Molecular prognostication of liver cancer: End of the beginning Snorri S. Thorgeirsson, Ju-Seog Lee, Joe W. Grisham  Journal of Hepatology  Volume 44, Issue 4, Pages 798-805 (April 2006) DOI: 10.1016/j.jhep.2006.01.008 Copyright © 2006 Terms and Conditions

Fig. 1 (A) Hierarchical clustering of 91 HCC tumors with 406 ‘survival genes’. The data are presented in matrix format in which rows represent the individual gene and columns represent each tissue. Each cell in the matrix represents the expression level of a gene feature in an individual tissue. The red and green colors in cells reflect high and low expression levels. (B) Significant association of gene expression patterns with patient survival. Kaplan–Meier plot of overall survival of HCC patients grouped on the basis of gene expression profiling shown in panel A. Journal of Hepatology 2006 44, 798-805DOI: (10.1016/j.jhep.2006.01.008) Copyright © 2006 Terms and Conditions

Fig. 2 Integrative functional genomics for early detection and personalized treatment of HCC. Gene expression signature for all HCC is extracted from human HCC data and used to identify serological markers for early detection. On the other hand, many independent gene expression data from in vitro and in vivo models are integrated with human HCC data to stratify patients into homogeneous subgroups. Each unique gene set will be used to identify serological markers and to develop the prediction models for stratification and prognosis of patients. In parallel, these gene sets will constitute the potential therapeutic targets for personalized treatment of HCC patients to uncover pathways that are most responsive to therapeutic intervention. Rationalized clinical trials using molecular stratification of HCC and novel targets will provide better therapeutic decision for patients in the future. HCC, hepatocellular carcinoma; ST, surrounding tissue. Journal of Hepatology 2006 44, 798-805DOI: (10.1016/j.jhep.2006.01.008) Copyright © 2006 Terms and Conditions