Congratulations to the successful awardees and their teams.


Dr Trang Pham (Liverpool Hospital, SWSLHD and UNSW Sydney): Targeting cancer heterogeneity with ultra-high field MRI and radiotherapy using machine learning

Organisations involved: Ingham Institute, SWSLHD, UNSW Sydney, University of Queensland, Western Sydney University

In Australia 70,000 cancer patients require radiotherapy annually and 30% will have cancer recurrence or die of their cancer. Tumours are biologically heterogeneous. Current radiotherapy treats tumours uniformly based on size, ignoring biological variation within tumours apart from type. MRI-Linacs, a new generation of radiotherapy machines combined with magnetic resonance imaging (MRI) offer a new degree of precision and image guidance in radiotherapy. The project will use rectal cancer to develop an MRI biomarker discovery and clinical translation pipeline to identify MRI biomarkers of heterogeneity for predicting radiotherapy response. Machine learning super-resolution will be applied for the first time in cancer imaging to improve the image quality on clinical MRI scanners.


Dr Liz Caldon (Garvan Institute of Medical Research and UNSW Sydney): Targeting FGF fusions in previously untreatable cancers: A new OMICS approach for personalised cancer medicine

Organisations involved: Garvan Institute of Medical Research, The Kinghorn Cancer Centre, SESLHD, UNSW Sydney

Personalised cancer medicine allows treatment to specifically target mutations unique to a patient’s cancer. However, we have not identified driver mutations in ~50% of cancers, which leaves those patients with fewer therapeutic options and ultimately shorter survival. The group discovered a previously undescribed class of gene fusions with the potential to be immediately matched to available therapies. These are “FGF-fusions”, which function in the FGFR (Fibroblast Growth Factor Receptor) pathway in cancer. This pathway signals cells to grow and invade, and it can be inhibited by FGFR therapies, two of which are FDA approved. Using cancer cells, the group has shown that an FGF-fusion turn on FGFR, but leave the cells vulnerable to FGFR inhibitors. In this project we will screen an FGF-fusion panel across a current patient cohort to identify novel FGF-fusions, creating a publicly available comprehensive map of FGF-fusions.

The EMCR seed grants fund academics and clinical academics up to 15 years post-PhD to lead new collaborative research with mentoring and support provided through a structured team. They aim to develop our research workforce and emerging leaders.