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Discover how the late Professor John Hopper AM led a team of researchers, including Associate Professor Shuai Li, to develop new and more accurate predictors of breast cancer risk that can be translated into breast cancer screening practice globally.

A pioneering genetic epidemiologist, Professor John Hopper AM (1950–2024) was awarded one of 9 inaugural Australian NHMRC Fellowships for his transformative research that improved understanding of how genetic and environmental factors impact human health. 

Professor Hopper’s career spanned over 40 years, significantly contributing to our national health and medical research sector – in particular, through his dedication to advancing breast, colorectal and prostate cancer epidemiology.

Inspired by Professor Hopper and his work, Associate Professor Shuai Li developed an interest in why some diseases cluster in families. In 2014, Associate Professor Li became one of Professor Hopper’s PhD students, eventually gaining his doctorate on the correlation between genetics, epigenetics and breast cancer risk factors. 

Throughout the decade of working together, Associate Professor Li’s greatest learning from Professor Hopper was to focus on the evidence and avoid having predetermined ideas by fully embracing the research journey. Associate Professor Li is now leading the work started by Professor Hopper in identifying new risk factors for breast cancer based on digital mammograms.

A mammogram is a low dose x-ray of the breast tissue used to screen for breast cancer. On a mammogram image, dense breast tissue appears solid white and is hard to see through. Mammographically dense breasts can hide existing tumours which also appear as solid white and can consequently develop into interval cancers. 

An NHMRC Ideas Grant, originally led by Professor Hopper, sought to address this problem by developing a new and more accurate predictor using automated measures that could identify women who were at high risk of developing interval breast cancer.

The research team demonstrated that the new mammogram based risk measures, Altocumulus and Cirrocumulus, were as strong as the genetic factors for predicting breast cancer risk. Furthermore, they were not related to genetic factors currently known to be associated with breast cancer risk. The discovery of genetic causes of these measures holds the potential to reveal new genetic causes of breast cancer.

‘We illustrated that in a mammogram, the lighter (less dense) areas have a causal effect on the brightest (highly dense) areas. This is consistent with the brightest areas being more aetiologically important for screen detected breast cancer, and light areas being more important for interval breast cancer.’ said Associate Professor Li.

This research laid the foundation for the recently established NHMRC Centre of Research Excellence, MyBRISK, having advanced our understanding of how genetic, lifestyle and environmental factors interact to influence breast cancer risk – a lasting legacy of Professor Hopper’s work.

Next steps

Women at higher risk of developing invasive breast cancer will be more accurately identified during mammographic screening, allowing for tailored reporting, personalised management, and potentially shorter screening intervals. Associate Professor Li and his team will use artificial intelligence (AI) to analyse mammograms and uncover new imaging features that predict invasive breast cancer risk. These AI-derived insights will be combined with traditional risk factors, such as mammographic density and age, to create a more precise and personalised breast screening approach for clinical use.

Grant information

Chief Investigator: Associate Professor Shuai Li (on behalf of the late Professor John Hopper AM)

Administering Institution: The University of Melbourne

Team members:

  • Dr Gillian Dite
  • Dr Daniel Lee
  • Dr Kevin Nguyen
  • Dr Osamah Al-qershi
  • Dr Zhoufeng Ye
  • Professor Melissa Southey

Grant: Ideas Grant

Year: 2019–2022

Funding amount: $895,468

  1. ^

     Altocumulus and Cirrocumulus are density measures that use higher pixel brightness to quantify dense areas on a breast mammogram.

  2. ^

     An interval cancer is diagnosed during the time between a regular screening mammogram that appears normal and the next screening mammogram, usually conducted 24 months a part. Interval breast cancers tend to be larger, grow and spread more quickly, and have a worse prognosis than those found on screening mammograms.

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