Techniques in DNA sequencing have advanced rapidly over the past few years. Next-generation sequencing (NGS) technology is an incredibly powerful tool that is transforming biomedical research, in large part because of technology improvements that have resulted in an astonishingly rapid decline in the cost of sequencing over time. NGS provides high-throughput information on genetic alterations, including single nucleotide variations, small insertions and deletions (indels), copy number variations, chromosomal rearrangements, and viral DNA integration. NGS technology is providing new insights into the highly complex process of liver carcinogenesis and is helping to identify key drivers of hepatocellular carcinoma (HCC) initiation and progression. This article briefly summarizes our current understanding of the pathogenesis of HCC and HCC tumor biology gained from recent studies using NGS technology to analyze HCC tumors. We also discuss potential strategies for harnessing this new information to improve therapy for patients with advanced HCC.
The first report of a comprehensive NGS study of HCC was published by Totoki et al. in 2011 (Table 1). HCC tumor tissue from a hepatitis C virus (HCV)–infected patient was sequenced with both whole genome sequencing (WGS) and whole exome sequencing (WES) approaches. A large number of previously uncharacterized genetic alterations, including 11,731 somatic nucleotide substitutions, 670 small indels, and 22 chromosomal rearrangements, were revealed. The genes harboring nonsynonymous substitutions and small indels in protein-coding regions included two tumor suppressor genes well known to be mutated in HCC [tumor protein p53 (TP53) and axin 1 (AXIN1)] and five genes known to be mutated in other cancer types but identified for the first time in this HCC [A disintegrin and metalloproteinase domain 22 (ADAM22), Janus kinase 2 (JAK2), KH domain containing RNA binding signal transduction associated 2 (KHDRBS2), NIMA-related kinase 8 (NEK8), and transformation/transcription domain-associated protein (TRRAP)]. One nonsense substitution in the tuberous sclerosis 1 gene was identified by WES but was not detected by WGS because of the small number of tumor alleles that harbored this substitution (13%). This suggested that only a small cancer cell population within the tumor contained this mutation and supported the concept of heterogeneity in genetic changes found within an individual tumor.
|Study||Patient Characteristics and Study Design||Major Findings||Strengths|
|Totoki et al. (2011)a, b||Single HCV-infected HCC||A substantial number of heterogeneous genetic alterations occurred within a single tumor (11,731||This is the first report of an HCC genome sequenced by NGS.|
|substitutions, 670 indels, and 22 rearrangements).|
|Matched normal lymphocyte DNA||Five novel mutations were found in ADAM22, JAK2, KHDRBS2, NEK8, and TRRAP.|
|Li et al. (2011)†||Discovery set: 10 HCV-infected HCCs||ARID2 is commonly mutated in HCCs of different etiologies.||There was a large, heterogeneous validation cohort.|
|Validation set: 139 HCCs with different etiologies|
|Matched noncancerous liver DNA|
|Tao et al. (2011)a, b||Single HBV-infected HCC||Mutated CCNG1 and P62 and a C5orf51- CPE4 fusion gene are drivers of HCC recurrence and metastasis.||This is the first extensive study of genetic alterations at different HCC stages by NGS.|
|Matched noncancerous liver DNA|
|Fujimoto et al. (2012)a||Discovery set: 27 HCC tumors||Mutations in chromatin remodeling family genes, including ARID1A, ARID1B, and ARID2, were present in 52% of the tumors and may be associated with aggressive HCC.||This is the first large-scale study of HCC genomes by WGS.|
|Validation set: 120 HCC tumors||HBV DNA integration was found in 8 of 11 HBV-induced HCCs (half occurred within or upstream of TERT).||Correlations between genetic changes and clinicopathological features were examined.|
|Matched normal lymphocyte DNA|
|Guichard et al. (2012)†||Discovery set: 24 HCCs||Mutations in chromatin remodeling genes were found in 24% of HCCs.||A novel interaction of oxidative stress and Wnt/β-catenin pathways was identified.|
|Validation set: 101 HCCs||Cell growth regulator IRF2 functions as a tumor suppressor by regulating p53 expression.||Novel mutated genes in known HCC pathways were identified.|
|Matched noncancerous liver DNA||Mutations were found in oxidative stress pathway genes, including NFE2L2.|
|Huang et al. (2012)†||Discovery set: 10 HBV-infected HCCs||Mutated ARID1A was found in 14 of 110 HCCs (13%) and may drive tumor metastasis.||This study addresses genetic changes in advanced HCCs.|
|Validation set: 100 HBV-infected HCCs||Novel mutations were found in genes regulating cell proliferation and survival, including the cell adhesion molecule encoding gene VCAM1.|
Li et al. applied WES to a larger number of HCV-related HCCs (n = 10) in a discovery set and then validated the findings in two independent cohorts of HCCs from patients with different HCC etiologies (n = 23 and n = 106). This study identified the chromatin remodeling gene AT rich interactive domain 2 (ARID2) as a commonly mutated gene in HCC and implied that ARID2 functions as a tumor suppressor gene in HCC on the basis of the predicted function of the mutated protein domains. The prevalences of ARID2 mutations in HCV-related, hepatitis B virus (HBV)–related, and non–viral-related HCCs were 14% (6/43), 2% (1/50), and 5% (2/44), respectively. The different prevalences of ARID2 mutations among HCCs of various etiologies supports the idea that HCCs of different etiologies have different profiles of genetic alterations. Six of nine tumors with mutated ARID2 also contained mutations in the catenin beta 1 (CTNNB1) gene encoding β-catenin, which is the major oncogene of the Wnt signaling pathway. Interestingly, none of the nine tumors had TP53 mutations, and this suggests that the mutation of either ARID2 or the TP53 gene is sufficiently permissive for carcinogenesis.
In a different study aimed at examining the clonal heterogeneity within a tumor and the genetic mechanisms for the acquisition of invasive and metastatic phenotypes in HCC, Tao et al. extensively studied the genomes of nine samples from three resected HCC nodules (seven samples from the primary tumor and one from each of the two recurrent tumors) and seven samples from the noncancerous tissue adjacent to the primary tumor from an HBV-infected patient by WGS, WES, and cell-population genetic analysis. After validation, 214 tumor-specific mutations were identified: 193 were noncoding, and 21 were coding. Nine point mutations and one deletion acquired during critical steps in HCC progression were identified and used to infer the evolution of the tumors. In the primary tumor, major and minor cancer cell populations were differentiated by four mutations, including within the cyclin G1 (CCNG1) encoding gene, and this suggests that these mutations facilitate tumor expansion. Mutations in CCNG1 and P62 and the formation of a chromosome 5 open reading frame 51 (C5orf51)–cytoplasmic polyadenylation element binding protein 4 (CPEB4) fusion gene due to the deletion of chromosome 5q were found to be driver alterations for HCC recurrence and intrahepatic metastasis. These alterations affected the cell cycle control, autophagy, and apoptosis pathways. Eighteen HBV DNA integrations—a key event for HCC development—were also observed. A cancer evolution analysis led to the conclusion that there was a prolonged period of accumulation of background mutations with predominant functions in inflammation, immunity, and cell anchoring. Subsequent to this, the rapid spread of a small number of foreground mutations in genes regulating the cell cycle and apoptosis mechanisms then led to the assertion of the cancer phenotype.
A larger scale study applying WGS to HCC genomes was conducted by Fujimoto et al. Genomes of 27 HCC tumors from 25 patients (HBV, 11; HCV, 14; and nonviral, 2) were sequenced. There were two sets of multicentric, synchronously occurring tumors that had similar whole genome substitution profiles but different mutation profiles; this suggested that the two tumors in each case developed independently within a similar context of genomic instability. Overall, a significant frequency of mutations was found in 15 genes. In addition to the expected mutations in the well-known HCC-associated genes TP53 and CTNNB1, somatic point mutations or indels in chromatin remodeling genes, including ARID1A, ARID1B, ARID2, myeloid/lymphoid or mixed-lineage leukemia (MLL), MLL3, bromodomain adjacent to zinc finger domain 2B (BAZ2B), bromodomain containing 8 (BRD8), bromodomain PHD finger transcription factor (BPTF), brain and reproductive organ-expressed (BRE), and histone cluster 1 H4b (HIST1H4B), were detected in 14 of 27 HCCs (52%). Decreased expression of these genes increased the proliferation of HCC cell lines, and this implied a tumor suppressor function of chromatin remodeling genes in HCC. HBV DNA integrations were found in 8 of the 11 HBV-induced HCCs, and 4 of these occurred within or upstream of the telomerase reverse transcriptase gene (TERT), which probably conferred a clonal advantage to these tumors. Interestingly, one tumor with a somatic nonsense mutation in the mutL homolog 1 DNA mismatch-repair gene had more than 33,000 somatic mutations with a predominance of C>T/G>A transitions at CpGs. A second tumor with an unidentified mismatch-repair defect showed similar characteristics of mismatch-repair deficiency. Overall, the etiological and genetic context of the individual appeared to significantly influence the pattern of somatic alterations that were seen. Significant correlations were found between somatic substitution patterns and habitual alcohol use, and a marginal association was found with the virus type.
The role of the chromatin remodeling pathway in HCC carcinogenesis was strongly supported by the findings from the study of another cohort of 125 HCC patients in which WES was performed on a subset of 24 tumors. In this cohort also, mutations in Wnt/β-catenin and p53 pathway genes were most frequent. Guichard et al. also found at least one mutated chromatin remodeling gene in 24% of HCCs. ARID1A and ARID2 mutations were present in 21 of 125 HCCs (17%) and in 7 of 125 HCCs (6%), respectively. ARID1A mutations were more frequent in alcohol-induced HCCs and were associated with CTNNB1 mutations. In addition, mutations in interferon regulatory factor 2 (IRF2), a cell growth–regulating gene, were identified in 6 of 125 HCCs (5%), which were exclusively HBV-induced. The biological function of IRF2 was studied with in vitro and in vivo experiments. An inactivating mutation of IRF2 decreased TP53 expression, and this suggests that IRF2 functions as a tumor suppressor by regulating the p53 pathway. Novel recurrent mutations were found in the ribosomal protein S6 kinase 90-kDa polypeptide 3 (RPS6KA3) gene, which encodes ribosomal S6 protein kinase 2, a feedback inhibitor of the extracellular signal-regulated kinase 1/2 pathway. RPS6KA3 mutations preferentially occurred in HCCs developing in the absence of cirrhosis and were associated with AXIN1 gene mutations. A potential role of the oxidative stress pathway in hepatocarcinogenesis was also revealed. The mutation of nuclear factor (erythroid-derived 2)-like 2 (NFE2L2), which encodes nuclear erythroid 2 p45-related factor 2, a transcription factor regulating the expression of antioxidant enzyme coding genes, was found in 8 of 125 HCCs (6%). A mutation in NFE2L2 was significantly correlated with CTNNB1 mutation, and this suggests that oxidative stress may cooperate with Wnt signaling pathway activation in HCC pathogenesis. A particularly striking finding was the fact that in contrast to most other solid tumor types, genetic variations in HCCs were characterized by the overrepresentation of G:C>T:A nucleotide transversions; this was particularly true for HCCs developing in the absence of cirrhosis. This observation may be related to a unique susceptibility of the liver to as yet unidentified genotoxic agents.
It is important to note that in most of the aforementioned studies, the HCC genomes were sequenced from tumor tissues obtained from surgical specimens. This approach is prone to a bias toward studying the genomes of early-stage HCCs. This issue was addressed by the most recent publication by Huang et al. The authors reported WES findings for HCC genomes and matched portal vein tumor thromboses (PVTTs), which were manifestations of advanced HCC with a poor prognosis, in 10 HBV-infected patients. The findings were then validated in an independent cohort of 100 HBV-induced HCCs. HCCs and PVTTs shared 94% of the identified somatic mutations. Genes mutated only in PVTTs were identified; they included lysine (K)-specific demethylase 6A (KDM6A), cullin 9 (CUL9), FYVE, RhoGEF and PH domain containing protein 6 (FGD6), A kinase anchor protein 3 (AKAP3), and ring finger protein 139 (RNF139). Mutated ARID1A was found in 14 of the 110 HBV-related HCC cases (13%). ARID1A appeared to be a key driver for HCC metastasis because mutated sequences were detected only in the HCC cell line that had the highest capacity for metastasis. Screening for potential driver gene mutations identified nonsilent mutations in homeobox A1 (HOXA1), vascular cell adhesion molecule 1 (VCAM1), transmembrane protein 35 (TMEM35), and phosphoinositide-3-kinase adaptor protein 1 (PIK3AP1). Finally, a loss of function RNA interference screen of 91 genes in eight HCC cell lines was undertaken to identify genes involved in cell proliferation or survival. Knockdown of VCAM1 and TMEM2 promoted HCC cell proliferation in four of the eight cell lines, whereas knockdown of cyclin-dependent kinase 14 (CDK14), HOXA1, TMEM35, elongation factor RNA polymerase II (ELL), and casein kinase 1 gamma 3 (CSNK1G3) suppressed cell proliferation in at least three of the eight cell lines.
In conclusion, WGS and WES are complementary approaches to the identification of genetic alterations in cancer. Growing evidence from NGS has revealed that the chromatin remodeling pathway is a major contributor to HCC carcinogenesis. Several new genes involved in previously known HCC pathways have also been discovered with these techniques (Fig. 1). This strategy, therefore, is identifying multiple potential new targets for HCC treatment.