ORIGINAL RESEARCH article
Front. Oncol.
Sec. Cancer Immunity and Immunotherapy
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1566993
This article is part of the Research TopicTargeted Therapies in Gastric Cancer: Molecular Signatures and Immune Microenvironment InsightsView all 11 articles
IL-36-related genes predict prognosis of gastric cancer
Provisionally accepted
Ying Zhang1,2
Yanbo Liu2Xin Guan2Meng Qu2Dianxiu Wu2Ning Liu2Zhengkun Lin1,2Yuqi Liu2Han Wang2
Lijuan Yang2*- 1Beihua University Hospital, Jilin, Jilin, China
- 2Basic Medical College,Beihua University,China, Jilin, China
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Introduction: Gastric cancer (GC) is one of the most frequently encountered malignant tumors in the clinic. Because effective early screening techniques are lacking, most patients have advanced disease at first diagnosis. The interleukin (IL)-36 family plays a vital role in regulating the immune system, inflammatory responses, and the occurrence and development of cancer. Hence, this study explored the potential role of IL-36 related genes (IL-36RGs) in GC and built a prognostic risk assessment model for GC based on IL-36RGs, which can help evaluate treatment and prognosis.Methods: First, relevant datasets were downloaded from public databases. After processing the datasets to remove batch effects, perform differential analysis, and take intersections, IL-36-related differentially expressed genes (IL-36RDEGs) were screened. A prognostic risk model containing nine model genes was constructed based on univariate Cox and least absolute shrinkage and selection operator (LASSO) regression methods. Then, to investigate the potential biological activities of the model genes in GC, we conducted enrichment, PPI interaction network, and immune infiltration analyses. Immunohistochemical staining was conducted to validate the expression of IL-36A in GC.The prognostic risk model analysis revealed that mortality events in the high-risk group were substantially elevated compared to those in the low-risk group. The model demonstrated excellent predictive capability at 1, 2, and 3 years and showed the best clinical predictive performance at 3 years. Bioinformatics analysis of the model genes indicate that they primarily participate in mechanisms that promote the synthesis and secretion of cytokines in GC. And hub genes may be strongly correlated with host immune response mechanisms. According to the immunohistochemical staining results, IL-36A expression was higher in the STAD group than in the control group.The results of the above analysis suggest that IL-36RDEGs can serve as independent prognostic biomarkers for GC and provide insights into IL-36RGs from both bioinformatics and experimental validation perspectives.
Keywords: GC, IL-36RDEGs, Prognosis model, risk score, prediction
Received: 17 Feb 2025; Accepted: 30 May 2025.
Copyright: © 2025 Zhang, Liu, Guan, Qu, Wu, Liu, Lin, Liu, Wang and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Lijuan Yang, Basic Medical College,Beihua University,China, Jilin, China
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