title: Gene signatures derived from a c-MET-driven liver cancer mouse model predict survival of patients with hepatocellular carcinoma.
abstract: Biomarkers 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.
authors.affiliation: Rosetta Inpharmatics LLC, Merck & Co., Inc., Seattle, Washington, United States of America. lrena_lvanovska@merck.com
authors.forename: Irena
authors.initials: I
authors.lastname: Ivanovska
authors.forename: Chunsheng
authors.initials: C
authors.lastname: Zhang
authors.forename: Angela M
authors.initials: AM
authors.lastname: Liu
authors.forename: Kwong F
authors.initials: KF
authors.lastname: Wong
authors.forename: Nikki P
authors.initials: NP
authors.lastname: Lee
authors.forename: Patrick
authors.initials: P
authors.lastname: Lewis
authors.forename: Ulrike
authors.initials: U
authors.lastname: Philippar
authors.forename: Dimple
authors.initials: D
authors.lastname: Bansal
authors.forename: Carolyn
authors.initials: C
authors.lastname: Buser
authors.forename: Martin
authors.initials: M
authors.lastname: Scott
authors.forename: Mao
authors.initials: M
authors.lastname: Mao
authors.forename: Ronnie T P
authors.initials: RT
authors.lastname: Poon
authors.forename: Sheung Tat
authors.initials: ST
authors.lastname: Fan
authors.forename: Michele A
authors.initials: MA
authors.lastname: Cleary
authors.forename: John M
authors.initials: JM
authors.lastname: Luk
authors.forename: Hongyue
authors.initials: H
authors.lastname: Dai
mesh_terms: D000818:Animals; D006528:Carcinoma, Hepatocellular / Q000175:diagnosis* / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D004195:Disease Models, Animal; D005260:Female; D006801:Humans; D008099:Liver / Q000166:cytology / Q000378:metabolism / Q000473:pathology; D008113:Liver Neoplasms / Q000175:diagnosis* / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D008297:Male; D051379:Mice; D008822:Mice, Transgenic; D011379:Prognosis; D019859:Proto-Oncogene Proteins c-met / Q000235:genetics*; D016019:Survival Analysis; D059467:Transcriptome
chemical_list: D019859:Proto-Oncogene Proteins c-met