Integrated multi-omics approach for glycosylation-based breast cancer subtyping

This project will utilise an integrated multi-omics approach for glycosylation-based breast cancer subtype discovery. Glycosylation is the process whereby carbohydrate structures are conjugated to cellular proteins and lipids, and in doing so, determines their functionality. Glycosylation is dysregulated in cancer and incorporating the glycome in cancer research has led to deeper mechanistic insight. Combining glycomic data with gene and protein expression, as well as metabolite concentrations, results in a panoramic view of cancer in which all aspects of tumour cell biology are included. Through the use of machine learning, these data types can be integrated and utilised for the discovery of breast cancer subtypes. This is a critical step towards personalized cancer treatment. The combination of computational knowledge at the Scientific Computing Research Unit, University of Cape Town, and the lectin microarray technology and integrated multi-omics approach of the Mahal lab, University of Alberta, will lead to deeper insight into tumorigenic mechanisms. This research is expected to identify breast cancer subtypes with similar functional aberrations. In addition, each subtype will be interrogated for diagnostic biomarkers and novel therapeutic targets.

Faculty Supervisor:

Lara Mahal

Student:

Partner:

University of Cape Town

Discipline:

Computer science

Sector:

Biotechnology; Health and Related Sciences & Technology; Artificial Intelligence

University:

University of Alberta

Program: