Andrew Walakira (Author), Cene Skubic (Author), Nejc Nadižar (Author), Damjana Rozman (Author), Tadeja Režen (Author), Miha Mraz (Author), Miha Moškon (Author)

Abstract

Hepatocellular carcinoma (HCC) is a major health problem around the world. The management of this disease is complicated by the lack of noninvasive diagnostic tools and the few treatment options available. Better clinical outcomes can be achieved if HCC is detected early, but unfortunately, clinical signs appear when the disease is in its late stages. We aim to identify novel genes that can be targeted for the diagnosis and therapy of HCC. We performed a meta-analysis of transcriptomics data to identify differentially expressed genes and applied network analysis to identify hub genes. Fatty acid metabolism, complement and coagulation cascade, chemical carcinogenesis and retinol metabolism were identified as key pathways in HCC. Furthermore, we integrated transcriptomics data into a reference human genome-scale metabolic model to identify key reactions and subsystems relevant in HCC. We conclude that fatty acid activation, purine metabolism, vitamin D, and E metabolism are key processes in the development of HCC and therefore need to be further explored for the development of new therapies. We provide the first evidence that GABRP, HBG1 and DAK (TKFC) genes are important in HCC in humans and warrant further studies.

Keywords

hepatocellular carcinoma;meta-analysis;genome-scale metabolic modeling;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL MF - Faculty of Medicine
UDC: 616-006
COBISS: 152497155 Link will open in a new window
ISSN: 1879-0534
Views: 36
Downloads: 8
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Other data

Secondary language: Slovenian
Secondary keywords: hepatocelularni karcinom;meta-analiza;presnovno modeliranje na ravni genoma;
Type (COBISS): Article
Pages: str. [1]-12
Issue: ǂVol. ǂ159
Chronology: Jun. 2023
DOI: 10.1016/j.compbiomed.2023.106957
ID: 19774103