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Updated: Apr 27, 2026

A Three-Dimensional Spheroid Model to Investigate the Tumor-Stromal Interaction in Hepatocellular Carcinoma
Published on: September 30, 2021
Identification of drivers from cancer genome diversity in hepatocellular carcinoma
Atsushi Takai1, Hien T Dang2, Xin W Wang3
1Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. atsushi.takai@nih.gov.
Abstract:
Hepatocellular carcinoma (HCC) is one of the most common cancers with a dismal outcome. The complicated molecular pathogenesis of HCC caused by tumor heterogeneity makes it difficult to identify druggable targets useful for treating HCC patients. One approach that has a potential for the improvement of patient prognosis is the identification of cancer driver genes that play a critical role in the development of HCC. Recent technological advances of high-throughput methods, such as gene expression profiles, DNA copy number alterations and somatic mutations, have expanded our understanding of the comprehensive genetic profiles of HCC. Integrative analysis of these omics profiles enables us to classify the molecular subgroups of HCC patients. As each subgroup classified according to genetic profiles has different clinical features, such as recurrence rate and prognosis, the tumor subclassification tools are useful in clinical practice. Furthermore, a global genetic analysis, including genome-wide RNAi functional screening, makes it possible to identify cancer vulnerable genes. Identification of common cancer driver genes in HCC leads to the development of an effective molecular target therapy.
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