Breast Cancer

Breast cancer is the most common cancer in women, affecting 1 in 8 Australian women, and 1 in 650 men, by the time they are 85. In Australia, breast cancer results in over 3,000 deaths per year.  Breast cancer results from the abnormal growth of the cells lining the breast lobules or ducts.

Both inherited and lifestyle factors contribute to risk of breast cancer. Rare genetic variants in breast cancer susceptibility genes like BRCA1 and BRCA2 greatly increase risk of breast cancer, but there are many more genes in which genetic variants confer a small increased risk.

Furthermore, the normal cells in the breast, including immune cells and blood vessel cells, interact with the breast cancer directly, and these interactions can promote or inhibit cancer growth, modulate the response to therapies and/or cause or inhibit the spread of the breast cancer to distant tissues (metastasis).

Although the overall 5-year survival rate for breast cancer is 91%, there are many different types of breast cancer, with different treatments and outcomes. We need to develop new treatments for the types of breast cancer with the worst outcome, and also acceptable risk reduction medications so that we can reduce the rates of breast cancer, particularly in high risk women.

Research at the QIMR Berghofer is aimed at developing a better understanding of who is at particular risk for this cancer, how the cancers develop from normal precursor cells and how it can be better treated.


  • understanding which variants in known cancer risk genes are clinically important
  • searching for genes that contribute to breast cancer risk
  • studying molecular processes to determine how cancer arises from healthy cells
  • improving responses to standard of care breast cancer therapies 
  • determining why some breast cancers develop resistance to current drug therapies
  • developing new therapies such as immunotherapies to treat advanced and early stage breast cancers
  • using genomic profiling to look for treatment opportunities
  • using artificial intelligence to understand the tumour microenvironment
  • understanding the interactions between cancer and non-cancer cells
  • developing strategies to identify patients at risk of metastases, and specific therapies for these individuals