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Genome sequencing analysis of liver cancer for precision medicine
Accepted Manuscript Title: Genome Sequencing Analysis of Liver Cancer for Precision Medicine Authors: Hidewaki Nakagawa, Masashi Fujita, Akihiro Fujimoto PII: DOI: Reference:
S1044-579X(17)30229-8 https://doi.org/10.1016/j.semcancer.2018.03.004 YSCBI 1463
To appear in:
Seminars in Cancer Biology
Received date: Revised date: Accepted date:
29-11-2017 19-3-2018 28-3-2018
Please cite this article as: Nakagawa H, Fujita M, Fujimoto A, Genome Sequencing Analysis of Liver Cancer for Precision Medicine, Seminars in Cancer Biology (2010), https://doi.org/10.1016/j.semcancer.2018.03.004 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Genome Sequencing Analysis of Liver Cancer for Precision Medicine Hidewaki Nakagawa1, Masashi Fujita1, and Akihiro Fujimoto1,2 1
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Laboratory for Genome Sequencing Analysis, RIKEN Center of Integrative medical Sciences, Tokyo 108-8639, Japan 2 Department of Drug Discovery Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8507, Japan *
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Corresponding should be addressed to H. Nakagawa (4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan), Email address: [email protected]
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Abstract Liver cancer is the third leading cause of cancer-related death worldwide. Some thousands of liver cancer genome have been sequenced globally so far and most of driver
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genes/mutations with high frequency are established in liver cancer, including Wnt/catenin pathway, TP53/cell-cycle pathways, telomere maintenance, and chromatin regulators. HBV integration into cancer-related genes is also a driver event in hepatocarcinogenesis. These genes are affected by structural variants, copy-number
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alterations and virus integrations as well as point mutations. Etiological factors of liver cancer is most understood among common cancers, such as hepatitis, aflatoxin, alcohol, and metabolic diseases, and mutational signatures of liver cancer can provide evidence of the association between specific etiological factors and mutational signatures. Molecular classifications based on somatic mutations profiles, RNA expression profiles, and DNA methylation profiles are related with patient prognosis. For precision medicine, several actionable mutations with solid evidence such as targets of multi-kinase inhibitors is observed in liver cancer, but there is few molecular target therapy so far. It is possible that rare actionable mutations in liver cancer can guide other specific molecular therapy and immune therapy
Keywords Liver cancer, genome sequencing, mutational signature, actionable gene, precision medicine
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1. Introduction Liver cancer is the third leading cause of cancer-related death worldwide, estimated to be responsible for nearly 746,000 deaths in 2012 (9.1% of the total) according to the International Agency for Research on Cancer (IARC) [1, 2]. Its prevalence is quite different among ethnic groups or areas; liver cancer is most common in East/SouthEastern Asian and African areas [1, 2], which is dependent on the prevalence of virus hepatitis. The most important etiological factor is virus infection, HBV (hepatitis B virus) and HCV (hepatitis C virus), and alcohol-induced liver damage also ranks high, mainly in Western countries. There is also a growing problem with hepatitis which develops in
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the setting of nonalcoholic fatty liver disease (NAFLD), or nonalcoholic steatohepatitis (NASH). NASH typically develops in the setting of obesity, type 2 diabetes, dyslipidemia, and hypertension, which is a significant problem in the developed countries [3]. Virus infection and metabolic stress induce liver damage such as fatty change, hepatitis, and cirrhosis, which set premalignant conditions for liver cancer through regeneration or cell cycle turnover and inflammatory environment. Chronic inflammation, virus infection, and liver regeneration have been reported to induce genetic and epigenetic damage to the genome [4]. Most liver cancers gradually develop from these premalignant stages by accumulation of these genetic alterations. Accordingly, highly damaged livers are extremely susceptible to multiple liver tumors.
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Despite the recent progress in diagnostic and therapeutic modalities such as radiofrequency ablation, multi-kinase inhibitors and liver transplantation, the 5-year survival rate of liver cancer is still 5-10% [3]. Characteristically, liver cancer shows a high rate of recurrence or multi-centric occurrence in strong carcinogenic backgrounds such as chronic hepatitis and liver cirrhosis. Liver function also determine the patient prognosis and therapeutic options, and patients with liver dysfunction cannot tolerant to surgery and other therapy, leading to poor prognosis. Therefore, new treatments, including molecular therapies for inoperable cases, and preventive strategies have been intensively sought, based on the biological feature and molecular profile of each patient. Innovation in DNA sequencing (NGS) technologies and computational analysis for
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these massive data have enabled us to analyze comprehensive profile of cancer genome and transcriptome in a large scale. This approach can rapidly identify potential driver genetic events, especially potential molecular therapeutic targets, in cancer [5]. Along with the application of NGS technologies in cancer research, international or domestic networks of cancer genome research have been initiated to effectively promote cancer genome sequencing and share high-quality data among scientists, such as the International Cancer Genome Consortium (ICGC) [6] and The Cancer Genome Atlas 2
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(TCGA) in the USA [7]. These projects collected samples with distinct epidemiological (virus and alcohol) and ethnic (Japanese, China, USA, and France) backgrounds, and the integration of these huge datasets is providing a much clearer understanding of the association between molecular or genetic features and epidemiological, environmental, and ethnic factors in liver cancer. Furthermore, now NGS technology is used for clinical sequencing or clinical setting as cancer precision medicine, which analyzes and identify actionable genes or mutations in the listed genes with actionability, and enter the patients with specific mutations into clinical trials. Here we summarize recent genome sequencing studies of liver cancer which cover
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driver gene discovery, virus integration, and mutational signatures. Based on these sequencing data, we also discuss about clinical sequencing in precision medicine for liver cancer.
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2. Whole genome/exome sequencing analyses for liver cancers A number of comprehensive genome sequencing studies by exome and whole genome sequencing (WGS) were conducted for liver cancer in the world. Whole exome sequencing (WES) can efficiently detect mutations in protein-coding exons, which are much more easily interpretable than mutations or variants in non-coding regions; this analysis was the most common platform for ICGC/TCGA projects. This approach
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involves target-enrichment of whole protein-coding exons of the human genome (30–40 Mb, approximately 1-2% of the human genome) using in-solution RNA or oligonucleotide DNA probe hybridization technologies [8]. The accuracy of sequencing analysis by using NGS is basically dependent on the sequence depth or coverage of the target regions, and WES following target-enrichment can usually cover more than ×80 sequence depth, which enables more accurate detection of single nucleotide variants (SNVs) and short indels than WGS. On the other hand, whole genome sequencing (WGS) can cover almost all the human genome sequences (approximately 3 Gb) and detect variants in non-coding regions, structural variants (SVs), copy number alterations (CNAs), and virus integrations in addition to SNV and short indels. This strategy is much more
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comprehensive and suitable for analyzing the cancer genome, because various kinds of mutations occurs in cancer genome. Following the evolutional progress of NGS technology and informatics, the cost and labor of WGS is rapidly dropping down and it is becoming a central technology for human and cancer genome analysis. Initial exome sequencing analysis for liver cancer in 2011, which did not cover the whole exome region but analyzed exons of ~18,000 genes, identified recurrent mutations of ARID2, which was further validated in more than 120 additional cases [9]. The whole 3
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genome of one HCV-related liver cancer was unveiled in 2011 by using NGS approach and demonstrated its genomic features in high resolution and intratumoral heterogeneity [10]. Whole genomes of multiple regions of one HBV-related liver cancer and its intrahepatic metastases were sequenced by NSG [11]. Jiang et al. analyzed whole genomes of four HBV-related liver cancer genomes by NGS [12] and detected a number of HBV integrations. WES analysis combined with copy-number analysis using SNP arrays for mainly alcohol-related liver cancers in France [13] showed that several pathways were involved in liver carcinogenesis. WGS analyses for 27 Japanese liver cancers [14] and 88 Chinese HBV-related liver cancers [15] detected driver mutations and
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HBV integrations comprehensively. WGS analysis on Japanese 300 liver cancers demonstrated structural variants and non-coding mutations [16], and TCGA consortium summarized comprehensive and integrative genomic characterization of hepatocellular carcinoma by combining WES, SNP chips, RNA analysis and DNA methylation analysis [17]. In clinical setting for precision medicine, it is important to accurately detect somatic mutations, and at present target deep sequencing is most common in cancer. However, if cost of WGS and computational burden are decreased in the near future, WGS could be a standard platform of clinical sequencing for cancer. In that case, computational methods for mutation detection should be standardized or be evaluated for its accuracy, because false-negative and false-positive of the NGS diagnosis is dependent on the computational
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algorisms [18]
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3. Mutated driver genes in liver cancer A number of genomic studies have attempted to elucidate molecular alterations in liver cancer. The list contains components of the p53/cell-cycle pathway (TP53 and CDKN2A), and Wnt pathway (CTNNB1 and AXIN1). Genome-wide copy number analyses also identified amplified regions including MYC and CCND1 and deleted regions such as CDKN2A [17]. NGS-based genome sequencing studies of liver cancer genomes can identify somatically mutated genes in an unbiased way and have almost established driver gene sets in liver cancer below. The list of driver genes for liver cancer is in Table 1.
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1) Wnt/-catenin pathway (Figure 1) Wnt/-catenin pathway is involved with organ development, regulation of cell stemness and oncogenesis through regulating cell proliferation, mobility, and polarity. Mutations of the molecules in this pathway are found in 40-50% of liver cancer. Mainly, point mutations in exon 3 of CTNNB1 (-catenin) can stabilize -catenin protein and can translate it into nucleus [19], trans-activating the downstream oncogenic molecules such 4
as Myc and CCND1 (cyclin D1). AXIN1 plays a critical role in degradation of -catenin protein as well as APC and GSK3A, and 10% of HCCs have mutations of AXIN1 [20]. In addition, other molecules in the upper stream of Wnt/-catenin pathway, such as Wnt ligands and Wnt receptors FZD and the lower stream such as TCF7L2 are mutated in a few cases of HCC, and these mutations are mutually exclusive (Figure 1).
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2) TP53 and cell cycle pathway TP53 is most frequently mutated in most types of cancer and it is “the Guardian” for the genome, maintaining genomic stability [21]. Overall, 30-40% of liver cancer have
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mutations of TP53, and a specific mutation at codon249 (Arg>Ser) is well known to recurrently occur in liver cancer developed by aflatoxin exposure [22]. The IRF2 protein acts as a transcriptional regulator through its DNA-binding activity and protein-protein interactions. WES identified recurrent IRF2 mutations in liver cancer (5%) [13]. IRF2 and TP53 mutations existed in a mutually exclusive manner, and down-regulation of IRF2 in TP53-wildtype liver cancer cell lines promoted cell proliferation and decreased p53 protein levels, confirming that IRF2 is a new tumor suppressor and is implicated in p53 regulation in liver cancer [23]. RB1 and CDKNA2 (=p16), which are involved with cell cycle regulation together with TP53, are inactivated in liver cancer with 10% by point mutations and copy-number alterations [13, 17].
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3) Ras/ERK pathway Ribosomal protein S6 kinase (RPS6KA3) or RSK2 encodes a serine/threonine kinase of the Ras/MAPK signaling pathway. It is directly phosphorylated and activated by extracellular-regulated kinases 1 and 2 (ERK1/2), and it exerts feedback inhibition on the Ras/ERK pathway [24]. RPS6KA3 affects p53-mediated downstream cellular events in response to DNA damage though phosphorylation of p53 and ATM [25]. Recurrent RPS6KA3 mutations, half of which led to premature stop codons altered splicing, or SVs, were discovered in ~10% of liver cancer [13]. These mutations may cause aberrant activation of the ERK pathway and TP53 pathway. ERRFI1 (ERBB receptor feedback
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inhibitor 1, MIG6) is a negative regulator of the EGFR family [26, 27] and its mutations and copy-number loss was observed in 10% of liver cancer [14, 17]. 4) SWI/SNF chromatin regulators and epigenetic modifiers The SWI/SNF-related chromatin remodeling complexes use ATP to remodel nucleosomes and control the accessibility of promoter regions to the transcriptional machinery. Two types of SWI/SNF complexes have been identified in humans: the BRG1-associated 5
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factors (BAF) and the polybromo BRG-1-associated factor (PBAF) [28]. The AT-rich interactive domain containing 1A (ARID1A) and ARID1B are mutually exclusive and are included in the BAF complex, whereas ARID2 is a component of the PBAF complex [29]. ARID2 mutations were reported to be frequent in HCV-positive liver cancer [9]. Recurrent ARID1A and ARID2 mutations were identified in most types of liver cancer cases [13, 14]. It has been reported that ARID1A mutations were significantly more frequent in liver cancer related to alcohol intake and showed significant association with CTNNB1 mutations [13]. These identified mutations included multiple indels and non-sense mutations, suggesting that they caused loss of function. Additionally, infrequent
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mutations of other SWI/SNF subunits, including the common subunits (SMARCA2, SMARCA4 [BRG], SMARCB1), the BAF subunit (SMARCA1), and the PBAF subunit (PBRM1, BRD7), have been identified in liver cancer. The SWI/SNF complexes regulate diverse biological phenomenon, including DNA repair, stem cell programming, and cell migration through changing chromatin conformation, and aberrations of these complex subunits may exert broad effects on liver cancer biology. Down-regulation of ARID family genes in liver cancer cell lines promoted cell proliferation, indicating that these epigenetic modifier genes have tumor suppressor functions in liver cancer [30]. ARID2 knockout in HCC cell lines contributed to disruption of DNA repair process, resulting in susceptibility to carcinogens and potential hypermutation [31].
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5) TERT and telomere maintenance (Figure 2) Telomerase is a RNA-dependent DNA polymerase catalytic component telomerase reverse transcriptase (TERT) gene. It can lengthen telomeric DNA (TTAGGG repeats) at the termini of chromosomes and maintain infinite proliferation and chromosome stability of malignant cells. TERT expression and telomerase activity is widespread and detectable in the majority of cancer. Recurrent mutations of the TERT core promoter at −124 and −146 bp from the first ATG site were reported in melanomas [32]. These TERT hotspot promoter mutation occurs frequently in HCC, as well as bladder, thyroid, glioblastoma and melanoma, with an overall frequency around 50-60%. TERT promoter mutations are
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observed in cirrhosis at the early steps of hepatocarcinogenesis since they are recurrently identified in low-grade and high-grade dysplastic nodules [33]. Furthermore, WGS analysis demonstrated SVs, HBV integrations, and CNAs affecting the promoter or exon1 region of TERT, which were associated with much higher expression of TERT that that in the cases with the promoter hotspot mutation [16]. Other telomere-associated genes were also mutated in liver cancers, such as ATRX and NSMCE2 [16, 34].
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6) Other driver genes Liver is the central organ of metabolic pathway in human body. Mutations of metabolismassociated genes are frequently observed in liver cancer. One of the highly mutated genes is Albumin (ALB) and APOB in its exon and introns. But they are very highly expressing in hepatocyte and it is likely that mutations can occur passively in these genes because their chromatin structure are sustainable open and easily subject to mutations. But there may be selection for ALB and APOB inactivating mutations to divert energy into cancerrelevant metabolic pathway [17]. HNF1A and HNF4A are the central regulators of liver metabolic pathway and hepatocyte differentiation [35, 36], which are frequently mutated
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and have their function lost, leading to disruption of hepatocyte differentiation. Hepatocellular adenomas (HCAs) are benign liver tumors which can develop into HCC, and HCA have activation of inflammatory signaling pathway (IL6ST, FRK, STAT3, JAK1), as well as activating mutations in β-catenin [37, 38]. The mutations in the inflammatory signaling pathway are observed in common HCCs and JAK1 mutations were also reported in Chinese HCCs with 9% frequency [39].
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3. Structural variants (SVs) and fusion genes in liver cancer WGS analysis identified several types of SVs in liver cancer genome. Basically these SVs recurrently affected driver genes for liver cancer, which are described above, such as
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TERT, CDKN2A, APC ARID1A, and some new genes such as TTC28, MACROD2, and LRP1B, and these SVs changed these expressions [16]. SVs can produce fusion transcript, which has some oncogenic ability and should be targeted by molecular therapy, such as ALK, MET, ROS in lung cancer. However, there is no recurrent fusion gene identified in common type of liver cancer, except for FGFR2 fusion transcript in 10 % of ICCs [40]. Fibrolamellar carcinoma (FL) is a distinct rare subtype of liver cancer that predominantly affects young patients without underlying cirrhosis, which shows a recurrent DNAJB1PRKACA fusion specifically [41].
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4. Copy number alterations in liver cancer Copy number alterations (CNAs), which affect large DNA segments (10kb and more), can lead to activation of oncogenes and inactivation of tumor suppressor genes in cancers. Gain of chromosome 1, 7, 8 and 20 and loss of chromosome 4, 8, 13 and 17 have been observed in HCC through traditional technical methods. Array CGH and SNP chip analysis efficiently have been detecting focal gain or loss CNAs. The CNA-associated oncogenes and tumor suppressors in liver cancer include the focal amplifications of 8q24.21 (MYC), 11q13.3 (CCND1/FGF3/FGF4/FGF19), 19q12 (CCNE1), 7q31.2 7
(MET), 5p15.33 (TERT), 9p24.2 (JAK2) whereas focal deletion involved 13q14.2 (RB1), 9p21.3 (CDKN2A) and 10q23.31 (PTEN). [13, 17, 42, 43]
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5. Virus integration HBV is a DNA virus whose genome comprises circular DNA of approximately 3K nucleotides. Previous Southern blot analysis showed that HBV DNA sequences were integrated into host genome in liver cancer samples and in non-tumorous tissues from patients with chronic HBV hepatitis [44, 45]. Moreover, HBV integration is likely to occur during the early stages of HBV infection. HBV-related liver cancer develops at a
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significantly young age (during a shorter period of chronic infection) with minor liver damage, and HBV integration into the host (human) genome is likely to be one of the first steps of liver carcinogenesis [14, 44]. NGS analysis and non-biased approaches have identified that the TERT region on chromosome 5p15 is a preferred target region for HBV integration [14, 15] and that HBV integration also occurs in the MLL4 gene on chromosome 19q13 [12, 14]. The most comprehensive search for HBV integration sites by using WGS showed that HBV integration events occurred repeatedly at the loci of TERT, MLL4, and CCN1 [15]. Dysregulation of telomerase expression in somatic cells is involved in carcinogenesis, and cancer cells frequently overexpress TERT, as described above. MLL4 encodes a histone methyltransferase, and MLL4 mutations or copy number
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alterations are reported in several types of cancer; it has critical roles in gene expression and epigenetics in cancer [46]. The number of HBV integration events was correlated with high serum HBs antigen and AFP levels, and patients with HBV integration seemed to develop liver cancer at a young age. The number of HBV integrations was significantly associated with poor prognosis [15]. The deep WGS analysis on one HBV-positive liver cancer and its non-tumor liver tissue indicated a heterogeneous and widespread viral integration landscape in liver cancer as well as non-tumor liver tissue [15, 47]. These findings suggested that HBV integration could randomly occur in each liver cell during the early stages of HBV infection, and a liver cell acquiring growth or survival advantages by virtue of its HBV integration and subsequent genomic alterations, is selected for or
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survives to monoclonal expansion to tumor. HBV integration can induce genomic instability locally and secondary, which can also provide some advantage in cancer development and evolution. Some studies reported the involvement of viral-human chimeric transcripts in liver carcinogenesis [48, 49, 50]. In addition to HBV, recent two studies [16, 51] demonstrated that AAV (adeno-associated virus) are present in liver cancer and non-cancer liver tissues and it can be integrated into human genome. But the pathological implication of AAV and its integration in liver is not clear and further should 8
be investigated.
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6. Mutational signature and its association with etiological factors (Figure 3) Somatic mutations in cancer are the consequence of multiple mutational processes, including the intrinsic infidelity of the DNA replication machinery, exogenous or endogenous mutagen exposures, enzymatic modification of DNA, and defective DNA repair. Different mutational processes generate unique combinations of mutation types, termed “Mutational Signatures” [52]. Each of the mutational signature patterns is associated with each of cancer etiology in a tissue-specific manner. For example,
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C>A/G>T transversions are the most frequent substitutions in the TP53 gene in liver cancer developed by aflatoxin exposure. Recent comprehensive mutational searches for some thousand mutations each case and NMF (non-negative matrix factorization) mathematical analysis have extracted more than 30 mutational signature for cancer genome shown in COSMIC database (http://cancer.sanger.ac.uk/cosmic/signatures), and researchers try to implicate each of these mutational signatures in biological and epidemiological aspects [52, 53]. Liver is the central organ for metabolism and detoxification in human body and have a lot of chances to be exposure with exogenous or endogenous mutagens, and the etiology of liver cancer is most understood among the common type cancers, such as virus infection, alcohol intake, and aflatoxin. Mutational
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signature analysis of liver cancers demonstrated that several mutational signatures could be associated with specific types of cancer etiology. Six representative mutational
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signatures observed in liver cancer is shown in Figure 3. Signature 1 represents clocklike mutational process (aging) and observed in all type of cancer [53]. Signature 24 represents the signature associated with aflatoxin [16, 17], Signature 4 with smoking exposure [16, 54], Signature 22 with aristolochic acid which is contained in Chinese
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herbal product [55], and Signature 16 is likely to represents alcohol and acetaldehyde exposure [56]. Signature 12 is observed specifically in liver cancer, but its associated etiology is unknown [16]. By observing genome-wide somatic mutational signature in an established cancer genome, we may presume its etiological factors for individual liver
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cancer development among the multiple etiological factors of liver cancer. 7. Biliary phenotype, cell origin, and molecular classification of liver cancer The main histology of liver cancer is HCC, while 5-10% show cholangiocarcinoma, whose cell origin is presumed to be bile duct cell. ICC and HCC are clinically disparate primary liver cancers with etiological and biological heterogeneity. But rare type of liver cancer show the mixed phenotype or combined phenotype of HCC and ICC (cHCC/CC), 9
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suggesting that cell-of-origin of liver cancer remain to be elucidated [57]. Pluripotent progenitor cells in the liver can differentiate into hepatocytes and cholangiocytes during liver regeneration, and it has also been shown that some ICCs originate from either pluripotent progenitor cells or multiple cell types [57, 58]. One of the major risk factors for the development of ICC is chronic hepatitis and cirrhosis associated with viral infection as well as HCC [59], and HCC and ICC have been reported to develop simultaneously in both human and mouse models [58]. They indicated that hepatitisassociated ICC and HCC share a common disease process for carcinogenesis and overlap of their cell-of-origin. Mutational signature analysis of biliary phenotype of liver cancer
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suggested that mutational signature of ICC with hepatitis was similar to that of HCC [60], indicating their common mutational process or common cell-of-origin. Further analysis for cell-of-origin of ICC by genomic and epigenomic analysis indicated common cell-oforigin of ICC and HCC [61]. The mutational landscape of ICC has been reported in some recent studies which indicated that some mutations are shared between ICC and HCC but some are unique to ICC [61, 62, 63, 64]. Chaisaingmongkol et al. [64] identified common molecular subtypes and driver genes linked to similar prognosis among Asian ICC and HCC patients. For molecular classification for HCC, many groups reported molecular classification based on somatic mutations profiles, RNA expression profiles, and DNA methylation profiles related with patient prognosis [16, 17, 34, 64, 65, 66]. It is
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summarized that HCC can be roughly divided into two major subtypes: one is characterized by the signal of cell proliferation and aggressive type. The second class is non-proliferation or normal hepatocyte-like class, which is related with aberrant signaling of Wnt pathway [67].
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8. Multi-centric tumor and recurrence One of the characteristic features of liver cancer recurrence is multiple occurrences in a strong carcinogenetic background. Although distinction between intrahepatic metastasis (IM) and de novo multi-centric occurrence (MC) is clinically difficult [68], MC liver
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cancers frequently develop in HCV-infected liver cirrhosis. More than 90% of HCVinfected patients who underwent curative resection for liver cancer had metachronous MC tumors within a 10-year follow-up period [69]. IM tumor basically shares somatic mutations with the primary liver tumor, while MC tumor does not share any somatic mutations between these MC tumors because they developed independently. Furuta et al. [70] performed WGS of multiple liver tumors and accurately distinguished MC/IM of liver cancer using somatic SNV information. Overall, 6 out of 23 cases with multiple liver 10
tumors have discrepancy between clinical diagnosis and sequencing-based diagnosis for IM/MC and this strategy is applicable in liver cancer clinic as precision medicine because the management of IM or MC tumors is different and intensive adjuvant therapy is required for patients with IM.
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9. Actionable genes or mutations in liver cancer and precision medicine The summary of driver events in liver cancer is shown in Figure 4 and Table 1. Various genomic events and mutations are accumulated and associated with liver cancer development and progression. Among them, unfortunately there are not so many
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“actionable” gene or mutations in liver cancer genome. In fact, more than 60% of lung cancers have potential clinically actionable drug targets [71]. Now the approved drug for liver cancer is solely a multi-kinase inhibitor sorafenib and other new multi-kinase inhibitors are on clinical trials for liver cancer [72]. Their main target is VEGFR2 (Vascular Endothelial Growth Factor Receptor 2) which regulates angiogenesis, but sorafenib and other promising multi-kinase inhibitors are targeting other oncogenic kinases such as PDGFRB, FGFR1, KIT, BRAF, and RET to suppress liver cancer proliferation [73]. The amplification of VEGFA at chromosome 6p21 [74] and the amplification of CCDN1/FGF2/FGF4/FGF19 at chromosome 11q13 [75] are reported to predict the response of sorafenib, but they are not still established yet. Other actionable
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gene or mutations in liver cancers are PIK3CA [76], TSC1/2 [77], KIT [49], and JAK1/2 [39], although their frequencies liver cancer are rare and we do not have any proof of their actionability or efficiency of molecular therapies to these targets in clinical trial level. Amplified actionable genes indicated that kinase inhibitors might be beneficial for 2030% of HCC patients by targeting amplification of EGFR, MET, BRAF or ERBB2 [17, 67]. AURKA (Aurora kinase A) is also frequently amplified in liver cancer, which might be good candidate to treat by alisertib [78]. Schulze et al. [79] reported that 28% of patients harboring at least one pathogenic alterations potentially targetable by an FDAapproved drug, and 86% harbored a mutation targetable by a drug studied in phase I and II clinical trials. The summary of the direct actionability of the mutated genes in liver
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cancer is shown in Table 1. Specifically in ICC, IDH1/2 mutation [80, 81] and FGFRfusion [61, 63, 82] are detected as actionable gene mutations in 5-10% of ICC and they are under clinical trials. Immunotherapy using immune checkpoint inhibitors has already shown great promise in some types of cancers. This approach has recently begun clinical testing in advanced HCC patients, and some promising results are obtained [83]. A phase I/II study of nivolumab in patients with advanced HCC demonstrated a 19% response rate (including 5% complete responses) [84]. The over-expression or genetic alterations of 11
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PD-L1 is likely to be associated with response to anti-PD-1/PD-L1 agents in some types of cancer such as lymphoma [85, 86], and immunohistochemical analysis showed that PD-L1 was expressed in 25% of HCC specimens and its expression was associated with the patient prognosis [87]. But PD-L1 is induced in hepatocytes by viral infection [88] and genomic alterations of PD-L1 was not detected in liver cancer, and other genomic biomarkers should be investigated to predict the response to the immune checkpoint inhibitor in liver cancer. Also, liver cancer has a uniquely immunosuppressive background [89]. It is required to address the specific issues of immuno-tolerance to virus infection and chronic liver inflammation that underlie HCC development and it is
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concerned that these immune checkpoint inhibitors and modulators can aggravate hepatitis or liver dysfunction in patients with liver cancer
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10. Conclusions Some thousands of liver cancer genome have been sequenced globally and most of driver
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genes/mutations with high frequency are established in liver cancer, including Wnt/catenin pathway, TP53/cell cycle pathway, telomere maintenance, and chromatin regulators. HBV integration is also a driver event in hepatocarcinogenesis. Etiology of liver cancer is most understood and mutational signatures of liver cancer can provide
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many evidence of the association between specific etiological factors and mutational signature. For precision medicine, actionable mutations with solid evidence is not frequently observed in liver cancer, and there is few molecular target therapy such as multi-kinase inhibitors so far. But it is possible that rare actionable mutations in liver cancer can guide other specific molecular therapy. Integration of large genomic data sets with functional and other omics data set will provide a new horizon for liver cancer treatment and evidences for precision medicine. Conflicts of interest None
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Acknowledgements The authors thank members of RIKEN-IMS, the Prof. Miyano’s laboratory in The Institute of Medical Sciences, The University of Tokyo, and all researchers involving TCGA for critical input into this manuscript. This work was supported partially by RIKEN President’s Fund 2011, and Grand-in-aid for RIKEN CGM and IMS,
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Figure Captions
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Figure 1 Mutations of Wnt/-catenin pathway in liver cancer. Mutations of the molecules in this pathway are found in 40-50% of liver cancer, mainly, CTNNB1, AXIN1, and APC. In addition, GSK3A, TCF7L2, several Wnt ligands and Wnt receptors FZD are mutated and these mutations are mutually exclusive. Figure 2 TERT mutations and TERT expression in liver cancers. These TERT hotspot promoter mutation occurs in HCC with 50-60% frequency. SVs,
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HBV integrations, and copy-number gain in the promoter or exon1 of TERT were associated with much higher expression of TERT that that in the cases with the promoter hotspot mutation, leading to the telomere maintenance, cell immortality, and chromosome stability of cancer cells.
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Figure 3 Mutational signature observed in liver cancers. Signature 24 represents the signature associated with aflatoxin, Signature 22 with aristolochic acid, Signature 4 with smoking. Signature 16 is likely to represents alcohol
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and acetaldehyde. Signature 12 is observed specifically in liver cancer, but its associated etiology is unknown. These signatures are from COSMIC database
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(http://cancer.sanger.ac.uk/cosmic/signatures).
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Figure 4 Diver mutations and etiological factors in hepatocarcinogenesis The left half pie indicates etiological factors in hepatocarcinogenesis, and the right half pie indicates driver mutations/pathways in liver cancer.
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Table 1 Driver mutated genes and actionability in liver cancer
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ARID1A BRD7 PBRM1 MLL4 Telomere maintenace TERT ATRX
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CCNE1 Ras/ERK pathway FGF19 RPS6KA3 ERRFI1 MET FGFR2 PRKACA Chromatin regulators ARID2
SV/ Virus Actionability CNA integration
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APC TCF7L2 TP53 /cell-cycle pathway TP53 IRF2 ATM RB1 CDKNA2 MYC CCND1
SNV /indel
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Wnt/-catenin pathway CTNNB1 AXIN1
Mutaion frequency
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Mutated genes
10-15% 5% 3-5% 5-10% 10% in ICC 90% in FL
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2% 2%
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JAK1/2 AKT/mTOR pathway PTEN TSC1/2 PIK3CA Oxidative stress pathway NFE2L2 KEAP1 Angiogenesis VEGFA
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Liver metabolic pathway HNF1A HNF4A NCOR1 ALB APOB Inflammatory pathway IL6ST STAT3
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Matabolism and epigenomics IDH1/2 10% in ICC
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S1044-579X(17)30229-8 https://doi.org/10.1016/j.semcancer.2018.03.004 YSCBI 1463
To appear in:
Seminars in Cancer Biology
Received date: Revised date: Accepted date:
29-11-2017 19-3-2018 28-3-2018
Please cite this article as: Nakagawa H, Fujita M, Fujimoto A, Genome Sequencing Analysis of Liver Cancer for Precision Medicine, Seminars in Cancer Biology (2010), https://doi.org/10.1016/j.semcancer.2018.03.004 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Genome Sequencing Analysis of Liver Cancer for Precision Medicine Hidewaki Nakagawa1, Masashi Fujita1, and Akihiro Fujimoto1,2 1
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Laboratory for Genome Sequencing Analysis, RIKEN Center of Integrative medical Sciences, Tokyo 108-8639, Japan 2 Department of Drug Discovery Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8507, Japan *
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Corresponding should be addressed to H. Nakagawa (4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan), Email address: [email protected]
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Abstract Liver cancer is the third leading cause of cancer-related death worldwide. Some thousands of liver cancer genome have been sequenced globally so far and most of driver
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genes/mutations with high frequency are established in liver cancer, including Wnt/catenin pathway, TP53/cell-cycle pathways, telomere maintenance, and chromatin regulators. HBV integration into cancer-related genes is also a driver event in hepatocarcinogenesis. These genes are affected by structural variants, copy-number
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alterations and virus integrations as well as point mutations. Etiological factors of liver cancer is most understood among common cancers, such as hepatitis, aflatoxin, alcohol, and metabolic diseases, and mutational signatures of liver cancer can provide evidence of the association between specific etiological factors and mutational signatures. Molecular classifications based on somatic mutations profiles, RNA expression profiles, and DNA methylation profiles are related with patient prognosis. For precision medicine, several actionable mutations with solid evidence such as targets of multi-kinase inhibitors is observed in liver cancer, but there is few molecular target therapy so far. It is possible that rare actionable mutations in liver cancer can guide other specific molecular therapy and immune therapy
Keywords Liver cancer, genome sequencing, mutational signature, actionable gene, precision medicine
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1. Introduction Liver cancer is the third leading cause of cancer-related death worldwide, estimated to be responsible for nearly 746,000 deaths in 2012 (9.1% of the total) according to the International Agency for Research on Cancer (IARC) [1, 2]. Its prevalence is quite different among ethnic groups or areas; liver cancer is most common in East/SouthEastern Asian and African areas [1, 2], which is dependent on the prevalence of virus hepatitis. The most important etiological factor is virus infection, HBV (hepatitis B virus) and HCV (hepatitis C virus), and alcohol-induced liver damage also ranks high, mainly in Western countries. There is also a growing problem with hepatitis which develops in
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the setting of nonalcoholic fatty liver disease (NAFLD), or nonalcoholic steatohepatitis (NASH). NASH typically develops in the setting of obesity, type 2 diabetes, dyslipidemia, and hypertension, which is a significant problem in the developed countries [3]. Virus infection and metabolic stress induce liver damage such as fatty change, hepatitis, and cirrhosis, which set premalignant conditions for liver cancer through regeneration or cell cycle turnover and inflammatory environment. Chronic inflammation, virus infection, and liver regeneration have been reported to induce genetic and epigenetic damage to the genome [4]. Most liver cancers gradually develop from these premalignant stages by accumulation of these genetic alterations. Accordingly, highly damaged livers are extremely susceptible to multiple liver tumors.
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Despite the recent progress in diagnostic and therapeutic modalities such as radiofrequency ablation, multi-kinase inhibitors and liver transplantation, the 5-year survival rate of liver cancer is still 5-10% [3]. Characteristically, liver cancer shows a high rate of recurrence or multi-centric occurrence in strong carcinogenic backgrounds such as chronic hepatitis and liver cirrhosis. Liver function also determine the patient prognosis and therapeutic options, and patients with liver dysfunction cannot tolerant to surgery and other therapy, leading to poor prognosis. Therefore, new treatments, including molecular therapies for inoperable cases, and preventive strategies have been intensively sought, based on the biological feature and molecular profile of each patient. Innovation in DNA sequencing (NGS) technologies and computational analysis for
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these massive data have enabled us to analyze comprehensive profile of cancer genome and transcriptome in a large scale. This approach can rapidly identify potential driver genetic events, especially potential molecular therapeutic targets, in cancer [5]. Along with the application of NGS technologies in cancer research, international or domestic networks of cancer genome research have been initiated to effectively promote cancer genome sequencing and share high-quality data among scientists, such as the International Cancer Genome Consortium (ICGC) [6] and The Cancer Genome Atlas 2
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(TCGA) in the USA [7]. These projects collected samples with distinct epidemiological (virus and alcohol) and ethnic (Japanese, China, USA, and France) backgrounds, and the integration of these huge datasets is providing a much clearer understanding of the association between molecular or genetic features and epidemiological, environmental, and ethnic factors in liver cancer. Furthermore, now NGS technology is used for clinical sequencing or clinical setting as cancer precision medicine, which analyzes and identify actionable genes or mutations in the listed genes with actionability, and enter the patients with specific mutations into clinical trials. Here we summarize recent genome sequencing studies of liver cancer which cover
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driver gene discovery, virus integration, and mutational signatures. Based on these sequencing data, we also discuss about clinical sequencing in precision medicine for liver cancer.
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2. Whole genome/exome sequencing analyses for liver cancers A number of comprehensive genome sequencing studies by exome and whole genome sequencing (WGS) were conducted for liver cancer in the world. Whole exome sequencing (WES) can efficiently detect mutations in protein-coding exons, which are much more easily interpretable than mutations or variants in non-coding regions; this analysis was the most common platform for ICGC/TCGA projects. This approach
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involves target-enrichment of whole protein-coding exons of the human genome (30–40 Mb, approximately 1-2% of the human genome) using in-solution RNA or oligonucleotide DNA probe hybridization technologies [8]. The accuracy of sequencing analysis by using NGS is basically dependent on the sequence depth or coverage of the target regions, and WES following target-enrichment can usually cover more than ×80 sequence depth, which enables more accurate detection of single nucleotide variants (SNVs) and short indels than WGS. On the other hand, whole genome sequencing (WGS) can cover almost all the human genome sequences (approximately 3 Gb) and detect variants in non-coding regions, structural variants (SVs), copy number alterations (CNAs), and virus integrations in addition to SNV and short indels. This strategy is much more
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comprehensive and suitable for analyzing the cancer genome, because various kinds of mutations occurs in cancer genome. Following the evolutional progress of NGS technology and informatics, the cost and labor of WGS is rapidly dropping down and it is becoming a central technology for human and cancer genome analysis. Initial exome sequencing analysis for liver cancer in 2011, which did not cover the whole exome region but analyzed exons of ~18,000 genes, identified recurrent mutations of ARID2, which was further validated in more than 120 additional cases [9]. The whole 3
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genome of one HCV-related liver cancer was unveiled in 2011 by using NGS approach and demonstrated its genomic features in high resolution and intratumoral heterogeneity [10]. Whole genomes of multiple regions of one HBV-related liver cancer and its intrahepatic metastases were sequenced by NSG [11]. Jiang et al. analyzed whole genomes of four HBV-related liver cancer genomes by NGS [12] and detected a number of HBV integrations. WES analysis combined with copy-number analysis using SNP arrays for mainly alcohol-related liver cancers in France [13] showed that several pathways were involved in liver carcinogenesis. WGS analyses for 27 Japanese liver cancers [14] and 88 Chinese HBV-related liver cancers [15] detected driver mutations and
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HBV integrations comprehensively. WGS analysis on Japanese 300 liver cancers demonstrated structural variants and non-coding mutations [16], and TCGA consortium summarized comprehensive and integrative genomic characterization of hepatocellular carcinoma by combining WES, SNP chips, RNA analysis and DNA methylation analysis [17]. In clinical setting for precision medicine, it is important to accurately detect somatic mutations, and at present target deep sequencing is most common in cancer. However, if cost of WGS and computational burden are decreased in the near future, WGS could be a standard platform of clinical sequencing for cancer. In that case, computational methods for mutation detection should be standardized or be evaluated for its accuracy, because false-negative and false-positive of the NGS diagnosis is dependent on the computational
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algorisms [18]
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3. Mutated driver genes in liver cancer A number of genomic studies have attempted to elucidate molecular alterations in liver cancer. The list contains components of the p53/cell-cycle pathway (TP53 and CDKN2A), and Wnt pathway (CTNNB1 and AXIN1). Genome-wide copy number analyses also identified amplified regions including MYC and CCND1 and deleted regions such as CDKN2A [17]. NGS-based genome sequencing studies of liver cancer genomes can identify somatically mutated genes in an unbiased way and have almost established driver gene sets in liver cancer below. The list of driver genes for liver cancer is in Table 1.
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1) Wnt/-catenin pathway (Figure 1) Wnt/-catenin pathway is involved with organ development, regulation of cell stemness and oncogenesis through regulating cell proliferation, mobility, and polarity. Mutations of the molecules in this pathway are found in 40-50% of liver cancer. Mainly, point mutations in exon 3 of CTNNB1 (-catenin) can stabilize -catenin protein and can translate it into nucleus [19], trans-activating the downstream oncogenic molecules such 4
as Myc and CCND1 (cyclin D1). AXIN1 plays a critical role in degradation of -catenin protein as well as APC and GSK3A, and 10% of HCCs have mutations of AXIN1 [20]. In addition, other molecules in the upper stream of Wnt/-catenin pathway, such as Wnt ligands and Wnt receptors FZD and the lower stream such as TCF7L2 are mutated in a few cases of HCC, and these mutations are mutually exclusive (Figure 1).
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2) TP53 and cell cycle pathway TP53 is most frequently mutated in most types of cancer and it is “the Guardian” for the genome, maintaining genomic stability [21]. Overall, 30-40% of liver cancer have
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mutations of TP53, and a specific mutation at codon249 (Arg>Ser) is well known to recurrently occur in liver cancer developed by aflatoxin exposure [22]. The IRF2 protein acts as a transcriptional regulator through its DNA-binding activity and protein-protein interactions. WES identified recurrent IRF2 mutations in liver cancer (5%) [13]. IRF2 and TP53 mutations existed in a mutually exclusive manner, and down-regulation of IRF2 in TP53-wildtype liver cancer cell lines promoted cell proliferation and decreased p53 protein levels, confirming that IRF2 is a new tumor suppressor and is implicated in p53 regulation in liver cancer [23]. RB1 and CDKNA2 (=p16), which are involved with cell cycle regulation together with TP53, are inactivated in liver cancer with 10% by point mutations and copy-number alterations [13, 17].
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3) Ras/ERK pathway Ribosomal protein S6 kinase (RPS6KA3) or RSK2 encodes a serine/threonine kinase of the Ras/MAPK signaling pathway. It is directly phosphorylated and activated by extracellular-regulated kinases 1 and 2 (ERK1/2), and it exerts feedback inhibition on the Ras/ERK pathway [24]. RPS6KA3 affects p53-mediated downstream cellular events in response to DNA damage though phosphorylation of p53 and ATM [25]. Recurrent RPS6KA3 mutations, half of which led to premature stop codons altered splicing, or SVs, were discovered in ~10% of liver cancer [13]. These mutations may cause aberrant activation of the ERK pathway and TP53 pathway. ERRFI1 (ERBB receptor feedback
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inhibitor 1, MIG6) is a negative regulator of the EGFR family [26, 27] and its mutations and copy-number loss was observed in 10% of liver cancer [14, 17]. 4) SWI/SNF chromatin regulators and epigenetic modifiers The SWI/SNF-related chromatin remodeling complexes use ATP to remodel nucleosomes and control the accessibility of promoter regions to the transcriptional machinery. Two types of SWI/SNF complexes have been identified in humans: the BRG1-associated 5
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factors (BAF) and the polybromo BRG-1-associated factor (PBAF) [28]. The AT-rich interactive domain containing 1A (ARID1A) and ARID1B are mutually exclusive and are included in the BAF complex, whereas ARID2 is a component of the PBAF complex [29]. ARID2 mutations were reported to be frequent in HCV-positive liver cancer [9]. Recurrent ARID1A and ARID2 mutations were identified in most types of liver cancer cases [13, 14]. It has been reported that ARID1A mutations were significantly more frequent in liver cancer related to alcohol intake and showed significant association with CTNNB1 mutations [13]. These identified mutations included multiple indels and non-sense mutations, suggesting that they caused loss of function. Additionally, infrequent
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mutations of other SWI/SNF subunits, including the common subunits (SMARCA2, SMARCA4 [BRG], SMARCB1), the BAF subunit (SMARCA1), and the PBAF subunit (PBRM1, BRD7), have been identified in liver cancer. The SWI/SNF complexes regulate diverse biological phenomenon, including DNA repair, stem cell programming, and cell migration through changing chromatin conformation, and aberrations of these complex subunits may exert broad effects on liver cancer biology. Down-regulation of ARID family genes in liver cancer cell lines promoted cell proliferation, indicating that these epigenetic modifier genes have tumor suppressor functions in liver cancer [30]. ARID2 knockout in HCC cell lines contributed to disruption of DNA repair process, resulting in susceptibility to carcinogens and potential hypermutation [31].
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5) TERT and telomere maintenance (Figure 2) Telomerase is a RNA-dependent DNA polymerase catalytic component telomerase reverse transcriptase (TERT) gene. It can lengthen telomeric DNA (TTAGGG repeats) at the termini of chromosomes and maintain infinite proliferation and chromosome stability of malignant cells. TERT expression and telomerase activity is widespread and detectable in the majority of cancer. Recurrent mutations of the TERT core promoter at −124 and −146 bp from the first ATG site were reported in melanomas [32]. These TERT hotspot promoter mutation occurs frequently in HCC, as well as bladder, thyroid, glioblastoma and melanoma, with an overall frequency around 50-60%. TERT promoter mutations are
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observed in cirrhosis at the early steps of hepatocarcinogenesis since they are recurrently identified in low-grade and high-grade dysplastic nodules [33]. Furthermore, WGS analysis demonstrated SVs, HBV integrations, and CNAs affecting the promoter or exon1 region of TERT, which were associated with much higher expression of TERT that that in the cases with the promoter hotspot mutation [16]. Other telomere-associated genes were also mutated in liver cancers, such as ATRX and NSMCE2 [16, 34].
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6) Other driver genes Liver is the central organ of metabolic pathway in human body. Mutations of metabolismassociated genes are frequently observed in liver cancer. One of the highly mutated genes is Albumin (ALB) and APOB in its exon and introns. But they are very highly expressing in hepatocyte and it is likely that mutations can occur passively in these genes because their chromatin structure are sustainable open and easily subject to mutations. But there may be selection for ALB and APOB inactivating mutations to divert energy into cancerrelevant metabolic pathway [17]. HNF1A and HNF4A are the central regulators of liver metabolic pathway and hepatocyte differentiation [35, 36], which are frequently mutated
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and have their function lost, leading to disruption of hepatocyte differentiation. Hepatocellular adenomas (HCAs) are benign liver tumors which can develop into HCC, and HCA have activation of inflammatory signaling pathway (IL6ST, FRK, STAT3, JAK1), as well as activating mutations in β-catenin [37, 38]. The mutations in the inflammatory signaling pathway are observed in common HCCs and JAK1 mutations were also reported in Chinese HCCs with 9% frequency [39].
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3. Structural variants (SVs) and fusion genes in liver cancer WGS analysis identified several types of SVs in liver cancer genome. Basically these SVs recurrently affected driver genes for liver cancer, which are described above, such as
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TERT, CDKN2A, APC ARID1A, and some new genes such as TTC28, MACROD2, and LRP1B, and these SVs changed these expressions [16]. SVs can produce fusion transcript, which has some oncogenic ability and should be targeted by molecular therapy, such as ALK, MET, ROS in lung cancer. However, there is no recurrent fusion gene identified in common type of liver cancer, except for FGFR2 fusion transcript in 10 % of ICCs [40]. Fibrolamellar carcinoma (FL) is a distinct rare subtype of liver cancer that predominantly affects young patients without underlying cirrhosis, which shows a recurrent DNAJB1PRKACA fusion specifically [41].
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4. Copy number alterations in liver cancer Copy number alterations (CNAs), which affect large DNA segments (10kb and more), can lead to activation of oncogenes and inactivation of tumor suppressor genes in cancers. Gain of chromosome 1, 7, 8 and 20 and loss of chromosome 4, 8, 13 and 17 have been observed in HCC through traditional technical methods. Array CGH and SNP chip analysis efficiently have been detecting focal gain or loss CNAs. The CNA-associated oncogenes and tumor suppressors in liver cancer include the focal amplifications of 8q24.21 (MYC), 11q13.3 (CCND1/FGF3/FGF4/FGF19), 19q12 (CCNE1), 7q31.2 7
(MET), 5p15.33 (TERT), 9p24.2 (JAK2) whereas focal deletion involved 13q14.2 (RB1), 9p21.3 (CDKN2A) and 10q23.31 (PTEN). [13, 17, 42, 43]
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5. Virus integration HBV is a DNA virus whose genome comprises circular DNA of approximately 3K nucleotides. Previous Southern blot analysis showed that HBV DNA sequences were integrated into host genome in liver cancer samples and in non-tumorous tissues from patients with chronic HBV hepatitis [44, 45]. Moreover, HBV integration is likely to occur during the early stages of HBV infection. HBV-related liver cancer develops at a
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significantly young age (during a shorter period of chronic infection) with minor liver damage, and HBV integration into the host (human) genome is likely to be one of the first steps of liver carcinogenesis [14, 44]. NGS analysis and non-biased approaches have identified that the TERT region on chromosome 5p15 is a preferred target region for HBV integration [14, 15] and that HBV integration also occurs in the MLL4 gene on chromosome 19q13 [12, 14]. The most comprehensive search for HBV integration sites by using WGS showed that HBV integration events occurred repeatedly at the loci of TERT, MLL4, and CCN1 [15]. Dysregulation of telomerase expression in somatic cells is involved in carcinogenesis, and cancer cells frequently overexpress TERT, as described above. MLL4 encodes a histone methyltransferase, and MLL4 mutations or copy number
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alterations are reported in several types of cancer; it has critical roles in gene expression and epigenetics in cancer [46]. The number of HBV integration events was correlated with high serum HBs antigen and AFP levels, and patients with HBV integration seemed to develop liver cancer at a young age. The number of HBV integrations was significantly associated with poor prognosis [15]. The deep WGS analysis on one HBV-positive liver cancer and its non-tumor liver tissue indicated a heterogeneous and widespread viral integration landscape in liver cancer as well as non-tumor liver tissue [15, 47]. These findings suggested that HBV integration could randomly occur in each liver cell during the early stages of HBV infection, and a liver cell acquiring growth or survival advantages by virtue of its HBV integration and subsequent genomic alterations, is selected for or
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survives to monoclonal expansion to tumor. HBV integration can induce genomic instability locally and secondary, which can also provide some advantage in cancer development and evolution. Some studies reported the involvement of viral-human chimeric transcripts in liver carcinogenesis [48, 49, 50]. In addition to HBV, recent two studies [16, 51] demonstrated that AAV (adeno-associated virus) are present in liver cancer and non-cancer liver tissues and it can be integrated into human genome. But the pathological implication of AAV and its integration in liver is not clear and further should 8
be investigated.
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6. Mutational signature and its association with etiological factors (Figure 3) Somatic mutations in cancer are the consequence of multiple mutational processes, including the intrinsic infidelity of the DNA replication machinery, exogenous or endogenous mutagen exposures, enzymatic modification of DNA, and defective DNA repair. Different mutational processes generate unique combinations of mutation types, termed “Mutational Signatures” [52]. Each of the mutational signature patterns is associated with each of cancer etiology in a tissue-specific manner. For example,
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C>A/G>T transversions are the most frequent substitutions in the TP53 gene in liver cancer developed by aflatoxin exposure. Recent comprehensive mutational searches for some thousand mutations each case and NMF (non-negative matrix factorization) mathematical analysis have extracted more than 30 mutational signature for cancer genome shown in COSMIC database (http://cancer.sanger.ac.uk/cosmic/signatures), and researchers try to implicate each of these mutational signatures in biological and epidemiological aspects [52, 53]. Liver is the central organ for metabolism and detoxification in human body and have a lot of chances to be exposure with exogenous or endogenous mutagens, and the etiology of liver cancer is most understood among the common type cancers, such as virus infection, alcohol intake, and aflatoxin. Mutational
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signature analysis of liver cancers demonstrated that several mutational signatures could be associated with specific types of cancer etiology. Six representative mutational
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signatures observed in liver cancer is shown in Figure 3. Signature 1 represents clocklike mutational process (aging) and observed in all type of cancer [53]. Signature 24 represents the signature associated with aflatoxin [16, 17], Signature 4 with smoking exposure [16, 54], Signature 22 with aristolochic acid which is contained in Chinese
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herbal product [55], and Signature 16 is likely to represents alcohol and acetaldehyde exposure [56]. Signature 12 is observed specifically in liver cancer, but its associated etiology is unknown [16]. By observing genome-wide somatic mutational signature in an established cancer genome, we may presume its etiological factors for individual liver
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cancer development among the multiple etiological factors of liver cancer. 7. Biliary phenotype, cell origin, and molecular classification of liver cancer The main histology of liver cancer is HCC, while 5-10% show cholangiocarcinoma, whose cell origin is presumed to be bile duct cell. ICC and HCC are clinically disparate primary liver cancers with etiological and biological heterogeneity. But rare type of liver cancer show the mixed phenotype or combined phenotype of HCC and ICC (cHCC/CC), 9
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suggesting that cell-of-origin of liver cancer remain to be elucidated [57]. Pluripotent progenitor cells in the liver can differentiate into hepatocytes and cholangiocytes during liver regeneration, and it has also been shown that some ICCs originate from either pluripotent progenitor cells or multiple cell types [57, 58]. One of the major risk factors for the development of ICC is chronic hepatitis and cirrhosis associated with viral infection as well as HCC [59], and HCC and ICC have been reported to develop simultaneously in both human and mouse models [58]. They indicated that hepatitisassociated ICC and HCC share a common disease process for carcinogenesis and overlap of their cell-of-origin. Mutational signature analysis of biliary phenotype of liver cancer
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suggested that mutational signature of ICC with hepatitis was similar to that of HCC [60], indicating their common mutational process or common cell-of-origin. Further analysis for cell-of-origin of ICC by genomic and epigenomic analysis indicated common cell-oforigin of ICC and HCC [61]. The mutational landscape of ICC has been reported in some recent studies which indicated that some mutations are shared between ICC and HCC but some are unique to ICC [61, 62, 63, 64]. Chaisaingmongkol et al. [64] identified common molecular subtypes and driver genes linked to similar prognosis among Asian ICC and HCC patients. For molecular classification for HCC, many groups reported molecular classification based on somatic mutations profiles, RNA expression profiles, and DNA methylation profiles related with patient prognosis [16, 17, 34, 64, 65, 66]. It is
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summarized that HCC can be roughly divided into two major subtypes: one is characterized by the signal of cell proliferation and aggressive type. The second class is non-proliferation or normal hepatocyte-like class, which is related with aberrant signaling of Wnt pathway [67].
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8. Multi-centric tumor and recurrence One of the characteristic features of liver cancer recurrence is multiple occurrences in a strong carcinogenetic background. Although distinction between intrahepatic metastasis (IM) and de novo multi-centric occurrence (MC) is clinically difficult [68], MC liver
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cancers frequently develop in HCV-infected liver cirrhosis. More than 90% of HCVinfected patients who underwent curative resection for liver cancer had metachronous MC tumors within a 10-year follow-up period [69]. IM tumor basically shares somatic mutations with the primary liver tumor, while MC tumor does not share any somatic mutations between these MC tumors because they developed independently. Furuta et al. [70] performed WGS of multiple liver tumors and accurately distinguished MC/IM of liver cancer using somatic SNV information. Overall, 6 out of 23 cases with multiple liver 10
tumors have discrepancy between clinical diagnosis and sequencing-based diagnosis for IM/MC and this strategy is applicable in liver cancer clinic as precision medicine because the management of IM or MC tumors is different and intensive adjuvant therapy is required for patients with IM.
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9. Actionable genes or mutations in liver cancer and precision medicine The summary of driver events in liver cancer is shown in Figure 4 and Table 1. Various genomic events and mutations are accumulated and associated with liver cancer development and progression. Among them, unfortunately there are not so many
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“actionable” gene or mutations in liver cancer genome. In fact, more than 60% of lung cancers have potential clinically actionable drug targets [71]. Now the approved drug for liver cancer is solely a multi-kinase inhibitor sorafenib and other new multi-kinase inhibitors are on clinical trials for liver cancer [72]. Their main target is VEGFR2 (Vascular Endothelial Growth Factor Receptor 2) which regulates angiogenesis, but sorafenib and other promising multi-kinase inhibitors are targeting other oncogenic kinases such as PDGFRB, FGFR1, KIT, BRAF, and RET to suppress liver cancer proliferation [73]. The amplification of VEGFA at chromosome 6p21 [74] and the amplification of CCDN1/FGF2/FGF4/FGF19 at chromosome 11q13 [75] are reported to predict the response of sorafenib, but they are not still established yet. Other actionable
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gene or mutations in liver cancers are PIK3CA [76], TSC1/2 [77], KIT [49], and JAK1/2 [39], although their frequencies liver cancer are rare and we do not have any proof of their actionability or efficiency of molecular therapies to these targets in clinical trial level. Amplified actionable genes indicated that kinase inhibitors might be beneficial for 2030% of HCC patients by targeting amplification of EGFR, MET, BRAF or ERBB2 [17, 67]. AURKA (Aurora kinase A) is also frequently amplified in liver cancer, which might be good candidate to treat by alisertib [78]. Schulze et al. [79] reported that 28% of patients harboring at least one pathogenic alterations potentially targetable by an FDAapproved drug, and 86% harbored a mutation targetable by a drug studied in phase I and II clinical trials. The summary of the direct actionability of the mutated genes in liver
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cancer is shown in Table 1. Specifically in ICC, IDH1/2 mutation [80, 81] and FGFRfusion [61, 63, 82] are detected as actionable gene mutations in 5-10% of ICC and they are under clinical trials. Immunotherapy using immune checkpoint inhibitors has already shown great promise in some types of cancers. This approach has recently begun clinical testing in advanced HCC patients, and some promising results are obtained [83]. A phase I/II study of nivolumab in patients with advanced HCC demonstrated a 19% response rate (including 5% complete responses) [84]. The over-expression or genetic alterations of 11
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PD-L1 is likely to be associated with response to anti-PD-1/PD-L1 agents in some types of cancer such as lymphoma [85, 86], and immunohistochemical analysis showed that PD-L1 was expressed in 25% of HCC specimens and its expression was associated with the patient prognosis [87]. But PD-L1 is induced in hepatocytes by viral infection [88] and genomic alterations of PD-L1 was not detected in liver cancer, and other genomic biomarkers should be investigated to predict the response to the immune checkpoint inhibitor in liver cancer. Also, liver cancer has a uniquely immunosuppressive background [89]. It is required to address the specific issues of immuno-tolerance to virus infection and chronic liver inflammation that underlie HCC development and it is
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concerned that these immune checkpoint inhibitors and modulators can aggravate hepatitis or liver dysfunction in patients with liver cancer
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10. Conclusions Some thousands of liver cancer genome have been sequenced globally and most of driver
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genes/mutations with high frequency are established in liver cancer, including Wnt/catenin pathway, TP53/cell cycle pathway, telomere maintenance, and chromatin regulators. HBV integration is also a driver event in hepatocarcinogenesis. Etiology of liver cancer is most understood and mutational signatures of liver cancer can provide
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many evidence of the association between specific etiological factors and mutational signature. For precision medicine, actionable mutations with solid evidence is not frequently observed in liver cancer, and there is few molecular target therapy such as multi-kinase inhibitors so far. But it is possible that rare actionable mutations in liver cancer can guide other specific molecular therapy. Integration of large genomic data sets with functional and other omics data set will provide a new horizon for liver cancer treatment and evidences for precision medicine. Conflicts of interest None
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Acknowledgements The authors thank members of RIKEN-IMS, the Prof. Miyano’s laboratory in The Institute of Medical Sciences, The University of Tokyo, and all researchers involving TCGA for critical input into this manuscript. This work was supported partially by RIKEN President’s Fund 2011, and Grand-in-aid for RIKEN CGM and IMS,
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Figure Captions
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Figure 1 Mutations of Wnt/-catenin pathway in liver cancer. Mutations of the molecules in this pathway are found in 40-50% of liver cancer, mainly, CTNNB1, AXIN1, and APC. In addition, GSK3A, TCF7L2, several Wnt ligands and Wnt receptors FZD are mutated and these mutations are mutually exclusive. Figure 2 TERT mutations and TERT expression in liver cancers. These TERT hotspot promoter mutation occurs in HCC with 50-60% frequency. SVs,
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HBV integrations, and copy-number gain in the promoter or exon1 of TERT were associated with much higher expression of TERT that that in the cases with the promoter hotspot mutation, leading to the telomere maintenance, cell immortality, and chromosome stability of cancer cells.
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Figure 3 Mutational signature observed in liver cancers. Signature 24 represents the signature associated with aflatoxin, Signature 22 with aristolochic acid, Signature 4 with smoking. Signature 16 is likely to represents alcohol
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and acetaldehyde. Signature 12 is observed specifically in liver cancer, but its associated etiology is unknown. These signatures are from COSMIC database
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(http://cancer.sanger.ac.uk/cosmic/signatures).
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Figure 4 Diver mutations and etiological factors in hepatocarcinogenesis The left half pie indicates etiological factors in hepatocarcinogenesis, and the right half pie indicates driver mutations/pathways in liver cancer.
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Table 1 Driver mutated genes and actionability in liver cancer
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ARID1A BRD7 PBRM1 MLL4 Telomere maintenace TERT ATRX
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30-40% 5% 2-5% 5% 10% 5-10% 10-15%
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3% 1-3%
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30% 7%
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10%
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CCNE1 Ras/ERK pathway FGF19 RPS6KA3 ERRFI1 MET FGFR2 PRKACA Chromatin regulators ARID2
SV/ Virus Actionability CNA integration
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APC TCF7L2 TP53 /cell-cycle pathway TP53 IRF2 ATM RB1 CDKNA2 MYC CCND1
SNV /indel
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Wnt/-catenin pathway CTNNB1 AXIN1
Mutaion frequency
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Mutated genes
10-15% 5% 3-5% 5-10% 10% in ICC 90% in FL
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10-15%
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10-15% 3% 2% 3%
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50-60% 2-3%
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25
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2% 2%
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2-10%
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5% 5% 2%
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3% 3%
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5-10%
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JAK1/2 AKT/mTOR pathway PTEN TSC1/2 PIK3CA Oxidative stress pathway NFE2L2 KEAP1 Angiogenesis VEGFA
3% 2-3% 2-3% 10-15% 7%
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Liver metabolic pathway HNF1A HNF4A NCOR1 ALB APOB Inflammatory pathway IL6ST STAT3
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Matabolism and epigenomics IDH1/2 10% in ICC
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