Integrative Genomic Analysis Identifies the Core Transcriptional Hallmarks of Human Hepatocellular Carcinoma

Abstract

Integrative genomics helped characterize molecular heterogeneity in hepatocellular carcinoma (HCC), leading to targeted drug candidates for specific HCC subtypes. However, no consensus was achieved for genes and pathways commonly altered in HCC. Here, we performed a meta-analysis of 15 independent datasets (n = 784 human HCC) and identified a comprehensive signature consisting of 935 genes commonly deregulated in HCC as compared with the surrounding nontumor tissue. In the HCC signature, upregulated genes were linked to early genomic alterations in hepatocarcinogenesis, particularly gains of 1q and 8q. The HCC signature covered well-established cancer hallmarks, such as proliferation, metabolic reprogramming, and microenvironment remodeling, together with specific hallmarks associated with protein turnover and epigenetics. Subsequently, the HCC signature enabled us to assess the efficacy of signature-relevant drug candidates, including histone deacetylase inhibitors that specifically reduced the viability of six human HCC cell lines. Overall, this integrative genomics approach identified cancer hallmarks recurrently altered in human HCC that may be targeted by specific drugs. Combined therapies targeting common and subtype-specific cancer networks may represent a relevant therapeutic strategy in liver cancer. Cancer Res; 76(21); 6374-81. ©2016 AACR.

Figure 1

Large scale meta-analysis of public genomic data identifies core transcriptional hallmarks in human HCC. A, analytical workflow of the meta-analysis that led to the identification of a core gene expression signature in human HCC (935-gene HCC signature). B, heat map of the 935-gene HCC signature. Induced and repressed genes in HCC as compared to the surrounding non-tumor tissue are represented in red and green respectively. Missing values are colored in grey. Numbers on the top represent the 15 HCC microarray datasets that were investigated to derive the signature. C, specific enrichment of induced (left) and repressed (right) genes of the 935-gene HCC signature on specific chromosomal arms. D, gene ontology analysis of induced (left) and repressed (right) genes of the 935-gene HCC signature highlighting functional cancer hallmarks. E, top gene networks identified by Ingenuity Pathway Analysis. Highlighted networks were associated with cell cycle and proliferation for induced genes (left) and with cellular metabolism for repressed genes (right). DAVID, database for annotation, visualization and integrated discovery; FDR, false discovery rate; HCC, hepatocellular carcinoma; ST, surrounding non-tumor tissue.

Figure 2

The 935-gene HCC signature highlights relevant drug candidates. A, connectivity map algorithm applied to the 935-gene HCC signature identified 5 candidate molecules: trichostatin A, LY294002, vorinostat, rapamycin, resveratrol and α-estradiol. The barview shows the enrichment of treatment instance ordered by their corresponding connectivity scores. All selected drug candidates exhibit a significant negative enrichment as regard to the 935-gene HCC signature. B, impact of identified drug candidates on the viability of 6 human HCC cell lines. Cell viability was determined after 72hrs of treatment with drugs at various concentrations (see methods, n=4 independent experiments). Each bar represents cell viability (mean ± SD) in the investigated cell lines (SNU-475, SNU-449, SNU-423, SNU-387, HepG2/C3A, SK-Hep-1, from left to right). A two-tailed non-parametric Mann-Whitney test was used for the comparison between experimental groups for each cell line (DMSO vs. untreated control and drug vs. DMSO). * denotes a P value <0.05. C, Gene set enrichment analysis (GSEA) of the induced genes (upper 3 panels) and the repressed genes (lower 3 panels) from the 935-gene HCC signature in the gene expression profiles of the SNU-423 cell line treated with DMSO or vorinostat (left 2 panels), resveratrol (middle 2 panels) and sorafenib (right 2 panels). Positive and negative enrichment scores (ES) were determined by GSEA. DMSO, dimethyl sulfoxide; HCC, hepatocellular carcinoma.

Figure 3

Therapeutic strategies integrating core and subtype-specific transcriptional hallmarks in human HCC. The meta-analysis presented in this study enhances our knowledge on the molecular characterization of HCC tumors and echoes previous studies focused on HCC stratification. Recently, a consensus has been achieved identifying 3 main HCC molecular subtypes (S1, S2 and S3) (6). S1 and S2 subtypes are associated with a poor prognosis and included highly proliferative and poorly differentiated tumors. S1 subtype is particularly associated with the activation of a pro-metastatic TGFβ signaling and the S2 subtype included tumors with a progenitor-like phenotype. S3 subtype is associated with a better prognosis, low proliferation and includes well-differentiated tumors that retained a hepatocyte-like phenotype. At the molecular level the S3 subtype is enriched in tumors that exhibit activating mutations in CTNNB1 gene encoding β-catenin. HCC stratification into homogeneous subtypes opened new avenues for personalized targeted therapies. The highlighting of core transcriptional hallmarks in human HCC suggests that efficient therapies should consider drugs targeting common HCC hallmarks together with drugs targeting specific HCC subtypes. CTNNB1^mut, mutated beta-catenin gene; HCC, hepatocellular carcinoma; TGFβ, transforming growth factor beta.