ORIGINAL RESEARCH article
Front. Oncol.
Sec. Cancer Immunity and Immunotherapy
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1584619
This article is part of the Research TopicTargeted Therapies in Gastric Cancer: Molecular Signatures and Immune Microenvironment InsightsView all 10 articles
Integrated single-cell and transcriptome sequencing data reveal the value of IL1RAP in gastric cancer microenvironment and prognosis
Provisionally accepted
- 1Nanping First Hospital affiliated to Fujian Medical University, Nanping,FuJian Province, China
- 2Department of Hepatobiliary Pancreatic and Spleen Surgery, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, China
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Background: Investigating the pivotal role of IL1RAP in the tumor microenvironment of gastric cancer.Method: Download and collate transcriptomic and single-cell data from gastric cancer patients. Three machine learning algorithms identified distinct sets of prognostic genes in gastric cancer patients. The CIBERSORT and ssGSEA algorithms elucidated immune infiltration patterns, while TIDE and TCGA predicted immune-related outcomes. Furthermore, single-cell sequencing data confirmed the interaction of IL1RAP within the tumor microenvironment. Finally, differential expression levels of IL1RAP protein and mRNA were validated.Result: After machine learning screening and independent dataset validation, high IL1RAP expression was identified as a poor prognostic factor for gastric cancer patients. Immune infiltration analysis indicated that the low IL1RAP expression group was associated with higher infiltration of CD8+ T cells and M1-type macrophages, whereas the high IL1RAP expression group exhibited increased presence of M2-type macrophages. Immunotherapy prediction models suggested a more favorable response to PD-1 treatment in the low IL1RAP expression group. Prognostic models incorporating IL1RAP demonstrated superior predictive performance. Single-cell data analysis revealed that IL1RAP plays a critical role in regulating intercellular communication within the tumor microenvironment. Our findings were further validated by confirming elevated IL1RAP expression levels in gastric cancer tissues.IL1RAP plays a critical role in the tumor microenvironment of gastric cancer and serves as a robust predictor of immunotherapy efficacy in gastric cancer.
Keywords: gastric cancer, machine learning, IL1RAP, Tumor Microenvironment, M2-type macrophages
Received: 27 Feb 2025; Accepted: 23 Apr 2025.
Copyright: © 2025 Yang, Wu, Wang, Ou and Huang. 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: Xing Huang, Department of Hepatobiliary Pancreatic and Spleen Surgery, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, China
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