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针对临床流行病学背景的肝癌风险预测分子生物标志物。

Liver cancer risk-predictive molecular biomarkers specific to clinico-epidemiological contexts.

机构信息

Liver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States.

Liver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States; Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

出版信息

Adv Cancer Res. 2022;156:1-37. doi: 10.1016/bs.acr.2022.01.005. Epub 2022 Feb 24.

DOI:10.1016/bs.acr.2022.01.005
PMID:35961696
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7616039/
Abstract

Hepatocellular carcinoma (HCC) risk prediction is increasingly important because of the low annual HCC incidence in patients with the rapidly emerging non-alcoholic fatty liver disease or cured HCV infection. To date, numerous clinical HCC risk biomarkers and scores have been reported in literature. However, heterogeneity in clinico-epidemiological context, e.g., liver disease etiology, patient race/ethnicity, regional environmental exposure, and lifestyle-related factors, obscure their real clinical utility and applicability. Proper characterization of these factors will help refine HCC risk prediction according to certain clinical context/scenarios and contribute to improved early HCC detection. Molecular factors underlying the clinical heterogeneity encompass various features in host genetics, hepatic and systemic molecular dysregulations, and cross-organ interactions, which may serve as clinical-context-specific biomarkers and/or therapeutic targets. Toward the goal to enable individual-risk-based HCC screening by incorporating the HCC risk biomarkers/scores, their assessment in patient with well-defined clinical context/scenario is critical to gauge their real value and to maximize benefit of the tailored patient management for substantial improvement of the poor HCC prognosis.

摘要

肝细胞癌 (HCC) 的风险预测变得越来越重要,因为在非酒精性脂肪性肝病或治愈的 HCV 感染患者中,HCC 的年发病率较低。迄今为止,文献中已经报道了许多临床 HCC 风险生物标志物和评分。然而,临床流行病学背景的异质性,例如肝脏疾病病因、患者种族/民族、区域环境暴露和与生活方式相关的因素,掩盖了它们的实际临床实用性和适用性。正确描述这些因素将有助于根据特定的临床背景/情况细化 HCC 风险预测,并有助于提高早期 HCC 的检测率。临床异质性的分子因素包括宿主遗传学、肝脏和全身分子失调以及跨器官相互作用中的各种特征,它们可以作为特定临床背景的生物标志物和/或治疗靶点。为了通过整合 HCC 风险生物标志物/评分来实现基于个体风险的 HCC 筛查,在具有明确临床背景/情况下评估这些生物标志物/评分对于评估其真正价值以及最大化个体化患者管理的获益至关重要,从而显著改善 HCC 的不良预后。

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Lancet Oncol. 2022 Jan;23(1):161-171. doi: 10.1016/S1470-2045(21)00603-3. Epub 2021 Dec 11.
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Integration of adeno-associated virus (AAV) into the genomes of most Thai and Mongolian liver cancer patients does not induce oncogenesis.腺相关病毒(AAV)整合到大多数泰国和蒙古肝癌患者的基因组中不会诱导致癌。
BMC Genomics. 2021 Nov 11;22(1):814. doi: 10.1186/s12864-021-08098-9.
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Oral Cyanobacteria and Hepatocellular Carcinoma.
口腔蓝藻与肝细胞癌。
Cancer Epidemiol Biomarkers Prev. 2022 Jan;31(1):221-229. doi: 10.1158/1055-9965.EPI-21-0804. Epub 2021 Oct 25.
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Prospective Study of Outcomes in Adults with Nonalcoholic Fatty Liver Disease.非酒精性脂肪性肝病成人患者结局的前瞻性研究。
N Engl J Med. 2021 Oct 21;385(17):1559-1569. doi: 10.1056/NEJMoa2029349.
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An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B.一种用于预测韩国和高加索慢性乙型肝炎患者肝细胞癌风险的人工智能模型。
J Hepatol. 2022 Feb;76(2):311-318. doi: 10.1016/j.jhep.2021.09.025. Epub 2021 Oct 2.
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CA Cancer J Clin. 2021 Nov;71(6):466-487. doi: 10.3322/caac.21695. Epub 2021 Sep 21.
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Current and Emerging Tools for Hepatocellular Carcinoma Surveillance.当前和新兴的肝细胞癌监测工具。
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