Fatty Acid Metabolism Signature Contributes to the Molecular Diagnosis of a Malignant Gastric Cancer Subtype with Poor Prognosis and Lower Mutation Burden.

IF 2.5 4区 医学 Q3 ONCOLOGY Recent patents on anti-cancer drug discovery Pub Date : 2024-01-01 DOI:10.2174/1574892819666230907145036
Zhengwei Chen, Guoxiong Cheng
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Abstract

Background: Gastric cancer (GC) is a common gastrointestinal tumor with high morbidity and mortality. Fatty acid metabolism (FAM) contributes to GC development. Patents have been issued for the use of compositions comprising fatty acid analogues for the treatment of many clinical conditions. However, its clinical significance and its relationship with tumor-related mutations have not been thoroughly discovered. This study was conducted to analyze and explore FAM-related genes' molecular characteristics, prognostic significance, and association with tumor- related mutations.

Methods: The gastric adenocarcinoma's transcriptome, clinical data, and tumor mutation load (TMB) data were downloaded from TCGA and GEO databases. The differentially expressed FAM genes (FAM DEGs) between cancer and control samples were screened, and their correlation with TMB and survival was analyzed. A PPI network of FAM DEGs was constructed, and a downscaling clustering analysis was performed based on the expression of the FAM DEGs. Further immuno- infiltration and GO/KEGG enrichment analyses of the identified FAM clusters were performed to explore their heterogeneity in biological functions. The effects of FAM score and gastric cancer (STAD) on TMB, MSI, survival prognosis, and drug sensitivity were jointly analyzed, and finally, a single-gene analysis of the obtained core targets was performed.

Results: Through differential analysis, 68 FAM DEGs were obtained, and they were highly associated with STAD tumor mutation load. In addition, a high FAM DEGs CNV rate was observed. The PPI network showed a complex mutual correlation between the FAM DEGs. Consensus clustering classified the patients into three clusters based on the FAM DEGs, and the clusters presented different survival rates. The GSVA and immune infiltration analysis revealed that metabolism, apoptosis, and immune infiltration-related pathways were variated. In addition, FAM genes, STAD prognostic risk genes, and PCA scores were closely associated with the survival status of STAD patients. FAM score was closely correlated with STAD TMB, MSI, and immunotherapy, and the TMB values in the low FAM score group were significantly higher than those in the high FAM score group. Finally, combining the above results, it was found that the core gene PTGS1 performed best in predicting STAD survival prognosis and TMB/MSI/immunotherapy.

Conclusion: Fatty acid metabolism genes affect the development of gastric adenocarcinoma and can predict the survival prognosis, tumor mutational load characteristics, and drug therapy sensitivity of STAD patients, which can help explore more effective immunotherapy targets for GC.

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脂肪酸代谢特征有助于对预后较差、突变负担较低的恶性胃癌亚型进行分子诊断
背景:胃癌(GC)是一种常见的胃肠道肿瘤,发病率和死亡率都很高。脂肪酸代谢(FAM)是导致胃癌发生的原因之一。脂肪酸类似物组合物用于治疗许多临床疾病的专利已经获得批准。然而,其临床意义及其与肿瘤相关突变的关系尚未被彻底发现。本研究旨在分析和探讨FAM相关基因的分子特征、预后意义以及与肿瘤相关突变的关系:方法:从 TCGA 和 GEO 数据库下载胃腺癌的转录组、临床数据和肿瘤突变负荷(TMB)数据。筛选了癌症样本和对照样本中差异表达的FAM基因(FAM DEGs),并分析了它们与TMB和生存率的相关性。构建了 FAM DEGs 的 PPI 网络,并根据 FAM DEGs 的表达进行了降尺度聚类分析。进一步对已识别的FAM集群进行免疫浸润和GO/KEGG富集分析,以探讨其生物学功能的异质性。联合分析了 FAM 评分和胃癌(STAD)对 TMB、MSI、生存预后和药物敏感性的影响,最后对获得的核心靶点进行了单基因分析:结果:通过差异分析,获得了68个FAM DEGs,它们与STAD肿瘤突变负荷高度相关。此外,还观察到了较高的 FAM DEGs CNV 率。PPI 网络显示 FAM DEGs 之间存在复杂的相互关联。共识聚类根据 FAM DEGs 将患者分为三个群组,各群组的生存率不同。GSVA和免疫浸润分析显示,新陈代谢、细胞凋亡和免疫浸润相关通路存在差异。此外,FAM基因、STAD预后风险基因和PCA评分与STAD患者的生存状况密切相关。FAM 评分与 STAD TMB、MSI 和免疫治疗密切相关,低 FAM 评分组的 TMB 值明显高于高 FAM 评分组。最后,综合上述结果,发现核心基因PTGS1在预测STAD生存预后和TMB/MSI/免疫治疗方面表现最佳:脂肪酸代谢基因影响胃腺癌的发生发展,并能预测STAD患者的生存预后、肿瘤突变负荷特征和药物治疗敏感性,有助于探索更有效的GC免疫治疗靶点。
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来源期刊
CiteScore
4.50
自引率
7.10%
发文量
55
审稿时长
3 months
期刊介绍: Aims & Scope Recent Patents on Anti-Cancer Drug Discovery publishes review and research articles that reflect or deal with studies in relation to a patent, application of reported patents in a study, discussion of comparison of results regarding application of a given patent, etc., and also guest edited thematic issues on recent patents in the field of anti-cancer drug discovery e.g. on novel bioactive compounds, analogs, targets & predictive biomarkers & drug efficacy biomarkers. The journal also publishes book reviews of eBooks and books on anti-cancer drug discovery. A selection of important and recent patents on anti-cancer drug discovery is also included in the journal. The journal is essential reading for all researchers involved in anti-cancer drug design and discovery. The journal also covers recent research (where patents have been registered) in fast emerging therapeutic areas/targets & therapeutic agents related to anti-cancer drug discovery.
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