{"title":"Mitochondrial Lipid Metabolism Genes as Diagnostic and Prognostic Indicators in Hepatocellular Carcinoma","authors":"Xuejing Li, Ying Tan, Bihan Liu, Houtian Guo, Yongjian Zhou, Jianhui Yuan, Feng Wang","doi":"10.2174/1389202924666230914110649","DOIUrl":null,"url":null,"abstract":"Background: Due to the heterogeneity of Hepatocellular carcinoma (HCC), there is an urgent need for reliable diagnosis and prognosis. Mitochondria-mediated abnormal lipid metabolism affects the occurrence and progression of HCC. Objective: This study aims to investigate the potential of mitochondrial lipid metabolism (MTLM) genes as diagnostic and independent prognostic biomarkers for HCC. Methods: MTLM genes were screened from the Gene Expression Omnibus (GEO) and Gene Set Enrichment Analysis (GSEA) databases, followed by an evaluation of their diagnostic values in both The Cancer Genome Atlas Program (TCGA) and the Affiliated Cancer Hospital of Guangxi Medical University (GXMU) cohort. The TCGA dataset was utilized to construct a gene signature and investigate the prognostic significance, immune infiltration, and copy number alterations. The validity of the prognostic signature was confirmed through GEO, International Cancer Genome Consortium (ICGC), and GXMU cohorts. Results: The diagnostic receiver operating characteristic (ROC) curve revealed that eight MTLM genes have excellent diagnostic of HCC. A prognostic signature comprising 5 MTLM genes with robust predictive value was constructed using the lasso regression algorithm based on TCGA data. The results of the Stepwise regression model showed that the combination of signature and routine clinical parameters had a higher area under the curve (AUC) compared to a single risk score. Further, a nomogram was constructed to predict the survival probability of HCC, and the calibration curves demonstrated a perfect predictive ability. Finally, the risk score also unveiled the different immune and mutation statuses between the two different risk groups. Conclusion: MTLT-related genes may serve as diagnostic and prognostic biomarkers for HCC as well as novel therapeutic targets, which may be beneficial for facilitating further understanding the molecular pathogenesis and providing potential therapeutic strategies for HCC.","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1389202924666230914110649","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Due to the heterogeneity of Hepatocellular carcinoma (HCC), there is an urgent need for reliable diagnosis and prognosis. Mitochondria-mediated abnormal lipid metabolism affects the occurrence and progression of HCC. Objective: This study aims to investigate the potential of mitochondrial lipid metabolism (MTLM) genes as diagnostic and independent prognostic biomarkers for HCC. Methods: MTLM genes were screened from the Gene Expression Omnibus (GEO) and Gene Set Enrichment Analysis (GSEA) databases, followed by an evaluation of their diagnostic values in both The Cancer Genome Atlas Program (TCGA) and the Affiliated Cancer Hospital of Guangxi Medical University (GXMU) cohort. The TCGA dataset was utilized to construct a gene signature and investigate the prognostic significance, immune infiltration, and copy number alterations. The validity of the prognostic signature was confirmed through GEO, International Cancer Genome Consortium (ICGC), and GXMU cohorts. Results: The diagnostic receiver operating characteristic (ROC) curve revealed that eight MTLM genes have excellent diagnostic of HCC. A prognostic signature comprising 5 MTLM genes with robust predictive value was constructed using the lasso regression algorithm based on TCGA data. The results of the Stepwise regression model showed that the combination of signature and routine clinical parameters had a higher area under the curve (AUC) compared to a single risk score. Further, a nomogram was constructed to predict the survival probability of HCC, and the calibration curves demonstrated a perfect predictive ability. Finally, the risk score also unveiled the different immune and mutation statuses between the two different risk groups. Conclusion: MTLT-related genes may serve as diagnostic and prognostic biomarkers for HCC as well as novel therapeutic targets, which may be beneficial for facilitating further understanding the molecular pathogenesis and providing potential therapeutic strategies for HCC.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.