Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population

Background: In the last years, the identification of different genetic and phenotypic biomarkers for prevention, early diagnostics and patient stratification have been a main objective in cancer research. Different proposals for multivariable models using biomarkers have been presented for the evaluation of individual risk of women to develop breast cancer. Methods: In this study, we describe and evaluate a multivariable model using 92 Single-nucleotide polymorphisms (SNPs) and five different phenotypic variables in a Spanish population of 642 healthy women and 455 breast cancer patients. Results: We were able to stratify both groups with our model. The 9th decile included 1% of controls vs 9% of cases, with an Odds ratio (OR) of 12.9 and a p-value of 3.43E-07. The first decile presented an inverse proportion: 1% of cases and 9% of controls, with an OR of 0.097 and a p-value of 1.86E-08. Conclusions: These results indicate the ability of the multivariable model to stratify women according to their risk to develop breast cancer over a maximum period of 5 years. The analysis present a proof of concept in a poorly studied population and it opens the possibility of using this type of method for routine screening in the Spanish population.