Characterization of susceptibility based on age and gender. (A,B) Liver samples were scored as described in the text, and the data are represented as number of liver nodules (≥0.5 cm) per mouse, over the time course of collection in the various groups of mice (top panel). The bottom panel shows the size of these liver nodules in the various categories of mice. Nodules <0.5 cm were scored as 0.2 cm for ease of enumeration, and were counted in this case. Data for mice injected at D7 (A) and 6 M or 12 M (B) are shown. Each dot represents a single mouse (top) or nodule (bottom). Horizontal bars represent average numbers of nodules (top panel). (C,D) Effect of gender on liver nodule development was determined by scoring the percentage of male or female mice with nodules (0.2 cm and above) at the various time points of collections, after injection at D7 (C) or at 6 M (D). *P≤0.05; ns, not significant.

Histological analysis of liver sections. (A-D) Liver samples were H&E-stained and analyzed by photomicrography from the various categories of mice injected at D7, at the different time points of collection. Representative pictures from at least six independent mice for each time point/category are shown. Liver tumors from each case, at 15 M of age, are shown in the last image of B-D (denoted by ‘Tumor - 15’). (E) Comparison of mouse liver nodules at 15 M with human HCC and adenoma.

Genomic characteristics of mouse HCC model. (A) Transcriptome profiling of normal livers and liver nodules from the various groups were performed by Affymetrix mouse arrays. PCA, shown in the left panel, revealed distinct clustering of tumor and normal samples, with adjacent normal clustered between tumor and normal samples. Each data point represents one sample and the ellipsoids represent the zone within 2 s.d. of each experimental group. Right panel shows the heat map of unsupervised hierarchical clustering based on probes with s.d.≥1, which reveals distinct clustering of tumor and normal samples. Within the tumor group, differential clustering was also observed based on genotype. Treatment parameters are indicated on the sides. (B) Heat map of 11 genes found to be differentially expressed between HBsAg_Oil_T and HBsAg_Oil_N in the mouse HCC model. Distinct clustering was observed as expected between tumor and normal samples, based on the expression pattern of these genes. Seven genes (underlined) could be mapped to human microarray chips.

HCC-specific gene expression signature. (A,B) Differential clustering between tumor and normal samples was observed when segregated by the HCC gene expression signature, similar to the mouse HCC model. (C,D) Heat map of unsupervised clustering based on the gene signature in human breast cancers (C) or colon cancers (D) showed less differential clustering of tumor and normal samples. (E) Summary of SVM model analysis of sensitivity of the gene expression signature to identify the human tumor types.