Allele-specific Copy Number Research Articles

Rawcopy: Improved copy number analysis with Affymetrix arrays.

Microarray data is subject to noise and systematic variation that negatively affects the resolution of copy number analysis. We describe Rawcopy, an R package for processing of Affymetrix CytoScan HD, CytoScan 750k and SNP 6.0 microarray raw intensities (CEL files). Noise characteristics of a large number of reference samples are used to estimate log ratio and B-allele frequency for total and allele-specific copy number analysis. Rawcopy achieves better signal-to-noise ratio and higher proportion of validated alterations than commonly used free and proprietary alternatives. In addition, Rawcopy visualizes each microarray sample for assessment of technical quality, patient identity and genome-wide absolute copy number states. Software and instructions are available at http://rawcopy.org.

Abstract 2396: Heterogeneity of colorectal cancers and multiple liver metastases by mutation and copy number profiling

Abstract To investigate genetic and genomic heterogeneity in liver metastases of colorectal cancer, multiple tumor foci in the liver per patient were identified on the basis of radiological images and samples from these systematically biobanked. For a total of 67 patients, 258 metastatic tumor samples were collected (minimum of 2 and maximum of 9 samples per patient, median of 4 samples per patient). Additionally, for n = 14 patients, tumor samples from the corresponding primary colorectal cancer were also available. DNA isolated from these samples was subjected to mutation profiling by Sanger sequencing for the genes BRAF, KRAS, PIK3CA and TP53, as well as allele-specific copy number profiling by CytoscanHD SNP array. For the four genes investigated for mutations, 39/67 (58%) of the patients were homogeneous in their mutation profile, while 21/67 (32%) were heterogeneous (one or more samples had mutations not detected in all samples). For 7/67 patients (10%), no mutations were detected in any of these four genes. For 9/14 patients with matching primary tumors, there was complete concordance between the primary tumor and all liver metastases profiled for mutations, while the remaining 5/14 patients showed discordance in mutation profile between the primary tumor and at least one of the liver metastases profiled. High resolution copy number profiles of this cohort detected many of the aberrations previously described in primary colorectal cancer, specifically gain of chromosomes 7, 8q, 13q and 20q, and loss of chromosomes 5q, 8p, 15q, 17p and 18q. The extent of heterogeneity observed in patient-wise mutation profiles was largely mirrored in the copy number profiles of the same tumors. 16/27 (60%) of the patients for which both mutation and copy number profiles were available showed concordance in the degree of heterogeneity per patient. In summary, intra-individual heterogeneity varied from patient to patient, with results from the genetic and genomic data types largely concurring. Citation Format: Sharmini Alagaratnam, Tuva Høst Brunsell, Stine Aske Danielsen, Anita Sveen, Mette Eknæs, Merete Hektoen, Bård Røsok, Bjørn Atle Bjørnbeth, Arild Nesbakken, Ragnhild Lothe. Heterogeneity of colorectal cancers and multiple liver metastases by mutation and copy number profiling. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2396.

Allele-Specific Quantification of Structural Variations in Cancer Genomes

SummaryAneuploidy and structural variations (SVs) generate cancer genomes containing a mixture of rearranged genomic segments with extensive somatic copy number alterations. However, existing methods can identify either SVs or allele-specific copy number alterations, but not both simultaneously, which provides a limited view of cancer genome structure. Here we introduce Weaver, an algorithm for the quantification and analysis of allele-specific copy numbers of SVs. Weaver uses a Markov Random Field to estimate joint probabilities of allele-specific copy number of SVs and their inter-connectivity based on paired-end whole-genome sequencing data. Weaver also predicts the timing of SVs relative to chromosome amplifications. We demonstrate the accuracy of Weaver using simulations and findings from whole-genome Optical Mapping. We apply Weaver to generate allele-specific copy numbers of SVs for MCF-7 and HeLa cell lines, and identify recurrent SV patterns in 44 TCGA ovarian cancer whole-genome sequencing datasets. Our approach provides a more complete assessment of the complex genomic architectures inherent to many cancer genomes.

FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing.

Allele-specific copy number analysis (ASCN) from next generation sequencing (NGS) data can greatly extend the utility of NGS beyond the identification of mutations to precisely annotate the genome for the detection of homozygous/heterozygous deletions, copy-neutral loss-of-heterozygosity (LOH), allele-specific gains/amplifications. In addition, as targeted gene panels are increasingly used in clinical sequencing studies for the detection of ‘actionable’ mutations and copy number alterations to guide treatment decisions, accurate, tumor purity-, ploidy- and clonal heterogeneity-adjusted integer copy number calls are greatly needed to more reliably interpret NGS-based cancer gene copy number data in the context of clinical sequencing. We developed FACETS, an ASCN tool and open-source software with a broad application to whole genome, whole-exome, as well as targeted panel sequencing platforms. It is a fully integrated stand-alone pipeline that includes sequencing BAM file post-processing, joint segmentation of total- and allele-specific read counts, and integer copy number calls corrected for tumor purity, ploidy and clonal heterogeneity, with comprehensive output and integrated visualization. We demonstrate the application of FACETS using The Cancer Genome Atlas (TCGA) whole-exome sequencing of lung adenocarcinoma samples. We also demonstrate its application to a clinical sequencing platform based on a targeted gene panel.

Clinical significance and origin of leukocytes that lack HLA-A allele expression in patients with acquired aplastic anemia.

To gain insight into the origin and clinical significance of leukocytes that lack human leukocyte antigen A (HLA-A) allele expression caused by a copy-number-neutral loss of heterozygosity in the short arm of chromosome 6 in patients with acquired aplastic anemia (AA),weused a high-sensitivity flow cytometry assay to investigate the presence of HLA-A allele-lacking leukocytes(HLA-LLs) in 144 AA patients. HLA-LLs, accounting for0.2-99.8% of each leukocyte population, were detected in 18 of 71 (25.4%) newly diagnosed patientsand in 25 of 73 (34.2%) previously treated patients. The lineage combination patterns of the HLA-LLs in the 43 HLA-LL(+)patients were granulocytes (Gs), monocytes (Ms), Bcells (Bs), and Tcells (Ts; GMBT) in 13 cases, GMB in 16 cases, GM in 11 cases, and B alone in three cases. The response rate to antithymocyte globulin plus cyclosporine therapy (100%) and the 2-year, failure-free survivalrate (100%) in 8 newly diagnosed HLA-LL(+) patients were significantly higher than in 23 HLA-LL(-) patients (52.2% for both). These data suggest that HLA-LLs are a useful marker of the presence of immune pathophysiology in AA and that T-cell attacks against hematopoietic progenitor cells, rather than against hematopoietic stem cells, can trigger bone marrow failure in AA patients.

Recurrent, truncating SOX9 mutations are associated with SOX9 overexpression, KRAS mutation, and TP53 wild type status in colorectal carcinoma.

PurposeThe extent to which the developmental transcription factor SOX9 functions as an oncogene or tumor suppressor in colorectal carcinoma (CRC) is debatable. We aimed to clarify the effect of SOX9 mutations on SOX9 protein expression and their association with known molecular subtypes and clinical characteristics in advanced CRC.Experimental DesignNext generation sequencing data (MSK-IMPACT) from CRC patients was used to interrogate SOX9, KRAS, NRAS, BRAF, TP53, APC, and PIK3CA. Mutant and wild type (WT) SOX9 cases underwent immunohistochemical (IHC) staining to assess protein expression. SOX9 allele-specific copy number was assessed by Affymetrix Oncoscan array.ResultsSOX9 was mutated in 38 of 353 (10.7%) CRC, of which 82% were frameshift or nonsense. Compared to SOX9 WT, SOX9 mutation was strongly associated with coexistent mutant KRAS (p=0.0001) and WT TP53 (p=0.0004). SOX9 was overexpressed in both SOX9 mutant and WT CRC. Among SOX9 mutants, the highest expression was noted for truncating exon 3 mutants (mean H scores 239±105 versus 147±119, p value=0.02). Further, SOX9 truncating mutants with loss of the WT allele demonstrated protein overexpression indicating the WT protein was not required for protein stabilization.ConclusionsSOX9 is overexpressed in CRC, including those with recurrent distal truncating mutations. The latter has structural similarity to the oncogenic isoform MiniSOX9, which is distally truncated due to aberrant splicing. This information suggests that truncated SOX9 has oncogenic features. SOX9 mutations are highly enriched in KRAS mutant and TP53 wild type CRC; and may provide a therapeutic target in approximately 11% of CRC.

Probe-free allele-specific copy number detection and analysis of tumors

Cancer development and progression frequently involve nucleotide mutations as well as amplifications and deletions of genomic segments. Quantification of allele-specific copy number is an important step in characterizing tumor genomes for precision medicine. Despite advances in approaches to high-throughput genomic DNA analysis, inexpensive and simple methods for analyzing complex nucleotide and copy number variants are still needed. Real-time polymerase chain reaction (PCR) methods for discovering and genotyping single nucleotide polymorphisms are becoming increasingly important in genetic analysis. In this study, we describe a simple, single-tube, probe-free method that combines SYBR Green I-based quantitative real-time PCR and quantitative melting curve analysis both to detect specific nucleotide variants and to quantify allele-specific copy number variants of tumors. The approach is based on the quantification of the targets of interest and the relative abundance of two alleles in a single tube. The specificity, sensitivity, and utility of the assay were demonstrated in detecting allele-specific copy number changes critical for carcinogenesis and therapeutic intervention. Our approach would be useful for allele-specific copy number analysis or precise genotyping.

Abstract C53: Homologous recombination deficiency (HRD) of high grade serous ovarian tumors from the NOVA Phase III clinical study

Abstract Background: Genome-wide analysis was conducted on tumors obtained from patients enrolled in the NOVA study, a Phase 3 clinical trial evaluating the PARP inhibitor niraparib as a maintenance treatment in patients with platinum-sensitive ovarian cancer. Homologous recombination deficiency (HRD) and mutations in DNA damage repair genes were evaluated. Material and methods: DNA was extracted from formalin-fixed paraffin-embedded (FFPE) tumor tissue and used to create libraries that were hybridized to a custom Agilent SureSelect capture array carrying probes for 54,091 single nucleotide polymorphism sites distributed across the human genome, as well as probes targeting 43 genes involved in DNA repair, including BRCA1 and BRCA2. The captured and enriched DNA was sequenced on an Illumina HiSeq 2500 sequencer. Sequences covering SNP positions were used to generate allelic imbalance profiles. Measures of genomic instability, including determination of an HRD score (integer value of 0-100), were calculated using allelic imbalance profiles and determination of loss of heterozygosity (LOH) by allele-specific copy number (ASCN). A previously identified HRD threshold score of 42 was used to define HRD positivity in the absence of a BRCA mutation. Results: The NOVA study is a Phase 3, multicenter, randomized, double-blind, placebo-controlled study of niraparib as maintenance therapy in ovarian cancer patients who have either gBRCAmut or a tumor with high-grade serous histology and who have responded to their most recent chemotherapy containing a platinum agent. Tumor BRCA mutational status, HRD score and genomic sequencing of 43 DNA repair genes were obtained from tumor samples from both gBRCAmut and non-gBRCAmut cohorts. In the gBRCAmut cohort, HRD analysis of the tumor confirmed the presence of a deleterious or suspected deleterious mutation in all cases. In addition, an HRD score ≥ 42 and the presence of a deleterious mutation in TP53 with loss of heterozygosity (LOH) were observed in nearly all tumors. In the non-gBRCA cohort, somatic BRCA mutations were observed in approximately 13% of tumors, and approximately half of tumors with no evidence of a BRCA mutation had a high HRD score. In both cohorts, the use of three scoring algorithms (LOH, telomeric allelic imbalance [TAI], large-scale state transitions [LST]), was more predictive of BRCA mutational status than LOH alone. Additional genomic sequencing identified deleterious mutations with LOH in DNA repair genes, such as BRIP1, CDK12, RAD51C, PTEN, and RAD51D, with many tumors exhibiting multiple deleterious mutations. Conclusions: High grade serous ovarian cancer is characterized by a high degree of genomic instability. Genomic analysis in the clinical setting is able to identify patients with both germline and somatic BRCA mutations, in addition to BRCAwt tumors with other genetic defects that may be sensitive to agents exploiting deficiencies in HR. Citation Format: Keith Wilcoxen, Christopher Neff, Victor Abkevich, Joshua Timothy Jones, Kathryn Kolquist, Michael Mirza, Jerry Lanchbury, Keith Mikule, Shefali Agarwal, Anne-Renee Hartman, Alexander Gutin, Kirsten Timms. Homologous recombination deficiency (HRD) of high grade serous ovarian tumors from the NOVA Phase III clinical study. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr C53.

BubbleTree: an intuitive visualization to elucidate tumoral aneuploidy and clonality using next generation sequencing data.

Tumors are characterized by properties of genetic instability, heterogeneity, and significant oligoclonality. Elucidating this intratumoral heterogeneity is challenging but important. In this study, we propose a framework, BubbleTree, to characterize the tumor clonality using next generation sequencing (NGS) data. BubbleTree simultaneously elucidates the complexity of a tumor biopsy, estimating cancerous cell purity, tumor ploidy, allele-specific copy number, and clonality and represents this in an intuitive graph. We further developed a three-step heuristic method to automate the interpretation of the BubbleTree graph, using a divide-and-conquer strategy. In this study, we demonstrated the performance of BubbleTree with comparisons to similar commonly used tools such as THetA2, ABSOLUTE, AbsCN-seq and ASCAT, using both simulated and patient-derived data. BubbleTree outperformed these tools, particularly in identifying tumor subclonal populations and polyploidy. We further demonstrated BubbleTree's utility in tracking clonality changes from patients’ primary to metastatic tumor and dating somatic single nucleotide and copy number variants along the tumor clonal evolution. Overall, the BubbleTree graph and corresponding model is a powerful approach to provide a comprehensive spectrum of the heterogeneous tumor karyotype in human tumors. BubbleTree is R-based and freely available to the research community (https://www.bioconductor.org/packages/release/bioc/html/BubbleTree.html).

Global copy number profiling of cancer genomes.

In this article, we introduce a robust and efficient strategy for deriving global and allele-specific copy number alternations (CNA) from cancer whole exome sequencing data based on Log R ratios and B-allele frequencies. Applying the approach to the analysis of over 200 skin cancer samples, we demonstrate its utility for discovering distinct CNA events and for deriving ancillary information such as tumor purity. https://github.com/xfwang/CLOSE CONTACT: xuefeng.wang@stonybrook.edu or michael.krauthammer@yale.edu Supplementary data are available at Bioinformatics online.

Abstract 4851: BubbleTree: an intuitive visualization to elucidate tumoral aneuploidy and clonality in somatic mosaicism using copy number ratio and allele frequency

Abstract Background Tumors are characterized by properties of instability, heterogeneity, and significant oligoclonality. Elucidating these patterns of tumor clonal evolution is critical to our understanding of neoplastic development, which can ultimately improve diagnosis and treatment decisions in cancer therapy. Methods BubbleTree is an intuitive tree-like graph used to simultaneously illustrate tumor cell prevalence, allele-specific copy number, and clonality in human tumor specimens. This method evaluates somatic copy number alterations (SCNAs) at the focal genomic segment level to determine allele-specific copy number and elucidate the clonal hierarchy within tumors. Further, BubbleTree can longitudinally track genetic alterations in clonality during tumor progression and/or recurrence. Two models, a Bayesian and finite mixture distribution-based method, were developed to automate the interpretation of the BubbleTree graph. Both whole genome and whole exome sequencing (WGS and WES, respectively) data from three case studies are presented using the BubbleTree method: paired primary tumors in the lung and ovary from a patient, matched primary and recurrent liver tumors from a hepatocellular carcinoma (HCC) patient, and matched primary liver and metastatic lung tumors in a second HCC patient. Results BubbleTree accurately identified both inherited and altered karyotypes, as well as their prevalence between primary and recurrent liver tumors in two HCC patients, which suggests that the recurrent HCC malignancy post orthotopic liver transplantation originated from the primary tumor, with novel subclonal expansion during metastasis. Furthermore, BubbleTree accurately reveals the dominant clone and instable subclones in the lung tumor of a patient with synchronous double malignancies; these results were validated by fluorescent in situ hybridization. Conclusions Our model is robust for both WGS and WES data, with consistency demonstrated on both data types from the same tumor biopsy. The BubbleTree diagram and model presented here is a powerful approach to provide a comprehensive spectrum of the heterogeneous tumor karyotype in tumors. Further, this tool is a free R package available for download at Bioconductor. Citation Format: Wei Zhu, Mike Kuziora, Chris Morehouse, Tianwei Zhang, Yinong Sebastian, Zheng Liu, Dong Shen, Jiaqi Huang, Zhengwei Dong, Yi Gu, Feng Xue, Liyan Jiang, Yihong Yao, Brandon W. Higgs. BubbleTree: an intuitive visualization to elucidate tumoral aneuploidy and clonality in somatic mosaicism using copy number ratio and allele frequency. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4851. doi:10.1158/1538-7445.AM2015-4851

Concordance of copy number alterations using a common analytic pipeline for genome-wide analysis of Illumina and Affymetrix genotyping data: a report from the Children's Oncology Group

Copy number alterations (CNAs) are a hallmark of pediatric cancer genomes. An increasing number of research groups use multiple platforms and software packages to detect and analyze CNAs. However, different platforms have experimental and analysis-specific biases that may yield different results. We sought to estimate the concordance of CNAs in children with de novo acute myeloid leukemia between two experimental platforms: Affymetrix SNP 6.0 array and Illumina OmniQuad 2.5 BeadChip. Forty-five paired tumor-remission samples were genotyped on both platforms, and CNAs were estimated from total signal intensity and allelic contrast values using the allele-specific copy number analysis of tumors (ASCAT) algorithm. The two platforms were comparable in detection of CNAs, each missing only two segments from a total of 42 CNAs (4.6%).Overall, there was an interplatform agreement of 96% for allele-specific tumor profiles. However, poor quality samples with low signal/noise ratios showed a high rate of false-positive segments independent of the genotyping platform. These results demonstrate that a common analytic pipeline can be utilized for SNP array data from these two platforms. The customized programming template for the preprocessing, data integration, and analysis is publicly available at https://github.com/AplenCHOP/affyLumCNA.

Allele-specific copy-number discovery from whole-genome and whole-exome sequencing.

Copy-number variants (CNVs) are a major form of genetic variation and a risk factor for various human diseases, so it is crucial to accurately detect and characterize them. It is conceivable that allele-specific reads from high-throughput sequencing data could be leveraged to both enhance CNV detection and produce allele-specific copy number (ASCN) calls. Although statistical methods have been developed to detect CNVs using whole-genome sequence (WGS) and/or whole-exome sequence (WES) data, information from allele-specific read counts has not yet been adequately exploited. In this paper, we develop an integrated method, called AS-GENSENG, which incorporates allele-specific read counts in CNV detection and estimates ASCN using either WGS or WES data. To evaluate the performance of AS-GENSENG, we conducted extensive simulations, generated empirical data using existing WGS and WES data sets and validated predicted CNVs using an independent methodology. We conclude that AS-GENSENG not only predicts accurate ASCN calls but also improves the accuracy of total copy number calls, owing to its unique ability to exploit information from both total and allele-specific read counts while accounting for various experimental biases in sequence data. Our novel, user-friendly and computationally efficient method and a complete analytic protocol is freely available at https://sourceforge.net/projects/asgenseng/.

Sequenza: allele-specific copy number and mutation profiles from tumor sequencing data

BackgroundExome or whole-genome deep sequencing of tumor DNA along with paired normal DNA can potentially provide a detailed picture of the somatic mutations that characterize the tumor. However, analysis of such sequence data can be complicated by the presence of normal cells in the tumor specimen, by intratumor heterogeneity, and by the sheer size of the raw data. In particular, determination of copy number variations from exome sequencing data alone has proven difficult; thus, single nucleotide polymorphism (SNP) arrays have often been used for this task. Recently, algorithms to estimate absolute, but not allele-specific, copy number profiles from tumor sequencing data have been described. Materials and methodsWe developed Sequenza, a software package that uses paired tumor-normal DNA sequencing data to estimate tumor cellularity and ploidy, and to calculate allele-specific copy number profiles and mutation profiles. We applied Sequenza, as well as two previously published algorithms, to exome sequence data from 30 tumors from The Cancer Genome Atlas. We assessed the performance of these algorithms by comparing their results with those generated using matched SNP arrays and processed by the allele-specific copy number analysis of tumors (ASCAT) algorithm. ResultsComparison between Sequenza/exome and SNP/ASCAT revealed strong correlation in cellularity (Pearson's r = 0.90) and ploidy estimates (r = 0.42, or r = 0.94 after manual inspecting alternative solutions). This performance was noticeably superior to previously published algorithms. In addition, in artificial data simulating normal-tumor admixtures, Sequenza detected the correct ploidy in samples with tumor content as low as 30%. ConclusionsThe agreement between Sequenza and SNP array-based copy number profiles suggests that exome sequencing alone is sufficient not only for identifying small scale mutations but also for estimating cellularity and inferring DNA copy number aberrations.

Allele-specific copy number profiling by next-generation DNA sequencing.

The progression and clonal development of tumors often involve amplifications and deletions of genomic DNA. Estimation of allele-specific copy number, which quantifies the number of copies of each allele at each variant loci rather than the total number of chromosome copies, is an important step in the characterization of tumor genomes and the inference of their clonal history. We describe a new method, falcon, for finding somatic allele-specific copy number changes by next generation sequencing of tumors with matched normals. falcon is based on a change-point model on a bivariate mixed Binomial process, which explicitly models the copy numbers of the two chromosome haplotypes and corrects for local allele-specific coverage biases. By using the Binomial distribution rather than a normal approximation, falcon more effectively pools evidence from sites with low coverage. A modified Bayesian information criterion is used to guide model selection for determining the number of copy number events. Falcon is evaluated on in silico spike-in data and applied to the analysis of a pre-malignant colon tumor sample and late-stage colorectal adenocarcinoma from the same individual. The allele-specific copy number estimates obtained by falcon allows us to draw detailed conclusions regarding the clonal history of the individual's colon cancer.

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.

A Likelihood-Based Framework for Association Analysis of Allele-Specific Copy Numbers

Copy number variants (CNVs) and single nucleotide polymorphisms (SNPs) coexist throughout the human genome and jointly contribute to phenotypic variations. Thus, it is desirable to consider both types of variants, as characterized by allele-specific copy numbers (ASCNs), in association studies of complex human diseases. Current SNP genotyping technologies capture the CNV and SNP information simultaneously via fluorescent intensity measurements. The common practice of calling ASCNs from the intensity measurements and then using the ASCN calls in downstream association analysis has important limitations. First, the association tests are prone to false-positive findings when differential measurement errors between cases and controls arise from differences in DNA quality or handling. Second, the uncertainties in the ASCN calls are ignored. We present a general framework for the integrated analysis of CNVs and SNPs, including the analysis of total copy numbers as a special case. Our approach combines the ASCN calling and the association analysis into a single step while allowing for differential measurement errors. We construct likelihood functions that properly account for case-control sampling and measurement errors. We establish the asymptotic properties of the maximum likelihood estimators and develop EM algorithms to implement the corresponding inference procedures. The advantages of the proposed methods over the existing ones are demonstrated through realistic simulation studies and an application to a genome-wide association study of schizophrenia. Extensions to next-generation sequencing data are discussed.

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

A Likelihood-Based Framework for Association Analysis of Allele-Specific Copy Numbers

A Likelihood-Based Framework for Association Analysis of Allele-Specific Copy Numbers

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.