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

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...

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Main Authors: Deena M A Gendoo, Robert E Denroche, Amy Zhang, Nikolina Radulovich, Gun Ho Jang, Mathieu Lemire, Sandra Fischer, Dianne Chadwick, Ilinca M Lungu, Emin Ibrahimov, Ping-Jiang Cao, Lincoln D Stein, Julie M Wilson, John M S Bartlett, Ming-Sound Tsao, Neesha Dhani, David Hedley, Steven Gallinger, Benjamin Haibe-Kains
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1006596
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spelling doaj-db08daf61ce64bfbb21f930f5552d95d2021-04-21T15:12:07ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582019-01-01151e100659610.1371/journal.pcbi.1006596Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer.Deena M A GendooRobert E DenrocheAmy ZhangNikolina RadulovichGun Ho JangMathieu LemireSandra FischerDianne ChadwickIlinca M LunguEmin IbrahimovPing-Jiang CaoLincoln D SteinJulie M WilsonJohn M S BartlettMing-Sound TsaoNeesha DhaniDavid HedleySteven GallingerBenjamin Haibe-KainsPancreatic 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.https://doi.org/10.1371/journal.pcbi.1006596
collection DOAJ
language English
format Article
sources DOAJ
author Deena M A Gendoo
Robert E Denroche
Amy Zhang
Nikolina Radulovich
Gun Ho Jang
Mathieu Lemire
Sandra Fischer
Dianne Chadwick
Ilinca M Lungu
Emin Ibrahimov
Ping-Jiang Cao
Lincoln D Stein
Julie M Wilson
John M S Bartlett
Ming-Sound Tsao
Neesha Dhani
David Hedley
Steven Gallinger
Benjamin Haibe-Kains
spellingShingle Deena M A Gendoo
Robert E Denroche
Amy Zhang
Nikolina Radulovich
Gun Ho Jang
Mathieu Lemire
Sandra Fischer
Dianne Chadwick
Ilinca M Lungu
Emin Ibrahimov
Ping-Jiang Cao
Lincoln D Stein
Julie M Wilson
John M S Bartlett
Ming-Sound Tsao
Neesha Dhani
David Hedley
Steven Gallinger
Benjamin Haibe-Kains
Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer.
PLoS Computational Biology
author_facet Deena M A Gendoo
Robert E Denroche
Amy Zhang
Nikolina Radulovich
Gun Ho Jang
Mathieu Lemire
Sandra Fischer
Dianne Chadwick
Ilinca M Lungu
Emin Ibrahimov
Ping-Jiang Cao
Lincoln D Stein
Julie M Wilson
John M S Bartlett
Ming-Sound Tsao
Neesha Dhani
David Hedley
Steven Gallinger
Benjamin Haibe-Kains
author_sort Deena M A Gendoo
title Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer.
title_short Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer.
title_full Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer.
title_fullStr Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer.
title_full_unstemmed Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer.
title_sort whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2019-01-01
description 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.
url https://doi.org/10.1371/journal.pcbi.1006596
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