Cambridge scientists have created an online tool for predicting an individual’s risk of developing prostate cancer, to enable more targeted testing, treatment and early diagnosis.
CanRisk-Prostate, developed by researchers at the University of Cambridge and The Institute of Cancer Research, London, will be incorporated into the group’s CanRisk web tool (opens in a new tab), which has now recorded almost 1.2 million risk predictions.
The free tool is already used by healthcare professionals worldwide to help predict the risk of developing breast and ovarian cancers.
This research on powerful, user-friendly, web-based prediction tools for patients and clinicians to detect cancer earlier, will form part of the work at the Early Cancer Institute Research Clinic, embedded within the new Cambridge Cancer Research Hospital.
Testing for prostate cancer
Prostate cancer is the most common type of cancer in men. According to Cancer Research UK, over 52,000 men are diagnosed with the disease each year and there are more than 12,000 deaths.
Over three-quarters (78%) of men diagnosed with prostate cancer survive for over ten years, but this proportion has barely changed over the past decade in the UK.
Testing for prostate cancer involves a blood test that looks for a protein known as a prostate-specific antigen (PSA) that is made only by the prostate gland; however, it is not always accurate.
According to the NHS website, around three in four men with a raised PSA level will not have cancer. Further tests, such as tissue biopsies or MRI scans, are therefore required to confirm a diagnosis.
For the first time, it combines information on the genetic makeup and prostate cancer family history, the main risk factors for the disease, to provide personalised cancer risks.
Professor Antonis Antoniou
Professor Antonis Antoniou from the Department of Public Health and Primary Care at the University of Cambridge said:
“Prostate cancer is the most common cancer in men in the UK, but population-wide screening based on PSA isn’t an option: these tests are often falsely positive, which means that many men would then be biopsied unnecessarily.
"Also, many prostate tumours identified by PSA tests are slow-growing and would not have been life-threatening. The treatment of these tumours may do more harm than good.
“What we need is a way of identifying those men who are at greatest risk, allowing us to target screening and diagnostic tests where they are most needed, while also reducing the harms for those men who have low risk of the disease. This is what CanRisk-Prostate aims to do."
Predicting cancer risk
Prostate cancer is one of the most genetically determined of common cancers. Inherited faulty versions of the BRCA2, HOXB13 and possibly BRCA1 genes are associated with moderate-to-high risk of prostate cancer, though such faults are rare in the population.
Writing in the Journal of Clinical Oncology, the researchers – supported by Cancer Research UK – describe the development of the first comprehensive prostate cancer model using genetic and cancer family history data from almost 17,000 families affected by prostate cancer.
One in six men (16%) will develop prostate cancer by the time they are 85 years old. Using the model, the team found that the predicted risk was higher for men who had a father diagnosed with prostate cancer – 27% if the father was diagnosed at an older age (80 years), but as high as 42% if the father was diagnosed at a young age (50 years).
In practice, say the researchers, clinicians will be able to use any combination of cancer family history, rare and common genetic variants to provide a personalised risk.
We’ve created the most comprehensive tool to date for predicting a man’s risk of developing prostate cancer.
Dr Tommy Nyberg
Dr Tommy Nyberg from the MRC Biostatistics Unit at Cambridge said:
“We hope this will help clinicians and genetic counsellors assess their clients’ risk and provide the appropriate follow-up.
“Over the next 12 months, we aim to build this tool into the widely used CanRisk tool, which will facilitate the risk-based clinical management of men seen in family cancer clinics and enable risk-adapted early detection approaches to the population at large.”
Professor Ros Eeles from The Institute of Cancer Research, London and co-author on the study said:
“This is an important step forward as it will enable clinicians to have conversations with men about their individual risk of prostate cancer based on the most accurate computer model to date. This will help them in making decisions about screening.”
So far, the data used to develop CanRisk-Prostate has been from men of European ancestry. The team hope to be able to include data from men of other ethnicities as further research is undertaken.
The University of Cambridge recently launched the Early Cancer Institute (opens in a new tab) with the aim of detecting cancer early enough to cure it.
It is the first physical institute in the UK dedicated to early cancer. The new Cambridge Cancer Research Hospital (opens in a new tab) is also planned for the near future, bringing together clinical and research expertise in a new, world-class hospital, designed in partnership with patients.
There is also an Early Detection and Diagnosis centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust where a prostate risk clinic has been established to translate these findings into targeted screening programmes.
The research was supported by the Cancer Research UK-funded CanRisk programme. Additional support for CanRisk-Prostate was provided by Prostate Cancer UK, The Institute of Cancer Research, Everyman Campaign, National Cancer Research Network UK, National Cancer Research Institute, NIHR Cambridge Biomedical Research Centre and the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust.
Reference
Nyberg, T et al. CanRisk-Prostate: a comprehensive, externally validated risk model for the prediction of future prostate cancer. Journal of Clinical Oncology; 9 Dec 2022; Link to paper here: https://doi.org/10.1200/JCO.22.01453 (opens in a new tab)
