Developing and improving models for risk stratification
We believe that we can optimise our approach to Cancer Prevention and Early Detection by calculating an individual’s total cancer risk.
For many common cancers, risk is related to combinations of lifestyle, environmental and genetic factors. Over recent years researchers have identified hundreds of genetic variations and gene mutations which can switch protective tumour suppression genes off, as well as moderate- and high-risk genes for many cancers.
Through our research we are:
- Further refining this approach by analysing DNA samples collected through the Predicting the Risk Of Cancer At Screening (PROCAS and PROCAS-2) studies using exome sequencing, to identify all known and suspected breast cancer genes and assess known breast cancer gene mutation risk.
- Increasing the amount of information available to produce accurate risk assessments and more personalised care.
- Developing and validating rules for differentiating between those at low, high and moderate risk of cancer
- Exploring the role epigenetics can play in cancer risk assessment and monitoring effectiveness of precision prevention interventions
This research will be supported by our biomarker and genomics expertise.
Progress to date
- Further SNPs identified to improve polygenic risk scores for breast cancer.
- Automated Low Dose Risk Assessment Mammography (ALDRAM): low dose mammography and AI for assessment of breast density as a marker of breast cancer risk in younger women, showing promising initial results
- Developing simple, non-invasive testing and guidance for screening endometrial cancer
- The use of SNP313 is to be piloted in PROCAS-2 (BC-Predict SNP sub-study)
- Refining the lung cancer risk assessment
- A combined risk assessment using biomarker, epidemiological and genetic data to better identify men in the community with clinically significant prostate cancer.