients. Genetic alteration in somatic mutation level and related pathways were also revealed.

Conclusion: The 23 co-expressed IRGs may act as immunotherapeutic biomarkers and potential therapeutic targets for laryngeal cancer with certain expression robustness. The molecular mechanisms deserve further investigation, which will guide clinical treatment in the future.

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http://dx.doi.org/10.1016/j.intimp.2020.106622DOI Listing

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