Publications by authors named "Astrid Deschênes"

11 Publications

  • Page 1 of 1

Intraductal Transplantation Models of Human Pancreatic Ductal Adenocarcinoma Reveal Progressive Transition of Molecular Subtypes.

Cancer Discov 2020 Oct 23;10(10):1566-1589. Epub 2020 Jul 23.

Cold Spring Harbor Laboratory, Cold Spring Harbor, New York.

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal common malignancy, with little improvement in patient outcomes over the past decades. Recently, subtypes of pancreatic cancer with different prognoses have been elaborated; however, the inability to model these subtypes has precluded mechanistic investigation of their origins. Here, we present a xenotransplantation model of PDAC in which neoplasms originate from patient-derived organoids injected directly into murine pancreatic ducts. Our model enables distinction of the two main PDAC subtypes: intraepithelial neoplasms from this model progress in an indolent or invasive manner representing the classical or basal-like subtypes of PDAC, respectively. Parameters that influence PDAC subtype specification in this intraductal model include cell plasticity and hyperactivation of the RAS pathway. Finally, through intratumoral dissection and the direct manipulation of gene dosage, we identify a suite of -regulated secreted and membrane-bound proteins that may represent potential candidates for therapeutic intervention in patients with PDAC. SIGNIFICANCE: Accurate modeling of the molecular subtypes of pancreatic cancer is crucial to facilitate the generation of effective therapies. We report the development of an intraductal organoid transplantation model of pancreatic cancer that models the progressive switching of subtypes, and identify stochastic and RAS-driven mechanisms that determine subtype specification...
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http://dx.doi.org/10.1158/2159-8290.CD-20-0133DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664990PMC
October 2020

SOAT1 promotes mevalonate pathway dependency in pancreatic cancer.

J Exp Med 2020 09;217(9)

Cold Spring Harbor Laboratory, Cold Spring Harbor, NY.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis, and new therapies are needed. Altered metabolism is a cancer vulnerability, and several metabolic pathways have been shown to promote PDAC. However, the changes in cholesterol metabolism and their role during PDAC progression remain largely unknown. Here we used organoid and mouse models to determine the drivers of altered cholesterol metabolism in PDAC and the consequences of its disruption on tumor progression. We identified sterol O-acyltransferase 1 (SOAT1) as a key player in sustaining the mevalonate pathway by converting cholesterol to inert cholesterol esters, thereby preventing the negative feedback elicited by unesterified cholesterol. Genetic targeting of Soat1 impairs cell proliferation in vitro and tumor progression in vivo and reveals a mevalonate pathway dependency in p53 mutant PDAC cells that have undergone p53 loss of heterozygosity (LOH). In contrast, pancreatic organoids lacking p53 mutation and p53 LOH are insensitive to SOAT1 loss, indicating a potential therapeutic window for inhibiting SOAT1 in PDAC.
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http://dx.doi.org/10.1084/jem.20192389DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7478739PMC
September 2020

Bioactivation of Napabucasin Triggers Reactive Oxygen Species-Mediated Cancer Cell Death.

Clin Cancer Res 2019 12 16;25(23):7162-7174. Epub 2019 Sep 16.

Cold Spring Harbor Laboratory, Cold Spring Harbor, New York.

Purpose: Napabucasin (2-acetylfuro-1,4-naphthoquinone or BBI-608) is a small molecule currently being clinically evaluated in various cancer types. It has mostly been recognized for its ability to inhibit STAT3 signaling. However, based on its chemical structure, we hypothesized that napabucasin is a substrate for intracellular oxidoreductases and therefore may exert its anticancer effect through redox cycling, resulting in reactive oxygen species (ROS) production and cell death.

Experimental Design: Binding of napabucasin to NAD(P)H:quinone oxidoreductase-1 (NQO1), and other oxidoreductases, was measured. Pancreatic cancer cell lines were treated with napabucasin, and cell survival, ROS generation, DNA damage, transcriptomic changes, and alterations in STAT3 activation were assayed and . Genetic knockout or pharmacologic inhibition with dicoumarol was used to evaluate the dependency on NQO1.

Results: Napabucasin was found to bind with high affinity to NQO1 and to a lesser degree to cytochrome P450 oxidoreductase (POR). Treatment resulted in marked induction of ROS and DNA damage with an NQO1- and ROS-dependent decrease in STAT3 phosphorylation. Differential cytotoxic effects were observed, where NQO1-expressing cells generating cytotoxic levels of ROS at low napabucasin concentrations were more sensitive. Cells with low or no baseline NQO1 expression also produced ROS in response to napabucasin, albeit to a lesser extent, through the one-electron reductase POR.

Conclusions: Napabucasin is bioactivated by NQO1, and to a lesser degree by POR, resulting in futile redox cycling and ROS generation. The increased ROS levels result in DNA damage and multiple intracellular changes, one of which is a reduction in STAT3 phosphorylation.
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http://dx.doi.org/10.1158/1078-0432.CCR-19-0302DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891204PMC
December 2019

Organoid Profiling Identifies Common Responders to Chemotherapy in Pancreatic Cancer.

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

Cold Spring Harbor Laboratory, Cold Spring Harbor, 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

Inferring and modeling inheritance of differentially methylated changes across multiple generations.

Nucleic Acids Res 2018 08;46(14):7466

Département de Médecine Moléculaire - Université Laval, Faculté de médecine, Pavillon Ferdinand-Vandry, 1050 avenue de la Médecine, bureau 4633, Québec, QC G1V 0A6, Canada.

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http://dx.doi.org/10.1093/nar/gky477DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101620PMC
August 2018

Inferring and modeling inheritance of differentially methylated changes across multiple generations.

Nucleic Acids Res 2018 08;46(14):e85

Département de Médecine Moléculaire - Université Laval, Faculté de médecine, Pavillon Ferdinand-Vandry, 1050 avenue de la Médecine, bureau 4633, Québec, QC G1V 0A6, Canada.

High-throughput methylation sequencing enables genome-wide detection of differentially methylated sites (DMS) or regions (DMR). Increasing evidence suggests that treatment-induced DMS can be transmitted across generations, but the analysis of induced methylation changes across multiple generations is complicated by the lack of sound statistical methods to evaluate significance levels. Due to software design, DMS detection was usually made on each generation separately, thus disregarding stochastic effects expected when a large number of DMS is detected in each generation. Here, we present a novel method based on Monte Carlo sampling, methylInheritance, to evaluate that the number of conserved DMS between several generations is associated to an effect inherited from a treatment and not randomness. Moreover, we developed an inheritance simulation package, methInheritSim, to demonstrate the performance of the methylInheritance method and to evaluate the power of different experimental designs. Finally, we applied methylInheritance to a DNA methylation dataset obtained from early-life persistent organic pollutants (POPs) exposed Sprague-Dawley female rats and their descendants through a paternal transmission. The results show that metylInheritance can efficiently identify treatment-induced inherited methylation changes. Specifically, we identified two intergenerationally conserved DMS at transcription start site (TSS); one of those persisted transgenerationally. Three transgenerationally conserved DMR were found at intra or integenic regions.
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http://dx.doi.org/10.1093/nar/gky362DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101575PMC
August 2018

metagene Profiles Analyses Reveal Regulatory Element's Factor-Specific Recruitment Patterns.

PLoS Comput Biol 2016 08 18;12(8):e1004751. Epub 2016 Aug 18.

Centre de Recherche du CHU de Québec - Université Laval, Québec, Québec, Canada.

ChIP-Sequencing (ChIP-Seq) provides a vast amount of information regarding the localization of proteins across the genome. The aggregation of ChIP-Seq enrichment signal in a metagene plot is an approach commonly used to summarize data complexity and to obtain a high level visual representation of the general occupancy pattern of a protein. Here we present the R package metagene, the graphical interface Imetagene and the companion package similaRpeak. Together, they provide a framework to integrate, summarize and compare the ChIP-Seq enrichment signal from complex experimental designs. Those packages identify and quantify similarities or dissimilarities in patterns between large numbers of ChIP-Seq profiles. We used metagene to investigate the differential occupancy of regulatory factors at noncoding regulatory regions (promoters and enhancers) in relation to transcriptional activity in GM12878 B-lymphocytes. The relationships between occupancy patterns and transcriptional activity suggest two different mechanisms of action for transcriptional control: i) a "gradient effect" where the regulatory factor occupancy levels follow transcription and ii) a "threshold effect" where the regulatory factor occupancy levels max out prior to reaching maximal transcription. metagene, Imetagene and similaRpeak are implemented in R under the Artistic license 2.0 and are available on Bioconductor.
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http://dx.doi.org/10.1371/journal.pcbi.1004751DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4990179PMC
August 2016

Using informative Multinomial-Dirichlet prior in a t-mixture with reversible jump estimation of nucleosome positions for genome-wide profiling.

Stat Appl Genet Mol Biol 2015 Dec;14(6):517-32

Genome-wide mapping of nucleosomes has revealed a great deal about the relationships between chromatin structure and control of gene expression. Recent next generation CHIP-chip and CHIP-Seq technologies have accelerated our understanding of basic principles of chromatin organization. These technologies have taught us that nucleosomes play a crucial role in gene regulation by allowing physical access to transcription factors. Recent methods and experimental advancements allow the determination of nucleosome positions for a given genome area. However, most of these methods estimate the number of nucleosomes either by an EM algorithm using a BIC criterion or an effective heuristic strategy. Here, we introduce a Bayesian method for identifying nucleosome positions. The proposed model is based on a Multinomial-Dirichlet classification and a hierarchical mixture distributions. The number and the positions of nucleosomes are estimated using a reversible jump Markov chain Monte Carlo simulation technique. We compare the performance of our method on simulated data and MNase-Seq data from Saccharomyces cerevisiae against PING and NOrMAL methods.
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http://dx.doi.org/10.1515/sagmb-2014-0098DOI Listing
December 2015

Development of highly reliable in silico SNP resource and genotyping assay from exome capture and sequencing: an example from black spruce (Picea mariana).

Mol Ecol Resour 2016 03 18;16(2):588-98. Epub 2015 Oct 18.

Canada Research Chair in Forest and Environmental Genomics, Centre for Forest Research, Université Laval, Québec, QC, G1V 0A6, Canada.

Picea mariana is a widely distributed boreal conifer across Canada and the subject of advanced breeding programmes for which population genomics and genomic selection approaches are being developed. Targeted sequencing was achieved after capturing P. mariana exome with probes designed from the sequenced transcriptome of Picea glauca, a distant relative. A high capture efficiency of 75.9% was reached although spruce has a complex and large genome including gene sequences interspersed by some long introns. The results confirmed the relevance of using probes from congeneric species to perform successfully interspecific exome capture in the genus Picea. A bioinformatics pipeline was developed including stringent criteria that helped detect a set of 97,075 highly reliable in silico SNPs. These SNPs were distributed across 14,909 genes. Part of an Infinium iSelect array was used to estimate the rate of true positives by validating 4267 of the predicted in silico SNPs by genotyping trees from P. mariana populations. The true positive rate was 96.2% for in silico SNPs, compared to a genotyping success rate of 96.7% for a set 1115 P. mariana control SNPs recycled from previous genotyping arrays. These results indicate the high success rate of the genotyping array and the relevance of the selection criteria used to delineate the new P. mariana in silico SNP resource. Furthermore, in silico SNPs were generally of medium to high frequency in natural populations, thus providing high informative value for future population genomics applications.
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http://dx.doi.org/10.1111/1755-0998.12468DOI Listing
March 2016

The landscape of nucleotide polymorphism among 13,500 genes of the conifer picea glauca, relationships with functions, and comparison with medicago truncatula.

Genome Biol Evol 2013 ;5(10):1910-25

Canada Research Chair in Forest and Environmental Genomics, Centre for Forest Research and Institute for Systems and Integrative Biology, Université Laval, Québec, Canada.

Gene families differ in composition, expression, and chromosomal organization between conifers and angiosperms, but little is known regarding nucleotide polymorphism. Using various sequencing strategies, an atlas of 212k high-confidence single nucleotide polymorphisms (SNPs) with a validation rate of more than 92% was developed for the conifer white spruce (Picea glauca). Nonsynonymous and synonymous SNPs were annotated over the corresponding 13,498 white spruce genes representative of 2,457 known gene families. Patterns of nucleotide polymorphisms were analyzed by estimating the ratio of nonsynonymous to synonymous numbers of substitutions per site (A/S). A general excess of synonymous SNPs was expected and observed. However, the analysis from several perspectives enabled to identify groups of genes harboring an excess of nonsynonymous SNPs, thus potentially under positive selection. Four known gene families harbored such an excess: dehydrins, ankyrin-repeats, AP2/DREB, and leucine-rich repeat. Conifer-specific sequences were also generally associated with the highest A/S ratios. A/S values were also distributed asymmetrically across genes specifically expressed in megagametophytes, roots, or in both, harboring on average an excess of nonsynonymous SNPs. These patterns confirm that the breadth of gene expression is a contributing factor to the evolution of nucleotide polymorphism. The A/S ratios of Medicago truncatula genes were also analyzed: several gene families shared between P. glauca and M. truncatula data sets had similar excess of synonymous or nonsynonymous SNPs. However, a number of families with high A/S ratios were found specific to P. glauca, suggesting cases of divergent evolution at the functional level.
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http://dx.doi.org/10.1093/gbe/evt143DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3814201PMC
May 2014

Development of high-density SNP genotyping arrays for white spruce (Picea glauca) and transferability to subtropical and nordic congeners.

Mol Ecol Resour 2013 Mar 25;13(2):324-36. Epub 2013 Jan 25.

Canada Research Chair in Forest and Environmental Genomics, Centre for Forest Research and Institute for Systems and Integrative Biology, Université Laval, Québec, Canada, QC, G1V 0A6.

High-density SNP genotyping arrays can be designed for any species given sufficient sequence information of high quality. Two high-density SNP arrays relying on the Infinium iSelect technology (Illumina) were designed for use in the conifer white spruce (Picea glauca). One array contained 7338 segregating SNPs representative of 2814 genes of various molecular functional classes for main uses in genetic association and population genetics studies. The other one contained 9559 segregating SNPs representative of 9543 genes for main uses in population genetics, linkage mapping of the genome and genomic prediction. The SNPs assayed were discovered from various sources of gene resequencing data. SNPs predicted from high-quality sequences derived from genomic DNA reached a genotyping success rate of 64.7%. Nonsingleton in silico SNPs (i.e. a sequence polymorphism present in at least two reads) predicted from expressed sequenced tags obtained with the Roche 454 technology and Illumina GAII analyser resulted in a similar genotyping success rate of 71.6% when the deepest alignment was used and the most favourable SNP probe per gene was selected. A variable proportion of these SNPs was shared by other nordic and subtropical spruce species from North America and Europe. The number of shared SNPs was inversely proportional to phylogenetic divergence and standing genetic variation in the recipient species, but positively related to allele frequency in P. glauca natural populations. These validated SNP resources should open up new avenues for population genetics and comparative genetic mapping at a genomic scale in spruce species.
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http://dx.doi.org/10.1111/1755-0998.12062DOI Listing
March 2013