20.500.12556/RUL-148294 Integrative computational modeling to unravel novel potential biomarkers in hepatocellular carcinoma 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. hepatocellular carcinoma meta-analysis genome-scale metabolic modeling network analysis enriched pathways enriched reactions enriched subsystems hepatocelularni karcinom metaanaliza presnovno modeliranje na ravni genoma true false true Angleški jezik Slovenski jezik Članek v reviji 2023-08-10 14:23:06 2023-08-10 14:23:10 2023-08-12 03:48:32 0000-00-00 00:00:00 2023 0 0 12 str. Vol. 159, art. 106957 Jun. 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 616-006 1879-0534 10.1016/j.compbiomed.2023.106957 152497155 1-s2.0-S0010482523004225-main.pdf 1-s2.0-S0010482523004225-main.pdf 1 C21BBBF209C7298E0F7C677BC59C2DB5 5e441177c41dda9d3a149006986f415b3a13b2a468892e9e6ff523d6a5c0c1e5 f7babb39-3778-11ee-b9d7-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=172381 https://www.sciencedirect.com/science/article/pii/S0010482523004225 0 aa90f363-3778-11ee-b9d7-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=172380 Medicinska fakulteta Fakulteta za računalništvo in informatiko 0 0 0