Resolving Prostate Cancer: Elucidating the epigenetics of tumour microenvironment
Background
Each year in Australia, 20,000 men are diagnosed with prostate cancer and 3,000 men die of the disease.
Almost 80% of men are diagnosed with low to intermediate risk disease, being assigned to either a monitoring program such as active surveillance (AS), or surgery, such as radical prostatectomy (RP). However, the current diagnostic approach can misclassify tumours, leading to under-treatment of men with high-risk prostate cancer, or to over-treatment of men with low to intermediate-risk prostate cancer.
For the men correctly assigned to monitoring programs, they are at risk of sepsis due to repeat biopsy. For the men who have surgery, up to 17% die of prostate cancer with current clinical parameters unable to accurately predict which men will progress.
Minimally invasive and accurate tests are therefore critical to further improve prostate cancer prognosis, to increase patient survival and quality of life.
About the Project
Dr Pidsley’s research will lead to the development of a novel sensitive epigenetic test, to accurately determine tumour risk, particularly for tumours that are inaccurately classified using current clinical tools. These tests will improve diagnostic sensitivity, as they will target known epigenetic changes, not just in the tumour, but also in the surrounding cells, called the tumour microenvironment (TME). Improved diagnosis will ensure the correct treatment for patients, to improve quality of life and oncological outcomes.
Impact
Dr Pidsley’s project will allow the team to improve criteria for assigning patients to monitoring programs and surgery. Improved treatment decisions will reduce the number of repeat biopsies, reduce follow-up visits and reduce clinical tests that monitor disease recurrence, leading to substantial health cost savings and improvements in outcomes.
In the long-term, the project will provide insight into the viability of using epigenetic tumour microenvironment (TME) PCR biomarkers for tumour detection, with the potential application to other cancers with similar TMEs, like breast cancer.