Characterization of tumor evolution by functional clonality and phylogenetics in hepatocellular carcinoma.

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.

Pan-viral serology uncovers distinct virome patterns as risk predictors of hepatocellular carcinoma and intrahepatic cholangiocarcinoma.

This study evaluates the pan-serological profiles of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA) compared to several diseased and non-diseased control populations to identify risk factors and biomarkers of liver cancer. We used phage immunoprecipitation sequencing, an anti-viral antibody screening method using a synthetic-phage-displayed human virome epitope library, to screen patient serum samples for exposure to over 1,280 strains of pathogenic and non-pathogenic viruses. Using machine learning methods to develop an HCC or iCCA viral score, we discovered that both viral scores were positively associated with several liver function markers in two separate at-risk populations independent of viral hepatitis status. The HCC score predicted all-cause mortality over 8 years in patients with chronic liver disease at risk of HCC, while the viral hepatitis status was not predictive of survival. These results suggest that non-hepatitis viral infections may contribute to HCC and iCCA development and could be biomarkers in at-risk populations.

Gut dysbiosis in Thai intrahepatic cholangiocarcinoma and hepatocellular carcinoma.

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.

Integration of adeno-associated virus (AAV) into the genomes of most Thai and Mongolian liver cancer patients does not induce oncogenesis.

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.

Common Molecular Subtypes Among Asian Hepatocellular Carcinoma and Cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) are clinically disparate primary liver cancers with etiological and biological heterogeneity. We identified common molecular subtypes linked to similar prognosis among 199 Thai ICC and HCC patients through systems integration of genomics, transcriptomics, and metabolomics. While ICC and HCC share recurrently mutated genes, including TP53, ARID1A, and ARID2, mitotic checkpoint anomalies distinguish the C1 subtype with key drivers PLK1 and ECT2, whereas the C2 subtype is linked to obesity, T cell infiltration, and bile acid metabolism. These molecular subtypes are found in 582 Asian, but less so in 265 Caucasian patients. Thus, Asian ICC and HCC, while clinically treated as separate entities, share common molecular subtypes with similar actionable drivers to improve precision therapy.

NSIT: novel sequence identification tool.

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.