ORIGINAL RESEARCH article
Front. Oncol.
Sec. Cancer Metabolism
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1570873
This article is part of the Research TopicMetabolic Crosstalk between Cancer Cells and Immune Cells in the Tumor Microenvironment: Cellular and Molecular Insights, and their Therapeutic ImplicationsView all 13 articles
Unveiling Fatty Acid Subtypes: Immunometabolic Interplay and Therapeutic Opportunities in Gastric Cancer
Provisionally accepted
- 1Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
- 2Zhongnan Hospital, Wuhan University, Wuhan, Hubei Province, China
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Background: The goal of this study was to develop a predictive signature using genes associated with fatty acid metabolism to evaluate the prognosis of individuals with gastric cancer (GC). Method: A total of 24 prognostic-related genes were identified by intersecting differentially expressed genes with 525 fatty acid metabolism (FAM) -related genes and applying a univariate Cox proportional hazards model. By performing consensus clustering of 24 genes associated with FAM, two distinct clusters of GC patients were identified. Subsequently, a risk model was constructed using 39 differentially expressed mRNAs from the two clusters through a random forest model and univariate Cox regression. Results: An R package, "GCFAMS", was developed to assess GC patients' prognosis based on FAM gene expression. The low-risk group exhibited a more favorable prognosis compared to the high-risk group across various datasets (P < 0.05). The model demonstrated strong predictive performance, with AUC values of 0.86, 0.623, and 0.508 for 5-year survival prediction in the training and two validation datasets. The high-risk group displayed lower IC50 values for embelin and imatinib, suggesting the potential efficacy of these drugs in this subgroup. Conversely, the low-risk group demonstrated an elevated response to immune checkpoints blockade therapy and a higher immunophenoscore, which was further validated in additional cancer cohorts. Public data from single-cell RNA sequencing confirmed that the characterized genes were predominantly expressed in endothelial cells and fibroblasts.Furthermore, the integration of transcriptomics and metabolomics revealed notable variations in fatty acid levels between the clusters, underscoring the clinical relevance of our fatty acid metabolism signature in shaping the metabolic profiles of GC patients. Conclusion: This developed FAM signature demonstrated potential as a biomarker for guiding treatment and predicting prognosis in GC.
Keywords: gastric cancer, fatty acid metabolism, multi-omics technologies, Immunotherapy, Single-cell transcriptomics
Received: 04 Feb 2025; Accepted: 28 Apr 2025.
Copyright: © 2025 Liu, Hu, Zhang, Yao, Wu, Ye, Dai, Chen and Liu. 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:
Kexin Chen, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
Ben Liu, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
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