{"title":"SPP1 promotes malignant characteristics and drug resistance in hepatocellular carcinoma by activating fatty acid metabolic pathway.","authors":"Zhijiang Wang, Chengfang Wang","doi":"10.1007/s10142-025-01664-4","DOIUrl":null,"url":null,"abstract":"<p><p>Hepatocellular carcinoma (HCC) progression and prognosis are influenced by various molecular markers. This study aimed to identify the hub gene associated with HCC clinical characteristics and its role in HCC progression. Differentially expressed genes (DEGs) between HCC tumor and normal tissues, as well as between stage I/II and stage III/IV, were analyzed. Machine learning algorithms were used to pinpoint three critical hub genes (SPP1, ADH4, and ANXA10). A prognostic risk model was constructed and evaluated using Kaplan-Meier curves, COX regression, and decision curve analysis, which could effectively predict HCC survival. Among the three hub genes, SPP1 was significantly associated with the overall survival (OS) of HCC patients and effectively predicted prognosis. More importantly, SPP1 was upregulated in HCC tumor tissues and cells, and its overexpression enhanced HCC cell proliferation, migration, invasion, and drug resistance. It also promoted fatty acid metabolism in HCC cells, with malignant characteristics and drug resistance induced by SPP1 being mitigated by fatty acid oxidation inhibition. In vivo experiments showed that SPP1 knockdown inhibited tumor growth and fatty acid metabolism of HCC mice. In conclusion, SPP1 is a pivotal gene that influences HCC prognosis by enhancing malignancy and drug resistance through fatty acid metabolism.</p>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"25 1","pages":"151"},"PeriodicalIF":3.9000,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Functional & Integrative Genomics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1007/s10142-025-01664-4","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Hepatocellular carcinoma (HCC) progression and prognosis are influenced by various molecular markers. This study aimed to identify the hub gene associated with HCC clinical characteristics and its role in HCC progression. Differentially expressed genes (DEGs) between HCC tumor and normal tissues, as well as between stage I/II and stage III/IV, were analyzed. Machine learning algorithms were used to pinpoint three critical hub genes (SPP1, ADH4, and ANXA10). A prognostic risk model was constructed and evaluated using Kaplan-Meier curves, COX regression, and decision curve analysis, which could effectively predict HCC survival. Among the three hub genes, SPP1 was significantly associated with the overall survival (OS) of HCC patients and effectively predicted prognosis. More importantly, SPP1 was upregulated in HCC tumor tissues and cells, and its overexpression enhanced HCC cell proliferation, migration, invasion, and drug resistance. It also promoted fatty acid metabolism in HCC cells, with malignant characteristics and drug resistance induced by SPP1 being mitigated by fatty acid oxidation inhibition. In vivo experiments showed that SPP1 knockdown inhibited tumor growth and fatty acid metabolism of HCC mice. In conclusion, SPP1 is a pivotal gene that influences HCC prognosis by enhancing malignancy and drug resistance through fatty acid metabolism.
期刊介绍:
Functional & Integrative Genomics is devoted to large-scale studies of genomes and their functions, including systems analyses of biological processes. The journal will provide the research community an integrated platform where researchers can share, review and discuss their findings on important biological questions that will ultimately enable us to answer the fundamental question: How do genomes work?