Molecular Classification and Novel Targets in Hepatocellular Carcinoma: Recent Advancements

Yujin Hoshida(Broad Institute), Sara Toffanin(Icahn School of Medicine at Mount Sinai), Anja Lachenmayer(Icahn School of Medicine at Mount Sinai), Augusto Villanueva(Universitat de Barcelona), Beatriz Mínguez(Icahn School of Medicine at Mount Sinai), Josep M. Llovet(Icahn School of Medicine at Mount Sinai)
Seminars in Liver Disease
February 1, 2010
Cited by 309Open Access
Full Text

Abstract

Hepatocellular carcinoma (HCC) is one of most lethal cancers worldwide. Strategic decisions for the advancement of molecular therapies in this neoplasm require a clear understanding of its molecular classification. Studies indicate aberrant activation of signaling pathways involved in cellular proliferation (e.g., epidermal growth factor and RAS/mitogen-activated protein kinase pathways), survival (e.g., AKT/mechanistic target of rapamycin pathway), differentiation (e.g., WNT and Hedgehog pathways), and angiogenesis (e.g., vascular endothelial growth factor and platelet-derived growth factor), which is heterogeneously presented in each tumor. Integrative analysis of accumulated genomic datasets has revealed global scheme of molecular classification of HCC tumors observed across diverse etiological factors and geographic locations. Such framework will allow systematic understanding of the frequently co-occurring molecular aberrations to design treatment strategy for each specific subclass of tumors. Accompanied with growing number of clinical trials of molecular targeted drugs, diagnostic and prognostic biomarker development will be facilitated with special attention on study design and with new assay technologies specialized for archived fixed tissues. New class of genomic information, microRNA dysregulation and epigenetic alterations, will provide insight for more precise understanding of disease mechanism and expand the opportunity of biomarker/therapeutic target discovery. These efforts will eventually enable personalized management of HCC.


Related Papers

No related papers found

Powered by citation graph analysis