Dataset Information

Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case -control study.

ABSTRACT:

Background

In recent years, the identification of genetic and phenotypic biomarkers of cancer for prevention, early diagnosis and patient stratification has been a main objective of research in the field. Different multivariable models that use biomarkers have been proposed for the evaluation of individual risk of developing breast cancer.

Methods

This is a case control study based on a population-based cohort. We describe and evaluate a multivariable model that incorporates 92 Single-nucleotide polymorphisms (SNPs) (Supplementary Table S1) and five different phenotypic variables and which was employed in a Spanish population of 642 healthy women and 455 breast cancer patients.

Results

Our model allowed us to stratify two groups: high and low risk of developing breast cancer. 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 capacity of our multivariable model to stratify women according to their risk of developing breast cancer. The major limitation of our analysis is the small cohort size. However, despite the limitations, the results of our analysis provide proof of concept in a poorly studied population, and opens up the possibility of using this method in the routine screening of the Spanish population.

SUBMITTER: Trivino JC

PROVIDER: S-EPMC7654173 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Publications

Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case -control study.

Triviño J C JC Ceba A A Rubio-Solsona E E Serra D D Sanchez-Guiu I I Ribas G G Rosa R R Cabo M M Bernad L L Pita G G Gonzalez-Neira A A Legarda G G Diaz J L JL García-Vigara A A Martínez-Aspas A A Escrig M M Bermejo B B Eroles P P Ibáñez J J Salas D D Julve A A Cano A A Lluch A A Miñambres R R Benitez J J

BMC cancer 20201110 1

<h4>Background</h4>In recent years, the identification of genetic and phenotypic biomarkers of cancer for prevention, early diagnosis and patient stratification has been a main objective of research in the field. Different multivariable models that use biomarkers have been proposed for the evaluation of individual risk of developing breast cancer.<h4>Methods</h4>This is a case control study based on a population-based cohort. We describe and evaluate a multivariable model that incorporates 92 Si ...[more]

PMID: 33167914

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Project description:BACKGROUND:No prior study to our knowledge has examined the joint contribution of a polygenic risk score (PRS), mammographic density (MD), and postmenopausal endogenous hormone levels-all well-confirmed risk factors for invasive breast cancer-to existing breast cancer risk prediction models. METHODS AND FINDINGS:We conducted a nested case-control study within the prospective Nurses' Health Study and Nurses' Health Study II including 4,006 cases and 7,874 controls ages 34-70 years up to 1 June 2010. We added a breast cancer PRS using 67 single nucleotide polymorphisms, MD, and circulating testosterone, estrone sulfate, and prolactin levels to existing risk models. We calculated area under the curve (AUC), controlling for age and stratified by menopausal status, for the 5-year absolute risk of invasive breast cancer. We estimated the population distribution of 5-year predicted risks for models with and without biomarkers. For the Gail model, the AUC improved (p-values < 0.001) from 55.9 to 64.1 (8.2 units) in premenopausal women (Gail + PRS + MD), from 55.5 to 66.0 (10.5 units) in postmenopausal women not using hormone therapy (HT) (Gail + PRS + MD + all hormones), and from 58.0 to 64.9 (6.9 units) in postmenopausal women using HT (Gail + PRS + MD + prolactin). For the Rosner-Colditz model, the corresponding AUCs improved (p-values < 0.001) by 5.7, 6.2, and 6.5 units. For estrogen-receptor-positive tumors, among postmenopausal women not using HT, the AUCs improved (p-values < 0.001) by 14.3 units for the Gail model and 7.3 units for the Rosner-Colditz model. Additionally, the percentage of 50-year-old women predicted to be at more than twice 5-year average risk (?2.27%) was 0.2% for the Gail model alone and 6.6% for the Gail + PRS + MD + all hormones model. Limitations of our study included the limited racial/ethnic diversity of our cohort, and that general population exposure distributions were unavailable for some risk factors. CONCLUSIONS:In this study, the addition of PRS, MD, and endogenous hormones substantially improved existing breast cancer risk prediction models. Further studies will be needed to confirm these findings and to determine whether improved risk prediction models have practical value in identifying women at higher risk who would most benefit from chemoprevention, screening, and other risk-reducing strategies.

Project description:BACKGROUND: Although there are solid findings regarding the detrimental effect of alcohol consumption, the existing evidence on the effect of other dietary factors on breast cancer (BC) risk is inconclusive. This study aimed to evaluate the association between dietary patterns and risk of BC in Spanish women, stratifying by menopausal status and tumour subtype, and to compare the results with those of Alternate Healthy Index (AHEI) and Alternate Mediterranean Diet Score (aMED). METHODS: We recruited 1017 incident BC cases and 1017 matched healthy controls of similar age (±5 years) without a history of BC. The association between 'a priori' and 'a posteriori' developed dietary patterns and BC in general and according to menopausal status and intrinsic tumour subtypes (ER+/PR+ and HER2-; HER2+; and ER-/PR- and HER2-) was evaluated using logistic and multinomial regression models. RESULTS: Adherence to the Western dietary pattern was related to higher risk of BC (OR for the top vs the bottom quartile 1.46 (95% CI 1.06-2.01)), especially in premenopausal women (OR=1.75; 95% CI 1.14-2.67). In contrast, the Mediterranean pattern was related to a lower risk (OR for the top quartile vs the bottom quartile 0.56 (95% CI 0.40-0.79)). Although the deleterious effect of the Western pattern was similarly observed in all tumour subtypes, the protective effect of our Mediterranean pattern was stronger for triple-negative tumours (OR=0.32; 95% CI 0.15-0.66 and Pheterogeneity=0.04). No association was found between adherence to the Prudent pattern and BC risk. The associations between 'a priori' indices and BC risk were less marked (OR for the top vs the bottom quartile of AHEI=0.69; 95% CI 0.51-0.94 and aMED=0.74; 95% CI 0.46-1.18)). CONCLUSIONS: Our results confirm the harmful effect of a Western diet on BC risk, and add new evidence on the benefits of a diet rich in fruits, vegetables, legumes, oily fish and vegetable oils for preventing all BC subtypes, and particularly triple-negative tumours.

Dataset Information

Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case -control study.

Background

Methods

Results

Conclusions

Publications

Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case -control study.

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