{"title":"FAT4 基因突变与胃癌的肿瘤突变负担和良好预后有关","authors":"Qingqing Li, Yuxin Chu, Yi Yao, Qibin Song","doi":"10.2174/0113892029300694240612081006","DOIUrl":null,"url":null,"abstract":"Objective: This study aimed to investigate the frequently mutated genes in Gastric Cancer (GC), assess their association with Tumor Mutation Burden (TMB) and the patients’ survival, and identify the potential biomarkers for tailored therapy. Methods: Simple somatic mutation data of GC were collected from the TCGA and ICGC databases. The high-frequency mutated genes were identified from both datasets. The samples were initially dichotomized into wild-type and mutation groups based on the status of overlapping genes. TMB difference between the two groups was evaluated by the Mann-Whitney U-test. Survival difference between the two groups was compared by the Kaplan-Meier method with a log-rank test. The prognostic value of the target gene was assessed by the Cox proportional hazards model. The signaling pathways involved in FAT4 mutation were identified by Gene Set Enrichment Analysis (GSEA). The fractions of different tumor-infiltrating immune cells were calculated by the CIBERSORT algorithm. Results: 21 overlapping genes with frequent mutation were identified in both datasets. Mutation of these genes was significantly associated with higher TMB (P<0.05) in GC. The survival of the FAT4 mutation group was superior to the wild-type group. FAT4 mutation was also identified as an independent favorable prognostic factor for the GC patients. GSEA indicated that FAT4 mutation activated the signaling pathways involved in energy metabolism. Finally, CD4 memory-activated T cells, follicular helper T cells, and gamma delta T cells were significantly more enriched, while naïve B cells and regulatory T cells (Tregs) were significantly less enriched in the FAT4 mutation group (P<0.05). Conclusion: FAT4 mutation is relevant to TMB and favorable prognosis in GC, which may become a useful biomarker for immunotherapy of GC patients.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"18 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"FAT4 Mutation is Related to Tumor Mutation Burden and Favorable Prognosis in Gastric Cancer\",\"authors\":\"Qingqing Li, Yuxin Chu, Yi Yao, Qibin Song\",\"doi\":\"10.2174/0113892029300694240612081006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objective: This study aimed to investigate the frequently mutated genes in Gastric Cancer (GC), assess their association with Tumor Mutation Burden (TMB) and the patients’ survival, and identify the potential biomarkers for tailored therapy. Methods: Simple somatic mutation data of GC were collected from the TCGA and ICGC databases. The high-frequency mutated genes were identified from both datasets. The samples were initially dichotomized into wild-type and mutation groups based on the status of overlapping genes. TMB difference between the two groups was evaluated by the Mann-Whitney U-test. Survival difference between the two groups was compared by the Kaplan-Meier method with a log-rank test. The prognostic value of the target gene was assessed by the Cox proportional hazards model. The signaling pathways involved in FAT4 mutation were identified by Gene Set Enrichment Analysis (GSEA). The fractions of different tumor-infiltrating immune cells were calculated by the CIBERSORT algorithm. Results: 21 overlapping genes with frequent mutation were identified in both datasets. Mutation of these genes was significantly associated with higher TMB (P<0.05) in GC. The survival of the FAT4 mutation group was superior to the wild-type group. FAT4 mutation was also identified as an independent favorable prognostic factor for the GC patients. GSEA indicated that FAT4 mutation activated the signaling pathways involved in energy metabolism. Finally, CD4 memory-activated T cells, follicular helper T cells, and gamma delta T cells were significantly more enriched, while naïve B cells and regulatory T cells (Tregs) were significantly less enriched in the FAT4 mutation group (P<0.05). Conclusion: FAT4 mutation is relevant to TMB and favorable prognosis in GC, which may become a useful biomarker for immunotherapy of GC patients.\",\"PeriodicalId\":10803,\"journal\":{\"name\":\"Current Genomics\",\"volume\":\"18 1\",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Genomics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.2174/0113892029300694240612081006\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Genomics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.2174/0113892029300694240612081006","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
FAT4 Mutation is Related to Tumor Mutation Burden and Favorable Prognosis in Gastric Cancer
Objective: This study aimed to investigate the frequently mutated genes in Gastric Cancer (GC), assess their association with Tumor Mutation Burden (TMB) and the patients’ survival, and identify the potential biomarkers for tailored therapy. Methods: Simple somatic mutation data of GC were collected from the TCGA and ICGC databases. The high-frequency mutated genes were identified from both datasets. The samples were initially dichotomized into wild-type and mutation groups based on the status of overlapping genes. TMB difference between the two groups was evaluated by the Mann-Whitney U-test. Survival difference between the two groups was compared by the Kaplan-Meier method with a log-rank test. The prognostic value of the target gene was assessed by the Cox proportional hazards model. The signaling pathways involved in FAT4 mutation were identified by Gene Set Enrichment Analysis (GSEA). The fractions of different tumor-infiltrating immune cells were calculated by the CIBERSORT algorithm. Results: 21 overlapping genes with frequent mutation were identified in both datasets. Mutation of these genes was significantly associated with higher TMB (P<0.05) in GC. The survival of the FAT4 mutation group was superior to the wild-type group. FAT4 mutation was also identified as an independent favorable prognostic factor for the GC patients. GSEA indicated that FAT4 mutation activated the signaling pathways involved in energy metabolism. Finally, CD4 memory-activated T cells, follicular helper T cells, and gamma delta T cells were significantly more enriched, while naïve B cells and regulatory T cells (Tregs) were significantly less enriched in the FAT4 mutation group (P<0.05). Conclusion: FAT4 mutation is relevant to TMB and favorable prognosis in GC, which may become a useful biomarker for immunotherapy of GC patients.
期刊介绍:
Current Genomics is a peer-reviewed journal that provides essential reading about the latest and most important developments in genome science and related fields of research. Systems biology, systems modeling, machine learning, network inference, bioinformatics, computational biology, epigenetics, single cell genomics, extracellular vesicles, quantitative biology, and synthetic biology for the study of evolution, development, maintenance, aging and that of human health, human diseases, clinical genomics and precision medicine are topics of particular interest. The journal covers plant genomics. The journal will not consider articles dealing with breeding and livestock.
Current Genomics publishes three types of articles including:
i) Research papers from internationally-recognized experts reporting on new and original data generated at the genome scale level. Position papers dealing with new or challenging methodological approaches, whether experimental or mathematical, are greatly welcome in this section.
ii) Authoritative and comprehensive full-length or mini reviews from widely recognized experts, covering the latest developments in genome science and related fields of research such as systems biology, statistics and machine learning, quantitative biology, and precision medicine. Proposals for mini-hot topics (2-3 review papers) and full hot topics (6-8 review papers) guest edited by internationally-recognized experts are welcome in this section. Hot topic proposals should not contain original data and they should contain articles originating from at least 2 different countries.
iii) Opinion papers from internationally recognized experts addressing contemporary questions and issues in the field of genome science and systems biology and basic and clinical research practices.