Oral Presentation 32nd Lorne Cancer 2020

Pancreatic adenocarcinoma single cell atlas. Decoding pancreatic cancer using single cell sequencing. (#30)

Fernando J. Rossello 1 , Luciano G. Martelotto 1 , Amber Johns 2 , Sean M. Grimmond 1
  1. University of Melbourne Centre for Cancer Research, Melbourne, Victoria, Australia
  2. Cancer Division, Garvan Institute of Medical Research, Sydney, New South Wales, Australia

Pancreatic adenocarcinoma is currently the 4th leading cause of cancer death in Western societies and is projected to become the 2nd leading cause within a decade. Five-year survival remains at <10%.

There is an urgent need to better understand the molecular pathology and oncogenesis of this disease to improve patient selection for current treatments and to develop novel therapeutic strategies. In recent years, genome-exploratory efforts by the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas efforts have revolutionized our understanding of pancreatic cancer. However, these studies are far from complete due to small cohort sizes and a reliance on bulk tumour tissue analysis.

In a multi-national effort, we have performed a large scale genomic/transcriptomic/epigenomic analyses of >1000 pancreatic adenocarcinomas, expanding the expanded the repertoire of driver mutations involved in this disease to more than 60.

While standard bulk sequencing efforts have increased our understanding of pancreatic adenocarcinoma, resolving intra-tumour heterogeneity, cancer cell states, cellular composition and cell-specific activation states of different cell types remains limited.

In this work, we performed single nucleus RNA and ATAC high throughput sequencing, from the same sample preparation, of 30 extensively characterised pancreatic adenocarcinomas - part of Australia ICGC program - using the 10X Genomics platform.

Using a multimodal integrative approach, we characterised the transcriptome and epigenome of each tumour sample within the context of the entire cohort. Analyses included cell classification and cell type sample composition, characterization of the interaction of neoplastic and non-neoplastic cells, genotyping and copy number alterations analyses at single nucleus resolution.

To date, this work constitutes the most comprehensive pancreatic adenocarcinoma cell atlas.