Modern Medical Journal, Volume. 53, Issue 7, 1069(2025)

Analysis of differentially expressed genes and KRAS mutations associated with immune therapy response in non-small cell lung cancer

ZHU Xiaodan1, GU Guomin1, SHEN Yanli1, MIREAYI Abudurezike1, and SUN Gang2、*
Author Affiliations
  • 12nd Ward, Department Pulmonary Medicine, Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi 830054, China
  • 2Department of Breast and Thyroid Surgery, Xinjiang Uygur Autonomous Region People's Hospital, Urumqi 830001, China
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    Objective:To investigate the molecular mechanisms associated with the response to anti-PD-1/PD-L1 therapy in non-small cell lung cancer (NSCLC), and the sensitivity of KRAS mutations to immunotherapy.MethodsDifferentially expressed genes (DEGs) between NSCLC and controls in the GSE75037, GSE81089, and TCGA datasets were analyzed, and gene co-expression networks was constructed using weighted gene co-expression network analysis (WGCNA). DEGs between responders and non-responders to anti-PD-1/PD-L1 therapy were identified in the GSE126044 dataset, and a Cox regression model was used to evaluate the effect of genes on overall survival (OS) of patients. The expression of prognostic-related genes was detected by RT-qPCR and Western blot. In addition, clinical data were collected from 56 NSCLC patients who received anti-PD-1/PD-L1 immunotherapy, and clinical information was analyzed among patients with partial response (PR), stable disease (SD), and progressive disease (PD). KRAS mutation status and its sensitivity to immunotherapy were analyzed in the TCGA dataset.ResultsA total of 1 298 common DEGs were identified in the GSE75037, GSE81089, and TCGA datasets. In the GSE126044 dataset, 2 111 DEGs associated with response to anti-PD-1/PD-L1 therapy were identified, and 10 gene modules were identified through WGCNA, among which the brown module was significantly positively correlated with the responder group. Cox regression analysis showed that SPP1, PTPRH, SLC35F2, GPR37, and PLA2G4F were significantly associated with prognosis in both the GSE81089 and TCGA datasets (all P<0.05). Compared with the non-responder group, RT-qPCR and Western blot analysis showed that SPP1, PTPRH, SLC35F2, and GPR37 were expressed at lower levels in the responder group, while PLA2G4F was expressed at a higher level. In addition, KRAS mutation differed significantly among the PR, SD, and PD groups (χ2=6.47, P<0.05). In the TCGA dataset, the KRAS mutation rate was 15.15%, and the mutation rate was higher in the responder group than in the non-responder group, suggesting a positive role in response to immunotherapy.ConclusionThe key genes identified in this study play important roles in the response to anti-PD-1/PD-L1 therapy in NSCLC patients. KRAS mutation may serve as a critical predictor of therapeutic efficacy. These findings provide new insights into personalized treatment strategies for NSCLC patients.

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    ZHU Xiaodan, GU Guomin, SHEN Yanli, MIREAYI Abudurezike, SUN Gang. Analysis of differentially expressed genes and KRAS mutations associated with immune therapy response in non-small cell lung cancer[J]. Modern Medical Journal, 2025, 53(7): 1069

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    Paper Information

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    Received: Nov. 28, 2024

    Accepted: Aug. 22, 2025

    Published Online: Aug. 22, 2025

    The Author Email: SUN Gang (sungang@xjmu.edu.cn)

    DOI:10.3969/j.issn.1671-7562.2025.07.006

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