Abstract
Liver cancer—also called hepatocellular carcinoma (HCC)—is the most frequent primary liver cancer in humans. As of today, it is mainly induced by chronic virus infections such as Hepatitis B and C viruses, which induce chronic hepatitis and fibrosis, the two most important conditions predisposing towards HCC development. Besides, chronic alcohol or drug consumption contributes to chronic liver injury and HCC development. Of note, in industrialized countries virus infections have recently been outcompeted by a high-fat and high-sugar diet as the most important etiology for HCC development in humans—now representing the fastest growing cancer in the USA as of today. It is believed that soon also in Europe high-fat diet caused HCC will become the fastest growing cancer. Today more than 800,000 people die every year due to cancer; however, despite a great research effort in the last 20 years, no efficient curative therapy is available at the moment. It has turned out that various subtypes of HCC exist in humans, complicating the therapy for HCC patients in general, and leading to the need for therapies of stratified patient cohorts as the variability of HCC phenotypes (6 different subtypes exist as of today) influences the responsiveness to treatment. Thus, it is important to dissect and characterize the various HCC subtypes in humans as well as in mouse models to identify the sub-cohorts that are responsive to particular therapies. One step to do so is the characterization of HCC nodules on genetic level. Here, we describe a protocol to characterize individual HCC nodules on genomic level, enabling to stratify the respective liver carcinoma and select them for a more targeted therapy.
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References
Haybaeck J et al (2009) A lymphotoxin-driven pathway to hepatocellular carcinoma. Cancer Cell 16:295–308
Van Beers EH et al (2006) A multiplex PCR predictor for aCGH success of FFPE samples. Br J Cancer 94:333–337
Hess J et al (2011) Gain of chromosome band 7q11 in papillary thyroid carcinomas of young patients is associated with exposure to low-dose irradiation. Proc Natl Acad Sci U S A 108: 9595–9600
Zitzelsberger H, Unger K (2011) DNA copy number alterations in radiation-induced thyroid cancer. Clin Oncol 23:289–296
R Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing. http://www.R-project.org
Van de Wiel MA et al (2007) CGHcall: calling aberrations for array CGH tumor profiles. Bioinformatics 23:892–894
Van de Wiel MA, van Wieringen WN (2007) CGHregions: dimension reduction for array CGH data with minimal information loss. Cancer Inform 3:55–63
Neuvial P et al (2006) Spatial normalization of array-CGH data. BMC Bioinformatics 7:264
Venkatraman ES, Olshen AB (2007) A faster circular binary segmentation algorithm for the analysis of array CGH data. Bioinformatics 23:657–663
Benjamini Y, Yekutieli D (2005) Quantitative trait loci analysis using the false discovery rate. Genetics 171:783–790
Vucur M et al (2013) RIP3 inhibits inflammatory hepatocarcinogenesis but promotes cholestasis by controlling caspase-8- and JNK-dependent compensatory cell proliferation. Cell Rep 4:776–790
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Unger, K., Heikenwälder, M. (2014). Analysis of Chromosomal Aberrations in Murine HCC. In: Waisman, A., Becher, B. (eds) T-Helper Cells. Methods in Molecular Biology, vol 1193. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1212-4_19
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DOI: https://doi.org/10.1007/978-1-4939-1212-4_19
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Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-1211-7
Online ISBN: 978-1-4939-1212-4
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