Integrative computational modeling to unravel novel potential biomarkers in hepatocellular carcinoma

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

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.

• Jezik: Angleški jezik
• Ključne besede: hepatocellular carcinoma, meta-analysis, genome-scale metabolic modeling, network analysis, enriched pathways, enriched reactions, enriched subsystems
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: MF - Medicinska fakulteta ; FRI - Fakulteta za računalništvo in informatiko
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2023
• Št. strani: 12 str.
• Številčenje: Vol. 159, art. 106957
• PID: 20.500.12556/RUL-148294
• UDK: 616-006
• ISSN pri članku: 1879-0534
• DOI: 10.1016/j.compbiomed.2023.106957
• COBISS.SI-ID: 152497155
• Datum objave v RUL: 10.08.2023

Gradivo je del revije

• Naslov: Computers in biology and medicine
• Skrajšan naslov: Comput. biol. & med.
• Založnik: Elsevier
• ISSN: 1879-0534
• COBISS.SI-ID: 518726681

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: hepatocelularni karcinom, metaanaliza, presnovno modeliranje na ravni genoma