Congratulations to the eight projects that have received funding under four rounds of grants to date. Following is a brief description of the funded projects and the team members and institutes involved. Grant Round 5 is now open. Find details here
ROUNDS 3 & 4
Analysis of Harmonized BCFR, CCFR, MCCS Datasets
MyBRISK CI: Associate Professor Robert MacInnis, Cancer Epidemiology Division, Cancer Council Victoria
Collaborators: the late Professor John Hopper, Prof Mary Beth Terry, Prof Mark Jenkins, Prof Roger Milne, Prof Melissa Southey, Prof Kelly Phillips
Awarded: Seed Funding of $10,000
Summary:
Certain risk factors are known to increase the chance of breast and colorectal cancer developing in women, but more information is needed as to whether these associations might differ by the strength of their family history of either cancer. Family history can be summarized as a continuous measure depending on the degree of diagnosed relatives and their ages of diagnosis. We will perform analyses using a harmonized dataset from three cohorts (Breast Cancer Family Registry, Colon Cancer Family Registry, Melbourne Collaborative Cohort Study) that oversampled participants with a cancer family history to be able to adequately estimate differences in associations.
RoBiN (Risk of Breast Neoplasia): An Acceptability and Feasibility Study of Personalised Screening
MyBRISK CI: Professor Jon Emery (CI) and Dr Anna Withanage Dona (Research Fellow and Clinical Trial Coordinator, Centre for Cancer Research), Victorian Comprehensive Cancer Centre, Department of General Practice and Primary Care, University of Melbourne
Collaborators: Dr Sibel Saya, the late Prof John Hopper, Dr Sue Malta, A/Prof Jennier Stone, Dr Erika Spaeth Tuff, Prof Helen Frazer, Dr Daniel Lee, A/Prof Justine Tse, Sally Doncovio, Sue Macaulay, Cindy Schultz Ferguson, Nikki Davis
Awarded: Larger Project Initiative Funding of $60,000 with additional funding from the Centre for Cancer Research
Summary
The concept of RoBiN is based on the value of personalised health care, emphasising the importance of understanding individual risk and tailoring screening according to risk. The study will offer BreastScreen Victoria (BSV) clients access to a comprehensive risk assessment incorporating a genomic test (GeneType) and measures of mammographic breast density. Women who consent to participate in this study will receive a tailored report of their individual risk of developing breast cancer and subsequent screening recommendations based on current evidence. By offering BSV clients this personalised approach through the free national program we aim to reach the broader community of women from diverse backgrounds to assess if risk-based screening is acceptable to women in the BSV program.
Assessing the acceptability and feasibility of this innovative approach to breast cancer risk assessment will help identify best practice for screening recommendations within primary care and inform more effective and efficient screening pathways to improve breast cancer outcomes in Australia. In addition, this study provides an opportunity to embed precision screening and medicine in primary care settings.
Breast Density Research Interest Group: Provision of Regular Updates to the MyBRISK CRE Extended Network Regarding Recent Publications and Initiatives
MyBRISK CI: Professor Rik Thompson, Queensland University of Technology
Collaborators: the late Prof John Hopper, Dr Sue Malta, Lynette Walker, Chloe Tannagan
Awarded: Seed Funding of $10,000 plus in-kind support by QUT
Summary
The project facilitates the online dissemination of the most recent studies in mammographic density within the domains of: (1) Methodology, measurement & deep learning (2) Pathobiology and clinical outcomes (3) Risk prediction, screening & public health (4) Environment and lifestyle. It is designed to foster a culture of continuous learning and collaboration within the breast cancer research community.
The utilisation of a designated Microsoft Teams platform encourages dialogue, debate, and knowledge exchange among participants. The interactive online platform facilitates a shared exploration of research articles and findings, thus cultivating a sense of community among professionals and enthusiasts, fostering connections and relationships that can lead to further collaboration and innovation in the field.
ROUND 2
Improved Heparinase Inhibitors to Reduce Mammographic Density to Enhance Mammography and/or Reduce Breast Cancer Risk
MyBRISK CI: Professor Rik Thompson, Queensland University of Technology
Collaborators: Konstantin Momot, Thomas Lloyd, Simone Birch, Neha Gandhi, Deirdre Coombe, Kathryn Fairfull-Smith, Larisa Haupt, Vito Ferro, Sandy Minck
Awarded: Seed Funding of $20,000
Summary
Mammographic Density (MD), the amount of white seen on the mammogram, is a well-established risk factor for breast cancer and impairs the efficiency of mammography by masking mammographic features of malignancy. Our studies are directed at short term reduction in mammographic density, which we have shown can be achieved experimentally with inhibitors of the enzyme heparinase. We have designed and validated new heparinase inhibitors and will test them here for reduction of mammographic density, along with optimised chemical variants. These inhibitors could help ‘clarify’ mammograms for women with high breast density, so that breast cancers are less commonly missed.
Optimising Public Dissemination of Breast Density and MyBRISK Research Through the InforMD Website
MyBRISK CI: Associate Professor Wendy Ingham, University of Adelaide
Collaborators: A/Prof Jennifer Stone, the late ProfJohn Hopper, Prof Erik Thompson, A/Prof Kara Britt
Awarded: Seed Funding of $20,000
Summary
The InforMD website provides the community with accurate information about breast density and keeps Australians up-to-date with new research as it becomes available. The website is unique as content is developed and provided by Australian scientific experts supported by community representatives who ensure the information provided is both accurate and interesting. This project will re-design and optimise the website to increase its visibility and accessibility so more Australians can learn about breast density research direct from the experts.
Using AI and Machine Learning Algorithms for Region-based Analyses of Existing GWAS Datasets to Identify Novel Genetic Risk Regions for Breast Cancer
MyBRISK CI: Professor Enes Makalic
Collaborators: the late Prof John Hopper, Dr Karen Alpen, Dr Miroslaw Kapuscinski, Dr Benjamin Goudey, A/Prof Shuai Li, Dr James Dowty, Dr John Lai, A/Prof Daniel F Schmidt
Awarded: Seed Funding of $20,000
Summary
Breast cancer is the most diagnosed cancer in women in Australia and the second leading cause of cancer-related death in Australian women. We will develop novel and highly accurate algorithms to estimate a woman’s risk of breast cancer. The machine learning tools to be developed will be disease agnostic and applicable to other cancer genomics data.
We will utilise state-of-the-art machine learning techniques to discover novel genomic regions associated with the risk of breast cancer. We will incorporate these novel genomic risk regions into an accurate prediction model for breast cancer risk. Our risk prediction models will incorporate the latest information on genomic risk factors, including those derived from the latest technologies. Our novel risk prediction models are expected to be more accurate than established models, based on family history in first-degree relatives, age and established susceptibility SNPs, given our preliminary findings regarding polygenic risk scores for coronary heart disease.
ROUND 1
Consumer-Driven Research to Improve Breast Cancer Screening Outcomes
MyBRISK CI: Associate Professor Jennifer Stone, University of Western Australia
Collaborators: Dr Shona Crabb, Dr Jocelyn Lippey, Mrs Gerda Evans, Mrs Ellen Kerrins, A/Prof Wendy Ingman, A/Prof Michelle Reintals, the late Professor Hopper, A/Prof Gretchen Gierach
Awarded: $20,000 Seed Funding with $27,431 matched funding from UWA RCA grant
Summary
It is becoming increasingly obvious that consumer-driven research provides improved relevance to patient needs, improved quality and outcomes, more effective research translation, and improved public confidence in research.
Associate Professor Stone’s research aims to work with consumer and community members to co-develop an interactive web-based platform that facilitates refinement, prioritization, funding, and conduct of consumer-driven research studies to improve breast cancer screening outcomes in Australia, focusing on prevention and early detection of the disease.
This innovative and compelling consumer-driven approach will generate highly translatable outcomes to improve care for women attending state-run BreastScreen programs in Australia. It is anticipated that the results from this project will also generate an MRFF grant application.
Registration and Alignment of Histology, Portable MRI and Micro-CT (x-ray) for Elucidating the Tissue Component of Mammographic Density Brightness
MyBRISK CI: Professor Rik Thompson, Queensland University of Technology
Collaborators: Dr Hang (Hollie) Min, Dr Jason Dowling, Dr Thomas Lloyd, Dr Konstantin Momot, Mr Satcha Foongkajornkiat, the late Prof John Hopper, Dr Kevin Nguyen, Dr Sandy Minck
Awarded: $19,821 Seed Funding with matched funds of $4,000 from QUT CGPH grant
Summary
MyBRISK researchers, the late Professor John Hopper, Kevin Nguyen and colleagues, have shown that the brightness of mammographic density (MD) correlates better with breast cancer risk than the total amount of MD.
Through histologic and regional assessments of mammographic density with a novel portable MRI and micro-CT (X-ray based), Professor Thompson’s team are attempting to define the cell and tissue composition of the brightest regions, which requires precise alignment of the multi-modal image data. This innovative project will develop a cross-modality registration software to accurately align the tissues across the different imaging modalities. This research has the potential to contribute to the understanding of bright MD and lead to improved breast cancer prediction, prevention and treatment.