Understanding pancreatic cancer genomes

Pancreatic cancer is the fourth leading cause of cancer death in our society, with a mortality that virtually parallels its incidence, a median survival of <12 months even with maximal therapy, and a 5-year survival rate of <5 %. The diversity of clinical outcomes and the molecular heterogeneity of histopathologically similar cancer types, incomplete knowledge of the genomic aberrations that drive carcinogenesis and the lack of therapeutics that specifically target most known genomic aberrations necessitates large-scale detailed analysis of cancer genomes to identify novel potential therapeutic strategies. As part of the International Cancer Genome Consortium (ICGC), the Australian Pancreatic Cancer Genome Initiative (APGI) used exomic sequencing and copy number analysis to define genomic aberrations that characterize a large, clinically focused, prospectively accrued cohort of patients with pancreatic cancer. The cohort consisted of early (clinical stages I and II) non-pre-treated patients with pancreatic ductal adenocarcinoma who underwent operative resection with curative intent. We devised approaches to adjust for low epithelial content in primary tumours and to define the genomic landscape of pancreatic cancer to identify novel candidate driver genes and mechanisms. We aim to develop stratified, molecular phenotype-guided therapeutic strategies using existing therapeutics that are either rescued, repurposed, in development, or are known to be effective in an undefined subgroup of PC patients. These are then tested in primary patient-derived xenografts and cell lines from the above deeply characterized cohort. In addition, we return information to treating clinicians that influences patient care and are launching a clinical trial called IMPaCT (Individualized Molecular Pancreatic Cancer Therapy). This umbrella design trial randomizes patients with metastatic disease to either standard first-line therapy with gemcitabine, or a molecular phenotype-guided approach using next-generation sequencing strategies to screen for actionable mutations defined through the ICGC effort.