Poster Presentation 35th Lorne Cancer Conference 2023

Establishing functional drivers and novel therapeutic targets in oesophageal adenocarcinoma (#255)

Ebtihal Mustafa 1 2 , Julia Milne 1 2 , Thomas Jackson 1 2 , Kenji Fujihara 1 3 , Wayne Phillips 1 2 , Nicholas Clemons 1 2
  1. Division of Cancer Research, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
  2. Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Victoria, Australia
  3. Sir Peter MacCallum Department of Oncology, The University of Melbourne., Melbourne, Victoria, Australia

Oesophageal adenocarcinoma (OAC) is a disease with an increasing incidence rate and limited treatment options. OAC develops within a pre-cancerous metaplasia condition known as Barrett's oesophagus, yet the molecular drivers of progression are not well defined. A recent genomic study identified 76 genes as putative drivers of OAC. We previously showed that in the background of mutant TP53, inactivating one putative OAC tumour suppressor, SMAD4, was sufficient to drive tumorigenesis in non-tumourigenic CP-B Barrett’s oesophagus cells xenografts. Herein, we decided to integrate this pre-clinical model with CRISPR-based functional genomics and single-cell sequencing (scRNA-seq) technology to investigate all putative OAC drivers and define their role in Barrett’s carcinogenesis, and to identify potential opportunities for therapeutic interventions targeting OAC drivers. Using in silico validation we divided putative genes into oncogenes (n=22), tumour suppressors (n=41), and 12 genes with equivocal data. These 12 genes were considered as both oncogenes (n=34 total) and tumour suppressors (n=53 total). CP-B and CP-D (a second Barrett’s cell line) cells were engineered to stably express Cas9 and dCas9 for CRISPR knockout or activation, respectively. An initial pilot study was performed in which cells were transduced with gRNAs to knockout SMAD4 or overexpress GATA6 (a putative oncogene) and then subjected to scRNA-seq. Consequently, we were able to cluster SMAD4 and GATA6 clones and find genes that are differentially expressed between clusters. Moreover, the pilot study identified some of the experimental conditions that we should take into account in the larger screen before we can cluster OAC drivers by their effects on the transcriptome, including depth of sequencing and the number of cells to be captured. In summary, this study provides a novel approach that utilise advance in genomic technology to individually study the functional effects of every OAC driver, as well as rational driver combinations.

 

Key Words

OAC, CRISPR, single cell RNA-sequencing