Back to Search Start Over

Identification of novel synthetic lethal interactions using multiplexed CRISPR-Cas9 screening

Authors :
Thompson, Nicola Anne
Adams, David
Publication Year :
2019
Publisher :
University of Cambridge, 2019.

Abstract

As our understanding of the cancer genome has progressed, traditional chemotherapeutic agents are being replaced, in part, by targeted therapies. Development of these therapies is driven by our understanding of genetic vulnerabilities harboured by tumours. The aim of this project is to identify novel synthetic lethal interactions within melanoma. Synthetic lethality describes a relationship between two genes, where loss of either of the pair is compatible with cellular viability, but simultaneous loss of both genes induces cell death. This approach can therefore exploit somatically acquired mutations to specifically kill tumour cells and to define new therapeutic targets. Abstract In order to do this, we selected a panel of putative synthetic lethal interactions and built a bespoke multiplex CRISPR-Cas9 library to interrogate 1192 gene-pair interactions. We deployed this library on a panel of melanoma cell lines and a retinal pigment epithelial cell line as a normal comparator. We went on to develop a bioinformatic pipeline with which to analyse the paired screen output and using this pipeline we have identified a number of novel synthetic lethal relationships. Using low throughput assays we validated a number of the interactions found by our screen. Finally, using human tumour expression data, we identified a candidate pair with potential therapeutic relevance. Using external datasets and isogenic knockout models we have further validated this relationship and performed mechanistic experiments to explore the role of these genes within the cell and generate a hypothesis to explain why loss of these two genes results in cell death.

Details

Language :
English
Database :
British Library EThOS
Publication Type :
Dissertation/ Thesis
Accession number :
edsble.774707
Document Type :
Electronic Thesis or Dissertation
Full Text :
https://doi.org/10.17863/CAM.38647