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BackgroundHepatocellular carcinoma (HCC) is a significant global cancer burden, with rising incidence and lacking a unified prevention strategy due to complex aetiologies. Viral exposures may shape host immunity via specific reactive viral antigens that could induce immune responses against hepatocarcinogenesis.ObjectiveWe aimed to characterise viral exposure differences between HCC patients and healthy individuals and identify potentially protective viral antigens against HCC.DesignWe profiled pan-viral serological antibody repertoires using a microbial phage library among 2647 study subjects and examined the biological activities of selective viral antigens on blood-derived immune cells from both healthy individuals and HCC patients.ResultWe identified 153 viral antigens with a significantly reduced serological response in HCC patients compared with healthy individuals. We also observed that a higher serological response to 153 viral antigens is associated with better clinical outcomes of patients with chronic liver diseases and HCC. These findings are consistent across different populations across sex, ethnicity and aetiology. We identified a common epitope (CE1) shared among 39% of reactive viral antigens that belong to the rhinovirus and enterovirus families. We demonstrated that CE1 could induce both CD4+ and CD8+ T-cell activation and CD8+ T-cell-mediated HCC cell killing.ConclusionsOur results suggest that past exposures to members of the Enterovirus genus may be advantageous for cancer patients, highlighting the potential for a viral peptide-based HCC vaccine.

Primary liver cancer (PLC), which includes intrahepatic cholangiocarcinoma (iCCA) and hepatocellular carcinoma (HCC), has the highest incidence of all cancer types in Thailand. Known etiological factors, such as viral hepatitis and chronic liver disease do not fully account for the country’s unusually high incidence. However, the gut-liver axis, which contributes to carcinogenesis and disease progression, is influenced by the gut microbiome. To investigate this relationship, fecal matter from 44 Thai PLC patients and 76 healthy controls were subjected to whole-genome metagenomic shotgun sequencing and then analyzed by marker gene-based and assembly based methods. Results revealed greater gut microbiome heterogeneity in iCCA compared to HCC and healthy controls. Two Veillonella species were found to be more abundant in iCCA samples and could distinguish iCCA from HCC and healthy controls. Conversely, Ruminococcus gnavus was depleted in iCCA patients and could distinguish HCC from iCCA samples. High Veillonella genus counts in the iCCA group were associated with enriched amino acid biosynthesis and glycolysis pathways, while enriched phospholipid and thiamine metabolism pathways characterized the HCC group with high Blautia genus counts. These findings reveal distinct landscapes of gut dysbiosis among Thai iCCA and HCC patients and warrant further investigation as potential biomarkers.

Background Engineered versions of adeno-associated virus (AAV) are commonly used in gene therapy but evidence revealing a potential oncogenic role of natural AAV in hepatocellular carcinoma (HCC) has raised concerns. The frequency of potentially oncogenic integrations has been reported in only a few populations. AAV infection and host genome integration in another type of liver cancer, cholangiocarcinoma (CCA), has been studied only in one cohort. All reported oncogenic AAV integrations in HCC come from strains resembling the fully sequenced AAV2 and partly sequenced AAV13. When AAV integration occurs, only a fragment of the AAV genome is detectable in later DNA or RNA sequencing. The integrated fragment is typically from the 3’ end of the AAV genome, and this positional bias has been only partly explained. Three research groups searched for evidence of AAV integration in HCC RNAseq samples in the Cancer Genome Atlas (TCGA) but reported conflicting results. Results We collected and analyzed whole transcriptome and viral capture DNA sequencing in paired tumor and non-tumor samples from two liver cancer Asian cohorts from Thailand ( N  = 147, 47 HCC and 100 intrahepatic cholangiocarcinoma (iCCA)) and Mongolia ( N  = 70, all HCC). We found only one HCC patient with a potentially oncogenic integration of AAV, in contrast to higher frequency reported in European patients. There were no oncogenic AAV integrations in iCCA patients. AAV genomic segments are present preferentially in the non-tumor samples of Thai patients. By analyzing the AAV genome positions of oncogenic and non-oncogenic integrated fragments, we found that almost all the putative oncogenic integrations overlap the X gene, which is present and functional only in the strain AAV2 among all fully sequenced strains. This gene content difference could explain why putative oncogenic integrations from other AAV strains have not been reported. We resolved the discrepancies in previous analyses of AAV presence in TCGA HCC samples and extended it to CCA. There are 12 TCGA samples with an AAV segment and none are in Asian patients. AAV segments are present in preferentially in TCGA non-tumor samples, like what we observed in the Thai patients. Conclusions Our findings suggest a minimal AAV risk of hepatocarcinogenesis in Asian liver cancer patients. The partial genome presence and positional bias of AAV integrations into the human genome has complicated analysis of possible roles of AAV in liver cancer.

Hepatocellular carcinoma (HCC) is a molecularly heterogeneous solid malignancy, and its fitness may be shaped by how its tumor cells evolve. However, ability to monitor tumor cell evolution is hampered by the presence of numerous passenger mutations that do not provide any biological consequences. Here we develop a strategy to determine the tumor clonality of three independent HCC cohorts of 524 patients with diverse etiologies and race/ethnicity by utilizing somatic mutations in cancer driver genes. We identify two main types of tumor evolution, i.e., linear, and non-linear models where non-linear type could be further divided into classes, which we call shallow branching and deep branching. We find that linear evolving HCC is less aggressive than other types. GTF2IRD2B mutations are enriched in HCC with linear evolution, while TP53 mutations are the most frequent genetic alterations in HCC with non-linear models. Furthermore, we observe significant B cell enrichment in linear trees compared to non-linear trees suggesting the need for further research to uncover potential variations in immune cell types within genomically determined phylogeny types. These results hint at the possibility that tumor cells and their microenvironment may collectively influence the tumor evolution process. Clonality study in HCC finds diverse evolution patterns. Linear HCC is less aggressive, with GTF2IRD2B driver mutations. Non-linear has shallow/deep branching patterns with frequent TP53 driver mutations.

Novel sequences are DNA sequences present in an individual's genome but absent in the human reference assembly. They are predicted to be biologically important, both individual and population specific, and consistent with the known human migration paths. Recent works have shown that an average person harbors 2-5 Mb of such sequences and estimated that the human pan-genome contains as high as 19-40 Mb of novel sequences. To identify them in a de novo genome assembly, some existing sequence aligners have been used but no computational method has been specifically proposed for this task. In this work, we developed NSIT (Novel Sequence Identification Tool), a software that can accurately and efficiently identify novel sequences in an individual's de novo whole genome assembly. We identified and characterized 1.1 Mb, 1.2 Mb, and 1.0 Mb of novel sequences in NA18507 (African), YH (Asian), and NA12878 (European) de novo genome assemblies, respectively. Our results show very high concordance with the previous work using the respective reference assembly. In addition, our results using the latest human reference assembly suggest that the amount of novel sequences per individual may not be as high as previously reported. We additionally developed a graphical viewer for comparisons of novel sequence contents. The viewer also helped in identifying sequence contamination; we found 130 kb of Epstein-Barr virus sequence in the previously published NA18507 novel sequences as well as 287 kb of zebrafish repeats in NA12878 de novo assembly. NSIT requires [Formula: see text]2GB of RAM and 1.5-2 hrs on a commodity desktop. The program is applicable to input assemblies with varying contig/scaffold sizes, ranging from 100 bp to as high as 50 Mb. It works in both 32-bit and 64-bit systems and outperforms, by large margins, other fast sequence aligners previously applied to this task. To our knowledge, NSIT is the first software designed specifically for novel sequence identification in a de novo human genome assembly.

BackgroundIntraductal papillary neoplasm of the bile duct (IPNB) is a specific entity characterized by slow intraluminal growth of bile duct epithelia with a fine fibro-vascular core. It is typically multi-focal with various degrees of invasion and progresses through the adenoma-carcinoma sequence. We examined its genetic heterogeneity via multi-region whole exome sequencing on surgical specimens of a patient whose IPNB was detected in the liver segment IV in 2010, but the patient refused surgery. In 2017, an additional growth was found in segment VIII and surgery was performed.MethodsThe surgical samples were collected after the informed consent of the patient, approved by the Institutional Review Boards of Chulabhorn Research Institute (protocol #18/2555) and Khon Kaen University (protocol #HE541099). Multiple surgical specimens were chosen based on gross findings: from segment IV, the common hepatic duct (CHD), segment VIII, and the right anterior duct (RAD). DNA was extracted from frozen tumor tissues and peripheral blood, and whole exome sequencing was conducted with each sample sequenced to an average coverage of 100X. The data was analyzed following the best practice workflow of the Genome Analysis Toolkit to identify somatic single nucleotide variants and small insertions and deletions in each sector.ResultsEvaluation of somatic mutations revealed two spatially unique tumor clones with non-overlapping mutational profiles. The first clone was localized to segments IV and CHD, whereas the second clone was to segments VIII and RAD. A notable result was that the adenoma-carcinoma sequence early, intermediate, and late driver genes, APC, KRAS, and TP53, respectively, were mutated in the first clone where the tumor had been developing since 2010 and was histologically confirmed to be carcinoma in situ in 2017. In addition, APC and TP53 were mutated in the second clone which was detected in 2017 and confirmed to have both adenoma and carcinoma in situ components.ConclusionsCombining the patient’s clinical records with spatial-genetic heterogeneity revealed the unique clonal evolution of IPNB. Our results showed two distinct mutational profiles demonstrating different tumor morphology and multifocality, supporting its slow-growing nature, and providing possible evidence of tumor development along the adenoma-carcinoma sequence.

Treatment effectiveness in hepatocellular carcinoma (HCC) depends on early detection and precision-medicine-based patient stratification for targeted therapies. However, the lack of robust biomarkers, particularly a non-invasive diagnostic tool, precludes significant improvement of clinical outcomes for HCC patients. Serum metabolites are one of the best non-invasive means for determining patient prognosis, as they are stable end-products of biochemical processes in human body. In this study, we aimed to identify prognostic serum metabolites in HCC. To determine serum metabolites that were relevant and representative of the tissue status, we performed a two-step correlation analysis to first determine associations between metabolic genes and tissue metabolites, and second, between tissue metabolites and serum metabolites among 49 HCC patients, which were then validated in 408 additional Asian HCC patients with mixed etiologies. We found that certain metabolic genes, tissue metabolites and serum metabolites can independently stratify HCC patients into prognostic subgroups, which are consistent across these different data types and our previous findings. The metabolic subtypes are associated with β-oxidation process in fatty acid metabolism, where patients with worse survival outcome have dysregulated fatty acid metabolism. These serum metabolites may be used as non-invasive biomarkers to define prognostic tumor molecular subtypes for HCC.

Novel sequences are DNA sequences present in an individual's genome but absent in the human reference assembly. They are predicted to be biologically important, both individual and population specific, and consistent with the known human migration paths. Recent works have shown that an average person harbors 2-5 Mb of such sequences and estimated that the human pan-genome contains as high as 19-40 Mb of novel sequences. To identify them in a de novo genome assembly, some existing sequence aligners have been used but no computational method has been specifically proposed for this task. In this work, we developed NSIT (Novel Sequence Identification Tool), a software that can accurately and efficiently identify novel sequences in an individual's de novo whole genome assembly. We identified and characterized 1.1 Mb, 1.2 Mb, and 1.0 Mb of novel sequences in NA18507 (African), YH (Asian), and NA12878 (European) de novo genome assemblies, respectively. Our results show very high concordance with the previous work using the respective reference assembly. In addition, our results using the latest human reference assembly suggest that the amount of novel sequences per individual may not be as high as previously reported. We additionally developed a graphical viewer for comparisons of novel sequence contents. The viewer also helped in identifying sequence contamination; we found 130 kb of Epstein-Barr virus sequence in the previously published NA18507 novel sequences as well as 287 kb of zebrafish repeats in NA12878 de novo assembly. NSIT requires 2GB of RAM and 1.5-2 hrs on a commodity desktop. The program is applicable to input assemblies with varying contig/scaffold sizes, ranging from 100 bp to as high as 50 Mb. It works in both 32-bit and 64-bit systems and outperforms, by large margins, other fast sequence aligners previously applied to this task. To our knowledge, NSIT is the first software designed specifically for novel sequence identification in a de novo human genome assembly.