Seeksv: an accurate tool for somatic structural variation and virus integration detection.

MOTIVATION: Many forms of variations exist in the human genome including single nucleotide polymorphism, small insert/deletion (DEL) (indel) and structural variation (SV). Somatically acquired SV may regulate the expression of tumor-related genes and result in cell proliferation and uncontrolled growth, eventually inducing tumor formation. Virus integration with host genome sequence is a type of SV that causes the related gene instability and normal cells to transform into tumor cells. Cancer SVs and viral integration sites must be discovered in a genome-wide scale for clarifying the mechanism of tumor occurrence and development. RESULTS: In this paper, we propose a new tool called seeksv to detect somatic SVs and viral integration events. Seeksv simultaneously uses split read signal, discordant paired-end read signal, read depth signal and the fragment with two ends unmapped. Seeksv can detect DEL, insertion, inversion and inter-chromosome transfer at single-nucleotide resolution. Different types of sequencing data, such as single-end sequencing data or paired-end sequencing data can accommodate to detect SV. Seeksv develops a rescue model for SV with breakpoints located in sequence homology regions. Results on simulated and real data from the 1000 Genomes Project and esophageal squamous cell carcinoma samples show that seeksv has higher efficiency and precision compared with other similar software in detecting SVs. For the discovery of hepatitis B virus integration sites from probe capture data, the verified experiments show that more than 90% viral integration sequences detected by seeksv are true. AVAILABILITY AND IMPLEMENTATION: seeksv is implemented in C ++ and can be downloaded from https://github.com/qkl871118/seeksv CONTACT: : dragonbw@163.comSupplementary information: Supplementary data are available at Bioinformatics online.

Distinct Subtypes of Gastric Cancer Defined by Molecular Characterization Include Novel Mutational Signatures with Prognostic Capability.

Gastric cancer is not a single disease, and its subtype classification is still evolving. Next-generation sequencing studies have identified novel genetic drivers of gastric cancer, but their use as molecular classifiers or prognostic markers of disease outcome has yet to be established. In this study, we integrated somatic mutational profiles and clinicopathologic information from 544 gastric cancer patients from previous genomic studies to identify significantly mutated genes (SMG) with prognostic relevance. Gastric cancer patients were classified into regular (86.8%) and hypermutated (13.2%) subtypes based on mutation burden. Notably, TpCpW mutations occurred significantly more frequently in regular, but not hypermutated, gastric cancers, where they were associated with APOBEC expression. In the former group, six previously unreported (XIRP2, NBEA, COL14A1, CNBD1, ITGAV, and AKAP6) and 12 recurrent mutated genes exhibited high mutation prevalence (≥3.0%) and an unexpectedly higher incidence of nonsynonymous mutations. We also identified two molecular subtypes of regular-mutated gastric cancer that were associated with distinct prognostic outcomes, independently of disease staging, as confirmed in a distinct patient cohort by targeted capture sequencing. Finally, in diffuse-type gastric cancer, CDH1 mutation was found to be associated with shortened patient survival, independently of disease staging. Overall, our work identified previously unreported SMGs and a mutation signature predictive of patient survival in newly classified subtypes of gastric cancer, offering opportunities to stratify patients into optimal treatment plans based on molecular subtyping. Cancer Res; 76(7); 1724-32. ©2016 AACR.

Identification of genomic alterations in oesophageal squamous cell cancer.

Oesophageal cancer is one of the most aggressive cancers and is the sixth leading cause of cancer death worldwide. Approximately 70% of global oesophageal cancer cases occur in China, with oesophageal squamous cell carcinoma (ESCC) being the histopathological form in the vast majority of cases (>90%). Currently, there are limited clinical approaches for the early diagnosis and treatment of ESCC, resulting in a 10% five-year survival rate for patients. However, the full repertoire of genomic events leading to the pathogenesis of ESCC remains unclear. Here we describe a comprehensive genomic analysis of 158 ESCC cases, as part of the International Cancer Genome Consortium research project. We conducted whole-genome sequencing in 17 ESCC cases and whole-exome sequencing in 71 cases, of which 53 cases, plus an additional 70 ESCC cases not used in the whole-genome and whole-exome sequencing, were subjected to array comparative genomic hybridization analysis. We identified eight significantly mutated genes, of which six are well known tumour-associated genes (TP53, RB1, CDKN2A, PIK3CA, NOTCH1, NFE2L2), and two have not previously been described in ESCC (ADAM29 and FAM135B). Notably, FAM135B is identified as a novel cancer-implicated gene as assayed for its ability to promote malignancy of ESCC cells. Additionally, MIR548K, a microRNA encoded in the amplified 11q13.3-13.4 region, is characterized as a novel oncogene, and functional assays demonstrate that MIR548K enhances malignant phenotypes of ESCC cells. Moreover, we have found that several important histone regulator genes (MLL2 (also called KMT2D), ASH1L, MLL3 (KMT2C), SETD1B, CREBBP and EP300) are frequently altered in ESCC. Pathway assessment reveals that somatic aberrations are mainly involved in the Wnt, cell cycle and Notch pathways. Genomic analyses suggest that ESCC and head and neck squamous cell carcinoma share some common pathogenic mechanisms, and ESCC development is associated with alcohol drinking. This study has explored novel biological markers and tumorigenic pathways that would greatly improve therapeutic strategies for ESCC.

SOAPfuse: an algorithm for identifying fusion transcripts from paired-end RNA-Seq data.

We have developed a new method, SOAPfuse, to identify fusion transcripts from paired-end RNA-Seq data. SOAPfuse applies an improved partial exhaustion algorithm to construct a library of fusion junction sequences, which can be used to efficiently identify fusion events, and employs a series of filters to nominate high-confidence fusion transcripts. Compared with other released tools, SOAPfuse achieves higher detection efficiency and consumed less computing resources. We applied SOAPfuse to RNA-Seq data from two bladder cancer cell lines, and confirmed 15 fusion transcripts, including several novel events common to both cell lines. SOAPfuse is available at http://soap.genomics.org.cn/soapfuse.html.

Transforming fusions of FGFR and TACC genes in human glioblastoma.

The brain tumor glioblastoma multiforme (GBM) is among the most lethal forms of human cancer. Here, we report that a small subset of GBMs (3.1%; 3 of 97 tumors examined) harbors oncogenic chromosomal translocations that fuse in-frame the tyrosine kinase coding domains of fibroblast growth factor receptor (FGFR) genes (FGFR1 or FGFR3) to the transforming acidic coiled-coil (TACC) coding domains of TACC1 or TACC3, respectively. The FGFR-TACC fusion protein displays oncogenic activity when introduced into astrocytes or stereotactically transduced in the mouse brain. The fusion protein, which localizes to mitotic spindle poles, has constitutive kinase activity and induces mitotic and chromosomal segregation defects and triggers aneuploidy. Inhibition of FGFR kinase corrects the aneuploidy, and oral administration of an FGFR inhibitor prolongs survival of mice harboring intracranial FGFR3-TACC3-initiated glioma. FGFR-TACC fusions could potentially identify a subset of GBM patients who would benefit from targeted FGFR kinase inhibition.