Mots-Clés

cancer systems biology networks machine learning

Description

The Ryan group at University College Dublin are recruiting a postdoctoral fellow to work on network approaches to target genetic alterations in cancer. This position will be funded through a Science Foundation Ireland award to understand and predict synthetic lethal interactions in cancer.

Project Description:
Synthetic lethality, where one gene becomes essential in the presence of a mutation in another, has emerged as a promising approach by which we might identify new therapeutic targets for a variety of cancer associated mutations. Advances in genetic screening technologies, most notably CRISPR gene-editing, have enabled large-scale efforts to identify new synthetic lethal targets in cancer. However, testing all human gene pairs for synthetic lethality in even a single cell line is well beyond the field’s current capacity. Furthermore, it has become clear that synthetic lethal interactions are highly context-specific: a combination of genetic perturbations that is lethal in one cell type or genetic background may be well tolerated in another. The nature of this context-specificity and the factors that influence it are almost entirely unknown. However, such knowledge is critical both for identifying new synthetic lethal therapies and for anticipating resistance to such therapies. The overall goal of this project is to understand what factors contribute to the context-specificity of synthetic lethality in cancer and to develop machine learning models capable of predicting context-specific synthetic lethality. Relevant recent papers from our lab include Lord et al, eLife (2020) and De Kegel et al, Cell Systems (2021).