Grant: CIHR Fellowship

Cancer cells become resistant to drugs via a natural selection process similar to antibiotic resistance. Learning how to rationally combine treatments to avoid drug resistance is a challenge. High grade serous ovarian cancer (HGSOC) is an example of a difficult to treat disease as it is diagnosed most of the time once it is already spread. We do not fully understand what makes HGSOC different between patients. We have so far developed new technologies and approaches to probe single cancer cells with unprecedented fidelity, and aim to find new therapies by exploiting the observation that HGSOC may differ in the way that the tumour DNA or RNA become unstable. The proposed work in HGSOC will serve as a model to solve similar problems in other primary as well as metastatic cancers. We propose to sequence the DNA and RNA of thousands of single cells from HGSOC patient tumours grown in mouse 'avatars'. We shall transplant patient's tumors on skin and inside the abdomen of the mice to create models very close to humans to learn which properties are associated with fitness to combination of drugs, taken in combination. We shall characterize the molecular nature of those transplants pre and post treatments for the discovery of potential new targets for drug discovery.