The effects of hepatitis B virus integration into the genomes of hepatocellular carcinoma patients

Abstract

Hepatitis B virus (HBV) infection is a leading risk factor for hepatocellular carcinoma (HCC). HBV integration into the host genome has been reported, but its scale, impact and contribution to HCC development is not clear. Here, we sequenced the tumor and nontumor genomes (>80× coverage) and transcriptomes of four HCC patients and identified 255 HBV integration sites. Increased sequencing to 240× coverage revealed a proportionally higher number of integration sites. Clonal expansion of HBV-integrated hepatocytes was found specifically in tumor samples. We observe a diverse collection of genomic perturbations near viral integration sites, including direct gene disruption, viral promoter-driven human transcription, viral-human transcript fusion, and DNA copy number alteration. Thus, we report the most comprehensive characterization of HBV integration in hepatocellular carcinoma patients. Such widespread random viral integration will likely increase carcinogenic opportunities in HBV-infected individuals.

Figure 1.

Tumor-specific clonal expansion of virus-integrated hepatocytes in HCC. For each sequenced human genome, viral integration is quantified as the total number of paired-end reads where at least one arm maps to the HBV genome (A), the number of human-viral chimeric reads (B), and the number of chimeric reads as a function of the genomic location of HBV integration sites in the human genome (C). In contrast to the matched nontumor samples, tumor samples carry a few loci with a substantially larger number of chimeric reads. (T) Hepatocellular carcinoma tumor samples. (N) Matched nontumor liver samples. (B) Blood samples. The legend in panel C indicates internal identifiers for the three HBV positive patients in this study.

Figure 2.

Transcriptional effect of HBV integration on the human genome. Local transcriptional effect of HBV integration on the human genome is shown, for the most abundant integration site for each patient (A–C) and for all integration sites (D), based on RNA-seq data. (A) MLL4 is highly overexpressed in the tumor sample with the HBV integration event (31107). (B) Substantial overexpression of ANGPT1 in the tumor from patient H442 with HBV integration upstream (∼10 kb) of ANGPT1. (C) A novel human-viral fusion transcript in the tumor sample with HBV integration in a nongenic region (patient: 31656). Asterisks indicate samples with viral integration. (D) Transcriptional effect at human-viral junctions defined by DNA-seq. The human-viral junctions supported by multiple DNA-seq chimeric reads (n = 48) are represented as a dotted line at the center. We then used the RNA-seq data to infer the transcriptional changes on each side of these junctions. The color in the heatmap represents the fold-change for each interval, measured as the difference in the generalized log of the RPKM of the altered genome (i.e., the genome containing the viral insertion) versus the unaltered genome. Samples carrying the insertion are indicated as either N (Nontumor) or T (Tumor). The rows were grouped by hierarchical clustering.

Figure 3.

Genomic instability at the viral integration site near the caspase locus. (A) DNA-seq coverage and transcription around a chr11q22 HBV integration site in patient 31656. (Top panel) Normalized, GC-corrected DNA-seq coverage values in 50-kb windows, with the horizontal red line representing the resulting copy-number segments. There is a copy-number breakpoint right at the HBV integration site, with a copy-number loss of the chromosomal region 3′ from the integration site. Red and blue bar plots show transcription (RNA-seq read coverage) in this locus in the tumor and matched normal, respectively. (B) Genes closest to the integration site within this deletion were significantly down-regulated, including CASP12, CASP4, CASP5, CASP1, CARD16, and CARD17.

Figure 4.

Viral-human fusion transcripts are common in both HCC and nontumor samples. (A) The genomic coordinate on the HBV genome of each chimeric RNA-seq read is plotted against its genomic coordinate on the human genome (linearized after concatenating all chromosomes). Only locations supported by two or more chimeric reads are shown. (B) Viral junctions determined from clusters of two or more chimeric reads are shown as vertical bars, with part of the remaining integrated viral sequence (50 bp) indicated as horizontal lines. Reads from both RNA- and DNA-seq are shown. A large majority of the RNA-seq junctions are in close proximity (10 bp) to the DR1 (Direct repeat 1) region on the HBV genome. (Blue) Clusters from nontumor liver samples; (red) clusters from tumor samples. (C) A global view of the transcriptional consequence of viral integration on the flanking human genome. The data were organized in the same manner as in Figure 2D, except that the human junctions in this panel are based on RNA-seq data instead of DNA-seq data. Most of the sites show strong unidirectional transcriptional up-regulation, starting at the integration site, while relatively fewer sites correlate with nondirectional transcriptional down-regulation or up-regulation.

Figure 5.

Mutation signature and structural variations in HCC patients. (A) High confidence, somatic single-base substitutions were classified into all six categories of base substitutions. The fraction of mutations belonging to each category is shown for the four HCC patients, and compared to signatures previously found in NSCLC (Lee et al. 2010), SCLC (Pleasance et al. 2010b), melanoma (Pleasance et al. 2010a), and germline variations. (B) Number of predicted structural variations detected in both HBV positive and negative HCC patients. (Intra) Intrachromosomal SVs. (Inter) Interchromosomal SVs.

Figure 6.

Summary of somatic genomic alterations in HCC patients. Various types of somatic alterations in the four HCC patient genomes using circos plots (Krzywinski et al. 2009) (A–D). High confidence somatic structural variations (SVs) are shown as lines, with red lines representing interchromosomal SVs and blue lines indicating intrachromosomal SVs. (Green bars) Regions of loss of heterozygosity and allelic imbalance. Somatic copy number alterations are shown as bar plots with copy number gain shown in red and copy number loss in blue (the scale ranges from −2 to 4). Each surrounding red dot represents the number of high-confidence somatic SNVs within a 1 million base pair window. (Triangles) Major HBV integration sites. Patient's identifier and HBV status are shown at the center of each circular view.