通过综合生物信息学分析鉴定与肝细胞癌相关的药物靶点和药物。

Identification of Drug Targets and Agents Associated with Hepatocellular Carcinoma through Integrated Bioinformatics Analysis.

机构信息

Bioinformatics Laboratory, Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.

Microbiology Laboratory, Department of Veterinary and Animal Sciences, University of Rajshahi, Rajshahi, 6205, Bangladesh.

出版信息

Curr Cancer Drug Targets. 2023;23(7):547-563. doi: 10.2174/1568009623666230214100159.

DOI:10.2174/1568009623666230214100159

PMID:36786134

Abstract

BACKGROUND

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death globally. The mechanisms underlying the development of HCC are mostly unknown till now.

OBJECTIVE

The main goal of this study was to identify potential drug target proteins and agents for the treatment of HCC.

METHODS

The publicly available three independent mRNA expression profile datasets were downloaded from the NCBI-GEO database to explore common differentially expressed genes (cDEGs) between HCC and control samples using the Statistical LIMMA approach. Hub-cDEGs as drug targets highlighting their functions, pathways, and regulators were identified by using integrated bioinformatics tools and databases. Finally, Hub-cDEGs-guided top-ranked drug agents were identified by molecular docking study for HCC.

RESULTS

We identified 160 common DEGs (cDEGs) from three independent mRNA expression datasets in which ten cDEGs (, and) were selected as Hub-cDEGs. The GO functional and KEGG pathway enrichment analysis of Hub-cDEGs revealed some crucial cancer-stimulating biological processes, molecular functions, cellular components, and signaling pathways. The interaction network analysis identified three TF proteins and five miRNAs as the key transcriptional and post-transcriptional regulators of HubcDEGs. Then, we detected the proposed Hub-cDEGs guided top-ranked three anti-HCC drug molecules (Dactinomycin, Vincristine, Sirolimus) that were also highly supported by the already published top-ranked HCC-causing Hub-DEGs mediated receptors.

CONCLUSION

The findings of this study would be useful resources for diagnosis, prognosis, and therapies of HCC.

摘要

背景

肝细胞癌（HCC）是全球癌症相关死亡的第三大主要原因。到目前为止，HCC 发展的机制在很大程度上还不清楚。

目的

本研究的主要目的是确定潜在的药物靶蛋白和治疗 HCC 的药物。

方法

从 NCBI-GEO 数据库下载了三个公开的独立 mRNA 表达谱数据集，使用 Statistical LIMMA 方法探索 HCC 和对照样本之间的常见差异表达基因（cDEGs）。通过整合生物信息学工具和数据库，确定了作为药物靶点的枢纽 cDEGs，突出了它们的功能、途径和调节剂。最后，通过分子对接研究确定了以枢纽 cDEGs 为指导的 HCC 顶级候选药物。

结果

我们从三个独立的 mRNA 表达数据集确定了 160 个常见的 DEG（cDEG），其中 10 个 cDEG（、和）被选为枢纽 cDEGs。枢纽 cDEGs 的 GO 功能和 KEGG 途径富集分析揭示了一些关键的癌症刺激生物过程、分子功能、细胞成分和信号通路。互作网络分析确定了三个 TF 蛋白和五个 miRNA 作为枢纽 cDEGs 的关键转录和转录后调节剂。然后，我们检测了建议的以枢纽 cDEGs 为指导的三种抗 HCC 药物分子（放线菌素 D、长春新碱、西罗莫司），这些药物分子也得到了已经发表的、排名靠前的 HCC 导致的枢纽 DEGs 介导的受体的高度支持。