Search

Pancreatic cancer, a highly aggressive tumour type with uniformly poor prognosis, exemplifies the classically held view of stepwise cancer development. The current model of tumorigenesis, based on analyses of precursor lesions, termed pancreatic intraepithelial neoplasm (PanINs) lesions, makes two predictions: first, that pancreatic cancer develops through a particular sequence of genetic alterations (KRAS, followed by CDKN2A, then TP53 and SMAD4); and second, that the evolutionary trajectory of pancreatic cancer progression is gradual because each alteration is acquired independently. A shortcoming of this model is that clonally expanded precursor lesions do not always belong to the tumour lineage, indicating that the evolutionary trajectory of the tumour lineage and precursor lesions can be divergent. This prevailing model of tumorigenesis has contributed to the clinical notion that pancreatic cancer evolves slowly and presents at a late stage. However, the propensity for this disease to rapidly metastasize and the inability to improve patient outcomes, despite efforts aimed at early detection, suggest that pancreatic cancer progression is not gradual. Here, using newly developed informatics tools, we tracked changes in DNA copy number and their associated rearrangements in tumour-enriched genomes and found that pancreatic cancer tumorigenesis is neither gradual nor follows the accepted mutation order. Two-thirds of tumours harbour complex rearrangement patterns associated with mitotic errors, consistent with punctuated equilibrium as the principal evolutionary trajectory. In a subset of cases, the consequence of such errors is the simultaneous, rather than sequential, knockout of canonical preneoplastic genetic drivers that are likely to set-off invasive cancer growth. These findings challenge the current progression model of pancreatic cancer and provide insights into the mutational processes that give rise to these aggressive tumours. Funding sources for this study include grants to the Pancreatic Cancer Sequencing Initiative program from the Ontario Institute for Cancer Research (OICR), through support from the Ontario Ministry of Research and Innovation, the Canada Foundation for Innovation; research award to F.N. from the OICR and the Canadian Institutes for Health Research (CIHR); Canadian Friends of the Hebrew University, the SMGS Family Foundation, NCI grant P50 CA102701 (Mayo Clinic SPORE in Pancreatic Cancer) and NCI grant R01 CA97075 (Pancreatic Cancer Genetic Epidemiology Consortium). F.N. is supported by a fellowship award from CIHR and is a recipient of a scholar’s research award from the Ontario Institute of Cancer Research (OICR), through support from the Ontario Ministry of Research and Innovation. G.Z. is a Clinician–Scientist of the Fonds de la Recherche en Sante du Quebec. P.J.C. is a Wellcome Trust Senior Clinical Fellow. T.J.H., L.D.S., J.D.M. and S.G. are recipients of Senior or Clinician–Scientist Awards from the Ontario Institute for Cancer Research

The SK-BR-3 cell line is one of the most important models for HER2+ breast cancers, which affect one in five breast cancer patients. SK-BR-3 is known to be highly rearranged, although much of the variation is in complex and repetitive regions that may be underreported. Addressing this, we sequenced SK-BR-3 using long-read single molecule sequencing from Pacific Biosciences and develop one of the most detailed maps of structural variations (SVs) in a cancer genome available, with nearly 20,000 variants present, most of which were missed by short-read sequencing. Surrounding the important ERBB2 oncogene (also known as HER2), we discover a complex sequence of nested duplications and translocations, suggesting a punctuated progression. Full-length transcriptome sequencing further revealed several novel gene fusions within the nested genomic variants. Combining long-read genome and transcriptome sequencing enables an in-depth analysis of how SVs disrupt the genome and sheds new light on the complex mechanisms involved in cancer genome evolution.

A locus on human chromosome 11q23 tagged by marker rs3802842 was associated with colorectal cancer (CRC) in a genome-wide association study; this finding has been replicated in case-control studies worldwide. In order to identify biologic factors at this locus that are related to the etiopathology of CRC, we used microarray-based target selection methods, coupled to next-generation sequencing, to study 103 kb at the 11q23 locus. We genotyped 369 putative variants from 1,030 patients with CRC (cases) and 1,061 individuals without CRC (controls) from the Ontario Familial Colorectal Cancer Registry. Two previously uncharacterized genes, COLCA1 and COLCA2, were found to be co-regulated genes that are transcribed from opposite strands. Expression levels of COLCA1 and COLCA2 transcripts correlate with rs3802842 genotypes. In colon tissues, COLCA1 co-localizes with crystalloid granules of eosinophils and granular organelles of mast cells, neutrophils, macrophages, dendritic cells and differentiated myeloid-derived cell lines. COLCA2 is present in the cytoplasm of normal epithelial, immune and other cell lineages, as well as tumor cells. Tissue microarray analysis demonstrates the association of rs3802842 with lymphocyte density in the lamina propria (p = 0.014) and levels of COLCA1 in the lamina propria (p = 0.00016) and COLCA2 (tumor cells, p = 0.0041 and lamina propria, p = 6 × 10(-5)). In conclusion, genetic, expression and immunohistochemical data implicate COLCA1 and COLCA2 in the pathogenesis of colon cancer. Histologic analyses indicate the involvement of immune pathways.

Prostate tumours are highly variable in their response to therapies, but clinically available prognostic factors can explain only a fraction of this heterogeneity. Here we analysed 200 whole-genome sequences and 277 additional whole-exome sequences from localized, non-indolent prostate tumours with similar clinical risk profiles, and carried out RNA and methylation analyses in a subset. These tumours had a paucity of clinically actionable single nucleotide variants, unlike those seen in metastatic disease. Rather, a significant proportion of tumours harboured recurrent non-coding aberrations, large-scale genomic rearrangements, and alterations in which an inversion repressed transcription within its boundaries. Local hypermutation events were frequent, and correlated with specific genomic profiles. Numerous molecular aberrations were prognostic for disease recurrence, including several DNA methylation events, and a signature comprised of these aberrations outperformed well-described prognostic biomarkers. We suggest that intensified treatment of genomically aggressive localized prostate cancer may improve cure rates.

Background A comprehensive assessment of the epigenetic dynamics in cancer cells is the key to understanding the molecular mechanisms underlying cancer and to improving cancer diagnostics, prognostics and treatment. By combining genome-wide ChIP-seq epigenomics and microarray transcriptomics, we studied the effects of oxygen deprivation and subsequent reoxygenation on histone 3 trimethylation of lysine 4 (H3K4me3) and lysine 27 (H3K27me3) in a breast cancer cell line, serving as a model for abnormal oxygenation in solid tumors. A priori, epigenetic markings and gene expression levels not only are expected to vary greatly between hypoxic and normoxic conditions, but also display a large degree of heterogeneity across the cell population. Where traditionally ChIP-seq data are often treated as dichotomous data, the model and experiment here necessitate a quantitative, data-driven analysis of both datasets. Results We first identified genomic regions with sustained epigenetic markings, which provided a sample-specific reference enabling quantitative ChIP-seq data analysis. Sustained H3K27me3 marking was located around centromeres and intergenic regions, while sustained H3K4me3 marking is associated with genes involved in RNA binding, translation and protein transport and localization. Dynamic marking with both H3K4me3 and H3K27me3 (hypoxia-induced bivalency) was found in CpG-rich regions at loci encoding factors that control developmental processes, congruent with observations in embryonic stem cells. Conclusions In silico-identified epigenetically sustained and dynamic genomic regions were confirmed through ChIP-PCR in vitro, and obtained results are corroborated by published data and current insights regarding epigenetic regulation. Electronic supplementary material The online version of this article (doi:10.1186/s13072-016-0090-4) contains supplementary material, which is available to authorized users.

Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.

FYSSION is a resource for researchers working on the fission yeast Schizosaccharomyces pombe. It currently comprises libraries of temperature-sensitive mutants in essential genes, and insertional mutants in non-essential genes, available for screening by visiting workers. Here we outline methods for constructing and using the libraries, and describe future prospects for functional genomics of this organism, here and elsewhere.

Background Accurate detection of somatic single nucleotide variants and small insertions and deletions from DNA sequencing experiments of tumour-normal pairs is a challenging task. Tumour samples are often contaminated with normal cells confounding the available evidence for the somatic variants. Furthermore, tumours are heterogeneous so sub-clonal variants are observed at reduced allele frequencies. We present here a cell-line titration series dataset that can be used to evaluate somatic variant calling pipelines with the goal of reliably calling true somatic mutations at low allele frequencies. Results Cell-line DNA was mixed with matched normal DNA at 8 different ratios to generate samples with known tumour cellularities, and exome sequenced on Illumina HiSeq to depths of >300×. The data was processed with several different variant calling pipelines and verification experiments were performed to assay >1500 somatic variant candidates using Ion Torrent PGM as an orthogonal technology. By examining the variants called at varying cellularities and depths of coverage, we show that the best performing pipelines are able to maintain a high level of precision at any cellularity. In addition, we estimate the number of true somatic variants undetected as cellularity and coverage decrease. Conclusions Our cell-line titration series dataset, along with the associated verification results, was effective for this evaluation and will serve as a valuable dataset for future somatic calling algorithm development. The data is available for further analysis at the European Genome-phenome Archive under accession number EGAS00001001016. Data access requires registration through the International Cancer Genome Consortium’s Data Access Compliance Office (ICGC DACO). Electronic supplementary material The online version of this article (doi:10.1186/s13104-015-1803-7) contains supplementary material, which is available to authorized users.

The emergence of next generation DNA sequencing technology is enabling high-resolution cancer genome analysis. Large-scale projects like the International Cancer Genome Consortium (ICGC) are systematically scanning cancer genomes to identify recurrent somatic mutations. Second generation DNA sequencing, however, is still an evolving technology and procedures, both experimental and analytical, are constantly changing. Thus the research community is still defining a set of best practices for cancer genome data analysis, with no single protocol emerging to fulfil this role. Here we describe an extensive benchmark exercise to identify and resolve issues of somatic mutation calling. Whole genome sequence datasets comprising tumor-normal pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, were shared within the ICGC and submissions of somatic mutation calls were compared to verified mutations and to each other. Varying strategies to call mutations, incomplete awareness of sources of artefacts, and even lack of agreement on what constitutes an artefact or real mutation manifested in widely varying mutation call rates and somewhat low concordance among submissions. We conclude that somatic mutation calling remains an unsolved problem. However, we have identified many issues that are easy to remedy that are presented here. Our study highlights critical issues that need to be addressed before this valuable technology can be routinely used to inform clinical decision-making.

As next-generation sequencing becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Through the International Cancer Genome Consortium (ICGC), we compared sequencing pipelines at five independent centers (CNAG, DKFZ, OICR, RIKEN and WTSI) using a single tumor-blood DNA pair. Analyses by each center and with one standardized algorithm revealed significant discrepancies. Although most pipelines performed well for coding mutations, library preparation methods and sequencing coverage metrics clearly influenced downstream results. PCR-free methods showed reduced GC-bias and more even coverage. Increasing sequencing depth to ~100x (two- to three-fold higher than current standards) showed a benefit, as long as the tumor:control coverage ratio remained balanced. To become part of routine clinical care, high-throughput sequencing must be globally compatible and comparable. This benchmarking exercise has highlighted several fundamental parameters to consider in this regard, which will allow for better optimization and planning of both basic and translational studies.

Herein we provide a detailed molecular analysis of the spatial heterogeneity of clinically localized, multifocal prostate cancer to delineate new oncogenes or tumor suppressors. We initially determined the copy number aberration (CNA) profiles of 74 patients with index tumors of Gleason score 7. Of these, 5 patients were subjected to whole-genome sequencing using DNA quantities achievable in diagnostic biopsies, with detailed spatial sampling of 23 distinct tumor regions to assess intraprostatic heterogeneity in focal genomics. Multifocal tumors are highly heterogeneous for single-nucleotide variants (SNVs), CNAs and genomic rearrangements. We identified and validated a new recurrent amplification of MYCL, which is associated with TP53 deletion and unique profiles of DNA damage and transcriptional dysregulation. Moreover, we demonstrate divergent tumor evolution in multifocal cancer and, in some cases, tumors of independent clonal origin. These data represent the first systematic relation of intraprostatic genomic heterogeneity to predicted clinical outcome and inform the development of novel biomarkers that reflect individual prognosis.

Genomic instability is one of the hallmarks of cancer, leading to widespread copy number variations, chromosomal fusions, and other structural variations in many cancers. The breast cancer cell line SK-BR-3 is an important model for HER2+ breast cancers, which are among the most aggressive forms of the disease and affect one in five cases. Through short read sequencing, copy number arrays, and other technologies, the genome of SK-BR-3 is known to be highly rearranged with many copy number variations, including an approximately twenty-fold amplification of the HER2 oncogene, along with numerous other amplifications and deletions. However, these technologies cannot precisely characterize the nature and context of the identified genomic events and other important mutations may be missed altogether because of repeats, multi-mapping reads, and the failure to reliably anchor alignments to both sides of a variation. To address these challenges, we have sequenced SK-BR-3 using PacBio long read technology. Using the new P6-C4 chemistry, we generated more than 70X coverage of the genome with average read lengths of 9-13kb (max: 71kb). Using Lumpy for split-read alignment analysis, as well as our novel assembly-based algorithms for finding complex variants, we have developed a detailed map of structural variations in this cell line. Taking advantage of the newly identified breakpoints and combining these with copy number assignments, we have developed an algorithm to reconstruct the mutational history of this cancer genome. From this we have characterized the amplifications of the HER2 region, discovering a complex series of nested duplications and translocations between chr17 and chr8, two of the most frequent translocation partners in primary breast cancers. We have also carried out full-length transcriptome sequencing using PacBio's Iso-Seq technology, which has revealed a number of previously unrecognized gene fusions and isoforms. Combining long-read genome and transcriptome sequencing technologies enables an in-depth analysis of how changes in the genome affect the transcriptome, including how gene fusions are created across multiple chromosomes. This analysis has established the most complete cancer reference genome available to date, and is already opening the door to applying long-read sequencing to patient samples with complex genome structures. Citation Format: Maria Nattestad, Karen Ng, Sara Goodwin, Timour Baslan, Fritz Sedlazeck, James Gurtowski, Elizabeth Hutton, Yogi Sundaravadanam, Tyler Garvin, Marley Alford, Elizabeth Tseng, Philipp Rescheneder, Jason Chin, Timothy Beck, Melissa Kramer, John McPherson, James Hicks, Michael C. Schatz, William R. McCombie. Comprehensive genome and transcriptome structural analysis of a breast cancer cell line using single molecule sequencing. [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 850.

Pancreatic cancer is the fifth leading cause of cancer-related death with a poor prognosis and 5-year survival rates of less than 5%. As a contributing member of the International Cancer Genome Consortium (ICGC), the Ontario Institute for Cancer Research (OICR) has committed to generating a comprehensive catalogue of genomic abnormalities found in pancreatic ductal adenocarcinomas (PDAC). Using next-generation sequencing technologies, 375 independent pancreatic tumors and their matched controls will be characterized over a 3- to 5-year time span. Many of the samples also have derived matching xenografts and a few have cell lines derived from the xenograft tumors. To date, this project has collected 173 ICGC consented matched samples comprised of 85 PDAC tumor/reference and 21 xenograft/ reference pairs. 32 sample sets have matched tumor/xenograft/reference. In addition, there are 16 cell lines derived from some of these xenografts. Whole-genome and exome target-enrichment sequencing is currently performed using the HiSeq 2000 platform. For efficient variant calling, all whole-genome analyses used a minimal depth of 30x reference and 50x tumor/xeno/cell line and exome analyses used greater than 100x target coverage, with most samples exceeding these targets. Sequence alignment is primarily performed with Novoalign (Novocraft.com) and variants called with the Genome Analysis Toolkit (McKenna et al., Genome Res. 20:1297) to identify germline and somatic variants in all matched sample sets. On average 35 coding non-synonymous variants have been observed per primary tumor exome. Validation of the coding non-synonymous variants is ongoing with data deposited in the ICGC Data Coordinating Center (www.icgc. org). Initial data have been combined with PDAC data sets from the Australian ICGC effort (S. Grimmond and A. Biankin) and from sequencing efforts at the Baylor College of Medicine (R. Gibbs) to increase analytical power. Sequencing of primary tumors and xenografts was complicated by human and mouse stroma, respectively. Complete whole-genome sequencing of the host mouse strain was needed for removal of “interspecies SNP” observed due to alignment of both species to regions of similarity in the human reference sequence. The “SNPs” are falsely identified as somatic variants after subtracting the human germline SNP. Methods are under development to improve this removal process. Current sequencing is focusing on expanding the data set of matched normal and primary tumor pairs. It is anticipated that 150 exome pairs will be sequenced by 4th quarter 2012 with whole-genome sequencing following closely. Continued development of xenograft resources is ongoing in parallel. Whole genome sequences will be generated from selected xenografts. Collectively, the sequence data, xenografts, and cell line models will make a rich resource for studying PDAC. Citation Format: Kimberly N. Begley, Debabrata Mukhopadhyay, Gloria M. Petersen, Alexei Protopopov, Sarah Thayer, Lynda Chin, Emin Ibrahimov, Patricia Shaw, Thomas Hudson, Steve Gallinger, Ming-Sound Tsao, Lincoln Stein, John D. McPherson, Lakshmi Muthuswamy, Timothy Beck, Christina Yung, Michelle Sam, Lee Timms, Carson Holt. The pancreatic ductal adenocarcinoma project at the Ontario Institute for Cancer Research. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Progress and Challenges; Jun 18-21, 2012; Lake Tahoe, NV. Philadelphia (PA): AACR; Cancer Res 2012;72(12 Suppl):Abstract nr A9.

Pancreatic cancer is the fifth leading cause of cancer deaths. Five-year survival rate is In our initial screen, whole-exome sequencing of 33 primary PDAC tumors and matched controls has been performed on the Illumina HiSeq 2000. Sequence alignment and variant calling have been performed using Novoalign and GATK, respectively. After manual review and validation on the Ion Torrent platform, we have identified 648 somatic mutations, 471 of which are non-silent mutations that impact 444 genes. Our results confirm several known mutations in PDAC such as KRAS, p53 and SMAD4. However, their mutation frequencies are lower than expected due to tumor cellularity. We have also screened for copy number alterations (CNAs) using Illumina Omni1-Quad BeadChip. Analysis was performed using Genome Studio, KSseg and PennCNV. In the 33 primary tumors, a median of 90 regions with copy number gain, copy number loss, or copy-neutral LOH have been detected per sample. Median genomic lengths are 19Mb and 20Mb in regions with copy number gain and loss, respectively. Annotation of the altered regions has identified 9152 protein-coding genes, miRNA and non-coding RNA that are altered in 4 or more tumors. To identify the pathways that contribute to PDAC, we have analyzed the genes with somatic mutations or CNAs by means of a functional interaction (FI) network. The FI network consists of curated pathways from Reactome and other databases and a high confidence set of functional interactions predicted by machine learning techniques. A PDAC-specific subnetwork is constructed by projecting the altered genes onto the FI network, and subsequently analyzed by a community clustering algorithm to identify network modules. These modules have been identified as KRAS, p53, TGFβ, Hedgehog, Integrin, Cadherin, Wnt, Rho GTPase and G-protein signaling pathways. While our effort in identifying driver mutations is ongoing, our initial screen has identified candidate genes that will be targeted for deep sequencing in all primary tumors. We will continue to perform whole-exome sequencing of other primary tumors along with xenografts derived from some of the primaries and cell lines derived from some of the xenografts. In addition, whole-genome sequencing of selected specimens is being performed to complement the exome data. The wealth of data will help to characterize the genomic abnormalities in PDAC. Citation Format: Christina K. Yung, Christine Ouellete, Lee Timms, Michelle Sam, Kimberly Begley, Thomas J. Hudson, John D. McPherson, Lincoln D. Stein, Timothy Beck, Lakshmi Muthuswamy, Richard De Borja, Carson Holt, Rob Denroche, Fouad Yousif, Zheng Zha, Niloofar Arshadi. Genomic analysis of pancreatic ductal adenocarcinoma. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Progress and Challenges; Jun 18-21, 2012; Lake Tahoe, NV. Philadelphia (PA): AACR; Cancer Res 2012;72(12 Suppl):Abstract nr B18.

Five to ten percent of pancreatic cancer (PC) clusters within families. Epidemiologic studies suggest that Familial Pancreas Cancer (FPC) is caused by highly penetrant germline mutations, but less than 20% of these genes have been identified. Characterizing the remaining genetic basis of FPC should improve outcomes through molecularly tailored prevention, screening and treatment protocols. Exome sequencing (ES) is a powerful new approach for detecting genetic causes of disease. However, the causal mutation is often indistinguishable from the hundreds of other rare nonsynonymous variants (RNV) detected by germline ES. In general, most familial cancer syndromes are caused by an inherited mutation that inactivates one allele of a tumor suppressor gene (TSG); the somatic inactivation of the second allele, i.e., loss of heterozygosity (LOH), initiates tumourigenesis. To increase the specificity of ES, we combined somatic and germline ES to identify candidate TSG (cTSG) in FPC with germline RNV and LOH. Patients with available snap frozen tumors were selected from the Ontario Pancreas Cancer Study. Histologic inspection of the snap frozen tumors determined their composition to be over 70% pancreatic ductal adenocarcinoma cells. DNA was extracted from snap frozen tumors and peripheral blood. Exomes were enriched using the Agilent ICGC or Illumina TruSeq kits, and sequenced with the Illumina Genome Analyzer IIx. Novoalign aligned sequencing reads, and SAMtools and Picard were used to process them further. The Genome Analysis Tool Kit detected variants. ANNOVAR and custom scripts annotated variants. We defined an RNV as: i) present in less than 0.1% of alleles in the 1000 Genomes Project March 2012 dataset, the NHLBI ESP5400 dataset, and dbSNP135; and ii) a missense, nonsense or splice site single-nucleotide variant, or an exonic indel. cTSG were defined as genes containing a germline heterozygous RNV and a second somatic intragenic RNV. Three FPC probands underwent somatic and germline ES. Over 90% of target bases were covered by at least 10 sequencing reads in all samples. FPC-1 was a 67-year-old male with PC whose maternal aunt and grandmother had PC. FPC-1 carried 1032 germline RNV and 11 somatic RNV. Only 2 somatic RNV were in genes with RNV in 24 PC sequenced by Jones et al. (Jones, Science, 2008). No KRAS or TP53 mutations were detected and no cTSG was identified. FPC-2 was a 55-year-old man with PC whose sister had PC at age 42 and mother also had PC. FPC2 carried 618 germline RNV and 18 somatic RNV. 5 of the somatic RNV were in genes mutated in Jones et al. This patient’s tumour has a KRAS and TP53 mutation. We identified a cTSG that may repress the mobilization of transposable elements. FPC-3 was a 20-yearold woman with PC whose maternal aunt had PC at 59. FPC-3 carried 418 germline RNV and 15 somatic RNV, 1 of which was in genes previously mutated in Jones et al. No mutations in KRAS or TP53 were detected. Here we identified a cTSG that is an ion channel strongly and selectively expressed in the pancreas. We are performing copy number analysis on blood and tumor samples to improve our sensitivity to detect LOH caused by large deletions. We are sequencing the coding region of the two cTSG we identified in 50 unrelated FPC probands to assess their contribution to FPC. These results will be ready for presentation at the AACR PC meeting. We have identified two cTSGs in FPC and characterized the somatic genetic landscape of three FPC, which seem to differ from sporadic PC. Recent studies suggest that FPC is genetically heterogeneous. Our new approach combining somatic and germline ES improves specificity, allowing the identification of causal germline mutations even when a gene is infrequently mutated in FPC. Citation Format: Robert C. Grant, Timothy Beck, Lakshmi Muthuswamy, Ayelet Borgida, Spring Holter, Stefano Serra, John McPherson, Steven Gallinger. Exome sequencing identifies candidate tumor suppressor genes in familial pancreatic cancer. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Progress and Challenges; Jun 18-21, 2012; Lake Tahoe, NV. Philadelphia (PA): AACR; Cancer Res 2012;72(12 Suppl):Abstract nr A15.

Background: Transient leukemia (TL) occurs in 30% of newborns with Down syndrome (DS) and typically resolves spontaneously. Approximately 20% of infants with TL go on to develop acute myeloid leukemia of DS (DS-AML) within the first four years of life. The blasts of both TL and DS-AML harbor somatic mutations of GATA1 . The objective of this study was to identify additional genetic events, which associated with the progression of TL to DS-AML. Methods: Leukemic blasts of TL, DS-AML and normal T lymphocytes were sorted from blood and bone marrow samples of five patients who successively developed both disorders. In addition, blasts of one patient with subsequent relapse of DS-AML were analyzed. Mutational spectrum and gene expression and were determined by exome sequencing and RNASeq (Illumina HiSeq2000). The presence of mutations, which were identified with this approach in DS-AML blasts, was examined by droplet digital PCR in TL blasts (BioRad QX200). Results: Blasts of TL overall harbored fewer mutations than those of DS-AML. Mutations of cohesin and RAS pathway genes were identified in a subset of DS-AML but not TL. In the patient who developed a relapse, different cohesin gene mutations were detected at initial diagnosis of AML and relapse; a minor clone present at initial diagnosis of AML emerged as the predominant clone at relapse. Concordant somatic GATA1 mutations were present in both TL and DS-AML blasts derived from the same patient. In contrast, other genetic events, which were detected in DS-AML blasts by exome sequencing, were confirmed to be absent in TL (by droplet digital PCR). The majority of differentially expressed genes showed higher expression levels in blasts of TL compared to DS-AML. They included genes encoding chemokines and related to IL1 and TGFb signaling. Conclusions: The pathogenic sequence starting with TL and culminating in AML is uniquely initiated in children with DS by somatic mutation of GATA1. In contrast, the events associated with the transformation of TL to DS-AML resemble progression factors also found in non-DS AML. These progression events were not detectable even in minor subclones of TL suggesting they are acquired after the onset of TL. This research was supported by funding from the Canadian Cancer Society Research Institute and Ontario Institute for Cancer Research. Disclosures No relevant conflicts of interest to declare.

Men with localized prostate cancer vary widely in clinical outcome, with a 30-50% failure rate after primary treatment. There is thus significant interest in developing genomically refined prognostic groups. We sought to evaluate the extent of genetic heterogeneity, both between patients (inter-prostate) and within individual prostate glands (intra-prostate) to assess the impact of genetic heterogeneity on risk stratification within a tight clinical cohort. Copy number aberrations (CNAs) from 75 Gleason 7 patients were determined by OncoScan SNP microarrays. We measure the percentage of genome involved in a CNA, termed percent genome aberration (PGA), a proxy for genomic instability. Additionally, whole genome sequencing was applied to 10 intermediate-risk prostate tumours and matched blood, including multiple manually macro-dissected regions from 5 of the prostates (range 2 to 9). Somatic single nucleotide variants (SNVs) and genomic rearrangements (GR) were extracted from each patient. We find a high degree of inter-prostatic heterogeneity between the 75 Gleason 7 patients, with the number of CNAs per patient ranging from 0 to 929, corresponding to PGA 0 to 16.7%. Known prognostic markers can differentiate between patients at higher risk for biochemical recurrence, but only account for a fraction of the cohort. Notably, when these prognostic genes are examined within multiple regions of five independent tumours, they differ in copy number between cancerous regions of the same prostate. For example, TP53 is deleted in 1/2, 1/3, 4/9, 0/4, and 4/5 prostate regions. Indeed, phylogenetic analysis of geographically distinct regions revealed multi-clonal disease in two of the five patients; separate analyses based on SNVs, CNAs, and GRs all concluded that these patient have two genetically distinct cancers within their prostate. We demonstrate dramatic levels of inter- and intra- prostate genetic heterogeneity within pathologically identical or similar cancers. The observed intra-prostatic genomic heterogeneity, both in terms of multi-focal and multi-clonal disease, has critical implications for clinical management. Prognostic information obtained by biopsy may be inconsistent depending on the site of biopsy, and applying personalized medicine to prostate cancer will be challenging. This study highlights the need for further evaluation of how intra-prostatic heterogeneity is related to patient prognosis. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B129. Citation Format: Emilie Lalonde, Paul C. Boutros, Michael Fraser, Richard de Borja, Nicholas J. Harding, Dominique Trudel, Alice Meng, Pablo H. Hennings-Yeomans, Andrew McPherson, Amin Zia, Jianxin Wang, Timothy Beck, Natalie S. Fox, Taryne Chong, Michelle Sam, Jeremy Johns, Lee Timms, Nicholas Buchner, Sohrab Shah, Cenk Sahinalp, Thomas J. Hudson, John D. McPherson, Theodorus van der Kwast, Robert G. Bristow. Clinical implications of inter- and intra- prostatic heterogeneity. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr B129.

Intermediate risk prostate cancer (CaP) with Gleason score (GS) of 7 show up to 100x variability in genetic instability. As CaP is multifocal and likely multiclonal, there is a need to characterize heterogeneity for patient stratification, which would increase the ability to act on genomic information by adding adjuvant therapies to offset systemic occult metastases that currently limit cure in ∼30% of patients. Individual genetic portraits could be used to improve cure on combined clinical-molecular staging criteria. We undertook a pilot study to assess the genetic heterogeneity of potentially curable GS=7 CaP. We selected 10 men with GS=7 CaP; 5 treated with external beam radiotherapy (frozen pre-treatment biopsies) and 5 treated with radical prostatectomy (RadP, frozen tumour). Additionally, DNA from 18 distinct formalin-fixed, paraffin-embedded (FFPE) foci from the 5 RadP were analysed. Each of these 28 foci were subjected to whole-genome sequencing (WGS) and OncoScan SNP arrays to yield comprehensive genetic profiles. mRNA expression was evaluated on frozen RadP by microarray. Germline DNA from whole-blood was also analysed. Following independent pathology reviews and manual macro-dissection of tumour areas of ≥70% cellularity, WGS (≥50x tumour, ≥30x germline) was performed on as little as 50 ng genomic DNA, and OncoScan arrays were performed using as little as 30ng DNA using either amplified or innate genomic DNA. Regions of CaP in FFPE RadP were recorded using a tissue map to identify independent malignant foci, and ERG immunostaining was performed to assist in the identification. In cases where ERG-positive and -negative foci were adjacent, ERG staining was repeated on an un-stained slide to confirm separate foci based on 3D multi-section analyses. ERG fusion status was also assessed in frozen samples by aCGH or IHC. Validation of SNVs via SNP array and deep-resequencing showed ∼99% accuracy. Tumour cellularity was estimated using Qpure and was >60% for all samples. Phylogenetic techniques were used to demonstrate clear multi-clonality in two tumours. Across all tumours, ∼50% of SNVs were specific to an individual tumour-region. Phylogenies were confirmed with both SNVs and CNAs, but CNAs generally exhibited greater concordance amongst different regions of the same tumour. Some previously observed recurrent mutations were previously identified as recurrent in CaP (e.g. SPOP), and the overall mutation rate for intermediate-risk CaP was only somewhat below that reported for castrate-resistant disease (11,230 somatic SNVs per tumour). Our studies support the concept that a complete characterization of inter- and intra-CaP heterogeneity is possible in fresh and archival tissues; the latter is important for correlations to clinical outcome. These approaches can then be streamlined for high-throughput analyses within personalized medicine laboratories leading to “point of care” molecular tests and individualization of therapy. Citation Format: Michael E. Fraser, Richard de Borja, Dominique Trudel, Nicholas J. Harding, Pablo H. Hennings-Yeomans, Alice Meng, Emilie R. Lalonde, Andrew Brown, Natalie S. Fox, Taryne Chong, Amin Zia, Michelle Sam, Jianxin Wang, Michelle A. Chan-Seng-Yue, Jeremy Johns, Lee Timms, Nicholas Buchner, Ada Wong, Fouad Yousif, Rob Denroche, Gaetano Zafarana, Maud HW Starmans, Hanbert Chen, Shaylan Govind, Francis Nguyen, Melania Pintilie, Neil Fleshner, Stanislav Volik, Lakshmi Muthuswamy, Colin C. Collins, Thomas J. Hudson, Lincoln D. Stein, Timothy Beck, John D. McPherson, Theodorus van der Kwast, Paul C. Boutros, Rob G. Bristow. A molecular portrait of potentially curable prostate 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 2003. doi:10.1158/1538-7445.AM2013-2003

Prostate cancer is the most commonly diagnosed malignancy among men in the United States. Due to an aging population, prostate cancer incidence has been increasing, with an estimated 200,000 men being diagnosed in 2010 and more than 32,000 deaths resulting from this disease. Better predictors of patient prognosis and treatment outcome are required to individualize prostate cancer treatment. High-throughput genomic sequence-based approaches offer a unique opportunity to identify biomarkers of disease-progression, thereby enabling more individualized therapy. The Canadian Prostate Cancer Genome Network (CPC-GENE) is an outcomes-based initiative that will sequence 500 specimens from 350 prostate cancer patients over a 5-year time span. Previously, whole genome sequencing efforts from biopsy specimens have been hindered by insufficient quantities of extracted DNA required as input for sequencing library construction. As a proof of concept to demonstrate the ability to sequence low input amounts of DNA from prostate biopsies, whole genome sequencing has been initiated for 50 prostate tumor biopsy samples along with their matched blood-derived reference sample. An on-bead sample preparation protocol was optimized using decreasing quantities of input DNA and used to construct sequencing libraries from as low as 100ng of DNA derived from macrodissected fresh frozen prostate biopsies (>70% cellularity). Sequencing is performed on the Illumina HiSeq 2000 platform to generate coverage depths of 50x for tumor samples and 30x for reference samples. Following alignment using NovoAlign and variant-calling using GATK, we compared our results to genotyping-array results generated using the Affymetrix OncoScan platform. Single-nucleotide variants detected using arrays were validated >99% of the time by sequence data, confirming that the use of a low-input library did not hinder mutation detection. Sequencing does not exhibit significant genome-wide coverage biases, and CNV calls were compared between the genotyping arrays and the next-generation sequencing data. Outcomes from the sequencing and analysis of the initial 50 sample sets will similarly be applied over a 5-year period to characterize an additional 450 prostate specimens. The ability to whole genome sequence specimens where minimal amounts of extracted DNA exist presents new opportunities to sequence many samples previously deemed unusable, while also providing encouraging prospects for whole genome sequencing applications for future studies using biopsy specimens. 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 3184. doi:1538-7445.AM2012-3184

Financial support was provided by the consortium projects READNA under grant agreement FP7 Health-F4- 2008-201418, ESGI under grant agreement 262055, GEUVADIS under grant agreement 261123 of the European Commission Framework Programme 7, ICGC-CLL through the Spanish Ministry of Science and Innovation (MICINN), the Instituto de Salud Carlos III(ISCIII) and the Generalitat de Catalunya, Alioto, T.S., Buchhalter, I., Derdak, S., Hutter, B., Eldridge, M.D., Hovig, E., Heisler, L.E., Beck, T.A., Simpson, J.T., Tonon, L., Sertier, A.-S., Patch, A.-M., Jäger, N., Ginsbach, P., Drews, R., Paramasivam, N., Kabbe, R., Chotewutmontri, S., Diessl, N., Previti, C., Schmidt, S., Brors, B., Feuerbach, L., Heinold, M., Gröbner, S., Korshunov, A., Tarpey, P.S., Butler, A.P., Hinton, J., Jones, D., Menzies, A., Raine, K., Shepherd, R., Stebbings, L., Teague, J.W., Ribeca, P., Giner, F.C., Beltran, S., Raineri, E., Dabad, M., Heath, S.C., Gut, M., Denroche, R.E., Harding, N.J., Yamaguchi, T.N., Fujimoto, A., Nakagawa, H., Quesada, V., Valdés-Mas, R., Nakken, S., Vodák, D., Bower, L., Lynch, A.G., Anderson, C.L., Waddell, N., Pearson, J.V., Grimmond, S.M., Peto, M., Spellman, P., He, M., Kandoth, C., Lee, S., Zhang, J., Létourneau, L., Ma, S., Seth, S., Torrents, D., Xi, L., Wheeler, D.A., López-Otín, C., Campo, E., Campbell, P.J., Boutros, P.C., Puente, X.S., Gerhard, D.S., Pfister, S.M., McPherson, J.D., Hudson, T.J., Schlesner, M., Lichter, P., Eils, R., Jones, D.T.W., Gut, I.G.

International audience; The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumors from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of over 25,000 cancer genomes at the genomic, epigenomic, and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically-relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.