DNA Copy Number Analysis Research Articles

Abstract LB-311: Whole-exome sequencing of polycythemia vera revealed novel driver genes and somatic mutation shared by T cells and granulocytes

Abstract Polycythemia vera (PV) is a myeloproliferative neoplasm characterized by augmented myelopoiesis leading to increased red cell mass with frequent excessive proliferation of other myeloid lineages. Over 95% of PV patients harbor JAK2V617F mutation, which confers proliferative advantage to affected myeloid progenitors. JAK2V617F, which is thought to be necessary but not sufficient for the disease, is often associated with acquired uniparental disomy on chromosome 9p (9pUPD). To better understand the underlying molecular basis of PV, we performed whole-exome sequencing and DNA copy-number analysis of 31 JAK2V617F-positive patients and further investigated the evolution of somatic mutations using longitudinal samples. In addition to JAK2 V617F and 9pUPD, we identified recurrent somatic mutation in an additional 5 genes including ASXL1, TET2, DNMT3A, and SF3B1 and recurrent DNA copy-number alterations at 1q and 18p. Forty-two percent of patients had at least one somatic mutation in an epigenetic modifier gene, and 23% of patients harbored mutation in RTK/RAS, RNA processing pathways, tumor suppressors and protein kinases. In 4 of 31 cases, variant allele abundance suggested somatic mutations of ASXL1, DNMT3A and SF3B1 may have preceded JAK2V617F. Interestingly, in 7 PV patients mutations also present in COSMIC were shared between the patients’ T-cell controls and granulocytes: 4 NF1, 2 ASXL1, and one each in TET2, IDH2, and DNMT3A, suggesting these genes mutated early in hematopoietic development. Absence of JAK2V617F in these T-cells ruled out cross-contamination of cell lineages. In an additional 4 cases, a minor JAK2V617F subclone acquired new mutations in DNMT3A, SF3B1, SMARCA2, and TET2 during PV progression. In summary, seventy percent of patients had mutation of at least one gene important to development of myeloid neoplasms, other than JAK2V617F. Our data reveal that these mutations, in particular NF1, may have arisen in some cases early in hematopoiesis but also in some patients during progression after diagnosis. These results suggest that the order of mutation is not as important as the total mutational burden in the development of PV. Citation Format: David A. Wheeler, Linghua Wang, Sabina Swierczek, Kimberly Hickman, Jennifer A. Drummond, Donna Muzny, Richard A. Gibbs, Joseph Prchal. Whole-exome sequencing of polycythemia vera revealed novel driver genes and somatic mutation shared by T cells and granulocytes. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-311. doi:10.1158/1538-7445.AM2014-LB-311

DNA copy number analysis of fresh and formalin-fixed specimens by shallow whole-genome sequencing with identification and exclusion of problematic regions in the genome assembly

Detection of DNA copy number aberrations by shallow whole-genome sequencing (WGS) faces many challenges, including lack of completion and errors in the human reference genome, repetitive sequences, polymorphisms, variable sample quality, and biases in the sequencing procedures. Formalin-fixed paraffin-embedded (FFPE) archival material, the analysis of which is important for studies of cancer, presents particular analytical difficulties due to degradation of the DNA and frequent lack of matched reference samples. We present a robust, cost-effective WGS method for DNA copy number analysis that addresses these challenges more successfully than currently available procedures. In practice, very useful profiles can be obtained with ∼0.1× genome coverage. We improve on previous methods by first implementing a combined correction for sequence mappability and GC content, and second, by applying this procedure to sequence data from the 1000 Genomes Project in order to develop a blacklist of problematic genome regions. A small subset of these blacklisted regions was previously identified by ENCODE, but the vast majority are novel unappreciated problematic regions. Our procedures are implemented in a pipeline called QDNAseq. We have analyzed over 1000 samples, most of which were obtained from the fixed tissue archives of more than 25 institutions. We demonstrate that for most samples our sequencing and analysis procedures yield genome profiles with noise levels near the statistical limit imposed by read counting. The described procedures also provide better correction of artifacts introduced by low DNA quality than prior approaches and better copy number data than high-resolution microarrays at a substantially lower cost.

Performance evaluation of DNA copy number segmentation methods.

A number of bioinformatic or biostatistical methods are available for analyzing DNA copy number profiles measured from microarray or sequencing technologies. In the absence of rich enough gold standard data sets, the performance of these methods is generally assessed using unrealistic simulation studies, or based on small real data analyses. To make an objective and reproducible performance assessment, we have designed and implemented a framework to generate realistic DNA copy number profiles of cancer samples with known truth. These profiles are generated by resampling publicly available SNP microarray data from genomic regions with known copy-number state. The original data have been extracted from dilutions series of tumor cell lines with matched blood samples at several concentrations. Therefore, the signal-to-noise ratio of the generated profiles can be controlled through the (known) percentage of tumor cells in the sample. This article describes this framework and its application to a comparison study between methods for segmenting DNA copy number profiles from SNP microarrays. This study indicates that no single method is uniformly better than all others. It also helps identifying pros and cons of the compared methods as a function of biologically informative parameters, such as the fraction of tumor cells in the sample and the proportion of heterozygous markers. This comparison study may be reproduced using the open source and cross-platform R package jointseg, which implements the proposed data generation and evaluation framework: http://r-forge.r-project.org/R/?group_id=1562.

Integrative Analysis of Dna Copy Number in Metastatic Nsclc Identifies Drug Sensitivity to Afatinib

ABSTRACT Aim: Afatinib (BIBW-2992) has been approved for patients with untreated metastatic non-small cell lung cancer (NSCLC) harboring EGFR exon 19 deletions or exon 21 L858R substitution mutations. Pharmacogenomic studies have found that genome-wide assays allows the unbiased discovery of genomic alterations which are associated with drug response to targeted therapy. The aim of our study was to identify the correlation between DNA copy number profiles and treatment response to afatinib. Methods: Integrative analysis of DNA copy number alterations (CNA) from 32 metastatic NSCLC patients were performed to identify recurrent regions of genomic change associated with primary response to afatinib using the Affymetrix Mapping 250K Nsp SNP array. Copy number-associated transciptome profiling was identified using Affymetrix Human genome U133 Plus 2.0 array. Comparison of candidate genes correlated with copy number variation and clinical outcome of afatinib treatment was conducted by quantitative-PCR (qPCR). Results: Predictive model scores generated from cross-validation were correlated with sensitivity to afatinib. Eight distinct genomic regions were identified in a predictive model for afatinib sensitivity. Regions contained chromosomal gain of EGFR (7p11.2) as well as chromosomal loss of HSD3B2 (1p12) and MTAP (9p21.3). The extreme concordance between DNA copy number and transcript abundance was highly significant for the genes mapping to 7p11.2 in the afatinib-sensitive group. Amplification of CCT6A was related to intrinsic resistance to afatinib. Conclusions: These data show that integrative analysis of DNA copy number analysis can be used to identify genetic alterations which can be used to discover clinically relevant predictors of drug sensitivity to afatinib. Disclosure: All authors have declared no conflicts of interest.

PD-0017 - Druggable Genetic Dependencies for Molecularly Defined Subgroups of Oesophageal Cancer Identified From High-Throughput Functional Profiling

Introduction: Recent DNA sequencing and copy number analysis of oesophageal cancer has delineated the first draft of the mutational landscape of this disease. The development of large scale RNA interference (RNAi) interventions, resulting in selective silencing of specific proteins, has the potential to pinpoint druggable candidate genetic dependencies relevant to defined molecular subtypes of oesophageal cancer. This study aims to identify candidate genetic dependencies and therapeutic targets for oesophageal cancers with specific genetic defects by high-throughput functional viability profiling of oesophageal cancer cell line models.

Integrative analysis of DNA copy number in metastatic NSCLC and drug sensitivity to afatinib.

e19094 Background: Afatinib (BIBW-2992) has been approved for patients with untreated metastatic non-small cell lung cancer (NSCLC) harboring EGFR exon 19 deletions or exon 21 L858R substitution mu...

High Resolution Copy Number Variation Data in the NCI-60 Cancer Cell Lines from Whole Genome Microarrays Accessible through CellMiner

Array-based comparative genomic hybridization (aCGH) is a powerful technique for detecting gene copy number variation. It is generally considered to be robust and convenient since it measures DNA rather than RNA. In the current study, we combine copy number estimates from four different platforms (Agilent 44 K, NimbleGen 385 K, Affymetrix 500 K and Illumina Human1Mv1_C) to compute a reliable, high-resolution, easy to understand output for the measure of copy number changes in the 60 cancer cells of the NCI-DTP (the NCI-60). We then relate the results to gene expression. We explain how to access that database using our CellMiner web-tool and provide an example of the ease of comparison with transcript expression, whole exome sequencing, microRNA expression and response to 20,000 drugs and other chemical compounds. We then demonstrate how the data can be analyzed integratively with transcript expression data for the whole genome (26,065 genes). Comparison of copy number and expression levels shows an overall medium high correlation (median r = 0.247), with significantly higher correlations (median r = 0.408) for the known tumor suppressor genes. That observation is consistent with the hypothesis that gene loss is an important mechanism for tumor suppressor inactivation. An integrated analysis of concurrent DNA copy number and gene expression change is presented. Limiting attention to focal DNA gains or losses, we identify and reveal novel candidate tumor suppressors with matching alterations in transcript level.

Intragenic integration in DLC1 sustains factor VIII expression in primary human cells without insertional oncogenicity

Techniques enabling precise genome modifications enhance the safety of gene-based therapy. DLC1 is a hot spot for phiC31 integrase-mediated transgene integration in vitro and in vivo. Here we show that integration of a coagulation factor VIII transgene into intron 7 of DLC1 supports durable expression of factor VIII in primary human umbilical cord-lining epithelial cells. Oligoclonal cells with factor VIII transgene integrated in DLC1 did not have altered expression of DLC1 or neighbouring genes within a 1-Mb interval. Only 1.9% of all expressed genes were transcriptionally altered; most were downregulated and mapped to cell cycle and DNA repair pathways. DLC1-integrated cells were not tumourigenic in vivo and were normal by high-resolution genomic DNA copy number analysis. Our data identify DLC1 as a locus for durable transgene expression that does not incur features of insertional oncogenesis, thus expanding options for developing ex vivo cell therapy mediated by site-specific integration methods.

Genomic analysis of circulating tumor cells (CTCs) from men with metastatic castration resistant prostate cancer (mCRPC) in the context of enzalutamide therapy.

65 Background: Given the evolving treatments available in metastatic castration resistant prostate cancer (mCRPC), predictive biomarkers are desirable that maximize benefit and minimize harms and costs.The goal of this study was to determine the feasibility of DNA copy number and whole exome sequencing (WES) analysis of circulating tumor cells (CTCs) from men with mCRPC receiving enzalutamide. Methods: We collected CTCs from men with mCRPC in the context of enzalutamide therapy. CTCs were isolated from EDTA blood through red cell lysis, CD45 depletion, and flow sorting on EpCAM/CD45 expression. Whole genomic amplification and array based comparative genomic hybridization (CGH) was performed using Qiagen Repli-Gene Single Cell kit, multiple displacement amplification, and Agilent microarray analysis. CTC copy number changes were compared with patient leukocyte DNA and reference metastatic PC datasets. CTC AR amplification and PTEN loss was confirmed with FISH. WES on REPLI-g amplified CTC and leukocyte DNA was performed using GeneWiz and TruSeq Exome Capture Kit, and sequenced with Illumina HiSeq 2000 (20x). Results: A novel method for CTC array CGH was developed that reproducibly identified genomic lesions previously reported in metastatic CRPC including: AR amplification or focal deletions, deletions of CHD1, Rb, PHLLP, FGFR2, FOXA1, and NCOA2, and amplifications of EZH2 and MYC. AR amplification was noted in a man with mCRPC who subsequently responded to enzalutamide, with loss of AR amplification and gain of MYCN and c-MET amplification noted at progression. CGH analysis was feasible down to 10 to 20 cells using spiked cell lines. Interpatient tumor specific genomic heterogeneity was observed. FISH confirmed AR changes and PTEN loss heterogeneity. WES demonstrated acquired PTEN, MAGI1, SMAD4, and RB1 mutations in a patient who progressed through enzalutamide therapy, in addition to AR region deletion detected by CGH. Conclusions: Whole genome DNA copy number and exome sequencing analysis from CTCs in men with mCRPC is feasible in men with high CTCs and identified previously validated and novel genomic lesions and suggest the potential to identify predictive biomarkers of enzalutamide efficacy and resistance in the clinic.

Molecular and genetic diversity in the metastatic process of melanoma

Diversity between metastatic melanoma tumours in individual patients is known; however, the molecular and genetic differences remain unclear. To examine the molecular and genetic differences between metastatic tumours, we performed gene-expression profiling of 63 melanoma tumours obtained from 28 patients (two or three tumours/patient), followed by analysis of their mutational landscape, using targeted deep sequencing of 1697 cancer genes and DNA copy number analysis. Gene-expression signatures revealed discordant phenotypes between tumour lesions within a patient in 50% of the cases. In 18 of 22 patients (where matched normal tissue was available), we found that the multiple lesions within a patient were genetically divergent, with one or more melanoma tumours harbouring 'private' somatic mutations. In one case, the distant subcutaneous metastasis of one patient occurring 3 months after an earlier regional lymph node metastasis had acquired 37 new coding sequence mutations, including mutations in PTEN and CDH1. However, BRAF and NRAS mutations, when present in the first metastasis, were always preserved in subsequent metastases. The patterns of nucleotide substitutions found in this study indicate an influence of UV radiation but possibly also DNA alkylating agents. Our results clearly demonstrate that metastatic melanoma is a molecularly highly heterogeneous disease that continues to progress throughout its clinical course. The private aberrations observed on a background of shared aberrations within a patient provide evidence of continued evolution of individual tumours following divergence from a common parental clone, and might have implications for personalized medicine strategies in melanoma treatment. Published by John Wiley & Sons, Ltd. www.pathsoc.org.uk

Whole-exome sequencing of polycythemia vera revealed novel driver genes and somatic mutation shared by T cells and granulocytes

To better understand the underlying molecular basis of polycythemia vera (PV), we performed whole-exome sequencing and DNA copy-number analysis of 31 JAK2V617F-positive patients and further investigated the evolution of somatic mutations using longitudinal samples. In addition to JAK2V617F and 9pUPD, we identified frequent recurrent somatic mutation in ASXL1, TET2, DNMT3A, SF3B1 and NF1. Forty two percent of patients had a somatic mutation in at least one epigenetic modifier gene. In 4 of 31 patients, variant allele abundance suggested mutation of JAK2V617F was preceded by other somatic mutations including ASXL1, DNMT3A and SF3B1. Strikingly, in 7 patients, apparent germline variants were detected at COSMIC codons in one or more PV-related genes in which we had also discovered somatic mutations across the cohort, suggesting that some pre-JAK2V617F mutations contribute to substantial T-lymphocyte progeny. This study contributes to novel understanding of the complexity of PV pathogenesis.

Integrated DNA Copy Number and Gene Expression Regulatory Network Analysis of Non-small Cell Lung Cancer Metastasis.

Integrative analysis of multi-level molecular profiles can distinguish interactions that cannot be revealed based on one kind of data in the analysis of cancer susceptibility and metastasis. DNA copy number variations (CNVs) are common in cancer cells, and their role in cell behaviors and relationship to gene expression (GE) is poorly understood. An integrative analysis of CNV and genome-wide mRNA expression can discover copy number alterations and their possible regulatory effects on GE. This study presents a novel framework to identify important genes and construct potential regulatory networks based on these genes. Using this approach, DNA copy number aberrations and their effects on GE in lung cancer progression were revealed. Specifically, this approach contains the following steps: (1) select a pool of candidate driver genes, which have significant CNV in lung cancer patient tumors or have a significant association with the clinical outcome at the transcriptional level; (2) rank important driver genes in lung cancer patients with good prognosis and poor prognosis, respectively, and use top-ranked driver genes to construct regulatory networks with the COpy Number and EXpression In Cancer (CONEXIC) method; (3) identify experimentally confirmed molecular interactions in the constructed regulatory networks using Ingenuity Pathway Analysis (IPA); and (4) visualize the refined regulatory networks with the software package Genatomy. The constructed CNV/mRNA regulatory networks provide important insights into potential CNV-regulated transcriptional mechanisms in lung cancer metastasis.

SeqCNA: an R package for DNA copy number analysis in cancer using high-throughput sequencing

BackgroundDeviations in the amount of genomic content that arise during tumorigenesis, called copy number alterations, are structural rearrangements that can critically affect gene expression patterns. Additionally, copy number alteration profiles allow insight into cancer discrimination, progression and complexity. On data obtained from high-throughput sequencing, improving quality through GC bias correction and keeping false positives to a minimum help build reliable copy number alteration profiles.ResultsWe introduce seqCNA, a parallelized R package for an integral copy number analysis of high-throughput sequencing cancer data. The package includes novel methodology on (i) filtering, reducing false positives, and (ii) GC content correction, improving copy number profile quality, especially under great read coverage and high correlation between GC content and copy number. Adequate analysis steps are automatically chosen based on availability of paired-end mapping, matched normal samples and genome annotation.ConclusionsseqCNA, available through Bioconductor, provides accurate copy number predictions in tumoural data, thanks to the extensive filtering and better GC bias correction, while providing an integrated and parallelized workflow.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-178) contains supplementary material, which is available to authorized users.

TEGS-CN: A Statistical Method for Pathway Analysis of Genome-wide Copy Number Profile.

The effects of copy number alterations make up a significant part of the tumor genome profile, but pathway analyses of these alterations are still not well established. We proposed a novel method to analyze multiple copy numbers of genes within a pathway, termed Test for the Effect of a Gene Set with Copy Number data (TEGS-CN). TEGS-CN was adapted from TEGS, a method that we previously developed for gene expression data using a variance component score test. With additional development, we extend the method to analyze DNA copy number data, accounting for different sizes and thus various numbers of copy number probes in genes. The test statistic follows a mixture of X2 distributions that can be obtained using permutation with scaled X2 approximation. We conducted simulation studies to evaluate the size and the power of TEGS-CN and to compare its performance with TEGS. We analyzed a genome-wide copy number data from 264 patients of non-small-cell lung cancer. With the Molecular Signatures Database (MSigDB) pathway database, the genome-wide copy number data can be classified into 1814 biological pathways or gene sets. We investigated associations of the copy number profile of the 1814 gene sets with pack-years of cigarette smoking. Our analysis revealed five pathways with significant P values after Bonferroni adjustment (<2.8 × 10−5), including the PTEN pathway (7.8 × 10−7), the gene set up-regulated under heat shock (3.6 × 10−6), the gene sets involved in the immune profile for rejection of kidney transplantation (9.2 × 10−6) and for transcriptional control of leukocytes (2.2 × 10−5), and the ganglioside biosynthesis pathway (2.7 × 10−5). In conclusion, we present a new method for pathway analyses of copy number data, and causal mechanisms of the five pathways require further study.

Computational methods for DNA copy-number analysis of tumors.

Study of DNA copy-number variation is a key part of cancer genomics. With the help of a comprehensive multistep computational procedure described here, copy-number profiles of tumor tissues or individual tumor cells may be generated and interpreted, starting with data acquired by next-generation sequencing. Several of the methods presented are specifically designed to handle cancer-related copy-number profiles. These include accounting for variation of ploidy and distilling somatic copy number alterations from the inherited background.

Abstract S4-01: An integrated genomics approach identifies novel drivers of oncogenic pathway activity in human breast cancer

Abstract Background: Breast cancer is not a single disease, but rather is a collection of unique diseases with distinct molecular mechanisms and clinical characteristics. Although substantial progress has been made in the development and directed administration of new cancer therapies, the reality is that most patients with advanced tumors will succumb to their disease. Since recent studies have suggested that the activity of altered oncogenic pathways may be an important determinant of the biology of the tumor and potential response to therapy, identifying mechanisms driving key oncogenic pathways is paramount to understanding the transformation process and ultimately enabling the development of therapeutic regimens that can match the complexity of a given patient's tumor. Methods: A series of gene expression signatures (n = 52) that measure oncogenic pathway activity in human breast tumors were utilized as a conceptual framework to integrate genome-wide level expression and DNA copy number data in order to identify genetic drivers of oncogenic pathway activity. Results: A panel of pathway-based gene expression signatures was applied to a collection of nearly 500 breast tumor samples from the TCGA project. In addition to expression data, each tumor had matched DNA copy number data that were used to identify chromosomal alterations associated with each pathway signature. This strategy was validated by identifying associations between pathway activity and copy number alterations (CNA) of core pathway components including the correlation between ERBB2, cMYC, and E2F1 amplification and the Her2, Myc, and E2F1 signatures, respectively. These results were further confirmed by analyzing Reverse Phase Protein Array (RPPA) data to identify functional activation of the pathway as illustrated by changes in protein expression including increased phosphorylated (p) AKT, Myc and pEGFR relative to the PI3K, Myc, and EGFR signatures, respectively. Finally, to identify those amplified genes that are essential for cell viability in a pathway-dependent manner, we analyzed a dataset of breast cancer cell lines with available mRNA expression and genome-wide shRNA proliferation data. By integrating DNA copy number and shRNA analyses, we identified SOX4 as a novel regulator of PI3K signaling in basal-like breast cancers. We determined that SOX4 is amplified in approximately 40% of basal-like breast tumors with high PI3K signaling, which is comparable to the frequency of PIK3CA or PTEN alterations. By analyzing RPPA data, we demonstrate that tumors with SOX4 amplification have increased expression of core PI3K protein components including pAKT, thus further confirming the association between SOX4 amplification and aberrant PI3K/AKT signaling. Conclusions: In this study, we used a panel of pathway-based gene expression signatures as a means to integrate four disparate forms of genomic data to identify drivers of oncogenic pathway activity, including SOX4 amplification as a novel modulator of PI3K signaling in basal-like breast cancers. This novel strategy is able to identify oncogenic events in a context specific manner, which is essential for understanding mechanisms driving tumorigenesis and for the development of personalized therapeutic strategies. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr S4-01.

AISAIC: a software suite for accurate identification of significant aberrations in cancers

Accurate identification of significant aberrations in cancers (AISAIC) is a systematic effort to discover potential cancer-driving genes such as oncogenes and tumor suppressors. Two major confounding factors against this goal are the normal cell contamination and random background aberrations in tumor samples. We describe a Java AISAIC package that provides comprehensive analytic functions and graphic user interface for integrating two statistically principled in silico approaches to address the aforementioned challenges in DNA copy number analyses. In addition, the package provides a command-line interface for users with scripting and programming needs to incorporate or extend AISAIC to their customized analysis pipelines. This open-source multiplatform software offers several attractive features: (i) it implements a user friendly complete pipeline from processing raw data to reporting analytic results; (ii) it detects deletion types directly from copy number signals using a Bayes hypothesis test; (iii) it estimates the fraction of normal contamination for each sample; (iv) it produces unbiased null distribution of random background alterations by iterative aberration-exclusive permutations; and (v) it identifies significant consensus regions and the percentage of homozygous/hemizygous deletions across multiple samples. AISAIC also provides users with a parallel computing option to leverage ubiquitous multicore machines. AISAIC is available as a Java application, with a user's guide and source code, at https://code.google.com/p/aisaic/.

Use of autocorrelation scanning in DNA copy number analysis

Data quality is a critical issue in the analyses of DNA copy number alterations obtained from microarrays. It is commonly assumed that copy number alteration data can be modeled as piecewise constant and the measurement errors of different probes are independent. However, these assumptions do not always hold in practice. In some published datasets, we find that measurement errors are highly correlated between probes that interrogate nearby genomic loci, and the piecewise-constant model does not fit the data well. The correlated errors cause problems in downstream analysis, leading to a large number of DNA segments falsely identified as having copy number gains and losses. We developed a simple tool, called autocorrelation scanning profile, to assess the dependence of measurement error between neighboring probes. Autocorrelation scanning profile can be used to check data quality and refine the analysis of DNA copy number data, which we demonstrate in some typical datasets. lzhangli@mdanderson.org. Supplementary data are available at Bioinformatics online.

Genome-Wide DNA Copy Number Analysis of Desmoplastic Infantile Astrocytomas and Desmoplastic Infantile Gangliogliomas

Little is known about the molecular features of desmoplastic infantile ganglioglioma (DIG) and desmoplastic infantile astrocytoma (DIA). We performed a genome-wide DNA copy number analysis in combination with a multiplex ligation-dependent probe amplification-based analysis of copy number changes of candidate genes in 4 DIAs and 10 DIGs. Molecular inversion probe (MIP) assay showed that large chromosomal alterations were rare among DIG and DIA. Focal recurrent genomic losses were observed in chromosome regions such as 5q13.3, 21q22.11, and 10q21.3 in both DIA and DIG. Principal component analysis did not show any significant differences between the molecular profiles of DIG and DIA, and a hierarchical cluster analysis did not clearly separate the 2 tumor groups according to their molecular profiles. In 6 cases, gain of genomic material at 7q31 (corresponding to MET gene) was found in multiplex ligation-dependent probe amplification (MLPA) analysis. Furthermore, two cases showed gain at 4q12, and a single case showed BRAF mutation. In agreement with previous analyses, this study demonstrates the absence of consistent recurrent chromosomal alterations in DIA and DIG and overall rarity of the BRAF mutation in these tumors. Notably, these results suggest that DIA and DIG represent a histologic spectrum of the same tumor rather than 2 separate entities.

Mutational and structural analysis of diffuse large B-cell lymphoma using whole-genome sequencing

AbstractDiffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous cancer composed of at least 2 molecular subtypes that differ in gene expression and distribution of mutations. Recently, application of genome/exome sequencing and RNA-seq to DLBCL has revealed numerous genes that are recurrent targets of somatic point mutation in this disease. Here we provide a whole-genome-sequencing-based perspective of DLBCL mutational complexity by characterizing 40 de novo DLBCL cases and 13 DLBCL cell lines and combining these data with DNA copy number analysis and RNA-seq from an extended cohort of 96 cases. Our analysis identified widespread genomic rearrangements including evidence for chromothripsis as well as the presence of known and novel fusion transcripts. We uncovered new gene targets of recurrent somatic point mutations and genes that are targeted by focal somatic deletions in this disease. We highlight the recurrence of germinal center B-cell-restricted mutations affecting genes that encode the S1P receptor and 2 small GTPases (GNA13 and GNAI2) that together converge on regulation of B-cell homing. We further analyzed our data to approximate the relative temporal order in which some recurrent mutations were acquired and demonstrate that ongoing acquisition of mutations and intratumoral clonal heterogeneity are common features of DLBCL. This study further improves our understanding of the processes and pathways involved in lymphomagenesis, and some of the pathways mutated here may indicate new avenues for therapeutic intervention.