Unveiling fatty acid subtypes: immunometabolic interplay and therapeutic opportunities in gastric cancer
BackgroundThe 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).MethodA total of 24 prognostic-related genes were identified by intersecting differentially expressed genes with...
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Frontiers Media S.A.
2025-05-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1570873/full |
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| author | Huahuan Liu Xin Hu Xin Hu Xiangnan Zhang Yanxin Yao Liuxing Wu Ye Tian Hongji Dai Kexin Chen Ben Liu |
| author_facet | Huahuan Liu Xin Hu Xin Hu Xiangnan Zhang Yanxin Yao Liuxing Wu Ye Tian Hongji Dai Kexin Chen Ben Liu |
| author_sort | Huahuan Liu |
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| description | BackgroundThe 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).MethodA 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.ResultsAn 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.ConclusionThis developed FAM signature demonstrated potential as a biomarker for guiding treatment and predicting prognosis in GC. |
| format | Article |
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| institution | Kabale University |
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| language | English |
| publishDate | 2025-05-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Oncology |
| spelling | doaj-art-3dde28189aa248dd8ab8c7eb858933702025-08-20T03:48:23ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-05-011510.3389/fonc.2025.15708731570873Unveiling fatty acid subtypes: immunometabolic interplay and therapeutic opportunities in gastric cancerHuahuan Liu0Xin Hu1Xin Hu2Xiangnan Zhang3Yanxin Yao4Liuxing Wu5Ye Tian6Hongji Dai7Kexin Chen8Ben Liu9Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, ChinaDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, ChinaCenter for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan, ChinaDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, ChinaDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, ChinaDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, ChinaDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, ChinaDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, ChinaDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, ChinaDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, ChinaBackgroundThe 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).MethodA 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.ResultsAn 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.ConclusionThis developed FAM signature demonstrated potential as a biomarker for guiding treatment and predicting prognosis in GC.https://www.frontiersin.org/articles/10.3389/fonc.2025.1570873/fullgastric cancerfatty acid metabolismmulti-omics technologiesimmunotherapysingle-cell transcriptomics |
| spellingShingle | Huahuan Liu Xin Hu Xin Hu Xiangnan Zhang Yanxin Yao Liuxing Wu Ye Tian Hongji Dai Kexin Chen Ben Liu Unveiling fatty acid subtypes: immunometabolic interplay and therapeutic opportunities in gastric cancer Frontiers in Oncology gastric cancer fatty acid metabolism multi-omics technologies immunotherapy single-cell transcriptomics |
| title | Unveiling fatty acid subtypes: immunometabolic interplay and therapeutic opportunities in gastric cancer |
| title_full | Unveiling fatty acid subtypes: immunometabolic interplay and therapeutic opportunities in gastric cancer |
| title_fullStr | Unveiling fatty acid subtypes: immunometabolic interplay and therapeutic opportunities in gastric cancer |
| title_full_unstemmed | Unveiling fatty acid subtypes: immunometabolic interplay and therapeutic opportunities in gastric cancer |
| title_short | Unveiling fatty acid subtypes: immunometabolic interplay and therapeutic opportunities in gastric cancer |
| title_sort | unveiling fatty acid subtypes immunometabolic interplay and therapeutic opportunities in gastric cancer |
| topic | gastric cancer fatty acid metabolism multi-omics technologies immunotherapy single-cell transcriptomics |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2025.1570873/full |
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