7), suggesting that the aberration of either gene may be involved in the maintenance of aggressive phenotype of an established tumor. We also performed preliminary AZD9668 solubility dmso functional characterizations
of both putative drivers by siRNA-mediated target knockdown in HCC cell lines that carry the respective target amplification and compared with models without the amplification. We noted that results on BCL9 were mixed in the HUH6 cell line, which is copy number neutral with respect to BCL9, but had decreased viability upon BCL9 knockdown in one of the assays. Because BCL9 is involved in the Wnt/β-catenin–signaling pathway,[17] there may exist other mechanisms for activating this pathway in HUH6 cells: It has been shown that the Wnt pathway may be activated in the HUH6 cell line as a result of β-catenin mutations.[20] Blocking the Wnt/β-catenin pathway by knocking down BCL9 gene expression could then lead to tumor growth inhibition in HUH6 cells, which may be addicted Selleckchem VX 809 to this pathway for its tumorigenic properties. More research is needed to fully validate these two genes
as oncogenic drivers in HCC and to explore their utility in targeted cancer therapy. Our work nevertheless demonstrates a proof of concept that systematic clinical genomics approaches, such as the one presented here, could be valuable in uncovering novel, clinically relevant cancer driver genes, and that testing of such genes needs to be performed in relevant preclinical models, both with and without the corresponding genetic aberration. Future directions of our work include high-throughput dropout screens to systematically test all genes within the focal amplicons, an unbiased approach similar to the forward genetic screening by Sawey et al.[9] One of the biggest challenges in CNA-driven target identification is to distinguish true driver gene(s) from
passengers in a focal amplicon. It has been shown that multiple drivers may even coexist in a highly focal amplicon, such as CCND1 and FGF19.[9] It would be valuable to perform unbiased screening to validate all candidate somatic CNA drivers selleck inhibitor in appropriate models and then dissect key attributes that distinguish drivers from passengers to facilitate future in silico algorithm development. Toward this end, the genomic characterization of a comprehensive collection of 30 HCC cell line models in our study will also serve as a valuable resource for future research in this direction. The authors thank Drs. John Lamb and Soonmyung Paik for scientific discussion in this study, Peter C. Roberts for facilitating data management and transfer, and Sylvie Sakata for study support. Additional Supporting Information may be found in the online version of this article. Figure S1. Association between somatic CNA, mRNA expression and clinical outcome.