Publications by authors named "Robert E Denroche"

31 Publications

Genomic Features and Classification of Homologous Recombination Deficient Pancreatic Ductal Adenocarcinoma.

Gastroenterology 2021 May 30;160(6):2119-2132.e9. Epub 2021 Jan 30.

PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada; Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Surgery, University of Toronto, Toronto, Ontario, Canada; Hepatobiliary/Pancreatic Surgical Oncology Program, University Health Network, Toronto, Ontario, Canada. Electronic address:

Background And Aims: Homologous recombination deficiency (HRD) in pancreatic ductal adenocarcinoma (PDAC), remains poorly defined beyond germline (g) alterations in BRCA1, BRCA2, and PALB2.

Methods: We interrogated whole genome sequencing (WGS) data on 391 patients, including 49 carriers of pathogenic variants (PVs) in gBRCA and PALB2. HRD classifiers were applied to the dataset and included (1) the genomic instability score (GIS) used by Myriad's MyChoice HRD assay; (2) substitution base signature 3 (SBS3); (3) HRDetect; and (4) structural variant (SV) burden. Clinical outcomes and responses to chemotherapy were correlated with HRD status.

Results: Biallelic tumor inactivation of gBRCA or PALB2 was evident in 43 of 49 germline carriers identifying HRD-PDAC. HRDetect (score ≥0.7) predicted gBRCA1/PALB2 deficiency with highest sensitivity (98%) and specificity (100%). HRD genomic tumor classifiers suggested that 7% to 10% of PDACs that do not harbor gBRCA/PALB2 have features of HRD. Of the somatic HRDetect cases, 69% were attributed to alterations in BRCA1/2, PALB2, RAD51C/D, and XRCC2, and a tandem duplicator phenotype. TP53 loss was more common in BRCA1- compared with BRCA2-associated HRD-PDAC. HRD status was not prognostic in resected PDAC; however in advanced disease the GIS (P = .02), SBS3 (P = .03), and HRDetect score (P = .005) were predictive of platinum response and superior survival. PVs in gATM (n = 6) or gCHEK2 (n = 2) did not result in HRD-PDAC by any of the classifiers. In 4 patients, BRCA2 reversion mutations associated with platinum resistance.

Conclusions: Germline and parallel somatic profiling of PDAC outperforms germline testing alone in identifying HRD-PDAC. An additional 7% to 10% of patients without gBRCA/PALB2 mutations may benefit from DNA damage response agents.
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http://dx.doi.org/10.1053/j.gastro.2021.01.220DOI Listing
May 2021

Subtype-Discordant Pancreatic Ductal Adenocarcinoma Tumors Show Intermediate Clinical and Molecular Characteristics.

Clin Cancer Res 2021 Jan 13;27(1):150-157. Epub 2020 Oct 13.

Pancreas Centre BC, Vancouver, British Columbia, Canada.

Purpose: RNA-sequencing-based subtyping of pancreatic ductal adenocarcinoma (PDAC) has been reported by multiple research groups, each using different methodologies and patient cohorts. "Classical" and "basal-like" PDAC subtypes are associated with survival differences, with basal-like tumors associated with worse prognosis. We amalgamated various PDAC subtyping tools to evaluate the potential of such tools to be reliable in clinical practice.

Experimental Design: Sequencing data for 574 PDAC tumors was obtained from prospective trials and retrospective public databases. Six published PDAC subtyping strategies (Moffitt regression tools, clustering-based Moffitt, Collisson, Bailey, and Karasinska subtypes) were used on each sample, and results were tested for subtype call consistency and association with survival.

Results: Basal-like and classical subtype calls were concordant in 88% of patient samples, and survival outcomes were significantly different ( < 0.05) between prognostic subtypes. Twelve percent of tumors had subtype-discordant calls across the different methods, showing intermediate survival in univariate and multivariate survival analyses. Transcriptional profiles compatible with that of a hybrid subtype signature were observed for subtype-discordant tumors, in which classical and basal-like genes were concomitantly expressed. Subtype-discordant tumors showed intermediate molecular characteristics, including subtyping gene expression ( < 0.0001) and mutant allelic imbalance ( < 0.001).

Conclusions: Nearly 1 in 6 patients with PDAC have tumors that fail to reliably fall into the classical or basal-like PDAC subtype categories, based on two regression tools aimed toward clinical practice. Rather, these patient tumors show intermediate prognostic and molecular traits. We propose close consideration of the non-binary nature of PDAC subtypes for future incorporation of subtyping into clinical practice.
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http://dx.doi.org/10.1158/1078-0432.CCR-20-2831DOI Listing
January 2021

Delving into Early-onset Pancreatic Ductal Adenocarcinoma: How Does Age Fit In?

Clin Cancer Res 2021 Jan 21;27(1):246-254. Epub 2020 Sep 21.

BC Cancer, Vancouver, British Columbia, Canada.

Purpose: With the rising incidence of early-onset pancreatic cancer (EOPC), molecular characteristics that distinguish early-onset pancreatic ductal adenocarcinoma (PDAC) tumors from those arising at a later age are not well understood.

Experimental Design: We performed bioinformatic analysis of genomic and transcriptomic data generated from 269 advanced (metastatic or locally advanced) and 277 resectable PDAC tumor samples. Patient samples were stratified into EOPC (age of onset ≤55 years; = 117), intermediate (age of onset 55-70 years; = 264), and average (age of onset ≥70 years; = 165) groups. Frequency of somatic mutations affecting genes commonly implicated in PDAC, as well as gene expression patterns, were compared between EOPC and all other groups.

Results: EOPC tumors showed significantly lower frequency of somatic single-nucleotide variant (SNV)/insertions/deletions (indel) in ( = 0.0017), and were more likely to achieve biallelic mutation of through homozygous copy loss as opposed to heterozygous copy loss coupled with a loss-of-function SNV/indel mutation, the latter of which was more common for tumors with later ages of onset ( = 1.5e-4). Transcription factor forkhead box protein C2 () was significantly upregulated in EOPC tumors ( = 0.032). Genes significantly correlated with in PDAC samples were enriched for gene sets related to epithelial-to-mesenchymal transition (EMT) and included ( = 1.8e-8), ( = 6.5e-5), and ( = 2.4e-2).

Conclusions: Our comprehensive analysis of sequencing data generated from a large cohort of PDAC patient samples highlights a distinctive pattern of biallelic mutation in EOPC tumors. Increased expression of in EOPC, with the correlation between and EMT pathways, represents novel molecular characteristics of EOPC..
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http://dx.doi.org/10.1158/1078-0432.CCR-20-1042DOI Listing
January 2021

A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination-deficient Pancreatic Cancer.

Clin Cancer Res 2020 10 14;26(20):5462-5476. Epub 2020 Aug 14.

Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.

Purpose: Pancreatic ductal adenocarcinoma (PDAC) arising in patients with a germline or (g) mutation may be sensitive to platinum and PARP inhibitors (PARPi). However, treatment stratification based on g mutational status alone is associated with heterogeneous responses.

Experimental Design: We performed a seven-arm preclinical trial consisting of 471 mice, representing 12 unique PDAC patient-derived xenografts, of which nine were g mutated. From 179 patients whose PDAC was whole-genome and transcriptome sequenced, we identified 21 cases with homologous recombination deficiency (HRD), and investigated prognostic biomarkers.

Results: We found that biallelic inactivation of / is associated with genomic hallmarks of HRD and required for cisplatin and talazoparib (PARPi) sensitivity. However, HRD genomic hallmarks persisted in xenografts despite the emergence of therapy resistance, indicating the presence of a genomic scar. We identified tumor polyploidy and a low Ki67 index as predictors of poor cisplatin and talazoparib response. In patients with HRD PDAC, tumor polyploidy and a basal-like transcriptomic subtype were independent predictors of shorter survival. To facilitate clinical assignment of transcriptomic subtype, we developed a novel pragmatic two-marker assay (GATA6:KRT17).

Conclusions: In summary, we propose a predictive and prognostic model of g-mutated PDAC on the basis of HRD genomic hallmarks, Ki67 index, tumor ploidy, and transcriptomic subtype.
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http://dx.doi.org/10.1158/1078-0432.CCR-20-1439DOI Listing
October 2020

Endogenous Retrovirus Transcript Levels Are Associated with Immunogenic Signatures in Multiple Metastatic Cancer Types.

Mol Cancer Ther 2020 09 9;19(9):1889-1897. Epub 2020 Jun 9.

Pancreas Centre BC, Vancouver, British Columbia, Canada.

Next-generation sequencing of solid tumors has revealed variable signatures of immunogenicity across tumors, but underlying molecular characteristics driving such variation are not fully understood. Although expression of endogenous retrovirus (ERV)-containing transcripts can provide a source of tumor-specific neoantigen in some cancer models, associations between ERV levels and immunogenicity across different types of metastatic cancer are not well established. We performed bioinformatics analysis of genomic, transcriptomic, and clinical data across an integrated cohort of 199 patients with metastatic breast, colorectal, and pancreatic ductal adenocarcinoma tumors. Within each cancer type, we identified a subgroup of viral mimicry tumors in which increased ERV levels were coupled with transcriptional signatures of autonomous antiviral response and immunogenicity. In addition, viral mimicry colorectal and pancreatic tumors showed increased expression of DNA demethylation gene Taken together, these data demonstrate the existence of an ERV-associated viral mimicry phenotype across three distinct metastatic cancer types, while indicating links between ERV abundance, epigenetic dysregulation, and immunogenicity.
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http://dx.doi.org/10.1158/1535-7163.MCT-20-0094DOI Listing
September 2020

GATA6 Expression Distinguishes Classical and Basal-like Subtypes in Advanced Pancreatic Cancer.

Clin Cancer Res 2020 09 10;26(18):4901-4910. Epub 2020 Mar 10.

Division of Pathology, University Health Network, Toronto, Ontario, Canada.

Purpose: To determine the impact of basal-like and classical subtypes in advanced pancreatic ductal adenocarcinoma (PDAC) and to explore GATA6 expression as a surrogate biomarker.

Experimental Design: Within the COMPASS trial, patients proceeding to chemotherapy for advanced PDAC undergo tumor biopsy for RNA-sequencing (RNA-seq). Overall response rate (ORR) and overall survival (OS) were stratified by subtypes and according to chemotherapy received. Correlation of with the subtypes using gene expression profiling, hybridization (ISH) was explored.

Results: Between December 2015 and May 2019, 195 patients (95%) had enough tissue for RNA-seq; 39 (20%) were classified as basal-like and 156 (80%) as classical. RECIST response data were available for 157 patients; 29 basal-like and 128 classical where the ORR was 10% versus 33%, respectively ( = 0.02). In patients with basal-like tumors treated with modified FOLFIRINOX ( = 22), the progression rate was 60% compared with 15% in classical PDAC ( = 0.0002). Median OS in the intention-to-treat population ( = 195) was 9.3 months for classical versus 5.9 months for basal-like PDAC (HR, 0.47; 95% confidence interval, 0.32-0.69; = 0.0001). expression by RNA-seq highly correlated with the classifier ( < 0.001) and ISH predicted the subtypes with sensitivity of 89% and specificity of 83%. In a multivariate analysis, GATA6 expression was prognostic ( = 0.02). In exploratory analyses, basal-like tumors, could be identified by keratin 5, were more hypoxic and enriched for a T-cell-inflamed gene expression signature.

Conclusions: The basal-like subtype is chemoresistant and can be distinguished from classical PDAC by GATA6 expression..
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http://dx.doi.org/10.1158/1078-0432.CCR-19-3724DOI Listing
September 2020

A Four-Chemokine Signature Is Associated with a T-cell-Inflamed Phenotype in Primary and Metastatic Pancreatic Cancer.

Clin Cancer Res 2020 04 21;26(8):1997-2010. Epub 2020 Jan 21.

The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada.

Purpose: The molecular drivers of antitumor immunity in pancreatic ductal adenocarcinoma (PDAC) are poorly understood, posing a major obstacle for the identification of patients potentially amenable for immune-checkpoint blockade or other novel strategies. Here, we explore the association of chemokine expression with effector T-cell infiltration in PDAC.

Experimental Design: Discovery cohorts comprised 113 primary resected PDAC and 107 PDAC liver metastases. Validation cohorts comprised 182 PDAC from The Cancer Genome Atlas and 92 PDACs from the Australian International Cancer Genome Consortium. We explored associations between immune cell counts by immunohistochemistry, chemokine expression, and transcriptional hallmarks of antitumor immunity by RNA sequencing (RNA-seq), and mutational burden by whole-genome sequencing.

Results: Among all known human chemokines, a coregulated set of four (, and ) was strongly associated with CD8 T-cell infiltration ( < 0.001). Expression of this "4-chemokine signature" positively correlated with transcriptional metrics of T-cell activation (, and ), cytolytic activity ( and ), and immunosuppression (, and ). Furthermore, the 4-chemokine signature marked tumors with increased T-cell activation scores (MHC I presentation, T-cell/APC costimulation) and elevated expression of innate immune sensing pathways involved in T-cell priming (STING and NLRP3 inflammasome pathways, BATF3-driven dendritic cells). Importantly, expression of this 4-chemokine signature was consistently indicative of a T-cell-inflamed phenotype across primary PDAC and PDAC liver metastases.

Conclusions: A conserved 4-chemokine signature marks resectable and metastatic PDAC tumors with an active antitumor phenotype. This could have implications for the appropriate selection of PDAC patients in immunotherapy trials.
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http://dx.doi.org/10.1158/1078-0432.CCR-19-2803DOI Listing
April 2020

Transcription phenotypes of pancreatic cancer are driven by genomic events during tumor evolution.

Nat Genet 2020 02 13;52(2):231-240. Epub 2020 Jan 13.

Canada's Michael Smith Genome Sciences Centre, Vancouver, British Columbia, Canada.

Pancreatic adenocarcinoma presents as a spectrum of a highly aggressive disease in patients. The basis of this disease heterogeneity has proved difficult to resolve due to poor tumor cellularity and extensive genomic instability. To address this, a dataset of whole genomes and transcriptomes was generated from purified epithelium of primary and metastatic tumors. Transcriptome analysis demonstrated that molecular subtypes are a product of a gene expression continuum driven by a mixture of intratumoral subpopulations, which was confirmed by single-cell analysis. Integrated whole-genome analysis uncovered that molecular subtypes are linked to specific copy number aberrations in genes such as mutant KRAS and GATA6. By mapping tumor genetic histories, tetraploidization emerged as a key mutational process behind these events. Taken together, these data support the premise that the constellation of genomic aberrations in the tumor gives rise to the molecular subtype, and that disease heterogeneity is due to ongoing genomic instability during progression.
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http://dx.doi.org/10.1038/s41588-019-0566-9DOI Listing
February 2020

Altered Gene Expression along the Glycolysis-Cholesterol Synthesis Axis Is Associated with Outcome in Pancreatic Cancer.

Clin Cancer Res 2020 01 3;26(1):135-146. Epub 2019 Sep 3.

Pancreas Centre BC, Vancouver, British Columbia, Canada.

Purpose: Identification of clinically actionable molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) is key to improving patient outcome. Intertumoral metabolic heterogeneity contributes to cancer survival and the balance between distinct metabolic pathways may influence PDAC outcome. We hypothesized that PDAC can be stratified into prognostic metabolic subgroups based on alterations in the expression of genes involved in glycolysis and cholesterol synthesis.

Experimental Design: We performed bioinformatics analysis of genomic, transcriptomic, and clinical data in an integrated cohort of 325 resectable and nonresectable PDAC. The resectable datasets included retrospective The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) cohorts. The nonresectable PDAC cohort studies included prospective COMPASS, PanGen, and BC Cancer Personalized OncoGenomics program (POG).

Results: On the basis of the median normalized expression of glycolytic and cholesterogenic genes, four subgroups were identified: quiescent, glycolytic, cholesterogenic, and mixed. Glycolytic tumors were associated with the shortest median survival in resectable (log-rank test = 0.018) and metastatic settings (log-rank test = 0.027). Patients with cholesterogenic tumors had the longest median survival. and -amplified tumors had higher expression of glycolytic genes than tumors with normal or lost copies of the oncogenes (Wilcoxon rank sum test = 0.015). Glycolytic tumors had the lowest expression of mitochondrial pyruvate carriers and . Glycolytic and cholesterogenic gene expression correlated with the expression of prognostic PDAC subtype classifier genes.

Conclusions: Metabolic classification specific to glycolytic and cholesterogenic pathways provides novel biological insight into previously established PDAC subtypes and may help develop personalized therapies targeting unique tumor metabolic profiles..
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http://dx.doi.org/10.1158/1078-0432.CCR-19-1543DOI Listing
January 2020

Meta-Analysis of 1,200 Transcriptomic Profiles Identifies a Prognostic Model for Pancreatic Ductal Adenocarcinoma.

JCO Clin Cancer Inform 2019 05;3:1-16

University Health Network, Toronto, Ontario, Canada.

Purpose: With a dismal 8% median 5-year overall survival, pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy. Only 10% to 20% of patients are eligible for surgery, and more than 50% of these patients will die within 1 year of surgery. Building a molecular predictor of early death would enable the selection of patients with PDAC who are at high risk.

Materials And Methods: We developed the Pancreatic Cancer Overall Survival Predictor (PCOSP), a prognostic model built from a unique set of 89 PDAC tumors in which gene expression was profiled using both microarray and sequencing platforms. We used a meta-analysis framework that was based on the binary gene pair method to create gene expression barcodes that were robust to biases arising from heterogeneous profiling platforms and batch effects. Leveraging the largest compendium of PDAC transcriptomic data sets to date, we show that PCOSP is a robust single-sample predictor of early death-1 year or less-after surgery in a subset of 823 samples with available transcriptomics and survival data.

Results: The PCOSP model was strongly and significantly prognostic, with a meta-estimate of the area under the receiver operating curve of 0.70 ( = 2.6E-22) and d-index (robust hazard ratio) of 1.9 (range, 1.6 to 2.3; ( = 1.4E-04) for binary and survival predictions, respectively. The prognostic value of PCOSP was independent of clinicopathologic parameters and molecular subtypes. Over-representation analysis of the PCOSP 2,619 gene pairs-1,070 unique genes-unveiled pathways associated with Hedgehog signaling, epithelial-mesenchymal transition, and extracellular matrix signaling.

Conclusion: PCOSP could improve treatment decisions by identifying patients who will not benefit from standard surgery/chemotherapy but who may benefit from a more aggressive treatment approach or enrollment in a clinical trial.
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http://dx.doi.org/10.1200/CCI.18.00102DOI Listing
May 2019

Gene Fusions Are Recurrent, Clinically Actionable Gene Rearrangements in Wild-Type Pancreatic Ductal Adenocarcinoma.

Clin Cancer Res 2019 Aug 8;25(15):4674-4681. Epub 2019 May 8.

Pancreas Centre British Columbia, Vancouver, Canada.

Purpose: Gene fusions involving neuregulin 1 () have been noted in multiple cancer types and have potential therapeutic implications. Although varying results have been reported in other cancer types, the efficacy of the HER-family kinase inhibitor afatinib in the treatment of fusion-positive pancreatic ductal adenocarcinoma is not fully understood.

Experimental Design: Forty-seven patients with pancreatic ductal adenocarcinoma received comprehensive whole-genome and transcriptome sequencing and analysis. Two patients with gene fusions involving received afatinib treatment, with response measured by pretreatment and posttreatment PET/CT imaging.

Results: Three of 47 (6%) patients with advanced pancreatic ductal adenocarcinoma were identified as wild type by whole-genome sequencing. All wild-type tumors were positive for gene fusions involving the ERBB3 ligand . Two of 3 patients with fusion-positive tumors were treated with afatinib and demonstrated a significant and rapid response while on therapy.

Conclusions: This work adds to a growing body of evidence that gene fusions are recurrent, therapeutically actionable genomic events in pancreatic cancers. Based on the clinical outcomes described here, patients with wild-type tumors harboring gene fusions may benefit from treatment with afatinib..
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http://dx.doi.org/10.1158/1078-0432.CCR-19-0191DOI Listing
August 2019

Integration of Genomic and Transcriptional Features in Pancreatic Cancer Reveals Increased Cell Cycle Progression in Metastases.

Cancer Cell 2019 02 24;35(2):267-282.e7. Epub 2019 Jan 24.

Mayo Clinic College of Medicine, Rochester, MN 55905, USA.

We integrated clinical, genomic, and transcriptomic data from 224 primaries and 95 metastases from 289 patients to characterize progression of pancreatic ductal adenocarcinoma (PDAC). Driver gene alterations and mutational and expression-based signatures were preserved, with truncations, inversions, and translocations most conserved. Cell cycle progression (CCP) increased with sequential inactivation of tumor suppressors, yet remained higher in metastases, perhaps driven by cell cycle regulatory gene variants. Half of the cases were hypoxic by expression markers, overlapping with molecular subtypes. Paired tumor heterogeneity showed cancer cell migration by Halstedian progression. Multiple PDACs arising synchronously and metachronously in the same pancreas were actually intra-parenchymal metastases, not independent primary tumors. Established clinical co-variates dominated survival analyses, although CCP and hypoxia may inform clinical practice.
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http://dx.doi.org/10.1016/j.ccell.2018.12.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6398439PMC
February 2019

Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer.

PLoS Comput Biol 2019 01 10;15(1):e1006596. Epub 2019 Jan 10.

PanCuRx Translational Research Initiative, Ontario Institute of Cancer Research (OICR), Toronto, Ontario, Canada.

Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis among solid malignancies and improved therapeutic strategies are needed to improve outcomes. Patient-derived xenografts (PDX) and patient-derived organoids (PDO) serve as promising tools to identify new drugs with therapeutic potential in PDAC. For these preclinical disease models to be effective, they should both recapitulate the molecular heterogeneity of PDAC and validate patient-specific therapeutic sensitivities. To date however, deep characterization of the molecular heterogeneity of PDAC PDX and PDO models and comparison with matched human tumour remains largely unaddressed at the whole genome level. We conducted a comprehensive assessment of the genetic landscape of 16 whole-genome pairs of tumours and matched PDX, from primary PDAC and liver metastasis, including a unique cohort of 5 'trios' of matched primary tumour, PDX, and PDO. We developed a pipeline to score concordance between PDAC models and their paired human tumours for genomic events, including mutations, structural variations, and copy number variations. Tumour-model comparisons of mutations displayed single-gene concordance across major PDAC driver genes, but relatively poor agreement across the greater mutational load. Genome-wide and chromosome-centric analysis of structural variation (SV) events highlights previously unrecognized concordance across chromosomes that demonstrate clustered SV events. We found that polyploidy presented a major challenge when assessing copy number changes; however, ploidy-corrected copy number states suggest good agreement between donor-model pairs. Collectively, our investigations highlight that while PDXs and PDOs may serve as tractable and transplantable systems for probing the molecular properties of PDAC, these models may best serve selective analyses across different levels of genomic complexity.
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http://dx.doi.org/10.1371/journal.pcbi.1006596DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328084PMC
January 2019

Organoid Profiling Identifies Common Responders to Chemotherapy in Pancreatic Cancer.

Cancer Discov 2018 09 31;8(9):1112-1129. Epub 2018 May 31.

Memorial Sloan Kettering Cancer Center, New York, New York.

Pancreatic cancer is the most lethal common solid malignancy. Systemic therapies are often ineffective, and predictive biomarkers to guide treatment are urgently needed. We generated a pancreatic cancer patient-derived organoid (PDO) library that recapitulates the mutational spectrum and transcriptional subtypes of primary pancreatic cancer. New driver oncogenes were nominated and transcriptomic analyses revealed unique clusters. PDOs exhibited heterogeneous responses to standard-of-care chemotherapeutics and investigational agents. In a case study manner, we found that PDO therapeutic profiles paralleled patient outcomes and that PDOs enabled longitudinal assessment of chemosensitivity and evaluation of synchronous metastases. We derived organoid-based gene expression signatures of chemosensitivity that predicted improved responses for many patients to chemotherapy in both the adjuvant and advanced disease settings. Finally, we nominated alternative treatment strategies for chemorefractory PDOs using targeted agent therapeutic profiling. We propose that combined molecular and therapeutic profiling of PDOs may predict clinical response and enable prospective therapeutic selection. New approaches to prioritize treatment strategies are urgently needed to improve survival and quality of life for patients with pancreatic cancer. Combined genomic, transcriptomic, and therapeutic profiling of PDOs can identify molecular and functional subtypes of pancreatic cancer, predict therapeutic responses, and facilitate precision medicine for patients with pancreatic cancer. .
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http://dx.doi.org/10.1158/2159-8290.CD-18-0349DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6125219PMC
September 2018

Recapitulating the clinical scenario of BRCA-associated pancreatic cancer in pre-clinical models.

Int J Cancer 2018 07 23;143(1):179-183. Epub 2018 Feb 23.

Oncology Institute, Sheba Medical Center, Tel Hashomer, Israel.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. BRCA-associated PDAC comprises a clinically relevant subtype. A portion of these patients are highly susceptible to DNA damaging therapeutics, however, responses are heterogeneous and clinical resistance evolves. We have developed unique patient-derived xenograft (PDX) models from metastatic lesions of germline BRCA-mutated patients obtained at distinct time points; before treatment and at progression. Thus, closely mimicking clinical scenarios, to further investigate treatment naïve and resistant patients. DNA was isolated from six BRCA-mutated PDXs and classified by whole-genome sequencing to stable-genome or homologous recombination deficient (HRD)-genome. The sensitivity to DNA-damaging agents was evaluated in vivo in three BRCA-associated PDAC PDXs models: (1) HRD-genome naïve to treatments; (2) stable-genome naïve to treatment; (3) HRD-genome resistant to treatment. Correlation between disease course at tissue acquisition and response to PARP inhibitor (PARPi)/platinum was demonstrated in PDXs in vivo. Only the HRD-genome PDX, naïve to treatment, was sensitive to PARP inhibitor/cisplatin treatments. Our results demonstrate heterogeneous responses to DNA damaging agents/PARPi in BRCA-associated PDX thus reflecting the wide clinical spectrum. An HRD-genome PDX generated from a naïve to treatment biopsy was sensitive to platinum/PARPi whereas no benefit was observed in treating a HRD-genome PDXs generated from a patient that had acquired resistance nor stable-genome PDXs.
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http://dx.doi.org/10.1002/ijc.31292DOI Listing
July 2018

Mutations in Mitochondrial DNA From Pancreatic Ductal Adenocarcinomas Associate With Survival Times of Patients and Accumulate as Tumors Progress.

Gastroenterology 2018 05 29;154(6):1620-1624.e5. Epub 2018 Mar 29.

Informatics Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Department of Pharmacology and Toxicology, University of Toronto, Toronto, Canada. Electronic address:

Somatic mutations have been found in the mitochondria in different types of cancer cells, but it is not clear whether these affect tumorigenesis or tumor progression. We analyzed mitochondrial genomes of 268 early-stage, resected pancreatic ductal adenocarcinoma tissues and paired non-tumor tissues. We defined a mitochondrial somatic mutation (mtSNV) as a position where the difference in heteroplasmy fraction between tumor and normal sample was ≥0.2. Our analysis identified 304 mtSNVs, with at least 1 mtSNV in 61% (164 of 268) of tumor samples. The noncoding control region had the greatest proportion of mtSNVs (60 of 304 mutations); this region contains sites that regulate mitochondrial DNA transcription and replication. Frequently mutated genes included ND5, RNR2, and CO1, plus 29 mutations in transfer RNA genes. mtSNVs in 2 separate mitochondrial genes (ND4 and ND6) were associated with shorter overall survival time. This association appeared to depend on the level of mtSNV heteroplasmy. Non-random co-occurrence between mtSNVs and mutations in nuclear genes indicates interactions between nuclear and mitochondrial DNA. In an analysis of primary tumors and metastases from 6 patients, we found tumors to accumulate mitochondrial mutational mutations as they progress.
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http://dx.doi.org/10.1053/j.gastro.2018.01.029DOI Listing
May 2018

Genomics-Driven Precision Medicine for Advanced Pancreatic Cancer: Early Results from the COMPASS Trial.

Clin Cancer Res 2018 03 29;24(6):1344-1354. Epub 2017 Dec 29.

PanCuRx Translational Research Initiative, Ontario, Institute for Cancer Research, Toronto, Ontario, Canada.

To perform real-time whole genome sequencing (WGS) and RNA sequencing (RNASeq) of advanced pancreatic ductal adenocarcinoma (PDAC) to identify predictive mutational and transcriptional features for better treatment selection. Patients with advanced PDAC were prospectively recruited prior to first-line combination chemotherapy. Fresh tumor tissue was acquired by image-guided percutaneous core biopsy for WGS and RNASeq. Laser capture microdissection was performed for all cases. Primary endpoint was feasibility to report WGS results prior to first disease assessment CT scan at 8 weeks. The main secondary endpoint was discovery of patient subsets with predictive mutational and transcriptional signatures. Sixty-three patients underwent a tumor biopsy between December 2015 and June 2017. WGS and RNASeq were successful in 62 (98%) and 60 (95%), respectively. Genomic results were reported at a median of 35 days (range, 19-52 days) from biopsy, meeting the primary feasibility endpoint. Objective responses to first-line chemotherapy were significantly better in patients with the classical PDAC RNA subtype compared with those with the basal-like subtype ( = 0.004). The best progression-free survival was observed in those with classical subtype treated with m-FOLFIRINOX. expression in tumor measured by RNA hybridization was found to be a robust surrogate biomarker for differentiating classical and basal-like PDAC subtypes. Potentially actionable genetic alterations were found in 30% of patients. Prospective genomic profiling of advanced PDAC is feasible, and our early data indicate that chemotherapy response differs among patients with different genomic/transcriptomic subtypes. .
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http://dx.doi.org/10.1158/1078-0432.CCR-17-2994DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5968824PMC
March 2018

Exome-Wide Association Study of Pancreatic Cancer Risk.

Gastroenterology 2018 02 24;154(3):719-722.e3. Epub 2017 Oct 24.

Ontario Institute for Cancer Research, Toronto, Canada; Ontario Pancreas Cancer Study, Toronto, Canada. Electronic address:

We conducted a case-control exome-wide association study to discover germline variants in coding regions that affect risk for pancreatic cancer, combining data from 5 studies. We analyzed exome and genome sequencing data from 437 patients with pancreatic cancer (cases) and 1922 individuals not known to have cancer (controls). In the primary analysis, BRCA2 had the strongest enrichment for rare inactivating variants (17/437 cases vs 3/1922 controls) (P = 3.27x10; exome-wide statistical significance threshold P < 2.5x10). Cases had more rare inactivating variants in DNA repair genes than controls, even after excluding 13 genes known to predispose to pancreatic cancer (adjusted odds ratio, 1.35; P = .045). At the suggestive threshold (P < .001), 6 genes were enriched for rare damaging variants (UHMK1, AP1G2, DNTA, CHST6, FGFR3, and EPHA1) and 7 genes had associations with pancreatic cancer risk, based on the sequence-kernel association test. We confirmed variants in BRCA2 as the most common high-penetrant genetic factor associated with pancreatic cancer and we also identified candidate pancreatic cancer genes. Large collaborations and novel approaches are needed to overcome the genetic heterogeneity of pancreatic cancer predisposition.
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http://dx.doi.org/10.1053/j.gastro.2017.10.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5811358PMC
February 2018

Pancreatic cancer ascites xenograft-an expeditious model mirroring advanced therapeutic resistant disease.

Oncotarget 2017 Jun;8(25):40778-40790

Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Pancreatic ductal adenocarcinoma has limited treatment options. There is an urgent need for developing appropriate pre-clinical models recapitulating metastatic disease, the most common clinical scenario at presentation. Ascites accumulation occurs in up to 20-30% of patients with pancreatic cancer; this milieu represents a highly cellular research resource of metastatic peritoneal spread. In this study, we utilized pancreatic ascites/pleural effusion cancer cells to establish patient derived xenografts.Ascites/pleural effusion-patient derived xenografts were established from twelve independent cases. Xenografts were serially passed in nude mice and tissue bio-specimen banking has been established. Histopathology of emergent tumors demonstrates poorly to moderately differentiated, glandular and mucin producing tumors, mirroring morphology of primary pancreatic cancer tumors. Whole genome sequencing of six patient derived xenografts samples demonstrates common mutations and structural variations similar to those reported in primary pancreatic cancer. Xenograft tumors were dissociated to single-cells and in-vitro drug sensitivity screen assays demonstrated chemo-resistance, correlating with patient clinical scenarios, thus serving as a platform for clinically relevant translational research.Therefore, establishment of this novel ascites/pleural effusion patient derived xenograft model, with extensive histopathology and genomic characterization, opens an opportunity for the study of advanced aggressive pancreatic cancer. Characterization of metastatic disease and mechanisms of resistance to therapeutics may lead to the development of novel drug combinations.
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http://dx.doi.org/10.18632/oncotarget.17253DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5522335PMC
June 2017

Genomic hallmarks of localized, non-indolent prostate cancer.

Nature 2017 01 9;541(7637):359-364. Epub 2017 Jan 9.

Genome Technologies Program, Ontario Institute for Cancer Research, Toronto, Canada.

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.
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http://dx.doi.org/10.1038/nature20788DOI Listing
January 2017

Association of Distinct Mutational Signatures With Correlates of Increased Immune Activity in Pancreatic Ductal Adenocarcinoma.

JAMA Oncol 2017 Jun;3(6):774-783

PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.

Importance: Outcomes for patients with pancreatic ductal adenocarcinoma (PDAC) remain poor. Advances in next-generation sequencing provide a route to therapeutic approaches, and integrating DNA and RNA analysis with clinicopathologic data may be a crucial step toward personalized treatment strategies for this disease.

Objective: To classify PDAC according to distinct mutational processes, and explore their clinical significance.

Design, Setting, And Participants: We performed a retrospective cohort study of resected PDAC, using cases collected between 2008 and 2015 as part of the International Cancer Genome Consortium. The discovery cohort comprised 160 PDAC cases from 154 patients (148 primary; 12 metastases) that underwent tumor enrichment prior to whole-genome and RNA sequencing. The replication cohort comprised 95 primary PDAC cases that underwent whole-genome sequencing and expression microarray on bulk biospecimens.

Main Outcomes And Measures: Somatic mutations accumulate from sequence-specific processes creating signatures detectable by DNA sequencing. Using nonnegative matrix factorization, we measured the contribution of each signature to carcinogenesis, and used hierarchical clustering to subtype each cohort. We examined expression of antitumor immunity genes across subtypes to uncover biomarkers predictive of response to systemic therapies.

Results: The discovery cohort was 53% male (n = 79) and had a median age of 67 (interquartile range, 58-74) years. The replication cohort was 50% male (n = 48) and had a median age of 68 (interquartile range, 60-75) years. Five predominant mutational subtypes were identified that clustered PDAC into 4 major subtypes: age related, double-strand break repair, mismatch repair, and 1 with unknown etiology (signature 8). These were replicated and validated. Signatures were faithfully propagated from primaries to matched metastases, implying their stability during carcinogenesis. Twelve of 27 (45%) double-strand break repair cases lacked germline or somatic events in canonical homologous recombination genes-BRCA1, BRCA2, or PALB2. Double-strand break repair and mismatch repair subtypes were associated with increased expression of antitumor immunity, including activation of CD8-positive T lymphocytes (GZMA and PRF1) and overexpression of regulatory molecules (cytotoxic T-lymphocyte antigen 4, programmed cell death 1, and indolamine 2,3-dioxygenase 1), corresponding to higher frequency of somatic mutations and tumor-specific neoantigens.

Conclusions And Relevance: Signature-based subtyping may guide personalized therapy of PDAC in the context of biomarker-driven prospective trials.
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http://dx.doi.org/10.1001/jamaoncol.2016.3916DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5824324PMC
June 2017

A renewed model of pancreatic cancer evolution based on genomic rearrangement patterns.

Nature 2016 Oct 12;538(7625):378-382. Epub 2016 Oct 12.

Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55905, USA.

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.
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http://dx.doi.org/10.1038/nature19823DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5446075PMC
October 2016

A cancer cell-line titration series for evaluating somatic classification.

BMC Res Notes 2015 Dec 26;8:823. Epub 2015 Dec 26.

Ontario Institute for Cancer Research, Toronto, ON, Canada.

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).
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http://dx.doi.org/10.1186/s13104-015-1803-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4691534PMC
December 2015

A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing.

Nat Commun 2015 Dec 9;6:10001. Epub 2015 Dec 9.

Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK.

As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼ 100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.
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http://dx.doi.org/10.1038/ncomms10001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682041PMC
December 2015

Fine mapping of chromosome 5p15.33 based on a targeted deep sequencing and high density genotyping identifies novel lung cancer susceptibility loci.

Carcinogenesis 2016 Jan 20;37(1):96-105. Epub 2015 Nov 20.

Division of Cancer Epidemiology and Genetics , National Cancer Institute , National Institutes of Health , Department of Health and Human Services , Bethesda , MD 20892 , USA.

Chromosome 5p15.33 has been identified as a lung cancer susceptibility locus, however the underlying causal mechanisms were not fully elucidated. Previous fine-mapping studies of this locus have relied on imputation or investigated a small number of known, common variants. This study represents a significant advance over previous research by investigating a large number of novel, rare variants, as well as their underlying mechanisms through telomere length. Variants for this fine-mapping study were identified through a targeted deep sequencing (average depth of coverage greater than 4000×) of 576 individuals. Subsequently, 4652 SNPs, including 1108 novel SNPs, were genotyped in 5164 cases and 5716 controls of European ancestry. After adjusting for known risk loci, rs2736100 and rs401681, we identified a new, independent lung cancer susceptibility variant in LPCAT1: rs139852726 (OR = 0.46, P = 4.73×10(-9)), and three new adenocarcinoma risk variants in TERT: rs61748181 (OR = 0.53, P = 2.64×10(-6)), rs112290073 (OR = 1.85, P = 1.27×10(-5)), rs138895564 (OR = 2.16, P = 2.06×10(-5); among young cases, OR = 3.77, P = 8.41×10(-4)). In addition, we found that rs139852726 (P = 1.44×10(-3)) was associated with telomere length in a sample of 922 healthy individuals. The gene-based SKAT-O analysis implicated TERT as the most relevant gene in the 5p15.33 region for adenocarcinoma (P = 7.84×10(-7)) and lung cancer (P = 2.37×10(-5)) risk. In this largest fine-mapping study to investigate a large number of rare and novel variants within 5p15.33, we identified novel lung and adenocarcinoma susceptibility loci with large effects and provided support for the role of telomere length as the potential underlying mechanism.
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http://dx.doi.org/10.1093/carcin/bgv165DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4715236PMC
January 2016

Spatial genomic heterogeneity within localized, multifocal prostate cancer.

Nat Genet 2015 Jul 25;47(7):736-45. Epub 2015 May 25.

Ontario Institute for Cancer Research, Toronto, Ontario, Canada.

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.
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http://dx.doi.org/10.1038/ng.3315DOI Listing
July 2015

SeqControl: process control for DNA sequencing.

Nat Methods 2014 Oct 31;11(10):1071-5. Epub 2014 Aug 31.

1] Informatics &Biocomputing Platform, Ontario Institute for Cancer Research, Toronto, Ontario, Canada. [2] Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. [3] Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada.

As high-throughput sequencing continues to increase in speed and throughput, routine clinical and industrial application draws closer. These 'production' settings will require enhanced quality monitoring and quality control to optimize output and reduce costs. We developed SeqControl, a framework for predicting sequencing quality and coverage using a set of 15 metrics describing overall coverage, coverage distribution, basewise coverage and basewise quality. Using whole-genome sequences of 27 prostate cancers and 26 normal references, we derived multivariate models that predict sequencing quality and depth. SeqControl robustly predicted how much sequencing was required to reach a given coverage depth (area under the curve (AUC) = 0.993), accurately classified clinically relevant formalin-fixed, paraffin-embedded samples, and made predictions from as little as one-eighth of a sequencing lane (AUC = 0.967). These techniques can be immediately incorporated into existing sequencing pipelines to monitor data quality in real time. SeqControl is available at http://labs.oicr.on.ca/Boutros-lab/software/SeqControl/.
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http://dx.doi.org/10.1038/nmeth.3094DOI Listing
October 2014

A two-dimensional pooling strategy for rare variant detection on next-generation sequencing platforms.

PLoS One 2014 11;9(4):e93455. Epub 2014 Apr 11.

Genome Technologies, Ontario Institute for Cancer Research, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.

We describe a method for pooling and sequencing DNA from a large number of individual samples while preserving information regarding sample identity. DNA from 576 individuals was arranged into four 12 row by 12 column matrices and then pooled by row and by column resulting in 96 total pools with 12 individuals in each pool. Pooling of DNA was carried out in a two-dimensional fashion, such that DNA from each individual is present in exactly one row pool and exactly one column pool. By considering the variants observed in the rows and columns of a matrix we are able to trace rare variants back to the specific individuals that carry them. The pooled DNA samples were enriched over a 250 kb region previously identified by GWAS to significantly predispose individuals to lung cancer. All 96 pools (12 row and 12 column pools from 4 matrices) were barcoded and sequenced on an Illumina HiSeq 2000 instrument with an average depth of coverage greater than 4,000×. Verification based on Ion PGM sequencing confirmed the presence of 91.4% of confidently classified SNVs assayed. In this way, each individual sample is sequenced in multiple pools providing more accurate variant calling than a single pool or a multiplexed approach. This provides a powerful method for rare variant detection in regions of interest at a reduced cost to the researcher.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0093455PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3984111PMC
December 2014