| Literature DB >> 31718031 |
Gianluigi Mazzoccoli1, Luca Miele2, Giuseppe Marrone2, Tommaso Mazza3, Manlio Vinciguerra4, Antonio Grieco2.
Abstract
The biological clock controls at the molecular level several aspects of mammalian physiology, by regulating daily oscillations of crucial biological processes such as nutrient metabolism in the liver. Disruption of the circadian clock circuitry has recently been identified as an independent risk factor for cancer and classified as a potential group 2A carcinogen to humans. Hepatocellular carcinoma (HCC) is the prevailing histological type of primary liver cancer, one of the most important causes of cancer-related death worldwide. HCC onset and progression is related to B and C viral hepatitis, alcoholic and especially non-alcoholic fatty liver disease (NAFLD)-related milieu of fibrosis, cirrhosis, and chronic inflammation. In this review, we recapitulate the state-of-the-art knowledge on the interplay between the biological clock and the oncogenic pathways and mechanisms involved in hepatocarcinogenesis. Finally, we propose how a deeper understanding of circadian clock circuitry-cancer pathways' crosstalk is promising for developing new strategies for HCC prevention and management.Entities:
Keywords: chronotherapy; circadian clock; hepatocellular carcinoma (HCC)
Year: 2019 PMID: 31718031 PMCID: PMC6895918 DOI: 10.3390/cancers11111778
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.639
Figure 1Isoform-specific impact of histone variant macroH2A1 on the expression level of circadian lipogenic genes involved in non-alcoholic fatty liver disease pathogenesis. (A) Heat-map rendering mRNA expression levels of 24-h oscillating genes upon free fatty acid challenge in Hepa 1-6 cells stably over-expressing histone variant macroH2A1.1 and macroH2A1.2 isoforms; (B) STRING interaction network wiring the 24-h oscillating genes rendered in the heat-map. Edges are colored according to the nature of the interactions between genes. Cyan and magenta links correspond to known interactions from curated databases and experimentally determined findings; green, red, and blue links correspond to predicted interactions by gene neighborhood, gene fusion, and gene co-occurrence, respectively; light green, black, and light blue links represent text mining, co-expression, and protein homology evidence of interaction, respectively. Original data from [22,75].