Bioinformatics combined with network pharmacology and experimental validation to identify key biomarkers of hepatocellular carcinoma and corresponding compounds in Radix Astragali and Pueraria Mirifica

被引:1
|
作者
Li, Mohan [1 ,2 ,3 ]
Liu, Bang [1 ,2 ,3 ]
Xian, Minghua [1 ,2 ,3 ]
Wang, Shumei [1 ,2 ,3 ,4 ]
Liu, Peiyi [5 ]
机构
[1] Guangdong Pharmaceut Univ, Guangzhou 510006, Peoples R China
[2] Guangdong Pharmaceut Univ, Sch Tradit Chinese Mat Med, Key Lab Digital Qual Evaluat Chinese Mat Med State, State Adm TCM, Guangzhou, Peoples R China
[3] Guangdong Pharmaceut Univ, Chinese Mat Med Qual Univ Guangdong Prov, Engn & Technol Res Ctr, Guangzhou, Peoples R China
[4] Tradit Chinese Med Resource Germplasm Bank Managem, Yunfu 527300, Peoples R China
[5] Huangpu Peoples Hosp Zhongshan, Zhongshan 528429, Peoples R China
关键词
Hepatocellular carcinoma; Network pharmacology; Bioinformatics; Biomarkers; Molecular docking; Hederagenin; DOCKING; GENES;
D O I
10.1007/s00210-024-03597-4
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
The occurrence and death rates of primary hepatocellular carcinoma (HCC) are increasing, and there remains a shortage of effective oral medications with minimal side effects. We aim to identify potential biomarkers and compounds from Radix Astragali (RA) and Pueraria Mirifica (PM) to treat liver cancer and improve prognosis. Differentially expressed genes (DEGs) associated with HCC were identified by bioinformatics analysis of three datasets, GSE112791, GSE101685, and GSE45114. Using public databases to predict the bioactive components and possible targets of RA and PM. Target crossover from Gene Expression Omnibus (GEO) and public databases were used to identify potential biomarkers for HCC. Subsequently, validation and prognostic value analyses were performed using the Gene Expression Profile Interaction Analysis (GEPIA) platform. The Cytoscape software created a network of "compound targets" to pinpoint compounds linked to the biomarkers. Molecular docking techniques were utilized to validate the connection between these compounds and the identified biomarkers. Ultimately, the HepG2 liver cancer cell line was chosen to assess the inhibitory effect of Hederagenin (HDG) and to confirm the expression of ADH1B through Western blot analysis. In this study, four key biomarkers (NR1I2, ADH1B, NQO1, GHR) were identified. Molecular docking showed that these four core targets could form stable conformations with the corresponding compounds. As the drug concentration decreases, the inhibitory effect on HepG2 diminishes, and the survival rate of HepG2 cells significantly declines following the administration of 100 mu mol/L HDG. Compared to the control, the expression of ADH1B protein is significantly increased in HepG2 cells treated with 100 mu mol/L HDG. The study identified four key biomarkers (ADH1B, GHR, NQO1, NR1I2) that have prognostic ability for HCC. This study provides biomarkers and potential targeted monomeric medicines for treating HCC.
引用
收藏
页码:5351 / 5371
页数:21
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