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结合生物信息学、网络药理学和实验验证来鉴定肝细胞癌的关键生物标志物以及黄芪和白高颗中的相应化合物。

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

作者信息

Li Mohan, Liu Bang, Xian Minghua, Wang Shumei, Liu Peiyi

机构信息

Guangdong Pharmaceutical University, Guangzhou, 510006, China.

Key Laboratory of Digital Quality Evaluation of Chinese Materia Medica of State Administration of TCM, School of Traditional Chinese Materia Medica, Guangdong Pharmaceutical University, Guangzhou, China.

出版信息

Naunyn Schmiedebergs Arch Pharmacol. 2025 May;398(5):5351-5371. doi: 10.1007/s00210-024-03597-4. Epub 2024 Nov 16.

Abstract

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 µmol/L HDG. Compared to the control, the expression of ADH1B protein is significantly increased in HepG2 cells treated with 100 µmol/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.

摘要

原发性肝细胞癌(HCC)的发病率和死亡率呈上升趋势,且目前仍缺乏副作用极小的有效口服药物。我们旨在从黄芪(RA)和葛氏米良姜(PM)中鉴定出潜在的生物标志物和化合物,以治疗肝癌并改善预后。通过对三个数据集GSE112791、GSE101685和GSE45114进行生物信息学分析,确定了与HCC相关的差异表达基因(DEG)。利用公共数据库预测RA和PM的生物活性成分及可能的靶点。通过基因表达综合数据库(GEO)和公共数据库的靶点交叉分析,确定HCC的潜在生物标志物。随后,使用基因表达谱相互作用分析(GEPIA)平台进行验证和预后价值分析。利用Cytoscape软件创建“化合物-靶点”网络,以找出与生物标志物相关的化合物。采用分子对接技术验证这些化合物与已鉴定生物标志物之间的联系。最终,选择HepG2肝癌细胞系评估羽扇豆醇(HDG)的抑制作用,并通过蛋白质免疫印迹分析确认乙醇脱氢酶1B(ADH1B)的表达。在本研究中,鉴定出四个关键生物标志物(NR1I2、ADH1B、NQO1、GHR)。分子对接表明,这四个核心靶点可与相应化合物形成稳定构象。随着药物浓度降低,对HepG2的抑制作用减弱,给予100 μmol/L HDG后,HepG2细胞的存活率显著下降。与对照组相比,用100 μmol/L HDG处理的HepG2细胞中ADH1B蛋白的表达显著增加。该研究鉴定出四个对HCC具有预后评估能力的关键生物标志物(ADH1B、GHR、NQO1、NR1I2)。本研究为治疗HCC提供了生物标志物和潜在的靶向单体药物。

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