Identifying diagnostic biomarkers and predicting the role of Salvia miltiorrhiza compounds in hepatocellular carcinoma

Background Previous studies have shown the potential therapeutic effect of Salvia miltiorrhiza on hepatocellular carcinoma (HCC). This study commenced to identify the diagnostic biomarkers and predict the role of Salvia miltiorrhiza in HCC. Methods TCGA-HCC cohort and HCCDB18 dataset were acquired from public database. Chemical components of Salvia miltiorrhiza was identified by the liquid chromatography-tandem mass spectrometry (LC-MS/MS). Differentially expressed genes (DEGs) between tumor and control groups were recognized by “DESeq2” and “Limma” packages. Prognosis-associated DEGs were screened through univariate cox analysis. The compounds-genes network was established using Cytoscape software, and the biomarkers were identified accordingly. Nomogram was constructed employing “rms” package, the diagnostic performance of which was assessed. Immune infiltration was evaluated via “CIBERSORT” and “estimate” packages. Pathways involved in biomarkers were analyzed by GSEA_4.2.2 software. Molecular docking model was constructed applying AutoDocktools software. The cell viability, migration and invasion of HCC cell line treated with β-Estradiol or/and overexpressing AKR1C3 were assessed by Cell Counting Kit-8 (CCK-8), Wound healing and Transwell assays. Results This study identified 57 compounds from Salvia miltiorrhiza and screened 54 poor and 4 good prognostic DEGs shared in TCGA-HCC cohort and HCCDB18 dataset. Further, we established the compounds-genes network of 10 Salvia miltiorrhiza components and 3 prognostic DEGs. Accordingly, AURKB , HDAC11 and AKR1C3 were identified as biomarkers to construct nomogram, displaying good diagnostic performance in HCC. Three biomarkers were notably correlated with most immune cells, and mainly participated in tumor proliferation, cell cycle, apoptosis and energy supply relevant pathways. Molecular docking model indicated that three compounds from Salvia miltiorrhiza (Ethinylestradiol, β-Estradiol, 16alpha-Hydroxyestrone) could stably bind to AKR1C3 . Thereinto, β-Estradiol could inhibit the proliferation, migration and invasion of HCC cells by targeting AKR1C3 . Conclusion This study could lay some foundation for further exploring the pathogenesis of HCC, and provide novel diagnostic biomarkers, treatment targets, and potential management drugs for HCC.