Antrodia cinnamomea is extensively used as a traditional medicine to prevention and treatment of liver cancer. However, its comprehensive chemical fingerprint is uncertain, and the mechanisms, especially the potential therapeutic target for anti-hepatocellular carcinoma (HCC) are still unclear. Using UPLC‒Q-TOF/MS, 139 chemical components were identified in A. cinnamomea dropping pills (ACDPs). Based on these chemical components, network pharmacology demonstrated that the targets of active components were significantly enriched in the pathways in cancer, which were closely related with cell proliferation regulation. Next, HCC data was downloaded from Gene Expression Omnibus database (GEO). The Cancer Genome Atlas (TCGA) and DisGeNET were analyzed by bioinformatics, and 79 biomarkers were obtained. Furtherly, nine targets of ACDP active components were revealed, and they were significantly enriched in PI3K/AKT and cell cycle signaling pathways. The affinity between these targets and their corresponding active ingredients was predicted by molecular docking. Finally, in vivo and in vitro experiments showed that ACDPs could reduce the activity of PI3K/AKT signaling pathway and downregulate the expression of cell cycle-related proteins, contributing to the decreased growth of liver cancer. Altogether, PI3K/AKT-cell cycle appears as the significant central node in anti-liver cancer of A. Cinnamomea.

OBJECTIVE To investigate the role of epigenetics in statins’ diabetogenic effect comparing DNA methylation (DNAm) between statin users and nonusers in an epigenome-wide association study in blood. RESEARCH DESIGN AND METHODS Five cohort studies’ participants (n = 8,270) were classified as statin users when they were on statin therapy at the time of DNAm assessment with Illumina 450K or EPIC array or noncurrent users otherwise. Associations of DNAm with various outcomes like incident type 2 diabetes, plasma glucose, insulin, and insulin resistance (HOMA of insulin resistance [HOMA-IR]) as well as with gene expression were investigated. RESULTS Discovery (n = 6,820) and replication (n = 1,450) phases associated five DNAm sites with statin use: cg17901584 (1.12 × 10⁻²⁵ [DHCR24]), cg10177197 (3.94 × 10⁻⁰⁸ [DHCR24]), cg06500161 (2.67 × 10⁻²³ [ABCG1]), cg27243685 (6.01 × 10⁻⁰⁹ [ABCG1]), and cg05119988 (7.26 × 10⁻¹² [SC4MOL]). Two sites were associated with at least one glycemic trait or type 2 diabetes. Higher cg06500161 methylation was associated with higher fasting glucose, insulin, HOMA-IR, and type 2 diabetes (odds ratio 1.34 [95% CI 1.22, 1.47]). Mediation analyses suggested that ABCG1 methylation partially mediates the effect of statins on high insulin and HOMA-IR. Gene expression analyses showed that statin exposure and ABCG1 methylation were associated with ABCG1 downregulation, suggesting epigenetic regulation of ABCG1 expression. Further, outcomes insulin and HOMA-IR were significantly associated with ABCG1 expression. CONCLUSIONS This study sheds light on potential mechanisms linking statins with type 2 diabetes risk, providing evidence on DNAm partially mediating statins’ effects on insulin traits. Further efforts shall disentangle the molecular mechanisms through which statins may induce DNAm changes, potentially leading to ABCG1 epigenetic regulation.