Background: Next-generation sequencing (NGS) is a powerful and high-throughput method for the detection of viral mutations. This article provides a brief overview about optimization of NGS analysis for hepatocellular carcinoma (HCC)-associated hepatitis B virus (HBV) mutations, and hepatocarcinogenesis of relevant mutations. Main body: For the application of NGS analysis in the genome of HBV, four noteworthy steps were discovered in testing. First, a sample-specific reference sequence was the most effective mapping reference for NGS. Second, elongating the end of reference sequence improved mapping performance at the end of the genome. Third, resetting the origin of mapping reference sequence could probed deletion mutations and variants at a certain location with common mutations. Fourth, using a platform-specific cut-off value to distinguish authentic minority variants from technical artifacts was found to be highly effective. One hundred and sixty-seven HBV single nucleotide variants (SNVs) were found to be studied previously through a systematic literature review, and 12 SNVs were determined to be associated with HCC by meta-analysis. From comprehensive research using a HBV genome- wide NGS analysis, 60 NGS-defined HCC-associated SNVs with their pathogenic frequencies were identified, with 19 reported previously. All the 12 HCC-associated SNVs proved by meta-analysis were confirmed by NGS analysis, except for C1766T and T1768A which were mainly expressed in genotypes A and D, but including the subgroup analysis of A1762T. In the 41 novel NGS-defined HCC-associated SNVs, 31.7% (13/41) had cut-off values of SNV frequency lower than 20%. This showed that NGS could be used to detect HCC-associated SNVs with low SNV frequency. Most SNV II (the minor strains in the majority of non-HCC patients) had either low (< 20%) or high (> 80%) SNV frequencies in HCC patients, a characteristic U-shaped distribution pattern. The cut-off values of SNV frequency for HCC-associated SNVs represent their pathogenic frequencies. The pathogenic frequencies of HCC-associated SNV II also showed a U-shaped distribution. Hepatocarcinogenesis induced by HBV mutated proteins through cellular pathways was reviewed. Conclusion: NGS analysis is useful to discover novel HCC-associated HBV SNVs, especially those with low SNV frequency. The hepatocarcinogenetic mechanisms of novel HCC-associated HBV SNVs defined by NGS analysis deserve further investigation. Keywords: Deletion mutation, Next-generation sequencing, Hepatitis B virus, Hepatocarcinogenesis, Hepatocellular carcinoma, Single-nucleotide variant, U-shaped distribution * Correspondence: email@example.com I-Chin Wu and Wen-Chun Liu contributed equally to this work. Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan 70403, Taiwan, Republic of China Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Wu et al. Journal of Biomedical Science (2018) 25:51 Page 2 of 12 Background HBV infection, ranging from 6% at age 20–29 years to Hepatitis B virus (HBV) is a serious health problem 35% at age 50–59 years in HBeAg-positive patients, and because patients with chronic HBV infection are at risk 60% in HCC patients . These deletion mutations are for development of liver cirrhosis and hepatocellular found more frequent in genotype B (25%) and genotype carcinoma (HCC). It is estimated that 240 million people C (24.5%) than in the other genotypes . Some studies are chronic HBV carriers worldwide and 15 to 40% of showed that pre-S deletion mutations are an independ- them will develop liver cirrhosis, liver failure, or HCC ent risk factor for HCC [35–37], while other studies during their lifetime [1–5]. showed that combination of mutations (pre-S deletion, HBV is classified into ten genotypes, labeled A precore, and BCP mutations) rather than a single muta- through J, and over 40 related sub-genotypes. The ten tion, are associated with liver cirrhosis and liver diseases genotypes are based on an intergroup divergence of at progression [38, 39]. Pre-S deletion mutations could in- least 8% in the complete nucleotide sequence, while the duce endoplasmic reticulum (ER) stress, genomic instabil- sub-genotypes are based on a 4 to 7.5% divergence [6, 7]. ity, and hepatocyte proliferation [40–43]. In the transgenic The ten genotypes are also commonly found in certain mouse model, the pre-S2 deletion mutations can induce geographic locations as followed. Genotype A is the pre- dysplasia of hepatocytes and HCC development [33, 44]. dominant genotype in Northern Europe and the United Hepatitis B virus X protein (HBx), a nonstructural pro- States. Genotypes B and C are common in East and tein, is required for HBV covalently closed circular DNA Southeast Asia, while Genotype D is prevalent in the (cccDNA) transcription and viral replication [45, 46]. In Mediterranean, Middle East, and South Asia. Genotype E addition, HBx contributes to hepatocarcinogenesis through has been reported in West Africa, genotype F in Central interactions with multiple cellular proteins that modulate and South America, genotype G in the United States, cell proliferation, cell death, gene expression, and DNA France, and Germany, genotype H in Central America, repair [47–50]. Truncated HBx proteins have also been genotype I in Vietnam, and genotype J in the Ryukyu reported to promote hepatocarcinogenesis [51, 52]. Islands of Japan [8, 9]. It is important to note that HBV Previous studies showed that the risk of HCC was genotype A and B are associated with earlier hepatitis B e associated with the existence of specific HBV variants, antigen (HBeAg) seroconversion, less active liver disease, which were the major stains identified by traditional and a slower rate of progression to liver cirrhosis and direct Sanger sequencing. Although direct Sanger se- HCC as compared to HBV genotype C and D [9–12]. quencing is the most common method for analyzing Naturally occurring mutations in the precore and basal viral mutations, it is unable to determine the profile of a core promoter (BCP) regions are common. The most heterogeneous viral population in a patient. Next- common precore mutations are G1896A and G1899A, generation sequencing (NGS) however, can do this, as well of which G1896A creates a stop codon and prevents the as perform high-throughput analysis from thousands of synthesis of HBeAg . The most common BCP muta- amplified regions, characterize genetic diversity, and tions are A1762T and G1764A, which are associated detect minor strains that direct sequencing or cloning with reduced synthesis of HBeAg by suppressing the neither can find [53–55]. This study provides an overview transcription of precore mRNA [14, 15]. The precore about the possible applications of next-generation se- and BCP mutants are usually found in HBeAg-negative quencing analysis for the detection of hepatocellular patients but could also present as a mixture with wild- carcinoma-associated hepatitis B virus mutations. type virus in HBeAg-positive patients [16, 17]. The pre- core mutations are more common in patients with HBV Optimization of NGS analysis for HBV: Four genotype B and D than in patients with HBV genotype recommended steps A and C, whereas the BCP mutations are more common Use the sample-specific reference sequence as the mapping in patients with HBV genotype A and C than in patients reference with HBV genotype B and D [9, 18–21]. The precore Assembling the NGS reads into whole-genome sequences and BCP mutants are associated with liver cirrhosis, could be performed by de novo assembly or mapping HCC, and advanced liver disease [19, 22–25]. using reference sequences. De novo assembly is usually The pre-S protein plays an important role in the inter- employed in studying unknown species and would be hin- action with the immune system, as it contains B-cell and dered by regions with high diversity. For studying HBV, T-cell epitopes [26–28]. The pre-S1 domain contains the mapping reference is often utilized [55–57]. Two main hepatocyte binding site and is essential for virion assem- NGS platforms, Illumina Genome Analyzer and Roche bly and transportation [29–31]. The pre-S2 domain can Genome Sequencer, were widely used in viral quasispecies bind to polymerized human serum albumin, but the studies. Illumina generates larger data sets with shorter significance of this binding is unknown . The pre-S read length, as compared with Roche. Therefore, the NGS deletion mutations are prevalent in patients with chronic data generated by Illumina are usually assembled using Wu et al. Journal of Biomedical Science (2018) 25:51 Page 3 of 12 reference sequences as templates while de novo assembly is applicable but not commonly used [58, 59]. One of the major challenges for NGS is to monitor quality control metrics over all stages of the data pro- cessing pipeline. Alignment with a reconcilable mapping reference is a required step for any re-sequencing ana- lysis and is crucial for successful variant detection . HBV quasispecies involves an error-prone reverse tran- scription step in its replication, so that its rate of nucleo- tide change during replication is high and closed to the rate observed for the RNA viruses. The evolution rate of − 2 − 5 HBV ranges from 1.8 × 10 to 1.5 × 10 nucleotide substitutions/site/year [61–63], while that of the human − 8 genome is 1.1–3×10 nucleotide substitutions/site/ generation . Furthermore, HBV has differences in genomic lengths among 10 HBV genotypes (from 3182 to Fig. 1 The percentage of false SNV calls for using a different 3248 base pairs), which could result in genotype reference sequence. Full-length HBV genome sequence, Clone_N6 alignments containing several regions of gaps . (KJ790199; genotype C, Taiwan) was cloned from a CHB patient and Previous HBV-related NGS analyses used the con- sequenced using a direct Sanger sequencer. This nucleotide sequence sensus genotype sequences from public viral databases would beused asastandard sequence.Clone_N6was also fragmented to be sequenced by NGS analysis. The mapping results of [55, 56] or the major viral sequence identified by poly- NGS reads from the Clone_N6 using the following mapping references: merase chain reaction (PCR)-director sequencing as sample-specific reference, genotype specific reference (JN315779; mapping references to detect HBV variants. A sample- genotype C, Asia) and incompatible genotype reference (FJ787477; specific reference sequence is the consensus sequence genotype B, Asia). When compared with the standard sequence of obtained from the NGS reads of each sample through Clone_N6, derived from direct sequencing, the percentage of false SNVs calls increased significantly from 0.09% using sample-specific alignment with its same genotype mapping reference. In reference as mapping reference to 28.95% using incompatible geno- our demonstrations, we found that using this type of type reference as the mapping reference. Sample-specific reference is reference sequence as the mapping reference has the best the consensus sequence obtained from the NGS reads of each sample mapping quality and the highest single nucleotide variant through alignment with its same genotype mapping reference. (SNV) calling accuracy, as compared with using the Reference is using the same genotype as the sample (genotype C). Reference is using the incompatible genotype as the sample compatible genotype sequence . The percentage of (genotype B) false SNV calls increased significantly from 0.09% using a sample-specific reference sequence to 28.95% using an incompatible genotype reference (Fig. 1). These false SNVs approach was beneficial to improve mapping perform- would be especially prone to call in regions with high ance at the end of genomic sequence and detect deletion divergence. In addition, the sample-specific reference mutations spanning position 1 of HBV genome . sequence is effective in the analysis of HBV quasispecies, which is more complex to analyze due to its hetereogene- Use a platform-specific cut-off value to distinguish ity and structure. authentic minority variants from technical artifacts High-throughput sequencing techniques can generate Elongate the end of reference sequence and reset the origin low-interest variants in the form of false-positives, of mapping reference sequence especially from misalignment of sequencing reads and HBV genome is a circular structure with position 1 inaccuracies of the reference sequence compared to a conventionally taken to be the first “T” nucleotide in the specific local population . In order to distinguish EcoR1 restriction site (“GAATTC”). Some variants authentic minority variants from technical artifacts, we and deletion mutations, such as pre-S deletion muta- estimated the technical error rate and identified a tions, cross this site. Most genome mappers for NGS threshold above which mutations detected by NGS using analysis, like BWA , were designed for linear gen- Illumina HiSeq™ 2500 were unlikely to be technical arti- ome, but they were not well suited for circular genomes facts. The technical error rate was estimated by PCR like HBV genomes and will have worse mapping amplification and NGS of a plasmid expressed with HBV performance when reads spanned the end of genome. full-length genome. The mean error rate among three To resolve the problem, we manually concatenated the runs was estimated by comparing each NGS sequence end of reference sequence for 600 bases and reset the read to the plasmid control sequences. The empirical origin of mapping reference sequence from nt1600. This distribution of mismatch and deletion errors in the clone Wu et al. Journal of Biomedical Science (2018) 25:51 Page 4 of 12 yielded an average of 0.32 and 1.8%, respectively. Ac- mutations (G1896A and G1899A). For nucleotide sites cordingly, we used this empirically observed distribution 273 and 2227, 273A and 2227 T were SNV I and pro- of mismatch errors to distinguish sequence errors from tective factors for HCC, whereas 273G and 2227G were authentic minor variants by excluding possible technical SNV II and risk factors for HCC. All the other 21 SNVs errors, which were mutations present in < 3.2% of se- were risk factors for HCC, 6 of them were SNV I and 15 quence reads, a value 1 log above the mean overall error of them were SNV II (Table 1). Seventeen of 25 SNVs rate in the Illumina HiSeq™ 2500 platform. For deletion were missense mutations at the polymerase, preS2, sur- mutations, an exclusionary cutoff of < 1.8% was used face, precore, and core regions. Seven of the 17 missense [66, 68]. Some other studies had proposed the similar mutations and 4 of the 8 silent mutations were at the approach to distinguish authentic minority variants from regulatory elements, including CpG islands I/II/III, X technical artifacts with different cut-off value in its promoter, enhancer (Enh) I, ε loop, and BCP (Fig. 2). current platform [55–57]. This is an important step not to be ignored after variant calling. HCC-associated HBV SNVs for genotype C For genotype C, all the 35 HCC-associated SNVs located Apply these two analytic methods to better identify the at distinct nucleotide site were found, including BCP deletion mutations in the HBV genome mutations (G1764A and C1653T). All the 35 SNVs were Higher heterogeneity increases the uncertainty of reads- risk factors for HCC, 17 of them were SNV I and 18 of mapped genomic coordinates and leads to greater chal- them were SNV II (Table 1). Twenty-eight of 35 SNVs lenges in discovering deletion mutations. Several methods were missense mutations located at 4 open reading for deletion mutation discovery have been proposed, such frames (ORFs), particularly at the preS1 region and the as BreakDancer , Pindel , Breakpointer , but spacer domain of polymerase. Twenty one of the 28 mis- all these tools were mainly designed for human NGS data sense mutations and 3 of the 6 silent mutations were at and not entirely applicable for viruses with a high muta- the regulatory elements, including CpG islands I/II/III, tion rate. DeF-GPU is a graphics processing unit-based negative regulatory element (NRE)/core upstream regu- data mining method that incorporates the pattern growth latory sequence (CURS)/BCP, Enh I/II, core promoter, approach to identify HBV genomic deletions. Validation of and S2 promoter (Fig. 2). DeF-GPU on synthetic and real datasets showed that DeF-GPU outperforms the representative and commonly- used method Pindel, a pattern growth approach originally designed to detect either large deletions or medium-sized The U-shaped distribution pattern of SNV frequency in SNV insertions, and is able to exactly identify the deletions in II and the novel HCC-associated SNVs with low SNV few seconds . VirDelect uses the split read alignment frequency detected by NGS analysis method to obtain the exact breakpoints of deletions. The Almost all SNV I had SNV frequencies higher than 80%. experiments on simulation data and real data indicated The great majority of SNV II had either low (< 20%) or that VirDelect can identify more exact breakpoints of high (> 80%) SNV frequencies, i.e. a characteristic U- deletions than Pindel and is suitable for researchers with shaped distribution pattern of SNV frequencies with low higher requirements in accuracy than speed . (< 20%) or high (> 80%) values (Fig. 3). The cut-off values of SNV frequency for HCC-associated SNVs rep- HCC-associated HBV SNVs determined by next-generation resent their pathogenic frequencies. Almost all HCC- sequencing analysis associated SNV I had pathogenic frequencies higher Through HBV genome-wide NGS analysis, our previous than 80% and the great majority of HCC-associated study identified 60 NGS-defined HCC-associated SNVs and SNV II had either low (< 20%) or high (> 80%) patho- their pathogenic frequencies, including 41 novel SNVs. genic frequencies, a U-shaped distribution pattern Each SNV was specific for either genotype B (n =24) or (Fig. 4). Among the 60 NGS-defined HCC-associated genotype C (n = 34), except for nt53C, which was identified SNVs, 19 had been reported previously and 41 were in both genotypes. SNV I was defined as the dominant novel ones. In 19 HCC-associated SNVs reported pre- strain of HBV in the majority of non-HCC patients. SNV II viously, 94.7% (18/19) had cut-off values of SNV fre- was defined as the variant other than SNV I at the same quency greater than 20%, except nt456G, which had a nucleotide position, i.e. the minor strain of HBV in the cut-off value of 10.2%. In the other 41 novel HCC- majority of non-HCC patients . associated SNVs, 68.3% (28/41) had cut-off values of SNV frequency greater than 20%, while 31.7% (13/41) HCC-associated HBV SNVs for genotype B had cut-off values of less than 20% (Fig. 5). This showed For genotype B, 25 HCC-associated SNVs located at 23 that NGS could be used to detect HCC-associated SNVs nucleotide sites were identified, including the precore with low SNV frequency. Wu et al. Journal of Biomedical Science (2018) 25:51 Page 5 of 12 Table 1 HCC-associated SNVs with their pathogenic frequencies through NGS analysis, categorized by level of supporting evidence Genotype B Genotype C Site NT Odds ratio (95% CI) Pathogenic frequency (%) Site NT Odds ratio (95% CI) Pathogenic frequency (%) Level A 53 C 4.5 (1.8, 11.5) 32 53 C 5.1 (1.6, 16.7) 52.4 1896 A 3.5 (1.1,10.7) 96.5 1613 A 10.1 (1.2, 83.6) 86.7 1899 A 5.8 (1.1, 31.0) 96.1 1653 T 4.2 (1.3, 14.2) 60.8 1674 C 11.5 (1.4, 94.8) 55.8 1753 G 3.1 (1.1, 9.4) 100 1764 A 4.6 (1.7, 12.4) 100 1846 T 3.1 (1.2, 8.2) 21.1 Level B 1913 C 5.5 (1.1, 28.2) 94.3 1386 A 5.2 (1.1, 25.9) 96.7 2441 C 11.5 (1.4, 96.5) 100 2875 A 5.6 (1.7, 18.3) 94.8 2525 T 7.5 (1.5, 36.7) 95.5 3066 T 5.6 (1.2, 26.6) 86.8 3120 G 4.8 (1.6, 14.4) 95.9 Level C 2444 C 4.8 (1.6, 14.3) 92.6 456 G 6.0 (1.2, 29.3) 10.2 Novel 216 C 5.6 (1.2, 28.3) 100 293 G 2.9 (1.3, 6.4) 1.8 273 G 5.0 (2.0, 12.8) 12.2 446 G 5.6 (2.0, 15.2) 6.4 273 A 0.3 (0.1, 0.8) 55 633 A 5.6 (1.1, 27.5) 3.6 529 G 4.1 (1.4, 12.0) 100 834 G 7.6 (2.1, 28.2) 76.9 530 A 4.2 (1.3, 14.0) 100 1092 C 5.6 (1.2, 26.6) 50.1 724 C 4.0 (1.3, 12.0) 91.7 1155 C 5.6 (1.2, 26.6) 87.1 1173 G 9.2 (1.1, 76.5) 94.1 2201 T 3.7 (1.1, 11.9) 93.3 1221 C 4.1 (1.1, 14.1) 4.3 2573 C 4.2 (1.3, 14.2) 100 1242 G 5.1 (1.8, 14.6) 5.5 2594 A 4.0 (1.3, 12.4) 100 1359 A 3.6 (1.0, 12.5) 2.4 2708 G 5.8 (1.5, 22.1) 100 2095 G 3.2 (1.3, 8.0) 10.1 2840 T 8.3 (1.8, 38.3) 4.4 2120 G 3.6 (1.0, 12.5) 67.2 2889 G 5.5 (1.8, 17.6) 85.3 2213 G 9.8 (1.2, 83.1) 1.7 2901 T 4.1 (1.1, 15.4) 85.1 2226 T 9.8 (1.2, 83.1) 1.7 2931 C 9.1 (2.0, 41.6) 87.1 2227 G 9.8 (1.2, 83.1) 1.8 2988 C 9.0 (1.1, 73.6) 92.1 2227 T 0.2 (0.1, 0.8) 95.5 2989 A 9.0 (1.1, 73.6) 91.7 2583 G 6.5 (1.2, 32.3) 100 2997 T 9.0 (1.1, 73.6) 90.8 2690 A 4.9 (1.2, 19.3) 12 2998 C 9.0 (1.1, 73.6) 92.2 3006 A 14.1 (1.8, 111.8) 94.2 3009 G 5.0 (1.0, 24.0) 92.9 3016 C 9.0 (1.1, 73.6) 92.9 3021 A 11.4 (1.4, 91.9) 92.6 3097 A 4.5 (1.2, 16.8) 93.5 Note: The pathogenic frequencies were the cut-off values of SNV frequency for HCC-associated SNVs. The table has been adopted from  Validation of the NGS-defined HCC-associated SNVs conducted. One hundred and sixty-seven HBV variants For validating the 60 NGS-defined HCC-associated SNVs, had been studied previously and were categorized into 4 a systematic literature review and meta-analysis was levels of supporting evidence associated with HCC. Level Wu et al. Journal of Biomedical Science (2018) 25:51 Page 6 of 12 Fig. 2 Distinct NGS-derived SNVs located in HBV regulatory element and ORFs associated with HCC among patients with genotype B and genotype C. a, Twenty-five distinct NGS-defined HCC-associated SNVs were located in HBV regulatory elements and ORFs for genotype B HBV. b,Thirty fivedistinct NGS-defined HCC-associated SNVs were located in HBV regulatory elements and ORFs for genotype C HBV. * and ** indicate risk of SNVs for HCC with an odds ratio of HCC > 1 and with P value of < 0.05 and < 0.01, respectively. Ɨ means protective SNVs for HCC with an odds ratio of HCC < 1 and with a P value < 0.05. ● missense mutation; ○ silent mutation; � SNVs located in regulatory element. Level A means HCC-associated HBV variants supported by meta-analysis with at least 4 studies. Level B means HCC-associated HBV variants supported by at least one study if total number of relevant studies is less than 4. Level C means HBV variants unassociated with HCC supported by all studies if total number of relevant studies is less than 4. Red box indicated Level A; Blue box indicated Level B; Yellow box indicated Level C. The figure has been adopted from  Wu et al. Journal of Biomedical Science (2018) 25:51 Page 7 of 12 Fig. 3 The distribution of SNV frequencies in SNV I and SNV II. Almost all SNV I had SNV frequencies higher than 80%. The great majority of SNV II had either low (< 20%) or high (> 80%) SNV frequencies, i.e. a characteristic U-shaped distribution pattern of SNV frequencies with low (< 20%) or high (> 80%) values. a, All SNVs in genotype B HCC group. b, All SNVs in genotype B non-HCC group. c, All SNVs in genotype C HCC group. d, All SNVs in genotype C non-HCC group. SNV I was defined as the dominant strain of HBV in non-HCC group. SNV II was defined as the variant other than SNV I at the same nucleotide position, i.e. the minor strain of HBV in non-HCC group Fig. 4 The distribution of pathogenic frequencies in HCC-associated Fig. 5 The distribution of pathogenic frequencies in previously SNV I and SNV II. Almost all HCC-associated SNV I had pathogenic reported and novel HCC-associated SNVs. Among the 60 NGS- frequencies higher than 80% and the great majority of HCC- defined HCC-associated SNVs, 19 had been reported previously and associated SNV II had either low (< 20%) or high (> 80%) pathogenic 41 were novel ones. In 19 HCC-associated SNVs reported previously, frequencies, i.e. a U-shaped distribution pattern. SNV I was defined 94.7% (18/19) had cut-off values of SNV frequency > 20%, expect as the dominant strain of HBV in non-HCC group. SNV II was defined nt456G, which had a cut-off value of 10.2%. In the other 41 novel as the variant other than SNV I at the same nucleotide position, HCC-associated SNVs, 68.3% (28/41) had cut-off values of SNV i.e. the minor strain of HBV in non-HCC group frequency > 20 and 31.7% (13/41) had cut-off values < 20% Wu et al. Journal of Biomedical Science (2018) 25:51 Page 8 of 12 A included 12 HCC-associated HBV variants supported studies had indicated that unique HBV oncoproteins by meta-analysis with at least 4 studies. Level B included (HBx isoforms and preS mutants) and mutated precore/ 60 HCC-associated HBV variants supported by at least core proteins could induce hepatocarcinogenesis through one study if total number of relevant studies were less induction of endoplasmic reticulum (ER) and oxidative than 4. Level C included 85 HBV variants unassociated stress , activation of ER-independent pathway , with HCC supported by all studies if total number of rele- regulation of microRNA expression , lipid metabolism vant studies were less than 4. Level D included 10 HBV disturbance , or epigenetic modification through variants unassociated with HCC supported by meta- modified genomic methylation status . Mutations of analysis with at least 4 studies. The proportions of NGS- HBV regulatory elements probably induced hepatocarci- defined HCC-associated SNVs among HBV variants with nogenesis through oncoprotein expression modulation different levels of supporting evidence declined signifi- [79, 80], HBV DNA integration leading to chromosomal cantly with decreasing levels of evidence from Level A to instability , or HBV DNA methylation . Level D. All the HCC-associated HBV variants with Level A evidence, except for C1766T and T1768A which were Surface gene and protein mainly expressed in genotypes A and D, and the subgroup The HBV surface (S) proteins are produced from ORF S analysis of A1762T, were identified by NGS analysis. gene with three different translation sites, pre-S1, pre- Besides, 5 novel NGS-defined HCC-associated SNVs in S2, and S, to large, middle, and small surface proteins. the small surface region identified by our previous study The variability of the pre-S1 and pre-S2 regions were did influence hepatocarcinogenesis pathways, including higher in the HCC group than in the non-HCC group endoplasmic reticulum-stress and DNA repair systems, as [68, 83], and the mutations at the promoter sites of pre- shown by microarray, real-time polymerase chain reaction S1 and pre-S2 were significantly associated with an in- and western blot analysis . creased risk of HCC [37, 84]. The pre-S mutated large surface protein are retained in the ER to induce ER The advantage of NGS for the detection of HCC-associated stress signals and upregulate COX-2 and cyclin A to in- HBV mutations duce cell cycle progression . According to our previ- Our previous NGS analysis showed that the association ous NGS analysis for pre-S deletion in genotype C HBV, of HCC was related to specific SNVs and deletion muta- the HCC group had more patients with deletion muta- tions with a certain frequency instead of presence or tions involving nt2977–3013 (amino acid 43–56), deletion absence of specific variant. Risk HCC-associated SNVs patterns II or III , deletion mutations at S2 promoter, had significantly higher SNV frequency in HCC group and heat shock protein binding site in the preS region than in non-HCC group, whether they were dominant than the non-HCC group . Pre-S deletion mutants can strains or minor strains in HCC group. Protective HCC- cause accumulation of HBsAg in the ER and lead to ER associated SNVs had significantly lower SNV frequency stress and oxidative stress, which is known to cause DNA in HCC group than in non-HCC group. For deletion damage and alterations of several signaling pathways that mutations, the deletion of preS region was significantly are related to cell proliferation, invasion, cell survival, and associated with HCC, in terms of deletion index, which apoptosis . is composed of the deletion length and the deletion fre- In addition, a few point mutations of HBV surface pro- quency by NGS analysis, but there was no significant teins were reported to be associated with HCC, such as difference in the proportions of patients with deletion Q10L in pre-S1 region , F22 L in pre-S2 region , mutations between HCC patients and non-HCC pa- and I126S, G130 N, M133 L/T, and G145R in S region tients. In addition, the lower limit of detection using dir- [86–89]. However, the hepatocarcinogenesis mechanisms ect Sanger sequencing technology is ~ 20% minor allele of these variants remain unclear. From our previous NGS frequency. In our previous study, 31.7% (13/41) novel results, 4 missense mutations and 2 silent mutations lo- HCC-associated SNVs and 83.6% (138/165) deletion mu- cated in ORF S gene of genotype B HBV and concentrated tations had cut-off values of SNV frequency lower than on pre-S2 and small S regions; 10 missense mutations and 20%, which could only be detected by NGS analysis . 11 silent mutations distributed in ORF S gene of genotype Therefore, NGS is a powerful tool to characterize minor C HBV. We showed again that amino acid F22 L (nt strains among viral quasispecies which could not be de- T53C), Q10L (nt C2875A) and A216T (nt G530A) were tected even by direct sequencing or cloning. HCC-associated variants. On the other hand, we also identified the other NGS-defined HCC-associated SNVs HBV SNVs and deletion mutations related to HCC in small S region (Genotype B, nt T216C and nt A273G; development Genotype C, nt A293G, nt C446G, and nt A456G) could The mechanisms of hepatocarcinogenesis induced by affect hepatocarcinogenesis pathway through inducing ER HBV quasispecies are still not completely known. Many stress and regulating DNA repair system . Wu et al. Journal of Biomedical Science (2018) 25:51 Page 9 of 12 X gene and protein risk of HCC development exclusively in genotype C, but HBx, a protein encoded by HBV ORF X gene, was not in genotype B . For our previous NGS results, involved in many intracellular signal pathways which G1896A and G1899A were HCC-associated variants were closely associated with cell proliferation and cell barely in genotype B, while G1613A, C1653T, T1674C, apoptosis . Different HBx isoforms and C-terminal T1753 V, G1764A, and A1846T were genotype C spe- truncated HBx play important roles in HCC develop- cific HCC-associated variants. A1762T was identified as ment [85, 90]. HBx C-terminal region could interact an HCC-associated SNV by our NGS-based subgroup with intracellular molecules, through phosphorylation/ analysis of HBeAg-positive patients with genotype C HBV methylation or binding to certain molecules, which dir- infection. Based on our meta-analysis and NGS results, we ectly or indirectly contribute towards tumorigenesis again confirmed the mutations T1727A, A1752G, C1773A [91–94]. The C-terminal truncation of HBx plays a role and C1799G at BCP region and that T1858C and in enhancing cell invasiveness and metastasis in HCC, G1862 T at ORF C gene were not the risk variants for regulating miRNA transcription and promoting hepato- HCC development . Mutations in BCP and core gene cellular proliferation [95–97]. From our previous NGS were usually considered to possess the trans-activating ef- analysis, HBx deletions occurred only in a minority of fect to the core promoter, resulting from alteration of patients with HCC (genotype B: 3% (1/40), genotype C: binding affinity with trans-activator . These hotspot 4% (2/53)) and non-HCC (genotype B: 4% (2/47), mutations then would influence the complicated changes genotype C: 3% (2/61)), and were indeed localized in the in genomic activity for HBeAg expression and HBV DNA C-terminal of HBx. However, the proportion of patients replication, which may possibly lead to a more active with C-terminal truncation of HBx did not differ be- hepatitis and the risk to HCC [107, 108]. tween HCC and non-HCC patients. HBx-Ser31, an HBx mutation, had been investigated to Polymerase gene and protein exercise as an anti-apoptotic protein, resulting in enhan- The association between HBV polymerase (P) gene mu- cing tumor growth and suppressing tumorigenesis . tations and HCC has been rarely reported. HBV P gene Another study showed that HBV BCP mutations contain 4 domains as follows: a terminal protein (TP) re- (A1762T/G1764A), harbored in HBx gene lead to gion involved in priming the viral template, a spacer L130 M and V131I substitutions, could enhance S-phase (SP) region, a catalytic domain with reverse transcriptase kinase-associated protein 2 transcription, conversely (RT) activity, and a C-terminus that has ribonuclease H down-regulate cell cycle inhibitors, and provide a poten- (RNase H) activity. Polymerase dysfunction, in the form tial mechanism for HCC development . The Combo of an inability to package pre-genomic RNA into core (T1753A/A1762T/G1764A/T1768A) mutations in BCP particles, appeared to result from a single missense mu- result in four amino acid substitutions in HBx protein tation in the 5′ region of the gene in a single patient including I127R/S/T, L130 M, V131I, and F132Y, which with HCC . Focusing on RT domain which overlaps cause constitutive activation of the Wnt signaling path- with S gene, Wu et al. had characterized spontaneous way and play a pivotal role in HBV-associated hepatocar- mutations in the HBV RT region and indicated that cinogenesis . According to our previous NGS results, A799G, A987G, and T1055A were independent risk genotype C HBV bear HCC-associated SNVs in X gene factors for HCC using Sanger sequencing . Li et al. (G1386A, G1613A, C1653T, T1674C, T1753G, and indicated that rtF221Y (T791A), identified by the Sanger G1764A) and most of them clustered on C terminal of method, was an independent risk factor for the postopera- HBx, while genotype B HBV did not. These mutations tive recurrence of HCC and poor overall survival rates changed HBx protein sequences to 5 M, 80I, 94Y, 101P, . Regarding the HCC-associated SNVs by our previ- 127S, and 131I, which might affect the regulatory do- ous NGS analysis, only rtN134D (nt A529G) and tpK93E main to change the self-regulatory mechanism of X gene (nt A2583G) of genotype B and rtH55R (nt A293G) and expression, and impact the transactivation domain to rtS106C (nt C446G) of genotype C were nonsynonymous regulate HBV replication and cellular pathway [99–102]. substitution in TP and RT domains affecting viral replica- tion fitness. The other SNVs, located in spacer region and Precore/core gene and protein overlapped with pre-S region, did not affect the poly- The BCP and its adjacent precore region are crucial for merase activity . The related mechanisms of these replication of HBV. HBV mutations at BCP and precore HCC-associated SNVs involved in polymerase activity and region have been considered classical risk factors for hepatocarcinogenesis need to be further explored. HBV-related HCC, such as T1753 V, G1896A, G1899A, G1613A, and C1653T, which occur in core promoter Conclusion and ORF C gene [103–106]. The BCP A1762T/G1764A NGS analysis is a powerful and high-throughput method double mutations have been indicated to increase the for the detection of HCC-associated HBV mutations. Wu et al. Journal of Biomedical Science (2018) 25:51 Page 10 of 12 This method is useful to discover novel HCC-associated 11. Chu CJ, Hussain M, Lok AS. 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Wild-type levels of pregenomic RNA and reticulum; HBeAg: Hepatitis B e antigen; HBV: Hepatitis B virus; HBx: Hepatitis replication but reduced pre-C RNA and e-antigen synthesis of hepatitis B B virus X protein; HCC: Hepatocellular carcinoma; NGS: Next-generation virus with C(1653) −> T, a(1762) −> T and G(1764) −> a mutations in the sequencing; NRE: Negative regulatory element; ORF: Open reading frame; core promoter. J Gen Virol. 1998;79(Pt 2):375–80. P: Polymerase; PCR: Polymerase chain reaction; RNaseH: Ribonuclease H; 16. Chu CJ, Keeffe EB, Han SH, Perrillo RP, Min AD, Soldevila-Pico C, et al. RT: Reverse transcriptase; S: Surface; SNV: Single nucleotide variant; Prevalence of HBV precore/core promoter variants in the United States. SP: Spacer; TP: Terminal protein Hepatology. 2003;38:619–28. 17. Hadziyannis SJ, Vassilopoulos D. Hepatitis B e antigen-negative chronic Authors’ contributions hepatitis B. Hepatology. 2001;34:617–24. I-CW and W-CL contributed equally to this article. All authors read and 18. Chan HL, Hussain M, Lok AS. Different hepatitis B virus genotypes are approved the final manuscript. associated with different mutations in the core promoter and precore regions during hepatitis B e antigen seroconversion. Hepatology. Ethics approval and consent to participate 1999;29:976–84. Not applicable. 19. Chen CH, Lee CM, Hung CH, Hu TH, Wang JH, Wang JC, et al. Clinical significance and evolution of core promoter and precore mutations in HBeAg-positive patients with HBV genotype B and C: a longitudinal study. Competing interests Liver Int. 2007;27:806–15. The authors declare that they have no competing interests. 20. Nguyen MH, Keeffe EB. Are hepatitis B e antigen (HBeAg)-positive chronic hepatitis B and HBeAg-negative chronic hepatitis B distinct diseases? Author details Clin Infect Dis. 2008;47:1312–4. Department of Internal Medicine, National Cheng Kung University Hospital, 21. Yuen MF, Fung SK, Tanaka Y, Kato T, Mizokami M, Yuen JC, et al. College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Longitudinal study of hepatitis activity and viral replication before and after Tainan 70403, Taiwan, Republic of China. Infectious Disease and Signaling HBeAg seroconversion in chronic hepatitis B patients infected with Research Center, National Cheng Kung University, Tainan, Taiwan, Republic of genotypes B and C. J Clin Microbiol. 2004;42:5036–40. China. 22. Chen CH, Lee CM, Lu SN, Changchien CS, Eng HL, Huang CM, et al. Clinical significance of hepatitis B virus (HBV) genotypes and precore and core Received: 11 January 2018 Accepted: 30 April 2018 promoter mutations affecting HBV e antigen expression in Taiwan. J Clin Microbiol. 2005;43:6000–6. 23. Kao JH, Chen PJ, Lai MY, Chen DS. Basal core promoter mutations of Reference hepatitis B virus increase the risk of hepatocellular carcinoma in hepatitis B 1. Lavanchy D. Hepatitis B virus epidemiology, disease burden, treatment, and carriers. 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Journal of Biomedical Science – Springer Journals
Published: Jun 2, 2018
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