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Translating Germline Cancer Genomics into Precision Prevention of Cancer

It is well known that early detection and monitoring of cancer greatly improves patient prognosis. However, specific interventions are only financially and logistically viable when targeting subsets of individuals who are at a specifically raised risk of developing cancer, rather than at a whole population level.

These specific interventions can include enhanced screening programmes, such as annual MRI scans for over 30s, primary surgical prevention like mastectomy, primary chemoprevention, and behavioural prevention.

Clare Turnbull, Professor of Translational Cancer Genetics at the ICR spoke at the Festival of Genomics and Biodata 2022 about how precision genomics can increase the effectiveness of early intervention in breast cancer patients.

Risk on three levels

Genes that put individuals at an altered risk of developing breast cancer come in clusters. Some are low penetrance but high frequency, while others are high penetrance but low frequency. BRCA1, BRCA2 and PALB2 are outliers in that they have relatively high penetrance for their moderately high frequency.

But genetic risk isn’t one dimensional, there are several factors that come into play. Clare discussed this risk on three levels.

The first was on the variant-level. While genetic variants can be generally split into “pathogenic” and “benign” , there are other additional  layers of complexity. Both the location of the variant within the gene, and the type of variant (i.e. truncating mutation versus missense mutations). Mutations within the centre of BRCA1 and BRCA2, for example, are associated with a higher risk of ovarian cancer, while mutations at the periphery of the gene are associated with a higher risk of breast cancer. The effects of variant type can be more dramatic in different genes. For example, truncation mutations convey much higher risk in BRCA1 and BRCA2 than in ATM and TP53 where missense mutations are more impactful.

Another level mentioned was the risk on the gene-level. BCRA1 and BCRA2 convey a much higher risk percentage for breast cancer than for ovarian cancer.

Finally, Clare highlighted the risk at the intervention level. For example, triple negative breast cancer generally has more successful and effective interventions, than ER+ breast cancer, and so the risk is lower.

The point here is what could be considered simple paradigms are actually multidimensional meshes of parameters.

A vicious circle

A major issue facing expanding capacity for early breast cancer intervention is a vicious circle of laborious approaches and lack of clinical manpower. The current testing process is labour intensive, leading to limited capacity for testing, which means that the testing needs to be ‘rationed’ out to people who need it most. Currently, the rationing of these tests is done by a complex assessment of family history and eligibility, which contributes further to the labour-intensive process. Breaking this cycle through germline cancer genomic risk scores could greatly expand capacity.

Clare outlined a pilot study which utilised an app to prompt women to send DNA samples through to NHS diagnostic laboratories and data systems. Women that were negative for BRCA1/BRCA2/PALB2 were notified via the app, whilst all positive individuals were called on the phone by a genetic councillor and entered into a clinical genetics process. The goal is to eventually incorporate a similar system into an appropriate current pathway for NHS care.

‘Tri-Partite’ predictive score

Finally, Clare showed how polygenic risk scores can be incorporated with questionnaire risk factors and mammographic density to form a ‘tri-partite’ predictive score.

The use of all these metrics together ‘spread out’ the distribution of risk amongst a test population. This meant that more people were being identified as lower than average risk, and more people were being identified as higher than average risk, rather than most people sitting quite close to the average. In other words, it greatly increased the precision of risk calculation, allowing much more accurate targeting of women who were classified as “moderately high” and “high” risk. There are a number of studies exploring the feasibility of implementing this tripartite score such as PROCAS, PERSPECTIVE, and MyPeBS.

Through using this knowledge and these techniques, it’s possible to develop a new strategy for early intervention.  Introduction of more targeted precision prevention of cancer will allow early intervention to reach far more individuals in the UK. Interventions will also be able to operate more effectively within the external economic and manpower restraints that the NHS faces.

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