{"title":"脂肪酸代谢相关基因标记可以预测胶质瘤的不良预后。","authors":"Chuanyu Li, Xinran Xue, Jiahui Kong, Jianjun Zhang","doi":"10.1097/CAD.0000000000001719","DOIUrl":null,"url":null,"abstract":"<p><p>Gliomas, arising from supportive glial cells in the central nervous system, present significant challenges in oncology due to their varying aggressiveness and poor prognosis, particularly in high-grade forms. Understanding the molecular pathways involved in glioma progression is essential for developing effective treatment strategies. This study aimed to develop a fatty acid metabolism (FAM)-related gene signature to better predict poor prognosis in glioma patients, thereby facilitating more targeted therapeutic approaches. We employed the Least Absolute Shrinkage and Selection Operator regression analysis to identify a gene signature associated with FAM from The Cancer Genome Atlas and Chinese Glioma Genome Atlas RNA-seq datasets. Survival analyses, including Kaplan-Meier and Cox regression analyses, were conducted to assess the prognostic value of the identified genes. A total of seven FAM-related genes were associated with survival outcomes in isocitrate dehydrogenase-1 wild-type glioblastoma. The constructed gene signature effectively stratified patients into high-risk and low-risk groups, with high-risk patients demonstrating significantly poorer survival. PTGR1 emerged as the core gene, closely linked to malignant progression and poor prognosis. The FAM-related gene signature developed in this study provides a reliable tool for predicting poor outcomes in glioma patients. PTGR1, identified as a pivotal gene within this signature, may serve as a potential target for future therapeutic interventions, offering promising avenues for enhancing patient survival.</p>","PeriodicalId":7969,"journal":{"name":"Anti-Cancer Drugs","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A fatty acid metabolism-related gene signature can predict poor prognosis in glioma.\",\"authors\":\"Chuanyu Li, Xinran Xue, Jiahui Kong, Jianjun Zhang\",\"doi\":\"10.1097/CAD.0000000000001719\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Gliomas, arising from supportive glial cells in the central nervous system, present significant challenges in oncology due to their varying aggressiveness and poor prognosis, particularly in high-grade forms. Understanding the molecular pathways involved in glioma progression is essential for developing effective treatment strategies. This study aimed to develop a fatty acid metabolism (FAM)-related gene signature to better predict poor prognosis in glioma patients, thereby facilitating more targeted therapeutic approaches. We employed the Least Absolute Shrinkage and Selection Operator regression analysis to identify a gene signature associated with FAM from The Cancer Genome Atlas and Chinese Glioma Genome Atlas RNA-seq datasets. Survival analyses, including Kaplan-Meier and Cox regression analyses, were conducted to assess the prognostic value of the identified genes. A total of seven FAM-related genes were associated with survival outcomes in isocitrate dehydrogenase-1 wild-type glioblastoma. The constructed gene signature effectively stratified patients into high-risk and low-risk groups, with high-risk patients demonstrating significantly poorer survival. PTGR1 emerged as the core gene, closely linked to malignant progression and poor prognosis. The FAM-related gene signature developed in this study provides a reliable tool for predicting poor outcomes in glioma patients. PTGR1, identified as a pivotal gene within this signature, may serve as a potential target for future therapeutic interventions, offering promising avenues for enhancing patient survival.</p>\",\"PeriodicalId\":7969,\"journal\":{\"name\":\"Anti-Cancer Drugs\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2025-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Anti-Cancer Drugs\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/CAD.0000000000001719\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anti-Cancer Drugs","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/CAD.0000000000001719","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
A fatty acid metabolism-related gene signature can predict poor prognosis in glioma.
Gliomas, arising from supportive glial cells in the central nervous system, present significant challenges in oncology due to their varying aggressiveness and poor prognosis, particularly in high-grade forms. Understanding the molecular pathways involved in glioma progression is essential for developing effective treatment strategies. This study aimed to develop a fatty acid metabolism (FAM)-related gene signature to better predict poor prognosis in glioma patients, thereby facilitating more targeted therapeutic approaches. We employed the Least Absolute Shrinkage and Selection Operator regression analysis to identify a gene signature associated with FAM from The Cancer Genome Atlas and Chinese Glioma Genome Atlas RNA-seq datasets. Survival analyses, including Kaplan-Meier and Cox regression analyses, were conducted to assess the prognostic value of the identified genes. A total of seven FAM-related genes were associated with survival outcomes in isocitrate dehydrogenase-1 wild-type glioblastoma. The constructed gene signature effectively stratified patients into high-risk and low-risk groups, with high-risk patients demonstrating significantly poorer survival. PTGR1 emerged as the core gene, closely linked to malignant progression and poor prognosis. The FAM-related gene signature developed in this study provides a reliable tool for predicting poor outcomes in glioma patients. PTGR1, identified as a pivotal gene within this signature, may serve as a potential target for future therapeutic interventions, offering promising avenues for enhancing patient survival.
期刊介绍:
Anti-Cancer Drugs reports both clinical and experimental results related to anti-cancer drugs, and welcomes contributions on anti-cancer drug design, drug delivery, pharmacology, hormonal and biological modalities and chemotherapy evaluation. An internationally refereed journal devoted to the fast publication of innovative investigations on therapeutic agents against cancer, Anti-Cancer Drugs aims to stimulate and report research on both toxic and non-toxic anti-cancer agents. Consequently, the scope on the journal will cover both conventional cytotoxic chemotherapy and hormonal or biological response modalities such as interleukins and immunotherapy. Submitted articles undergo a preliminary review by the editor. Some articles may be returned to authors without further consideration. Those being considered for publication will undergo further assessment and peer-review by the editors and those invited to do so from a reviewer pool.