PT  - JOURNAL ARTICLE
AU  - Deena M.A. Gendoo
AU  - Robert E. Denroche
AU  - Amy Zhang
AU  - Nikolina Radulovich
AU  - Gun Ho Jang
AU  - Mathieu Lemire
AU  - Sandra Fischer
AU  - Dianne Chadwick
AU  - Ilinca M. Lungu
AU  - Emin Ibrahimov
AU  - Ping-Jiang Cao
AU  - Lincoln D. Stein
AU  - Julie M. Wilson
AU  - John M.S. Bartlett
AU  - Ming-Sound Tsao
AU  - Neesha Dhani
AU  - David Hedley
AU  - Steven Gallinger
AU  - Benjamin Haibe-Kains
TI  - Whole Genomes Define Concordance of Matched Primary, Xenograft, and Organoid Models of Pancreas Cancer
AID  - 10.1101/209692
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 209692
4099  - http://biorxiv.org/content/early/2017/12/28/209692.short
4100  - http://biorxiv.org/content/early/2017/12/28/209692.full
AB  - 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 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 new pipeline to score concordance between PDAC models and their paired human tumours for genomic events, including mutations, structural variations, and copy number variations. Comparison of genomic events in the tumours and matched disease models displayed single-gene concordance across major PDAC driver genes, and genome-wide similarities of copy number changes. Genome-wide and chromosome-centric analysis of structural variation (SV) events revealed high variability across tumours and disease models, but also highlighted previously unrecognized concordance across chromosomes that demonstrate clustered SV events. Our approach and results demonstrate that PDX and PDO recapitulate PDAC tumourigenesis with respect to simple somatic mutations and copy number changes, and capture major SV events that are found in both resected and metastatic tumours.