Cellular Genome-Scale Metabolic Modeling Identifies New Potential Drug Targets Against Hepatocellular Carcinoma.
OMICS
; 26(12): 671-682, 2022 12.
Article
in En
| MEDLINE
| ID: mdl-36508280
ABSTRACT
Genome-scale metabolic modeling (GEM) is one of the key approaches to unpack cancer metabolism and for discovery of new drug targets. In this study, we report the Transcriptional Regulated Flux Balance Analysis-CORE (TRFBA-), an algorithm for GEM using key growth-correlated reactions using hepatocellular carcinoma (HCC), an important global health burden, as a case study. We generated a HepG2 cell-specific GEM by integrating this cell line transcriptomic data with a generic human metabolic model to forecast potential drug targets for HCC. A total of 108 essential genes for growth were predicted by the TRFBA-CORE. These genes were enriched for metabolic pathways involved in cholesterol, sterol, and steroid biosynthesis. Furthermore, we silenced a predicted essential gene, 11-beta dehydrogenase hydroxysteroid type 2 (HSD11B2), in HepG2 cells resulting in a reduction in cell viability. To further identify novel potential drug targets in HCC, we examined the effect of nine drugs targeting the essential genes, and observed that most drugs inhibited the growth of HepG2 cells. Some of these drugs in this model performed better than Sorafenib, the first-line therapeutic against HCC. A HepG2 cell-specific GEM highlights sterol metabolism to be essential for cell growth. HSD11B2 downregulation results in lower cell growth. Most of the compounds, selected by drug repurposing approach, show a significant inhibitory effect on cell growth in a wide range of concentrations. These findings offer new molecular leads for drug discovery for hepatic cancer while also illustrating the importance of GEM and drug repurposing in cancer therapeutics innovation.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Carcinoma, Hepatocellular
/
Liver Neoplasms
Type of study:
Prognostic_studies
Limits:
Humans
Language:
En
Journal:
OMICS
Journal subject:
BIOLOGIA MOLECULAR
Year:
2022
Document type:
Article
Affiliation country:
Sweden