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      Copy Number Variation Analysis on a Non-Hodgkin Lymphoma Case-Control Study Identifies an 11q25 Duplication Associated with Diffuse Large B-Cell Lymphoma

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          Abstract

          Recent GWAS have identified several susceptibility loci for NHL. Despite these successes, much of the heritable variation in NHL risk remains to be explained. Common copy-number variants are important genomic sources of variability, and hence a potential source to explain part of this missing heritability. In this study, we carried out a CNV analysis using GWAS data from 681 NHL cases and 749 controls to explore the relationship between common structural variation and lymphoma susceptibility. Here we found a novel association with diffuse large B-cell lymphoma (DLBCL) risk involving a partial duplication of the C-terminus region of the LOC283177 long non-coding RNA that was further confirmed by quantitative PCR. For chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), known somatic deletions were identified on chromosomes 13q14, 11q22-23, 14q32 and 22q11.22. Our study shows that GWAS data can be used to identify germline CNVs associated with disease risk for DLBCL and somatic CNVs for CLL/SLL.

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          Molecular subtypes of diffuse large B-cell lymphoma arise by distinct genetic pathways.

          Georg Lenz, George W Wright, N C Tolga Emre … (2008)
          Gene-expression profiling has been used to define 3 molecular subtypes of diffuse large B-cell lymphoma (DLBCL), termed germinal center B-cell-like (GCB) DLBCL, activated B-cell-like (ABC) DLBCL, and primary mediastinal B-cell lymphoma (PMBL). To investigate whether these DLBCL subtypes arise by distinct pathogenetic mechanisms, we analyzed 203 DLBCL biopsy samples by high-resolution, genome-wide copy number analysis coupled with gene-expression profiling. Of 272 recurrent chromosomal aberrations that were associated with gene-expression alterations, 30 were used differentially by the DLBCL subtypes (P < 0.006). An amplicon on chromosome 19 was detected in 26% of ABC DLBCLs but in only 3% of GCB DLBCLs and PMBLs. A highly up-regulated gene in this amplicon was SPIB, which encodes an ETS family transcription factor. Knockdown of SPIB by RNA interference was toxic to ABC DLBCL cell lines but not to GCB DLBCL, PMBL, or myeloma cell lines, strongly implicating SPIB as an oncogene involved in the pathogenesis of ABC DLBCL. Deletion of the INK4a/ARF tumor suppressor locus and trisomy 3 also occurred almost exclusively in ABC DLBCLs and was associated with inferior outcome within this subtype. FOXP1 emerged as a potential oncogene in ABC DLBCL that was up-regulated by trisomy 3 and by more focal high-level amplifications. In GCB DLBCL, amplification of the oncogenic mir-17-92 microRNA cluster and deletion of the tumor suppressor PTEN were recurrent, but these events did not occur in ABC DLBCL. Together, these data provide genetic evidence that the DLBCL subtypes are distinct diseases that use different oncogenic pathways.
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            Comparing CNV detection methods for SNP arrays.

            Laura Winchester, Christopher Yau, Jiannis Ragoussis (2009)
            Data from whole genome association studies can now be used for dual purposes, genotyping and copy number detection. In this review we discuss some of the methods for using SNP data to detect copy number events. We examine a number of algorithms designed to detect copy number changes through the use of signal-intensity data and consider methods to evaluate the changes found. We describe the use of several statistical models in copy number detection in germline samples. We also present a comparison of data using these methods to assess accuracy of prediction and detection of changes in copy number.
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              A genome-wide association study identifies multiple susceptibility loci for chronic lymphocytic leukemia.

              Helen E Speedy, Maria Chiara Di Bernardo, Georgina P Sava … (2014)
              Genome-wide association studies (GWAS) of chronic lymphocytic leukemia (CLL) have shown that common genetic variation contributes to the heritable risk of CLL. To identify additional CLL susceptibility loci, we conducted a GWAS and performed a meta-analysis with a published GWAS totaling 1,739 individuals with CLL (cases) and 5,199 controls with validation in an additional 1,144 cases and 3,151 controls. A combined analysis identified new susceptibility loci mapping to 3q26.2 (rs10936599, P = 1.74 × 10(-9)), 4q26 (rs6858698, P = 3.07 × 10(-9)), 6q25.2 (IPCEF1, rs2236256, P = 1.50 × 10(-10)) and 7q31.33 (POT1, rs17246404, P = 3.40 × 10(-8)). Additionally, we identified a promising association at 5p15.33 (CLPTM1L, rs31490, P = 1.72 × 10(-7)) and validated recently reported putative associations at 5p15.33 (TERT, rs10069690, P = 1.12 × 10(-10)) and 8q22.3 (rs2511714, P = 2.90 × 10(-9)). These findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to CLL.
              Article 0 comments Cited 90 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Dale J. Hedges: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, USA )
                ISSN (Electronic): 1932-6203
                Publication date Collection: 2014
                Publication date (Electronic): 18 August 2014
                Volume: 9
                Issue: 8
                Electronic Location Identifier: e105382
                Affiliations
                [1 ]Department of Epidemiology, School of Public Health and Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
                [2 ]Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America
                The Ohio State University, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: LC CFS. Performed the experiments: LC JR JZ. Analyzed the data: LC. Contributed reagents/materials/analysis tools: LC JR PMB CFS. Contributed to the writing of the manuscript: LC CFS.

                Article
                Publisher ID: PONE-D-14-15772
                DOI: 10.1371/journal.pone.0105382
                PMC ID: 4136881
                PubMed ID: 25133503
                SO-VID: 3a6b0126-3ede-4ac6-9764-4a4af8487c3f
                Copyright statement: Copyright @ 2014
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 8 April 2014
                Date accepted : 23 July 2014
                Page count
                Pages: 5
                Funding
                This work was supported by National Institutes of Health grants CA122663, CA154643-01A1 and CA104682 (C.F.S.) and CA087014 (P.M.B.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Research Article
                Subject: Biology and Life Sciences
                Subject: Computational Biology
                Subject: Genome Analysis
                Subject: Genome-Wide Association Studies
                Subject: Genome Complexity
                Subject: Copy Number Variation
                Subject: Genetics
                Subject: Genetics of Disease
                Subject: Genetic Predisposition
                Subject: Human Genetics
                Subject: Genetic Association Studies
                Subject: Cancer Genetics
                Subject: Genomics
                Subject: Medicine and health sciences
                Subject: Epidemiology
                Subject: Genetic Epidemiology
                Subject: Hematology
                Subject: Hematologic cancers and related disorders
                Subject: Lymphomas
                Subject: B-cell chronic lymphocytic lymphoma
                Subject: Diffuse large B-cell lymphoma
                Subject: Follicular lymphoma
                Subject: Non-Hodgkin lymphoma
                Subject: Oncology
                Subject: Cancer Risk Factors
                Subject: Genetic Causes of Cancer
                Subject: Cancers and Neoplasms
                Custom metadata
                Data Availability The authors confirm that all data underlying the findings are fully available without restriction. Signal intensity data (LRR and BAF values) have been deposited in the NCBI’s Gene Expression Omnibus database ( http://www.ncbi.nlm.nih.gov/geo/) and are accessible through GEO Series accession number GSE58718.

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                Data availability:
                ScienceOpen disciplines: Uncategorized

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