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Polygenic Risk Scores for cancer mortality prediction

BACKGROUND: Polygenic risk scores (PRSs) have shown great accuracy in predicting cancer risk. In screening-based cancer prevention, it is important to be able to predict lethal cancer risk and PRSs have the potential to improve such prediction. This preliminary analysis, conducted on the UK BioBank,...

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Detalles Bibliográficos
Autores principales: Sciurti, A, De Blasiis, M R, Bolli, A, Busby, G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10595846/
http://dx.doi.org/10.1093/eurpub/ckad160.221
Descripción
Sumario:BACKGROUND: Polygenic risk scores (PRSs) have shown great accuracy in predicting cancer risk. In screening-based cancer prevention, it is important to be able to predict lethal cancer risk and PRSs have the potential to improve such prediction. This preliminary analysis, conducted on the UK BioBank, investigates the ability of 5 cancer PRSs to predict cancer incidence and mortality. METHODS: Five cohorts were derived from the UK BioBank for 5 common types of cancer (breast, colorectal, lung, pancreas and prostate). PRSs for cancer were constructed for each participant. The PRS hazard ratio per standard deviation (HR×SD) for cancer incidence and mortality was estimated using two proportional hazards Cox regression models for each type of cancer controlling for genotyping array, the first ten principal components of ancestry, family history, sex (where applicable), and age at enrolment. RESULTS: In the breast cancer cohort, PRS showed a HR×SD of 1.74 (95%CI:1.70-1.78) for cancer incidence and 1.66 (95%CI:1.52-1.81) for cancer mortality. In the prostate cancer cohort the PRS had a HRxSD of 1.78 (95%CI:1.74-1.81) for incidence and 1.73 (95%CI:1.61-1.86) for mortality. Similar results were found in the colorectal cancer cohort with a 1.27 (95%CI:1.24-1.31) PRS HR×SD for incidence and 1.30 (95%CI:1.24-1.37) for mortality, as well as in the pancreas cancer cohort with a 1.44 (95%CI:1.38-1.51) PRS HR×SD for incidence and 1.48 (95%CI:1.40-1.57) for mortality. In the lung cancer cohort a marginal PRS HR×SD was found for incidence and for mortality [1.07 (95%CI:1.04-1.10) and 1.07 (95%CI:1.03-1.12), respectively]. CONCLUSIONS: These results suggest that, for most types of cancer, PRSs can predict cancer mortality, as well as incidence, indicating their potential use as a tool to identify people at risk of lethal disease. KEY MESSAGES: • These results may contribute to outline clinical utility of PRSs in cancer prevention. • PRSs may be a useful addition to screening-based cancer prevention, in order to prioritise patients at risk of lethal cancer.