Jung-Hyo Cho, Hyeong-Geug Kim, Menghao Huang, Shen Wang, Sheng Liu, Alex Lu, Kyle McCrocklin, Yang Zhang, Zhigang Fang, Juexin Wang, Wanqing Liu, Jun Wan, X Charlie Dong
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引用次数: 0
Abstract
Patatin-like phospholipase domain-containing 3 (PNPLA3) protein 148M variant is strongly associated with cirrhosis and hepatocellular carcinoma (HCC); however, the underlying mechanisms remain elusive. This study aimed to elucidate the role of the PNPLA3148M variant in alcohol-related HCC development. Control and humanized PNPLA3148M transgenic mice were fed with an ethanol-containing diet for 12 weeks. The animals were examined for liver tumors. After the alcohol feeding, the PNPLA3148M mice had twofold higher liver cancer incidence rates and larger tumor sizes than those in the control mice. Cancer stem cell markers in the PNPLA3148M mouse livers were elevated relative to those in the control mouse livers. Alcohol detoxification was impaired in the PNPLA3148M mouse livers. Hepatic oxidative stress and DNA damage were elevated in the PNPLA3148M mice. Wnt/β-catenin and Yes-associated protein (YAP) and WW domain-containing transcription regulator 1 (TAZ) were activated in the PNPLA3148M mouse livers. The data suggest that the PNPLA3148M variant has a strong interaction with alcohol in HCC development through attenuation of alcohol detoxification and promotion of oncogenic pathways. Targeting the PNPLA3148M variant might be useful for the prevention or treatment of alcohol-associated HCC in patients carrying this variant.
期刊介绍:
The American Journal of Pathology, official journal of the American Society for Investigative Pathology, published by Elsevier, Inc., seeks high-quality original research reports, reviews, and commentaries related to the molecular and cellular basis of disease. The editors will consider basic, translational, and clinical investigations that directly address mechanisms of pathogenesis or provide a foundation for future mechanistic inquiries. Examples of such foundational investigations include data mining, identification of biomarkers, molecular pathology, and discovery research. Foundational studies that incorporate deep learning and artificial intelligence are also welcome. High priority is given to studies of human disease and relevant experimental models using molecular, cellular, and organismal approaches.