To survey hepatitis B virus (HBV) integration in liver cancer genomes, we conducted massively parallel sequencing of 81 HBV-positive and 7 HBV-negative hepatocellular carcinomas (HCCs) and adjacent normal tissues. We found that HBV integration is observed more frequently in the tumors (86.4%) than in adjacent liver tissues (30.7%). Copy-number variations (CNVs) were significantly increased at HBV breakpoint locations where chromosomal instability was likely induced. Approximately 40% of HBV breakpoints within the HBV genome were located within a 1,800-bp region where the viral enhancer, X gene and core gene are located. We also identified recurrent HBV integration events (in ≥ 4 HCCs) that were validated by RNA sequencing (RNA-seq) and Sanger sequencing at the known and putative cancer-related TERT, MLL4 and CCNE1 genes, which showed upregulated gene expression in tumor versus normal tissue. We also report evidence that suggests that the number of HBV integrations is associated with patient survival.

Tumor heterogeneity presents a challenge for inferring clonal evolution and driver gene identification. Here, we describe a method for analyzing the cancer genome at a single-cell nucleotide level. To perform our analyses, we first devised and validated a high-throughput whole-genome single-cell sequencing method using two lymphoblastoid cell line single cells. We then carried out whole-exome single-cell sequencing of 90 cells from a JAK2-negative myeloproliferative neoplasm patient. The sequencing data from 58 cells passed our quality control criteria, and these data indicated that this neoplasm represented a monoclonal evolution. We further identified essential thrombocythemia (ET)-related candidate mutations such as SESN2 and NTRK1, which may be involved in neoplasm progression. This pilot study allowed the initial characterization of the disease-related genetic architecture at the single-cell nucleotide level. Further, we established a single-cell sequencing method that opens the way for detailed analyses of a variety of tumor types, including those with high genetic complex between patients.

We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the United States Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed, for these and qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.

Hepatocellular carcinoma (HCC) is one of the most deadly cancers worldwide and has no effective treatment, yet the molecular basis of hepatocarcinogenesis remains largely unknown. Here we report findings from a whole-genome sequencing (WGS) study of 88 matched HCC tumor/normal pairs, 81 of which are Hepatitis B virus (HBV) positive, seeking to identify genetically altered genes and pathways implicated in HBV-associated HCC. We find beta-catenin to be the most frequently mutated oncogene (15.9%) and TP53 the most frequently mutated tumor suppressor (35.2%). The Wnt/beta-catenin and JAK/STAT pathways, altered in 62.5% and 45.5% of cases, respectively, are likely to act as two major oncogenic drivers in HCC. This study also identifies several prevalent and potentially actionable mutations, including activating mutations of Janus kinase 1 (JAK1), in 9.1% of patients and provides a path toward therapeutic intervention of the disease.

In this cohort, approximately 85% of individuals have known driver mutations (EGFR 59.4%, KRAS 7.4%, ALK 7.4%, ERBB2 2.6%, ROS1 2.2%, RET 2.2%, MET 1.8%, BRAF 1.1%, and NRAS 0.4%). Seventy percent of smokers and 90% of nonsmokers had defined oncogenic drivers matching the U.S. Food and Drug Administration-approved targeted therapies.