Transcriptomic classification of HCC

Read Also

During the last 10 years, analysis of a large number of human HCC using expression microarray techniques enabled to identify new sub-groups of tumors defined by specific deregulation of expression of gene networks. Comparisons with functional gene modification induced in animal models or cell lines allowed to characterize the nature of these networks. The first example of integrative analyzes of transcriptomic and functional was done in the Snorri Thorgeirsson’s laboratory (NCI, Bethesda, USA). In 2006, by integrating gene expression data from rat fetal hepatoblasts with HCC from human and mouse models, this team identified a subgroup of HCC that may arise from hepatic progenitor cells⁸. Importantly, this subgroup of tumors shared a gene expression pattern with fetal hepatoblasts and had a poor prognosis.

In our series of HCC surgically treated in France, we performed a genome wide transcriptomic analysis of 60 tumors together with an exhaustive characterization of structural genetic alterations and clinical parameters ³⁶. In this study, unsupervised transcriptomic analysis identified six robust subgroups of HCC (termed G1 to G6) associated with clinical and genetic characteristics (Figure 1). The main classification divider was the chromosome stability status. Tumors from group G1 to G3 were chromosome instable whereas tumors from G4 to G6 were chromosome stable. Indeed, tumors presenting chromosome instable phenotype demonstrated a trancriptomic profile strikingly different from chromosome stable ones (Figure 1). Chromosome instability appears as the main driver of tumor classification as previously shown in classifications based on chromosomal and genetic aberrations ^{20, 21, 28, 37}. In addition, genetic alterations and pathways analyses allowed for a refined transcriptomic classification: G1-tumors were related to a low copy number of HBV and overexpression of genes expressed in fetal liver and controlled by parental imprinting; G2 included HCC infected with a high copy number of HBV, PIK3CA and TP53 mutated cases; G3-tumors were TP53 mutated without HBV infection, a frequent P16 methylation and showed over-expression of genes controlling cell-cycle; G4 was a heterogeneous subgroup of tumors including TCF1 mutated adenomas and carcinomas; G5 and G6, were strongly related to ß-catenin mutations leading to Wnt pathway activation; G6-tumors presented satellite nodules, higher activation of the Wnt pathway and a E-cadherin under-expression. This 6-group classification has clinical application regarding the development of targeted therapies for HCC because specific pathway activations, particularly AKT and Wnt pathways, are closely associated to subgroups G1-G2 and G5-G6 respectively. Therefore we identified and validated a robust 16-gene signature to classify HCC tumors into the 6-group transcriptomic classification. This signature should be very useful to determine alterations of specific pathways and to predict putative response to targeted drugs ³⁶.

Actually several transcriptomic analyses have been reported ^{7, 8, 36, 38-45}. Successively, a large number of molecular subgroups of tumors have been identified underlining the broad diversity of HCC in human. Despite disparities among studies in term of risk factors, geographical origin, grading of the tumors, some similar subgroups of tumors have been recurrently identified. In an attempt to describe a common molecular classification, Hoshida and collaborators performed the first “biostatistical meta-analysis” of 9 different transcriptome HCC studies⁴⁵. This constitutes an important opening step to construct an international consensus defining common bases of a robust molecular classification of HCC.