Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma

Abstract

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy. Here, we performed high-resolution copy-number analysis on 125 HCC tumors and whole-exome sequencing on 24 of these tumors. We identified 135 homozygous deletions and 994 somatic mutations of genes with predicted functional consequences. We found new recurrent alterations in four genes (ARID1A, RPS6KA3, NFE2L2 and IRF2) not previously described in HCC. Functional analyses showed tumor suppressor properties for IRF2, whose inactivation, exclusively found in hepatitis B virus (HBV)-related tumors, led to impaired TP53 function. In contrast, inactivation of chromatin remodelers was frequent and predominant in alcohol-related tumors. Moreover, association of mutations in specific genes (RPS6KA3-AXIN1 and NFE2L2-CTNNB1) suggested that Wnt/β-catenin signaling might cooperate in liver carcinogenesis with both oxidative stress metabolism and Ras/mitogen-activated protein kinase (MAPK) pathways. This study provides insight into the somatic mutational landscape in HCC and identifies interactions between mutations in oncogene and tumor suppressor gene mutations related to specific risk factors.

Figure 1

Comparison of mutation profiles in HCC. a, Number of gene mutations in each HCC. b, Frequency of indels and nucleotide substitutions in each HCC. c–d, Fraction of nucleotide substitutions on the transcribed (blue) and the non transcribed (red) strand from the list of somatic mutations identified the exome sequencing of 24 HCC (means with 95% IC, c) and the complete list of gene mutations found in a series of validation of 125 HCC (absolute number of variants per HCC is indicated, d). P-values refer to significant (P=0.0003 and 0.002) elevation in G-to-T transversion on the non-transcribed strand and T-to-C transition on the transcribed strand, respectively.

Figure 2

Overview of mutations and major associated clinical features. The heatmap displays genes (row) and tumors (columns) with or without mutations (dark blue) or homozygous deletion (clear blue). The total number of cases (resp. genes) in which each gene (resp. case) contained a mutation is shown. The number of events is indicated. Potential occurrence with major clinical and pathological features and whole-exome sequenced cases are pointed (dark red).

Figure 3

Altered pathways and somatic mutation spectra in 125 HCC. a, Major pathways commonly altered by somatic mutations or homozygous gene deletions. Alteration frequencies are expressed as a percentage mutation and/or homozygous deletion in the validation series of 125 (red or blue when activated or inactivated, respectively) or 24 exome-sequenced (grey) HCC; for unique gene mutation, no frequency is indicated. Arrows are positive interactions and lines are inhibitory interactions. b, Spectrum of somatic mutations identified in HCC. Inactivating and activating mutations are shown above and below the core protein, respectively. Functional domains are colored boxes. ANK: Ankyrin repeat, ARM: Armadillo repeat, βCatB: βCatenin binding Domain, CDH: Cadherin Domain, Cyt: Cytosolic Domain, DBD: DNA Binding domain, Dim: Dimerization Domain, GSK3B: GSK3 Binding Domain, GTPB: GTP binding Domain, IL6BD: IL6 Binding Domain, K: Kinase domain, LID: Lipid interaction domain, Neh: Nrf2-ECH Homology Domain, NES: Nuclear Export Signal, NLS: Nuclear Localization Signal, NTD: Negative Transactivation Domain, P53B: P53 Binding Domain, P85B: P85 Binding Domain, PP2AB: PP2A Binding Domain, RasB: Ras Binding Domain, RGS: regulator of G-protein signalling, TD: Transactivation domain, TM: Transmembrane domain, UbD: Ubiquitinylated domain.

Figure 4

IRF2 is a new tumor suppressor gene in HCC that controls the P53 pathway. a, Effect of in vitro IRF2 silencing in HepaRG cell line: increased cell proliferation with IRF2 siRNA (siIRF2) when compared to control siRNA (siControl) in triplicate with regression analysis. Relative mRNA and protein expression were quantified by qRT-PCR and Western blot, respectively (n=3; mean ± SD). b, IRF2 overexpression in HepaRG cell line (pIRF2) induced dramatic cell death when compared to HepaRG transfected with an empty plasmid (pControl) in triplicate with regression analysis. Relative mRNA and protein expression (n=3; mean ± SD). c, Increased apoptosis in HepaRG cells overexpressing IRF2 compared to pControl: flow cytometry analysis shows a higher percentage of AnV+, IP+ cells with pIRF2 (n=3; mean ± SD). d. Stable IRF2 silencing by shRNAs (shIRF2(1) and shIRF2(2)) in HepaRG cell line enhanced tumor growth in a subcutaneous xenograft mouse model (n=5; mean tumor volume ± SD). Immunohistochemical analysis of IRF2 in xenograft tumor with shControl and shIRF2 HepaRG cell confirmed IRF2 silencing. e, Western-blot analysis comparing P53 (53 kDa), IRF2 (39 kDa) and βActin (42 kDa) expression levels between HepaRG cells transfected with siControl and siIRF2 (siIRF2(1) and siIRF2(2)) after 48h, 72h and 96h transfection. Western-blot analysis shows reduced expression of P53 following IRF2 silencing. Strong positive correlation between P53 and IRF2 expression levels was observed (linear regression analysis, Pearson correlation). f, P53 pathway target genes expression in HepaRG cells with silenced (blue) or enhanced (red) IRF2 expression, qRT-PCR data were normalised to the mean expression with siControl or pControl indicated by a line, respectively (n=3; mean ± SD).