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

Research output: Contribution to journalArticle

Authors

  • 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

Colleges, School and Institutes

External organisations

  • Informatics and Bio-computing Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
  • Princess Margaret Living Biobank Core, University Health Network, Toronto, Ontario, Canada.
  • Department of Statistical Science, University of Toronto, Toronto, Ontario, Canada.
  • Department of Pathology, University Health Network, University of Toronto, Toronto, Ontario, Canada.
  • UHN Program in BioSpecimen Sciences, Department of Pathology, University Health Network, Toronto, Ontario, Canada.
  • Transformative Pathology, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
  • Division of Medical Oncology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.
  • Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
  • Hepatobiliary/Pancreatic Surgical Oncology Program, University Health Network, Toronto, Ontario, Canada.
  • Vector Institute, Toronto, Ontario, Canada.
  • PanCuRx Translational Research Initiative, Ontario Institute of Cancer Research (OICR), Toronto, Ontario, Canada.

Abstract

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.

Details

Original languageEnglish
Article numbere1006596
JournalPLoS Computational Biology
Volume15
Issue number1
Publication statusPublished - 10 Jan 2019