Identification of Drug Targets and Agents Associated with Hepatocellular Carcinoma through Integrated Bioinformatics Analysis.
Hepatocellular carcinoma
differentially expressed genes (DEGs)
drug agents
drug targets
hub-degs
integrated bioinformatics approaches
Journal
Current cancer drug targets
ISSN: 1873-5576
Titre abrégé: Curr Cancer Drug Targets
Pays: Netherlands
ID NLM: 101094211
Informations de publication
Date de publication:
2023
2023
Historique:
received:
29
04
2022
revised:
02
11
2022
accepted:
27
12
2022
medline:
7
6
2023
pubmed:
15
2
2023
entrez:
14
2
2023
Statut:
ppublish
Résumé
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. The main goal of this study was to identify potential drug target proteins and agents for the treatment of HCC. 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. We identified 160 common DEGs (cDEGs) from three independent mRNA expression datasets in which ten cDEGs ( The findings of this study would be useful resources for diagnosis, prognosis, and therapies of HCC.
Sections du résumé
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 (
CONCLUSION
The findings of this study would be useful resources for diagnosis, prognosis, and therapies of HCC.
Identifiants
pubmed: 36786134
pii: CCDT-EPUB-129489
doi: 10.2174/1568009623666230214100159
doi:
Substances chimiques
RNA, Messenger
0
MELK protein, human
EC 2.7.1.-
Protein Serine-Threonine Kinases
EC 2.7.11.1
UBE2T protein, human
EC 2.3.2.23
Ubiquitin-Conjugating Enzymes
EC 2.3.2.23
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
547-563Informations de copyright
Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.