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.