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Published on: October 9, 2018
Systematic Analyses of a Chemokine Family-Based Risk Model Predicting Clinical Outcome and Immunotherapy Response in
Jiarui Chen1, Xingyu Liu1, Qiuji Wu1,2,3
1Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Abstract:
Chemokines exhibited complicated functions in antitumor immunity, with their expression profile and clinical importance of lung adenocarcinoma (LUAD) patients remaining largely undetermined. This study aimed to explore the expression patterns of chemokine family in LUAD and construct a predictive chemokine family-based signature. A total of 497 samples were downloaded from the Cancer Genome Atlas (TCGA) data portal as the training set, and the combination of 4 representative Gene Expression Omnibus (GEO) datasets, including GSE30219, GSE50081, GSE37745, and GSE31210, were utilized as the validation set. A three gene-based signature was constructed using univariate and stepwise multivariate Cox regression analysis, classifying patients into high and low risk groups according to the overall survival. The independent GEO datasets were utilized to validate this signature. Another multivariate analysis revealed that this signature remained an independent prognostic factor in LUAD patients. Furthermore, patients in the low risk group featured immunoactive tumor microenvironment (TME), higher IPS scores and lower TIDE scores, and was regarded as the potential beneficiaries of immunotherapy. Finally, the role of risky CCL20 was validated by immunohistochemistry (IHC), and patients possessed higher CCL20 expression presented shorter overall survival (P = 0.011).

