Polygenic Risk Scores for Breast Cancer—Can They Deliver on the Promise of Precision Medicine?

ABSTRACTPolygenic risk scores (PRS) for breast cancer have potential to improve risk prediction, but there is limited information on their clinical applicability. We set out to study how PRS could help in clinical decision making. Among 99,969 women in the FinnGen study with 6,879 breast cancer cases, the PRS was associated not only with breast cancer incidence but also with a range of breast cancer-related endpoints. Women with a breast cancer PRS above the 90th percentile had both higher breast cancer mortality (HR 2.40, 95%CI 1.82-3.17) and higher risk for non-localized disease at diagnosis (HR 2.94, 95%CI 2.63-3.28), compared to those with PRS <80th percentile. The PRS modified the breast cancer risk of two high-impact frameshift risk variants. Women with the c.1592delT variant in PALB2 (242-fold enrichment in Finland, 263 carriers) and an average PRS (20-80th percentile) had a lifetime risk of breast cancer at 58% (95%CI 50-66%), which increased to 85% (70-100%) with a high PRS (>90th percentile), and decreased to 27% (15-39%) with a low PRS (<20th percentile). Similarly, for c.1100delC in CHEK2 (3.7-fold enrichment; 1,543 carriers), the respective lifetime risks were 27% (95%CI 25-30%), 59% (52-67%), and 18% (13-22%). Among breast cancer cases, a PRS >90th percentile was associated with risk of contralateral breast cancer with HR 1.66 (95%CI 1.24-2.22). Finally, the PRS significantly refined the risk assessment of women with first-degree relatives diagnosed with breast cancer, i.e. the combination of high PRS (>90th percentile) and a positive family-history was associated with a 2.33-fold elevated risk (95%CI 1.57-3.46) compared to a positive family history alone. These findings demonstrate opportunities for a comprehensive way of assessing genetic risk in the general population, in breast cancer patients, and in unaffected family members.

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The role of polygenic risk and susceptibility genes in breast cancer over the course of life

Nature Communications ◽

10.1038/s41467-020-19966-5 ◽

2020 ◽

Vol 11 (1) ◽

Author(s):

Nina Mars ◽

◽

Elisabeth Widén ◽

Sini Kerminen ◽

Tuomo Meretoja ◽

...

Keyword(s):

Breast Cancer ◽

Risk Assessment ◽

Positive Family History ◽

Breast Cancer Diagnosis ◽

Risk Scores ◽

Limited Information ◽

Breast Cancer Patients ◽

Polygenic Risk ◽

First Degree Relatives ◽

Fold Enrichment

AbstractPolygenic risk scores (PRS) for breast cancer have potential to improve risk prediction, but there is limited information on their utility in various clinical situations. Here we show that among 122,978 women in the FinnGen study with 8401 breast cancer cases, the PRS modifies the breast cancer risk of two high-impact frameshift risk variants. Similarly, we show that after the breast cancer diagnosis, individuals with elevated PRS have an elevated risk of developing contralateral breast cancer, and that the PRS can considerably improve risk assessment among their female first-degree relatives. In more detail, women with the c.1592delT variant in PALB2 (242-fold enrichment in Finland, 336 carriers) and an average PRS (10–90th percentile) have a lifetime risk of breast cancer at 55% (95% CI 49–61%), which increases to 84% (71–97%) with a high PRS ( > 90th percentile), and decreases to 49% (30–68%) with a low PRS ( < 10th percentile). Similarly, for c.1100delC in CHEK2 (3.7–fold enrichment; 1648 carriers), the respective lifetime risks are 29% (27–32%), 59% (52–66%), and 9% (5–14%). The PRS also refines the risk assessment of women with first-degree relatives diagnosed with breast cancer, particularly among women with positive family history of early-onset breast cancer. Here we demonstrate the opportunities for a comprehensive way of assessing genetic risk in the general population, in breast cancer patients, and in unaffected family members.

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Abstract 962: Validation of breast cancer risk model incorporating classical risk factors and polygenic risk scores in 14 prospective cohort studies in 6 countries

10.1158/1538-7445.am2019-962 ◽

2019 ◽

Author(s):

Parichoy Pal Choudhury ◽

Amber Wilcox ◽

Chi Gao ◽

Brian Carter ◽

Anika Husing ◽

...

Keyword(s):

Breast Cancer ◽

Risk Factors ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Cohort Studies ◽

Prospective Cohort ◽

Risk Model ◽

Risk Scores ◽

Polygenic Risk ◽

Prospective Cohort Studies

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Deep neural network improves the estimation of polygenic risk scores for breast cancer

Journal of Human Genetics ◽

10.1038/s10038-020-00832-7 ◽

2020 ◽

Author(s):

Adrien Badré ◽

Li Zhang ◽

Wellington Muchero ◽

Justin C. Reynolds ◽

Chongle Pan

Keyword(s):

Breast Cancer ◽

Neural Network ◽

Deep Neural Network ◽

Risk Scores ◽

Polygenic Risk

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Impact of Personalized Genetic Breast Cancer Risk Estimation With Polygenic Risk Scores on Preventive Endocrine Therapy Intention and Uptake

Cancer Prevention Research ◽

10.1158/1940-6207.capr-20-0154 ◽

2020 ◽

pp. canprevres.0154.2020

Author(s):

Julian O. Kim ◽

Daniel J. Schaid ◽

Celine M. Vachon ◽

Andrew Cooke ◽

Fergus J. Couch ◽

...

Keyword(s):

Breast Cancer ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Endocrine Therapy ◽

Risk Estimation ◽

Risk Scores ◽

Polygenic Risk

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Perspective: The Clinical Use of Polygenic Risk Scores: Race, Ethnicity, and Health Disparities

Ethnicity & Disease ◽

10.18865/ed.29.3.513 ◽

2019 ◽

Vol 29 (3) ◽

pp. 513-516 ◽

Cited By ~ 2

Author(s):

Megan C. Roberts ◽

Muin J. Khoury ◽

George A. Mensah

Keyword(s):

Precision Medicine ◽

Association Studies ◽

Clinical Care ◽

Genomic Research ◽

Risk Scores ◽

Genome Wide Association Studies ◽

Polygenic Risk ◽

Adverse Health Outcomes ◽

Genome Wide ◽

Disease Risks

Polygenic risk scores (PRS) are an emerging precision medicine tool based on multiple gene variants that, taken alone, have weak associations with disease risks, but collectively may enhance disease predictive value in the population. However, the benefit of PRS may not be equal among non-European populations, as they are under-represented in genome-wide association studies (GWAS) that serve as the basis for PRS development. In this perspective, we discuss a path forward, which includes: 1) inclusion of underrepresented populations in PRS research; 2) global efforts to build capacity for genomic research; 3) equitable implementation of these tools in clinical practice; and 4) traditional public health approaches to reduce risk of adverse health outcomes as an important component to precision health. As precision medicine is implemented in clinical care, researchers must ensure that advances from PRS research will benefit all.Ethn Dis.2019;29(3):513-516; doi:10.18865/ed.29.3.513.

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