Allele-specific Copy Number Analysis Research Articles

1p36 deletion is a marker for tumour dissemination in microsatellite stable stage II-III colon cancer.

BackgroundThe clinical behaviour of colon cancer is heterogeneous. Five-year overall survival is 50-65% with all stages included. Recurring somatic chromosomal alterations have been identified and some have shown potential as markers for dissemination of the tumour, which is responsible for most colon cancer deaths. We investigated 115 selected stage II-IV primary colon cancers for associations between chromosomal alterations and tumour dissemination.MethodsFollow-up was at least 5 years for stage II-III patients without distant recurrence. Affymetrix SNP 6.0 microarrays and allele-specific copy number analysis were used to identify chromosomal alterations. Fisher’s exact test was used to associate alterations with tumour dissemination, detected at diagnosis (stage IV) or later as recurrent disease (stage II-III).ResultsLoss of 1p36.11-21 was associated with tumour dissemination in microsatellite stable tumours of stage II-IV (odds ratio = 5.5). It was enriched to a similar extent in tumours with distant recurrence within stage II and stage III subgroups, and may therefore be used as a prognostic marker at diagnosis. Loss of 1p36.11-21 relative to average copy number of the genome showed similar prognostic value compared to absolute loss of copies. Therefore, the use of relative loss as a prognostic marker would benefit more patients by applying also to hyperploid cancer genomes. The association with tumour dissemination was supported by independent data from the The Cancer Genome Atlas.ConclusionDeletions on 1p36 may be used to guide adjuvant treatment decisions in microsatellite stable colon cancer of stages II and III.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2407-14-872) contains supplementary material, which is available to authorized users.

Abstract 1533: A time course study of genomic instability in breast cancer patients receiving neoadjuvant therapy with or without bevacizumab

Abstract Tumor heterogeneity is an area of intense research, revealing tumors with high complexity consisting of different subclones and infiltrating cells. Identification of subclones that are resistant to therapy may be critical to improve treatment outcome. The NeoAva study is a randomized phase II, clinical trial of Her2 negative breast cancer patients treated in a neoadjuvant setting with chemotherapy (FEC and taxane) +/- bevacizumab. Core needle biopsies were obtained at screening and after 12 weeks, and the tumor was surgically removed after 25 weeks. DNA copy number changes in the tumors were analyzed using Affymetrix SNP Array 6.0. Allele specific copy number changes were assessed using the Allele-Specific Copy number Analysis of Tumors (ASCAT) algorithm (Van Loo, Norgard et al., PNAS 2010) and allele-specific Piecewise Constant Fitting (asPCF) algorithms (Nilsen, Liestol et al., BMC Genomics 2012). Measures of genomic instability were obtained through the complex arm-wise aberration index (CAAI) that captures local rearrangements (‘firestorms’) (Russnes, Vollan et al., Sci Transl Med 2010). Changes in copy number aberrations between the three different time points were observed in almost all tumors. Some tumors showed a decrease in tumor percentage and aberrations after just 12 weeks of treatment, where others showed loss of aberrations only at the time of surgery (25 weeks). Most of the tumors that did retain aberrations at all time points during treatment, did not demonstrate any decrease in tumor size. Other profiles indicated subclonal reduction, where some aberrations are kept throughout treatment and others disappear. Many of the tumors shrinking in size showed fewer whole arm aberrations than before treatment, but retained their focal amplicons. Some of the tumor aberrations seem to disappear after 12 weeks, but to reappear after 25 weeks, but with the addition of novel aberration. Complex rearrangements were identified in 67% of tumors before treatment. The most frequent ‘firestorms’ were found on 20p, 11q and 8p. Some events were persistent through therapy, but the majority changed. An association between complex tumor genomes and patients having progressive disease/non-responders were observed. These results show the complex structure of a tumor and suggest that heterogeneity will influence the response to treatment. The subclonal patterns of tumors may be of great importance for clinical decision-making, as well as for monitoring treatment efficacy. Citation Format: Elen K. Møller, Silje Nord, Hans Kristian Moen Vollan, Hedda von der Lippe Gythfeldt, Hege Edvardsen, Laxmi Silwal- Pandit, Marit Krohn, Thomas Fleischer, Ellen Schlitchting, Elin Borgen, Øystein Garred, Anne Fangberget, Marit M. Holmen, Helle Skjerven, Steinar Lundgren, Erik Wist, Bjørn Naume, Anne-Lise Børresen-Dale, Ole Christian Lingjærde, Olav Engebråten, Vessela N. Kristensen. A time course study of genomic instability in breast cancer patients receiving neoadjuvant therapy with or without bevacizumab. [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 1533. doi:10.1158/1538-7445.AM2014-1533

Abstract P4-06-01: Expression and DNA copy number profiling suggest novel therapeutic approaches for triple negative breast cancer subtypes

Abstract The aggressive triple negative breast cancers (TNBCs), which lack ER, PR and HER2, comprise a high-risk subset of human breast cancers which remain poorly characterized and lack effective treatments. While recent meta-analyses indicate the complexity of these tumors, no robust independently validated phenotypes have been defined. We have identified four distinct molecular subtypes through independent non-negative matrix factorization of expression data from 84 Discovery and 114 Validation Set TNBCs profiled at a single institution, with matching CNV data (SNP array). We then classified 485 publically available TNBCs via a centroid signature of only 80 genes. All three sets supported stratification of tumors by cell cycle, DNA repair, and immunological signaling pathways that have significantly different clinical outcomes. The first subtype, composed of intermediate grade tumors, resembles the “Molecular Apocrine” or “Luminal AR” subtype described previously and was defined by enrichment of prolactin, aryl hydrocarbon receptor, and ERBB4 signaling with activated downstream expression patterns of ESR1 signaling. Large deletions of chromosome 6 were specific to this subtype. While focal deletions at 14q21.2 and 12q13.13 were present in >60% of tumors of the other subtypes, the genes at these loci (FOXA1 and ERBB3) were overexpressed in the first subtype. Inhibitors of AR and MUC1, both overexpressed, may prove effective for these tumors. A second subtype defined as “Claudin-Low” or “Mesenchymal Stem-Like” showed overexpression of markers of mesenchymal lineage (ADIPOQ and OGN). Targets responsive to beta-blockers (ADRB2), and targetable molecules associated with platelet and endothelial function (EDNRB, PLA2G2A, PTGER3/4, PTGFR, PTGFRA) were also upregulated. Two basal-like subtypes were found with significant differences in DFS and OS, even after correction for available clinical covariates. The high-risk (31% 5-year DFS), low immune function subtype was regulated by SOX 10, 8, and 6 and had unique copy-number driven expression of FGFR2. The second, low-risk (78% 5-year DFS) basal-like subtype was enriched for overexpression of many immune pathways, regulated by increased STAT1 and activated STAT downstream signaling, as well as exclusive upregulation of CTLA4. This subtype also had the lowest tumor cell fraction as calculated by allele specific copy number analysis of tumors (ASCAT). Both basal-like subtypes expressed TTK, CHEK1, TOP2A, and AURKA. CDK1 was correlated with copy number variation at 10q21.1. We proposed and validated four molecular subtypes of TNBC before applying the resulting gene signature to 7 external expression sets. The described subtypes vary by clinical behavior and inferred biology. Each subtype appears to have specific gene expression regulated by copy number variation and a set of genes targetable by currently available agents. These findings further define the heterogeneity of TNBCs and suggest potential therapeutic targets for each subtype. This work was supported by a Promise grant from the Susan G. Komen for the Cure Foundation (KG081694). Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P4-06-01.

Abstract P4-14-01: A time course study of genomic instability in breast cancer patients receiving neoadjuvant therapy with or without bevacizumab

Abstract Tumor heterogeneity is an area of intense research, revealing tumors with high complexity consisting of different subclones and infiltrating cells. Identification of subclones that are resistant to therapy may be critical to improve treatment outcome. The NeoAva study is a randomized phase II, clinical trial of Her2 negative breast cancer patients treated in a neoadjuvant setting with chemotherapy (FEC and taxane) +/- bevacizumab. Core needle biopsies were obtained at screening and after 12 weeks, and the tumor was surgically removed after 25 weeks. DNA copy number changes in the tumors were analyzed using Affymetrix SNP Array 6.0. Allele specific copy number changes were assessed using the Allele-Specific Copy number Analysis of Tumors (ASCAT) algorithm (Van Loo, Norgard et al., PNAS 2010) and allele-specific Piecewise Constant Fitting (asPCF) algorithms (Nilsen, Liestol et al., BMC Genomics 2012). Measures of genomic instability were obtained through the complex arm-wise aberration index (CAAI) that captures local rearrangements (‘firestorms’) (Russnes, Vollan et al., Sci Transl Med 2010). Changes in copy number aberrations between the three different time points were observed in almost all tumors. Some tumors showed a decrease in tumor percentage and aberrations after just 12 weeks of treatment, where others showed loss of aberrations only at the time of surgery (25 weeks). Most of the tumors that did retain aberrations at all time points during treatment, did not demonstrate any decrease in tumor size. Other profiles indicated subclonal reduction, where some aberrations are kept throughout treatment and others disappear. Many of the tumors shrinking in size showed fewer whole arm aberrations than before treatment, but retained their focal amplicons. Some of the tumor aberrations seem to disappear after 12 weeks, but to reappear after 25 weeks, but with the addition of novel aberration. Complex rearrangements were identified in 67% of tumors before treatment. The most frequent ‘firestorms’ were found on 20p, 11q and 8p. Some events were persistent through therapy, but the majority changed. An association between complex tumor genomes and patients having progressive disease/non-responders were observed. These results show the complex structure of a tumor and suggest that heterogeneity will influence the response to treatment. The subclonal patterns of tumors may be of great importance for clinical decision-making, as well as for monitoring treatment efficacy. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P4-14-01.

Genomic Architecture and Treatment Response In Pediatric Acute Myeloid Leukemia: A Report From The Children's Oncology Group

BackgroundChildhood acute myeloid leukemia (AML) is characterized by chromosomal instability and requires intensive therapy for cure. Here we present a large-scale study from 3 Children's Oncology Group (COG) trials to define the genomic architectural profiles of pediatric AML and to describe whole-arm gains and losses and focal rearrangements using SNP microarrays, accounting for mutation status, non-neoplastic cell infiltration and aneuploidy. We also investigate the association between somatic copy number aberrations (CNAs) and event free survival (EFS). Patients and MethodsA total of 505 matched tumor-remission samples from 459 children with de novo AML were obtained from the COG studies AAML-0531, AAML-03P1, and CCG-2961. 254 paired tumor-remission samples were genotyped on the Affymetrix SNP 6.0 chip at the University of Washington, Seattle, WA, and 251 on the Illumina 2.5M OmniQuad at the Children's Hospital of Philadelphia, PA. All genotyping output was converted to log R ratio and B-allele frequency values and annotations updated to hg19, GRCh37. Illumina intensities were additionally corrected for patterns of genomic wave.A matched allele-specific copy number analysis of tumors (ASCAT) was performed using ASCAT 2.2. A total of 246 (98%) Illumina and 247 (97%) Affymetrix samples passed quality control criteria. ASCAT profiles of patients genotyped on both platforms were manually reviewed and those with highest false CNA calls excluded. Samples with a low signal-to-noise ratio were either eliminated or visually annotated. All CNA segments were manually inspected and false positives removed. The resulting 452 ASCAT profiles were stratified into the risk categories 1) favorable, e.g. inv(16), t(16;16), t(8;21), NPM1, and CEBPα, 2) standard, e.g. normal karyotype, +8, +21, +22, del(7q), del(9q), abnormal 11q23, or other structural changes, and 3) poor, e.g. -5, -7, del(5q), or FLT3/ITD+. GISTIC 2.0 was used to identify genomic areas with significant recurrent aberrations, e.g. amplifications, deletions, and copy-neutral loss-of-heterozygosity (CN-LOH) events. Finally, we investigated whether profiles of genomic instability in the AML genome are predictive of 3 year EFS by using the total number of CNAs as a measure for allelic imbalance. ResultsThe inter-platform concordance for samples genotyped on the two platforms was very high. On average leukemic samples acquire 1.14 somatic CNAs, with a mean of 1.1, 1.3, and 0.8 in the favorable, standard, and poor risk groups respectively (Fig 1). CN-LOH events are observed in 14% (n = 64) of the patients, with 28% involving chromosome 13, and others involving the arms of 11p (23%), 1p (11%), 9p (8%), 7q (6%), 19q (6%), and 3q (5%). Known mutations in AML were enriched in recurrent focal CNA regions, as shown by amplifications on 17q24 (*TK1), 1q32, 3q28, 11q23 (*MLL), 6q27 (*DLL1), 2q32.1, and 4q35.2 (Fig 2). Focal CN-LOH regions were confined to 11p15.5 (*NUP98, *PICALM, *WT1), 1p36.3 (*RUNX3, *NRAS), 9p24.3 (*MLLT3), 3q25.3, 6p23 and 7q35 (*MLL3). Deletions include 7q36.1 (*MLL3, *EZH2), 16p13.11 (*MYH11), 9q21.32, 11p13 (*WT1), 2q37.1 (*IDH1, *DNMT3A), 10p12.31 (*MLLT10), 11q23.3 (*MLL), 16q22.1 (*CBFB), and 1p36.3 (*RUNX3). The association between CNA status and 3 year EFS approached statistical significance for all patients (Table 1), and EFS was significantly lower in standard risk patients with CNAs (51% no CNA vs 34% with CNAs, P 0.03). CNA status did not alter the event risk in the other risk groups. [Display omitted] [Display omitted] Table 1Prognostic Properties of CNAsRisk categoryCNATotal3yr EFSLogrank POverall021554% ± 7%0.0871+23547% ± 7%Favorable08066% ± 11%0.8091+8765% ± 10%Standard08051% ± 11%0.0301+10034% ± 10%Poor04842% ± 15%0.3761+4137% ± 15% ConclusionsThe number of CNAs occurring in this cohort is lower than previously reported. However, the presence of somatic CNAs in standard risk patients is significantly associated with a worse treatment outcome that is similar to the poor risk group. This study confirms the established regions of CNA enrichment in pediatric AML and identifies novel regions that may involve driving mediators of tumor fitness and/or acquired resistance to targeted therapies. Disclosures:No relevant conflicts of interest to declare.

Abstract 661: Identification of epigenomic markers on chromosome 11 that distinguish between choroid plexus carcinoma (CPC) and papilloma (CPP).

Abstract Choroid plexus tumors are rare epithelial brain tumors occurring predominantly in early childhood. Understanding molecular events leading to development and progression of these tumors is critical in determining patient treatment and increased survival. Loss of heterozygosity (LOH) is a common alteration observed during carcinogenesis. To investigate somatic genetic abnormalities in different subtypes of choroid plexus cancers and identify LOH hotspots, we utilized SNP 6.0 arrays (Affymetrix). Allele specific copy number analysis of 25 CPCs and 31 CPPs using Chromosome Analysis Suite (Affymetrix) revealed much higher frequency of LOH events throughout the genome in CPCs (8.4/case) compared with CPPs (1.2/case). One LOH hotspot, neutral copy loss of heterozygosity on chromosome 11, was identified in most CPCs but in no CPPs. Chromosome 11 is known to harbor an imprinted cluster that has been associated with growth dysregulation and pediatric cancer. Both maternal (KvDMR1) and paternal (H19DMR) differentially methylated regions overlap this imprinting cluster. Therefore, we investigated whether the observed LOH is related to uniparental disomy (UPD). Bisulfite pyrosequencing on a subset of CPP and CPC were studied for DNA methylation at both H19DMR and KvDMR1. Our data showed a reverse correlation in the degree of DNA methylation between the 2 DMRs in CPCs and CPPs. These data correlate well with the concept of UPD identified through our SNP arrays. Next, we investigated whether the observed higher expression of insulin like growth factor (IGF2) in CPP compared to CPC is associated with DNA methylation aberrations at the imprinted control region (H19 DMR) on 11p15.5. We identified higher DNA methylation at the H19DMR in CPC compared to CPP. Increased activity of the IGF2 gene has been associated with many types of cancer. To investigate the mechanism of CPC distinct IGF2 expression we examined the expression levels of microRNAs (miRNAs). MicroRNAs are often found to be misregulated in human cancer, and they can act posttranscriptionally as either potent oncogenes or tumor suppressor genes. We studied expression of miR-675-3p, miR-483-3p as well as miR-125-a-3p associated with IGF2/H19 imprinted locus. By quantitative RT-PCR, both miR-675 and miR-125 were found to be more significantly upregulated in CPCs than in CPPs whereas miR-483 was expressed at very low levels in CPCs and in higher levels in CPPs compared with normal control tissues . Misregulation of miR-483 was positively correlated with IGF2 levels in both groups. Our data suggest that dysregulation of epigenetic mechanisms contribute to the molecular events leading to tumor development and progression in CPC and may eventually facilitate identification of new diagnostic markers for CPC, as well as new therapeutic targets for this aggressive, lethal tumor. Citation Format: Malgorzata Pienkowska, Sanaa Choufani, Boleslaw Lach, Diana M. Merino, Ana Novokmet, Uri Tabori, Richard Gilbertson, David Malkin. Identification of epigenomic markers on chromosome 11 that distinguish between choroid plexus carcinoma (CPC) and papilloma (CPP). [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 661. doi:10.1158/1538-7445.AM2013-661

Abstract 3157: Loss of heterozygosity as a molecular ‘second hit’ In familial pancreatic cancer.

Abstract BACKGROUND/HYPOTHESIS: Familial Pancreatic Cancer (FPC) has an autosomal dominant, variable penetrant mode of inheritance with >80% of its genetic cause yet to be discovered. We hypothesize that a high density DNA microarray analysis of Formalin-Fixed Paraffin Embedded (FFPE) FPC tumors will yield novel regions of genomic loss harboring disease causing FPC gene(s). METHODS: 158 FFPE FPC tumor specimens with matched normal tissue were reviewed by a pancreatic pathologist and tumors with <70% cellularity underwent laser capture microdissection. The samples with >70% cellularity were microdissected directly from marked unstained slides. A total of 74 samples were DNA extracted, whole genome amplified and processed on the Affymetrix 660K Oncoscan Microarray. Copy number analysis was performed using Nexus Copy Number Variation Version 6.1 software employing the SNP-FASST2 segmentation and Allele Specific Copy Number Analysis of Tumors (ASCAT) algorithms. PRELIMINARY RESULTS: A pair-wise analysis of 55 FPC samples with matched normal tissue was performed. Recurrent regions of loss of heterozygosity (LOH) were known loci of importance in pancreatic tumorigenesis, including CDKN2A, p53 and SMAD4. Copy neutral/gain LOH was observed throughout the genome and may account for >35% of chromosomal loss. Recurrent novel genetic loci displaying LOH was observed on chromosomes: 3p(25%), 5q(18%), 6p(22%), 12q(18%) and Xq (42%). Examination of 2 FPC siblings elucidates shared loss regions spanning the 3p22.2-3p22.3 and 17p13.3 loci. Candidate tumor suppressor genes (TSGs) of interest include DCLK3, SERPINF1, SERPINF2 and SMYD4. CONCLUSION: We have described for the first time the presence of copy neutral/gain LOH in FPC highlighting previously unknown regions displaying genetic loss. Further confirmation with quantitative PCR, integrating with germline exome sequencing data, and validation of putative TSGs shared by members of high risk FPC kindreds will help uncover novel genes associated with this disease. Citation Format: Zaheer S. Kanji, Stefano Serra, Spring Holter, Ayelet Borgida, Robert Grant, Steven Gallinger. Loss of heterozygosity as a molecular ‘second hit’ In familial pancreatic cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3157. doi:10.1158/1538-7445.AM2013-3157

Analysis of genomic abnormalities in tumors: a review of available methods for Illumina two-color SNP genotyping and evaluation of performance

Several methods have recently been proposed for identifying copy number alterations (CNAs) in genomic DNA from tumors, using the signals arising from two-color genotyping technologies. Although copy number estimation in normal tissue has been well studied, methods developed for normal tissue tend to perform poorly when applied to tumors, due to normal cell contamination, varying levels of ploidy, and genetic heterogeneity within the tumor. Here we compare the performance of seven methods (DNA-Chip Analyzer software (dCHIP), GenoCNA software, allele-specific copy number analysis of tumors (ASCAT), OncoSNP software, genome alteration print (GAP) visualization, CNVpartition software plug-in for the Genome Studio software, and Partek Genomics Suite software) that have been established for two-color CNA analysis on the Illumina platform, using two ovarian cancer cell lines where spectral karyotyping analysis has also been performed, and two tissue samples, one from a highly malignant ovarian cancer and one from a benign ovarian tumor, all of which harbor significantly different genomic abnormalities. ASCAT shows very stable estimates of CNAs, as does OncoSNP when jointly analyzing paired normal DNA. We found the best performance, in general to be from ASCAT.

Bivariate segmentation of SNP-array data for allele-specific copy number analysis in tumour samples

BackgroundSNP arrays output two signals that reflect the total genomic copy number (LRR) and the allelic ratio (BAF), which in combination allow the characterisation of allele-specific copy numbers (ASCNs). While methods based on hidden Markov models (HMMs) have been extended from array comparative genomic hybridisation (aCGH) to jointly handle the two signals, only one method based on change-point detection, ASCAT, performs bivariate segmentation.ResultsIn the present work, we introduce a generic framework for bivariate segmentation of SNP array data for ASCN analysis. For the matter, we discuss the characteristics of the typically applied BAF transformation and how they affect segmentation, introduce concepts of multivariate time series analysis that are of concern in this field and discuss the appropriate formulation of the problem. The framework is implemented in a method named CnaStruct, the bivariate form of the structural change model (SCM), which has been successfully applied to transcriptome mapping and aCGH.ConclusionsOn a comprehensive synthetic dataset, we show that CnaStruct outperforms the segmentation of existing ASCN analysis methods. Furthermore, CnaStruct can be integrated into the workflows of several ASCN analysis tools in order to improve their performance, specially on tumour samples highly contaminated by normal cells.

Patchwork: allele-specific copy number analysis of whole-genome sequenced tumor tissue.

Whole-genome sequencing of tumor tissue has the potential to provide comprehensive characterization of genomic alterations in tumor samples. We present Patchwork, a new bioinformatic tool for allele-specific copy number analysis using whole-genome sequencing data. Patchwork can be used to determine the copy number of homologous sequences throughout the genome, even in aneuploid samples with moderate sequence coverage and tumor cell content. No prior knowledge of average ploidy or tumor cell content is required. Patchwork is freely available as an R package, installable via R-Forge (http://patchwork.r-forge.r-project.org/).

Abstract 2479: TP53 status as a marker of recurrence and survival in choroid plexus carcinomas

Abstract Choroid plexus carcinoma (CPC) is a rare intraventricular tumor more frequently observed in children, accounting for ∼20% of brain tumors in children under 2 yrs of age. This malignant neoplasm is categorized as a grade III tumor by the WHO, while benign choroid plexus papilloma (CPP) and atypical choroid plexus papilloma (aCPP) are categorized as grade I and II, respectively. More than 50% of CPC's carry a mutation in TP53. The role of p53 in the malignant progression of this tumor is not well understood, yet this knowledge is crucial to optimize patient treatment, increase survival and reduce long-term sequelae. The current treatment approach for CPC includes surgical resection and combination chemo- and radiation therapy. However, treatment response is highly variable; tumor progression and relapse is observed in ∼60% of patients, and most survivors experience significant long-term deficits. In this study, we sought to determine whether TP53 status could be used as a reliable marker to predict tumor aggressiveness and response to treatment in CPC patients. Thirty CPC, 26 CPP and 8 aCPP tumor samples for which TP53 status was available were selected from the SickKids Cancer Genetics tissue bank. Sequencing analysis revealed somatic TP53 in 60% of CPCs. These mutations were significantly less frequent in CPPs (12%, p=1.84x10−4). All aCPPs were wildtype (wt) for TP53. Relapse-free survival was only 12% in TP53 mut CPC patients compared to 40% for TP53 wt patients. Only 1 CPP patient relapsed 9 months after initial diagnosis. Five-year overall survival for TP53 mut CPC patients was significantly lower than that of TP53 wt patients (39% vs. 80%, respectively, p=0.04). Overall survival for 18 CPP patients for which we had 5-year survival data was 94%, and 100% for aCPP patients. Allele-specific copy number (ASCN) and FISH analysis, revealed extensive chromosomal imbalances in CPC tumors with TP53 mutations. TP53 wt CPCs had fewer chromosomal imbalances or none at all, very similar to CPPs. Gene expression data was used to examine the unsupervised clustering of our tumors. As expected, CPCs and CPPs cluster independently according to raw gene expression intensity, with TP53 wt CPCs segregating from the CPC mutant samples and clustering more closely to CPPs. Using an integrative analysis, we were able to identify unique behaviors and molecular characteristics that distinguish TP53 wt from TP53 mut CPCs. The clinical outcomes observed, supported by the genomic and transcriptomic data analyzed, suggest that TP53 mut and wt CPCs indeed form two distinct subgroups. This molecular genotyping approach may be valuable in stratifying patients to modulated therapy protocols in order to diminish treatment-related toxicity, and improve disease response and survival. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2479. doi:1538-7445.AM2012-2479

Genomic Landscape of Immunoglobulin Light Chain (AL) Amyloidosis and Comparative Analyses with Related Malignant Plasma Cell Disorder- Multiple Myeloma

Abstract 809Immunoglobulin light chain amlyloidosis (AL) is a rare plasma cell disorder characterized by deposition of misfolded light chains in various organ systems with an average survival of 1–2 years. AL is also the most common form of systemic amyloidosis with 1200–3200 newly diagnosed cases reported annually in the United States. Very little is known regarding specific genomic aberrations associated with AL-amyloidosis. Aside from the light chain selection, no phenotypic or genetic features have been identified that distinguish AL amyloidosis from other plasma cell dyscrasias. Understanding the genetics of AL and the molecular mechanisms involved in amyloid formation may lead to early diagnosis and the identification of novel drug targets and therapies. We therefore have attempted to study the genomic landscape of AL patients and MM for comparison. Genomic copy number and loss of heterozygosity (LOH) analyses were performed on DNA derived from tumor (CD138 sorted cells) and matched germline (skin) from biopsy proven AL patients using Affymetrix single nucleotide polymorphism (SNP) 6.0 arrays. Numerous genomic changes with gains in chromosome 1q, 6, 9, 11q, 15, 19 and 21 and loss on chromosome 1p, 2q, 8, 10, 12, 13, 14, 16, 18, 20 and 22 were observed in more than 10% of the patients. Recurrent genomic changes in about 249 segments involving 457 genes were present in about 1/3 of AL patients. In particular, deletion of IGK, IGH, PIK3CA, FLT3, RB1, PCDH9, GPC6, RASA3, ADAM6 genes and amplification of CFHR1, JAK2, GCNT1, TSC1, PGR genes were observed. Gene network analysis showed five distinct major modules consisting of 51 distinct elements and involving PDGF, TP53, interleukin signaling, TRKA signaling, cell cycle and mitotic pathways were enriched. Allele specific copy number analysis in tumor (ASCAT) profile showed increased ploidy status of the AL genome in 47% of the assessed patients. LOH was observed in chromosomes 4, 5, 6, 8, 9, 12, 13, 18 and 22 in 30% of patients, ranging from 5Mb to entire chromosome. Furthermore, genomic comparisons of AL with multiple myeloma (MM) showed the typical archetype of myeloma’s signature with exception of gain of chromosomes 3, 5, 7 and loss of chromosome 6q and 8p. Interestingly deletion of IGH, IGK locus and PIK3CA gene were observed at a higher frequency in AL patients. Categorical analysis using isotype specific classification in AL showed a significantly higher frequency of deletion in chromosome 14, 13, 8 and amplification of chromosome 9q in the kappa type than lambda isotype. To the best of our knowledge, this is the first ultra-high resolution study of the genomic landscape of AL amyloidosis. In this study, we have found several novel genes and pathways associated with this rare disease. The numerous copy number alterations of AL thus reflect the genomic complexity and the heterogeneity of this disease. Additional genome-wide analysis in a larger panel with target organ stratified patients is under way and may further our understanding of genetic changes specifically associated with AL. Disclosures:No relevant conflicts of interest to declare.

Identification of Recurrent Submicroscopic Deletions of chromosome1q31.3 As Possible Molecular Prognostic Markers in Acute Promyelocytic Leukemia (APL)

Abstract 420▪▪This icon denotes a clinically relevant abstract Introduction:The characteristic hallmark of acute promyelocytic leukemia (APL) is a balanced reciprocal chromosomal translocation between chromosomes 15 and 17 leading to a fusion product consisting of the promyelocytic leukemia gene (PML) and the retinoic acid receptor alpha (RARA). The PML-RARA fusion product is necessary but not sufficient for the generation of leukemia and it is hypothesized that additional genomic lesions play a role in the pathogenesis of APL. Therefore, we have performed a high density SNP array analysis on 101 APL patient samples to identify new copy number alterations (CNAs) which may be relevant for the biology and prognosis of APL. Patients and Methods: Molecular and clinical outcome analyses were carried out retrospectively on patients diagnosed with APL, whose samples were referred to the molecular laboratory of the Department of Hematology and Oncology of the Medical Faculty Mannheim, University of Heidelberg, Germany between 1997 and 2010. 500 ng of genomic DNA from leukemic blasts per sample were processed according to the Genome Wide Human SNP 6.0 Array protocol (Affymetrix, Santa Clara, CA). The CNAG 3.3 software was used to perform allele-specific copy number analysis with anonymous references. CNAs of special interest were validated to be acquired in leukemia cells by performing allele-specific copy number analysis in matched pair SNP 6.0 array analysis, quantitative real time PCR and direct sequencing of genomic DNA from initial diagnosis and molecular remission samples. Results: We identified 279 acquired CNAs consisting of 185 heterozygous deletions, 87 amplifications and 7 regions of copy number neutral loss of heterozygosity (CNLOH). Besides common chromosomal aberrations such as trisomy 8 or duplications of the long arm of chromosome 8, deletions of 7q or isochromosome ider(17)(q10)t(15;17), numerous novel recurrent micro-deletions were discovered. The most common was a somatically acquired ∼100 kilobase deletion of chromosome 1q31.3 in 13 of 101 (13%) patients. These deletions encompassed the coding regions for the microRNAs mir181a1/b1. In univariate analyses of overall survival (OS) and relapse free survival (RFS) using Logrank tests, we found that patients carrying 2 or more CNAs as compared to 0 or 1 CNA as detected by SNP array had a significantly increased risk of death (p=0.016) and relapse (p=0.019). Patients carrying the recurrent deletion of chromosome 1q31.3 as compared to patients not carrying this deletion had a significantly increased risk of relapse (p=0.005), a markedly higher number of CNAs (median 8 vs. 2, p < 0.0001) and significantly higher white blood cell counts (WBC) at initial diagnosis (median 2550/μl vs. 16900/μl, p=0.009). We performed a multivariable analysis using Cox proportional hazards models to evaluate power of CNAs detected by SNP-array and deletions of chr. 1q31.3 as possible independent prognostic markers in APL as compared to age, WBC, platelet count (PC) and FLT3 mutational status. For the full model of OS only age and the number of CNAs detected by SNP-A met a 0.10 level of entry into the model and confirmed that the group of patients with 2 or more CNAs represent a subgroup with inferior outcome (“2 or more lesions”: hazard ratio = 5.942, p = 0.0015, age: hazard ratio = 1.08, p < 0.0001). Of note, for the analysis of RFS the presence of a chr. 1q31.3 deletion was the only effect, which met the entry level into the model of RFS and therefore was identified as a new strong predictor for an increased risk of relapse (“presence of del1q31.3”: hazard ratio = 28.9, p = 0.0031). Conclusion: The profiles of submicroscopic CNAs in APL patients are heterogeneic and may serve as strong independent prognostic markers for disease risk definition. Recurrent submicroscopic deletions of chr. 1q31.3 in leukemia cells of APL patients were associated with an increased number and characteristic pattern of further newly identified CNAs, unfavorable laboratory parameters and a higher risk of relapse. The number of CNAs was shown to be predictive for early death rate and overall survival. The further pursuit of these new potential molecular markers is highly warranted as they could refine the current risk stratification of APL by identifying new subgroups of patients, who could possibly gain from adapted treatment strategies. Disclosures:No relevant conflicts of interest to declare.

Dealing with sample aneuploidy and mosaicsm using the ASCAT algorithm on different SNP array platforms

Cancer samples pose a challenging problem for analysis using microarray technology. The basic array CGH (aCGH) approach can confidently detect changes in copy number when a sample is measured against a normal control. However, the necessary normalization pre-processing step will essentially wash away the information associated with hyperdiploid samples. This can be an issue especially with cancer samples. Additionally, mosaic samples, due to different mixture of cells in the sample, can also severely complicate the analysis and interoperation of samples with microarray technology. One of the recently proposed approaches to simultaneously deal with these issues is called the Allele Specific Copy Number Analysis of Tumors (ASCAT) algorithm (1). The approach takes advantage of the SNP information from SNP microarrays to combine the change in total signal strength (log-R value) with the B-Allele Frequency (BAF) to create an optimization function that has local minimas at values corresponding to possible sample ploidy and percent normal contamination. Here we demonstrate an efficient implementation of the ASCAT algorithm on processing cancer samples generated by The Cancer Genome Atlas (TCGA) project. Using Affymetrix and Illumina SNP array data, results are compared between the different platforms as well as with and without application of the ASCAT algorithm. Characterization of a percentage of the cells as normal contaminants within the samples using the ASCAT algorithm reveals many more gains and losses in the aberration profile of the tumors than in samples processed without ASCAT. ASCAT also identified that a large percentage of samples contain high ploidy numbers. With the sample ploidy and extent of normal contamination identified using ASCAT, clearer and more accurate calls can be made for cancer samples. 1. Van Loo P, Nordgard SH, Lingjaerde OC, et al. Allele-specific copy number analysis of tumors. Proc Natl Acad Sci USA 2010;107:16910-16915.

Abstract LB-345: Amplification of miR-26a-2 in human liposarcoma is correlated with poor patient survival

Abstract Human liposarcoma (LPS) is one of the most common soft tissue sarcomas in adults. However, its molecular mechanism is poorly understood. For better understanding of the disease, we examined 54 human liposarcoma samples including 51 primary tumors and 3 cell lines (SW872, LP6, LP141) using Affymetrix 250K single nucleotide polymorphism (SNP) array. Allele-specific copy number (CN) analysis using anonymous references revealed that CN gain was dominant event over CN loss and loss of heterozygosity (LOH) in human LPS. Recurrent CN gain at 1q21–24 (43% of the samples), 5p13-p15 (46%), and 8q24 (41%) were identified. The most prominent CN gain was found in the 12q13-q15 region. 88% of the samples, mostly well-differentiated / de-differentiated subtype (WDLPS / DDLPS), showed various levels of CN gains centered at MDM2 gene. In addition to MDM2 amplicon, we also identified an MDM2-independent amplicon in the 12q13-q15 region centered at miR-26a-2 gene at the same frequency (88%). MDM2 amplicon almost always accompanied miR-26a-2 amplicon. Likewise, samples without MDM2 amplicon did not have a miR-26a-2 amplicon. Quantitative reverse transcription real-time PCR (qRT-PCR) analysis showed that this CN gain of miR-26a-2 was strongly correlated with high mRNA expression of the gene in the WDLPS / DDLPS subtype. Furthermore, high mRNA expression of miR-26a-2 significantly correlated with a worse patient survival (p=0.05). Interestingly, some samples in myxoid / round-cell subtype (MRC) also showed high expression of miR-26a-2 without any prominent CN changes. High expression in the MRC subtype was also correlated with poor patient survival (p=0.0029). Western blot analysis using LPS cell lines revealed that cells with high miR-26a-2 expression showed decreased levels of RB1 and PTEN, which are two verified targets of miR-26a-2. In conclusion, our analysis demonstrated the clinical importance of miR-26a-2 gene in human LPS. This finding may contribute to the discovery of prognostic markers as well as novel therapeutic targets for human LPS. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr LB-345. doi:10.1158/1538-7445.AM2011-LB-345

Estimation of Parent Specific DNA Copy Number in Tumors using High-Density Genotyping Arrays

Chromosomal gains and losses comprise an important type of genetic change in tumors, and can now be assayed using microarray hybridization-based experiments. Most current statistical models for DNA copy number estimate total copy number, which do not distinguish between the underlying quantities of the two inherited chromosomes. This latter information, sometimes called parent specific copy number, is important for identifying allele-specific amplifications and deletions, for quantifying normal cell contamination, and for giving a more complete molecular portrait of the tumor. We propose a stochastic segmentation model for parent-specific DNA copy number in tumor samples, and give an estimation procedure that is computationally efficient and can be applied to data from the current high density genotyping platforms. The proposed method does not require matched normal samples, and can estimate the unknown genotypes simultaneously with the parent specific copy number. The new method is used to analyze 223 glioblastoma samples from the Cancer Genome Atlas (TCGA) project, giving a more comprehensive summary of the copy number events in these samples. Detailed case studies on these samples reveal the additional insights that can be gained from an allele-specific copy number analysis, such as the quantification of fractional gains and losses, the identification of copy neutral loss of heterozygosity, and the characterization of regions of simultaneous changes of both inherited chromosomes.

Allele-specific copy number analysis of tumor samples with aneuploidy and tumor heterogeneity

We describe a bioinformatic tool, Tumor Aberration Prediction Suite (TAPS), for the identification of allele-specific copy numbers in tumor samples using data from Affymetrix SNP arrays. It includes detailed visualization of genomic segment characteristics and iterative pattern recognition for copy number identification, and does not require patient-matched normal samples. TAPS can be used to identify chromosomal aberrations with high sensitivity even when the proportion of tumor cells is as low as 30%. Analysis of cancer samples indicates that TAPS is well suited to investigate samples with aneuploidy and tumor heterogeneity, which is commonly found in many types of solid tumors.

Allele-specific copy number analysis of tumors

We present an allele-specific copy number analysis of the in vivo breast cancer genome. We describe a unique bioinformatics approach, ASCAT (allele-specific copy number analysis of tumors), to accurately dissect the allele-specific copy number of solid tumors, simultaneously estimating and adjusting for both tumor ploidy and nonaberrant cell admixture. This allows calculation of "ASCAT profiles" (genome-wide allele-specific copy-number profiles) from which gains, losses, copy number-neutral events, and loss of heterozygosity (LOH) can accurately be determined. In an early-stage breast carcinoma series, we observe aneuploidy (>2.7n) in 45% of the cases and an average nonaberrant cell admixture of 49%. By aggregation of ASCAT profiles across our series, we obtain genomic frequency distributions of gains and losses, as well as genome-wide views of LOH and copy number-neutral events in breast cancer. In addition, the ASCAT profiles reveal differences in aberrant tumor cell fraction, ploidy, gains, losses, LOH, and copy number-neutral events between the five previously identified molecular breast cancer subtypes. Basal-like breast carcinomas have a significantly higher frequency of LOH compared with other subtypes, and their ASCAT profiles show large-scale loss of genomic material during tumor development, followed by a whole-genome duplication, resulting in near-triploid genomes. Finally, from the ASCAT profiles, we construct a genome-wide map of allelic skewness in breast cancer, indicating loci where one allele is preferentially lost, whereas the other allele is preferentially gained. We hypothesize that these alternative alleles have a different influence on breast carcinoma development.

794 Allele-specific copy number analysis of breast carcinomas

This prospective study includes 103 cases of chondroid pulmonary hamartomas, resected over a period of nearly six years. Genes encoding proteins of the high motility group (HMGI-C, (Y), chromosomes 12q15 and 6p21) were analyzed cytogenetically. Furthermore, we examined the expression of growth-regulatory markers, including galectins-1, -3, -8, heparin-binding lectin (HBL), calcyclin (S100A6) and macrophage migration inhibitory factor (MIF), as well as that of Ki-67 (MIB-1). Syntactic structure analysis was applied to automated classification of stained histological slides and for the detection of topological properties in hamartomas and disease-free lung. These data were set in relation to clinical features, including environmental hazards, smoking habit, and the occurrence of heart-lung disease. Men and women contributed to the study in 61 and 42 cases, respectively. Smoking was frequent (75% men and 54% women), with a mean tobacco consumption of 36 pack years. Aberrations affecting exclusively the HMGI-C gene and the HGMI(Y) gene were seen in 46 cases (44.7%) and in 22 cases (21.3%), respectively. Both genes were affected in only one case. Abnormalities most frequently occurred in chromosomal bands 6p12 and 12q14. Genetic aberrations were significantly increased in men exposed to environmental (occupational) risk factors, excluding smoking (p < 0.05), and in tumors larger than average hamartomas. There were significant differences in staining profiles, particularly for calcyclin and MIF. The mean proliferation index was Nv = 9.9 ± 6.4%; structural entropy was similar in all markers applied. Owing to their remarkably high values (from 142 to 148), these data were in contrast to a low current of entropy seen in most markers applied. The staining profile identified several markers that delimited cell positivity from normal parenchymal cells. These results contribute to the definition of biochemical characteristics in hamartomas and can be useful for distinguishing them from chronic degenerative disorders.

Abstract PL1-1: Genomic architecture characterizes tumor progression paths and fate in breast cancer patients

Abstract Breast cancer is a heterogeneous disease as reflected by histopathology, molecular alterations and clinical behavior. In order to relate cellular and sub-cellular features to clinical parameters and outcome, substantial effort has been exerted towards identifying tumor groups with distinct molecular features. The gene expression based classification that we proposed ten years ago identified five different subgroups with difference in survival; two Luminal-cell related groups (Luminal A and luminal B), a myoepithelial-cell related group (Basal-like), a HER2 enriched, and a Normal-like group. The Basal-like and Luminal carcinomas have different etiologies and for most purposes may be considered as distinct diseases. This is also reflected in the genomic portraits defined by aCGH (array Comparative Genomic Hybridization), and it seems evident that the history of the molecular subgroups is written in the DNA alterations. We have developed two platform independent algorithms to explore genomic architectural distortion using aCGH data to measure whole arm gains and losses (WAAI) and complex rearrangements (CAAI). By applying CAAI and WAAI to data from 595 breast cancer patients we were able to separate the cases into eight subgroups with different distribution of genomic distortion. Within each subgroup data from expression analyses, sequencing and ploidy indicated that progression occurs along separate paths into more complex genotypes. Several of the CGH based subgroups were enriched for either luminal related or basal related tumors, and showed distinct patterns of genomic alterations. In particular, basal related tumors were separated into genomic classes with distinct patterns of alterations emphasizing genomic heterogeneity also in this expression subclass. Histological grade had prognostic impact only in the Luminal related groups while the complexity identified by CAAI had an overall independent prognostic power. These results emphasizes the relationship between structural genomic alterations, expression subtypes and clinical behavior, and provides a score of genomic complexity as a new tool for prognostication in breast cancer. Using SNP arrays and a novel bioinformatic approach, ASCAT (Allele-Specific Copy number Analysis of Tumors), we have performed genome wide allele-specific copy number analysis of 112 breast cancer genomes. We were able to accurately dissect the allele-specific copy number in each tumor, simultaneously estimating and adjusting for both tumor ploidy and non-aberrant cell admixture, allowing calculation of “Tumor Profiles” (genome-wide allele-specific copy-number profiles) from which gains, losses, copy-number-neutral events and LOH could be determined. The tumors had on average a non-aberrant cell admixture of 49%, and 45% of them were aneuploid (&amp;gt;2.7n). By aggregation of Tumor Profiles across the sample set a genome-wide view of LOH and copy-number-neutral events was obtained. The Tumor Profiles also revealed differences in aberrant tumor cell fraction, ploidy, gains, losses, LOH and copy-number-neutral events between the five expression subtypes. Basal-like breast carcinomas have a significantly higher frequency of LOH compared to other subtypes, and their Tumor Profiles show large-scale loss of genomic material during tumor development, followed by a whole-genome duplication, resulting in near-triploid genomes. From the Tumor Profiles we could also construct a genome-wide map of allelic skewness, indicating loci where one allele is preferentially lost while the other allele is preferentially gained. We hypothesize that these alternative alleles have a different influence on breast carcinoma development. Citation Information: Clin Cancer Res 2010;16(7 Suppl):PL1-1