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In recent years,\n APOC1<\/jats:italic>\n and\n APOE<\/jats:italic>\n have been shown to play key roles in the occurrence and development of various cancers. However, the expression levels, gene regulatory networks, prognostic values, and target predictions of\n APOC1<\/jats:italic>\n and\n APOE<\/jats:italic>\n in adrenocortical carcinoma (ACC) remain unclear.\n <\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n Various bioinformatics analysis methods were used, including gene expression profiling interactive analysis, the University of Alabama at Birmingham cancer data analysis portal, biomarker exploration of solid tumors software, the BioPortal for Cancer Genomics, search tool for the retrieval of interacting genes\/proteins, gene multiple association network integration algorithm, Metascape, transcriptional regulatory relationships unraveled by sentence-based text-mining, LinkedOmics, and genomics of drug sensitivity in cancer analysis.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n APOC1<\/jats:italic>\n and\n APOE<\/jats:italic>\n expression were strongly downregulated in patients with ACC.\n APOC1<\/jats:italic>\n and\n APOE<\/jats:italic>\n expression levels were lower in male patients with ACC than those in female patients. Furthermore,\n APOC1<\/jats:italic>\n and\n APOE<\/jats:italic>\n expression levels affected the prognosis of patients with ACC. The main functions of\n APOC1<\/jats:italic>\n and its altered neighboring genes (ANG) were organophosphate ester transport, rRNA processing, and positive regulation of cytokine production. Cytolysis, protein ubiquitination, and histone modification were the main functions of\n APOE<\/jats:italic>\n and its ANGs. The transcription factor E2F1, tumor protein p53, miR-182, miR-493, Erb-B2 receptor tyrosine kinase 2, and cyclin dependent kinase 1 were key regulatory targets of\n APOC1<\/jats:italic>\n ,\n APOE<\/jats:italic>\n , and the ANGs.\n APOC1<\/jats:italic>\n and\n APOE<\/jats:italic>\n expression in patients with ACC were positively associated with immune cell infiltration\n .<\/jats:italic>\n Furthermore, anti-programmed cell death protein 1 immunotherapy strongly downregulated the expression of\n APOC1<\/jats:italic>\n in patients with ACC. Both pilaralisib and elesclomol strongly inhibited SW13 cell growth.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n \n This study preliminarily clarified that\n APOC1<\/jats:italic>\n and\n APOE<\/jats:italic>\n might be potential therapeutic and prognostic targets for ACC, and identified new targets and treatment strategies for ACC.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1177\/18758592241308440","type":"journal-article","created":{"date-parts":[[2025,3,20]],"date-time":"2025-03-20T04:52:43Z","timestamp":1742446363000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Apolipoprotein C1 and apoprotein E as potential therapeutic and prognostic targets for adrenocortical carcinoma"],"prefix":"10.1177","volume":"42","author":[{"given":"Shaojin","family":"Li","sequence":"first","affiliation":[{"name":"Clinical laboratory, Shenzhen Longhua District Central Hospital, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuixiu","family":"Xiao","sequence":"additional","affiliation":[{"name":"Department of Gynecology, Shenzhen Longhua District Central Hospital, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2244-115X","authenticated-orcid":false,"given":"Yongli","family":"Situ","sequence":"additional","affiliation":[{"name":"Department of Parasitology, Guangdong Medical University, Zhanjiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,3,20]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.3389\/fcell.2015.00045"},{"key":"e_1_3_3_3_2","first-page":"4667","article-title":"Screening and identification of key biomarkers in adrenocortical carcinoma based on bioinformatics analysis","volume":"18","author":"Xing Z","year":"2019","unstructured":"Xing Z, Luo Z, Yang H, et al. 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