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Article: Gene signatures derived from a c-MET-driven liver cancer mouse model predict survival of patients with hepatocellular carcinoma

TitleGene signatures derived from a c-MET-driven liver cancer mouse model predict survival of patients with hepatocellular carcinoma
Authors
Issue Date2011
PublisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.action
Citation
Plos One, 2011, v. 6 n. 9 How to Cite?
AbstractBiomarkers derived from gene expression profiling data may have a high false-positive rate and must be rigorously validated using independent clinical data sets, which are not always available. Although animal model systems could provide alternative data sets to formulate hypotheses and limit the number of signatures to be tested in clinical samples, the predictive power of such an approach is not yet proven. The present study aims to analyze the molecular signatures of liver cancer in a c-MET-transgenic mouse model and investigate its prognostic relevance to human hepatocellular carcinoma (HCC). Tissue samples were obtained from tumor (TU), adjacent non-tumor (AN) and distant normal (DN) liver in Tet-operator regulated (TRE) human c-MET transgenic mice (n = 21) as well as from a Chinese cohort of 272 HBV- and 9 HCV-associated HCC patients. Whole genome microarray expression profiling was conducted in Affymetrix gene expression chips, and prognostic significances of gene expression signatures were evaluated across the two species. Our data revealed parallels between mouse and human liver tumors, including down-regulation of metabolic pathways and up-regulation of cell cycle processes. The mouse tumors were most similar to a subset of patient samples characterized by activation of the Wnt pathway, but distinctive in the p53 pathway signals. Of potential clinical utility, we identified a set of genes that were down regulated in both mouse tumors and human HCC having significant predictive power on overall and disease-free survival, which were highly enriched for metabolic functions. In conclusions, this study provides evidence that a disease model can serve as a possible platform for generating hypotheses to be tested in human tissues and highlights an efficient method for generating biomarker signatures before extensive clinical trials have been initiated. © 2011 Ivanovska et al.
Persistent Identifierhttp://hdl.handle.net/10722/143475
ISSN
2014 Impact Factor: 3.234
2013 SCImago Journal Rankings: 1.724
PubMed Central ID
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorIvanovska, Ien_HK
dc.contributor.authorZhang, Cen_HK
dc.contributor.authorLiu, AMen_HK
dc.contributor.authorWong, KFen_HK
dc.contributor.authorLee, NPen_HK
dc.contributor.authorLewis, Pen_HK
dc.contributor.authorPhilippar, Uen_HK
dc.contributor.authorBansal, Den_HK
dc.contributor.authorBuser, Cen_HK
dc.contributor.authorScott, Men_HK
dc.contributor.authorMao, Men_HK
dc.contributor.authorPoon, RTPen_HK
dc.contributor.authorFan, STen_HK
dc.contributor.authorCleary, MAen_HK
dc.contributor.authorLuk, JMen_HK
dc.contributor.authorDai, Hen_HK
dc.date.accessioned2011-12-02T05:19:30Z-
dc.date.available2011-12-02T05:19:30Z-
dc.date.issued2011en_HK
dc.identifier.citationPlos One, 2011, v. 6 n. 9en_HK
dc.identifier.issn1932-6203en_HK
dc.identifier.urihttp://hdl.handle.net/10722/143475-
dc.description.abstractBiomarkers derived from gene expression profiling data may have a high false-positive rate and must be rigorously validated using independent clinical data sets, which are not always available. Although animal model systems could provide alternative data sets to formulate hypotheses and limit the number of signatures to be tested in clinical samples, the predictive power of such an approach is not yet proven. The present study aims to analyze the molecular signatures of liver cancer in a c-MET-transgenic mouse model and investigate its prognostic relevance to human hepatocellular carcinoma (HCC). Tissue samples were obtained from tumor (TU), adjacent non-tumor (AN) and distant normal (DN) liver in Tet-operator regulated (TRE) human c-MET transgenic mice (n = 21) as well as from a Chinese cohort of 272 HBV- and 9 HCV-associated HCC patients. Whole genome microarray expression profiling was conducted in Affymetrix gene expression chips, and prognostic significances of gene expression signatures were evaluated across the two species. Our data revealed parallels between mouse and human liver tumors, including down-regulation of metabolic pathways and up-regulation of cell cycle processes. The mouse tumors were most similar to a subset of patient samples characterized by activation of the Wnt pathway, but distinctive in the p53 pathway signals. Of potential clinical utility, we identified a set of genes that were down regulated in both mouse tumors and human HCC having significant predictive power on overall and disease-free survival, which were highly enriched for metabolic functions. In conclusions, this study provides evidence that a disease model can serve as a possible platform for generating hypotheses to be tested in human tissues and highlights an efficient method for generating biomarker signatures before extensive clinical trials have been initiated. © 2011 Ivanovska et al.en_HK
dc.languageengen_US
dc.publisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.actionen_HK
dc.relation.ispartofPLoS ONEen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subject.meshCarcinoma, Hepatocellular - diagnosis - genetics - metabolism - pathology-
dc.subject.meshLiver - cytology - metabolism - pathology-
dc.subject.meshLiver Neoplasms - diagnosis - genetics - metabolism - pathology-
dc.subject.meshProto-Oncogene Proteins c-met - genetics-
dc.subject.meshTranscriptome-
dc.titleGene signatures derived from a c-MET-driven liver cancer mouse model predict survival of patients with hepatocellular carcinomaen_HK
dc.typeArticleen_HK
dc.identifier.emailLee, NP: nikkilee@hku.hken_HK
dc.identifier.emailPoon, RTP: poontp@hkucc.hku.hken_HK
dc.identifier.emailFan, ST: stfan@hku.hken_HK
dc.identifier.emailLuk, JM: jmluk@hkucc.hku.hken_HK
dc.identifier.authorityLee, NP=rp00263en_HK
dc.identifier.authorityPoon, RTP=rp00446en_HK
dc.identifier.authorityFan, ST=rp00355en_HK
dc.identifier.authorityLuk, JM=rp00349en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1371/journal.pone.0024582en_HK
dc.identifier.pmid21949730en_US
dc.identifier.pmcidPMC3174972en_US
dc.identifier.scopuseid_2-s2.0-80052841535en_HK
dc.identifier.hkuros197816-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80052841535&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume6en_HK
dc.identifier.issue9en_HK
dc.identifier.isiWOS:000295173800028-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridIvanovska, I=6507113691en_HK
dc.identifier.scopusauthoridZhang, C=9747304800en_HK
dc.identifier.scopusauthoridLiu, AM=36134439500en_HK
dc.identifier.scopusauthoridWong, KF=49362744900en_HK
dc.identifier.scopusauthoridLee, NP=7402722690en_HK
dc.identifier.scopusauthoridLewis, P=35083820500en_HK
dc.identifier.scopusauthoridPhilippar, U=6506975144en_HK
dc.identifier.scopusauthoridBansal, D=46061812500en_HK
dc.identifier.scopusauthoridBuser, C=7004680051en_HK
dc.identifier.scopusauthoridScott, M=7403481621en_HK
dc.identifier.scopusauthoridMao, M=7102960472en_HK
dc.identifier.scopusauthoridPoon, RTP=7103097223en_HK
dc.identifier.scopusauthoridFan, ST=7402678224en_HK
dc.identifier.scopusauthoridCleary, MA=7202006129en_HK
dc.identifier.scopusauthoridLuk, JM=7006777791en_HK
dc.identifier.scopusauthoridDai, H=7402206916en_HK
dc.identifier.citeulike11367281-

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