AbstractCopy number variation (CNV) is a common form of structural variation detected in human genomes, occurring as both constitutional and somatic events. Cytogenetic techniques like chromosomal microarray (CMA) are widely used in analyzing CNVs. However, CMA techniques cannot resolve the full nature of these structural variations (i.e. the orientation and location of associated breakpoint junctions) and must be combined with other cytogenetic techniques, such as karyotyping or FISH, to do so. This makes the development of a next‐generation sequencing (NGS) approach capable of resolving both CNVs and breakpoint junctions desirable. Mate‐pair sequencing (MPseq) is a NGS technology designed to find large structural rearrangements across the entire genome. Here we present an algorithm capable of performing copy number analysis from mate‐pair sequencing data. The algorithm uses a step‐wise procedure involving normalization, segmentation, and classification of the sequencing data. The segmentation technique combines both read depth and discordant mate‐pair reads to increase the sensitivity and resolution of CNV calls. The method is particularly suited to MPseq, which is designed to detect breakpoint junctions at high resolution. This allows for the classification step to accurately calculate copy number levels at the relatively low read depth of MPseq. Here we compare results for a series of hematological cancer samples that were tested with CMA and MPseq. We demonstrate comparable sensitivity to the state‐of‐the‐art CMA technology, with the benefit of improved breakpoint resolution. The algorithm provides a powerful analytical tool for the analysis of MPseq results in cancer.
Abstract Motivation The ability to produce and analyze whole genome sequencing (WGS) data from samples with structural variations (SV) generated the need to visualize such abnormalities in simplified plots. Conventional two-dimensional representations of WGS data frequently use either circular or linear layouts. There are several diverse advantages regarding both these representations, but their major disadvantage is that they do not use the two-dimensional space very efficiently. We propose a layout, termed the Genome U-Plot, which spreads the chromosomes on a two-dimensional surface and essentially quadruples the spatial resolution. We present the Genome U-Plot for producing clear and intuitive graphs that allows researchers to generate novel insights and hypotheses by visualizing SVs such as deletions, amplifications, and chromoanagenesis events. The main features of the Genome U-Plot are its layered layout, its high spatial resolution and its improved aesthetic qualities. We compare conventional visualization schemas with the Genome U-Plot using visualization metrics such as number of line crossings and crossing angle resolution measures. Based on our metrics, we improve the readability of the resulting graph by at least 2-fold, making apparent important features and making it easy to identify important genomic changes. Results A whole genome visualization tool with high spatial resolution and improved aesthetic qualities. Availability and implementation An implementation and documentation of the Genome U-Plot is publicly available at https://github.com/gaitat/GenomeUPlot. Supplementary information Supplementary data are available at Bioinformatics online.
Retention of Interstitial Genes between
TMPRSS2
and
ERG
Is Associated with Low-Risk Prostate Cancer
Common fragile sites (CFS) and extremely large CFS genes are targets for human papillomavirus integrations and chromosome rearrangements in oropharyngeal squamous cell carcinoma
Abstract PURPOSE: Previous mutational analyses have failed to identify a predictive or prognostic marker for pulmonary carcinoid tumors (PCT). The heterogeneity of PCTs coupled with a lack of detailed information about the tumor biology, impedes patient stratification into groups based on tumor phenotypes or treatment response. We sought to use high-throughput next-generation sequencing to improve prognostication. METHODS: We stratified 37 patients with resected PCTs as low risk (n = 17) and high risk (n = 20) based on a 5 year long follow up for recurrence. Patients with no recurrence within 5 years from initial treatment were deemed low risk. Macrodissection was followed by genomic DNA isolation and next-generation sequencing was performed using an Illumina Mate Pair library protocol. Sequence reads were mapped to the human genome, and primers spanning the fusion junctions were used for validation polymerase chain reaction. RESULTS: Carcinoids commonly harbor rearrangements (median 3.5, range 1-167). Large chromosomal gains or losses were found in 24 of the cases (64.8%). We developed a prognostic score that included the total amount of genetic alterations (deletions and translocations). ROC analysis revealed an AUC of 0.76. High risk patients had a mean score of 20 and low risk patients had a mean score of 5.45 (p value = 0.03, Welch Two Sample t-test). Further analysis of the specific genetic alterations harbored by high and low risk PCTs and correlation with the pathologic and immunohistochemical information is currently underway. CONCLUSION: Large chromosomal rearrangements and aneuploidy portend a poor prognosis for patients with PCTs. Mate Pair sequencing of PCTs provides valuable prognostic information for this highly heterogeneous group of cancers. Citation Format: Konstantinos Leventakos, Aaron S. Mansfield, Stephen J. Murphy, Sarah H. Johnson, Sarah E. Kerr, Marie Christine Aubry, George Vasmatzis, Julian R. Molina. A prognostic model for pulmonary carcinoid tumors based on large chromosomal alterations. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4513.
Abstract 440: Quantification of somatic chromosomal rearrangements in circulating cell-free DNA from ovarian cancers
Abstract Circulating tumor DNA (ctDNA) provides great potential for the non-invasive clinical assessment of tumor burden. We developed a monitoring protocol using next generation mate-pair sequencing to identify chromosomal rearrangement signatures in primary tumors to follow ctDNA in blood. Primary tumors of 10 patients with ovarian cancer were sequenced, and individualized tumor-specific panels were designed to detect the junctions in ctDNA. A novel algorithm was developed and applied to data generated by quantitative PCR to calculate the percent of ctDNA. Selected junctions, some with potential as therapeutic targets, were detected in pre-surgically drawn blood in eight out of ten patients. Of these eight, three demonstrated the continued presence of circulating tumor DNA post-surgery, and five had undetectable levels, consistent with their documented presence or absence of disease. The detection of somatic junctions derived from ctDNA could be an effective way to monitor ovarian cancer patients for relapse and therapy response. Citation Format: Faye R. Harris, Irina Kovtun, James Smadbeck, Francesco Multinu, Aminah Jatoi, Kimberly R. Kalli, Stephen J. Murphy, Geoffrey C. Halling, Farhad Kosari, Sarah H. Johnson, Andrea Mariani, George Vasmatzis. Quantification of somatic chromosomal rearrangements in circulating cell-free DNA from ovarian cancers. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 440.
Integrated mate-pair and RNA sequencing identifies novel, targetable gene fusions in peripheral T-cell lymphoma
Abstract Peripheral T-cell lymphomas (PTCLs) represent a heterogeneous group of T-cell malignancies that generally demonstrate aggressive clinical behavior, often are refractory to standard therapy, and remain significantly understudied. The most common World Health Organization subtype is PTCL, not otherwise specified (NOS), essentially a “wastebasket” category because of inadequate understanding to assign cases to a more specific diagnostic entity. Identification of novel fusion genes has contributed significantly to improving the classification, biologic understanding, and therapeutic targeting of PTCLs. Here, we integrated mate-pair DNA and RNA next-generation sequencing to identify chromosomal rearrangements encoding expressed fusion transcripts in PTCL, NOS. Two of 11 cases had novel fusions involving VAV1, encoding a truncated form of the VAV1 guanine nucleotide exchange factor important in T-cell receptor signaling. Fluorescence in situ hybridization studies identified VAV1 rearrangements in 10 of 148 PTCLs (7%). These were observed exclusively in PTCL, NOS (11%) and anaplastic large cell lymphoma (11%). In vitro, ectopic expression of a VAV1 fusion promoted cell growth and migration in a RAC1-dependent manner. This growth was inhibited by azathioprine, a clinically available RAC1 inhibitor. We also identified novel kinase gene fusions, ITK-FER and IKZF2-ERBB4, as candidate therapeutic targets that show similarities to known recurrent oncogenic ITK-SYK fusions and ERBB4 transcript variants in PTCLs, respectively. Additional novel and potentially clinically relevant fusions also were discovered. Together, these findings identify VAV1 fusions as recurrent and targetable events in PTCLs and highlight the potential for clinical sequencing to guide individualized therapy approaches for this group of aggressive malignancies.
Integrated Genomic Analysis of Pancreatic Ductal Adenocarcinomas Reveals Genomic Rearrangement Events as Significant Drivers of Disease