gene signatures derived from a c-met-driven liver cancer mouse model predict survival of patients with hepatocellular carcinoma基因签名来自c-met-driven肝癌小鼠模型预测肝细胞癌患者的生存.pdfVIP

gene signatures derived from a c-met-driven liver cancer mouse model predict survival of patients with hepatocellular carcinoma基因签名来自c-met-driven肝癌小鼠模型预测肝细胞癌患者的生存.pdf

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gene signatures derived from a c-met-driven liver cancer mouse model predict survival of patients with hepatocellular carcinoma基因签名来自c-met-driven肝癌小鼠模型预测肝细胞癌患者的生存

Gene Signatures Derived from a c-MET-Driven Liver Cancer Mouse Model Predict Survival of Patients with Hepatocellular Carcinoma 1,4 1,4 2,3 3 2 Irena Ivanovska *, Chunsheng Zhang , Angela M. Liu , Kwong F. Wong , Nikki P. Lee , Patrick 1 4 4 5 4 1¤a 2 Lewis , Ulrike Philippar , Dimple Bansal , Carolyn Buser , Martin Scott , Mao Mao , Ronnie T. P. Poon , Sheung Tat Fan2, Michele A. Cleary1¤b, John M. Luk2,3*, Hongyue Dai1,4* 1 Rosetta Inpharmatics LLC, Merck Co., Inc., Seattle, Washington, United States of America, 2 Department of Surgery, The University of Hong Kong, Pokfulam, Hong Kong, China, 3 Department of Pharmacology, Department of Surgery, and Cancer Science Institute, National University of Singapore, Singapore, Singapore, 4 Merck Research Laboratories, Merck Co., Inc., Boston, Massachusetts, United States of America, 5 Molecular Profiling and Pharmacology, Merck Co., Inc., North Wales, Pennsylvania, United States of America 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

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