SpringerLink
Log in

Polygenic Risk Scores for Breast Cancer

  • Review
  • Published:
Current Breast Cancer Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Polygenic risk scores (PRS) for breast cancer (BC) estimate risk based on the cumulative impact of single-nucleotide polymorphisms. This review outlines current data regarding potential applications of breast cancer PRS.

Recent Findings

PRS may have use in unaffected and affected individuals and in those with and without germline pathogenic variants. Incorporation of clinical risk factors strengthens estimates. Multi-ancestry PRS have mitigated but not resolved concerns about applicability across ancestry groups.

Summary

PRS represents an important, emerging component of BC risk estimation. Research will help inform optimal utilization and communication, as well as clinical and psychological impact.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Lei S, Zheng R, Zhang S, Wang S, Chen R, Sun K, et al. Global patterns of breast cancer incidence and mortality: a population-based cancer registry data analysis from 2000 to 2020. Cancer Commun. 2021;41(11):1183–94 (Lond).

    Article  Google Scholar 

  2. Cancer Genome Atlas N. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490(7418):61–70.

    Article  Google Scholar 

  3. Genomes Project C, Abecasis GR, Altshuler D, Auton A, Brooks LD, Durbin RM, et al. A map of human genome variation from population-scale sequencing. Nature. 2010;467(7319):1061–73.

    Article  Google Scholar 

  4. Roberts E, Howell S, Evans DG. Polygenic risk scores and breast cancer risk prediction. Breast. 2023;67:71–7.

    Article  PubMed  PubMed Central  Google Scholar 

  5. •• Mavaddat N, Michailidou K, Dennis J, Lush M, Fachal L, Lee A, et al. Polygenic risk scores for prediction of breast cancer and breast cancer subtypes. Am J Hum Genet. 2019;104(1):21–34. This report describes the development of the 313-SNP PRS, the most well studied of the breast cancer polygenic risk scores, that predicts overall and subtype-specific cancer risks.

  6. •• Barnes DR, Rookus MA, McGuffog L, Leslie G, Mooij TM, Dennis J, et al. Polygenic risk scores and breast and epithelial ovarian cancer risks for carriers of BRCA1 and BRCA2 pathogenic variants. Genet Med. 2020;22(10):1653–66. This study evaluated the predictive ability of PRS for breast cancer overall, ER-negative, and ER-positive breast cancer among BRCA1 and BRCA2 carriers. PRS were associated with breast cancer in BRCA1/2 carriers, although the hazard ratios were less than general population estimates.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Borde J, Laitman Y, Blumcke B, Niederacher D, Weber-Lassalle K, Sutter C, et al. Polygenic risk scores indicate extreme ages at onset of breast cancer in female BRCA1/2 pathogenic variant carriers. BMC Cancer. 2022;22(1):706.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Shi M, O’Brien KM, Weinberg CR. Interactions between a polygenic risk score and non-genetic risk factors in young-onset breast cancer. Sci Rep. 2020;10(1):3242.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. • Kramer I, Hooning MJ, Mavaddat N, Hauptmann M, Keeman R, Steyerberg EW, et al. Breast cancer polygenic risk score and contralateral breast cancer risk. Am J Hum Genet. 2020;107(5):837–48. The 313-SNP PRS independently associated with contralateral breast cancer among European ancestry and Asian ancestry women.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. •• Lopes Cardozo JMN, Andrulis IL, Bojesen SE, Dork T, Eccles DM, Fasching PA, et al. Associations of a breast cancer polygenic risk score with tumor characteristics and survival. J Clin Oncol. 2023;41(10):1849–63. The 313-SNP PRS was associated with favorable tumor characteristics but was not independently associated with survival.

  11. McCarthy AM, Manning AK, Hsu S, Welch M, Moy B, Lehman CD, Armstrong K. Breast cancer polygenic risk scores are associated with short-term risk of poor prognosis breast cancer. Breast Cancer Res Treat. 2022;196(2):389–98.

    Article  CAS  PubMed  Google Scholar 

  12. • Hughes E, Tshiaba P, Wagner S, et al. Integrating clinical and polygenic factors to predict breast cancer risk in women undergoing genetic testing. JCO Precis Oncol. 2021;5:PO.20.00246. https://doi.org/10.1200/PO.20.00246. A combined score using an 86-SNP PRS and the Tyrer-Cuzick score significantly improved risk prediction compared to the Tyrer-Cuzick alone.

  13. Mavaddat N, Ficorella L, Carver T, Lee A, Cunningham AP, Lush M, et al. Incorporating alternative polygenic risk scores into the BOADICEA breast cancer risk prediction model. Cancer Epidemiol Biomarkers Prev. 2023;32(3):422–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Yang X, Eriksson M, Czene K, Lee A, Leslie G, Lush M, et al. Prospective validation of the BOADICEA multifactorial breast cancer risk prediction model in a large prospective cohort study. J Med Genet. 2022;59(12):1196–205.

    Article  CAS  PubMed  Google Scholar 

  15. Rudolph A, Song M, Brook MN, Milne RL, Mavaddat N, Michailidou K, et al. Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium. Int J Epidemiol. 2018;47(2):526–36.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Evans DGR, van Veen EM, Harkness EF, Brentnall AR, Astley SM, Byers H, et al. Breast cancer risk stratification in women of screening age: incremental effects of adding mammographic density, polygenic risk, and a gene panel. Genet Med. 2022;24(7):1485–94.

    Article  CAS  PubMed  Google Scholar 

  17. Pal Choudhury P, Brook MN, Hurson AN, Lee A, Mulder CV, Coulson P, et al. Comparative validation of the BOADICEA and Tyrer-Cuzick breast cancer risk models incorporating classical risk factors and polygenic risk in a population-based prospective cohort of women of European ancestry. Breast Cancer Res. 2021;23(1):22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Lakeman IMM, Rodriguez-Girondo M, Lee A, Ruiter R, Stricker BH, Wijnant SRA, et al. Validation of the BOADICEA model and a 313-variant polygenic risk score for breast cancer risk prediction in a Dutch prospective cohort. Genet Med. 2020;22(11):1803–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Lakeman IMM, Hilbers FS, Rodriguez-Girondo M, Lee A, Vreeswijk MPG, Hollestelle A, et al. Addition of a 161-SNP polygenic risk score to family history-based risk prediction: impact on clinical management in non-BRCA1/2 breast cancer families. J Med Genet. 2019;56(9):581–9.

    Article  CAS  PubMed  Google Scholar 

  20. Gallagher S, Hughes E, Wagner S, Tshiaba P, Rosenthal E, Roa BB, et al. Association of a polygenic risk score with breast cancer among women carriers of high- and moderate-risk breast cancer genes. JAMA Netw Open. 2020;3(7):e208501.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Gallagher S, Hughes E, Kurian AW, et al. Comprehensive breast cancer risk assessment for chek2 and atm pathogenic variant carriers incorporating a polygenic risk score and the tyrer-cuzick model. JCO Precis Oncol. 2021;5:PO.20.00484. https://doi.org/10.1200/PO.20.00484.

  22. Kuchenbaecker KB, McGuffog L, Barrowdale D, Lee A, Soucy P, Dennis J, et al. Evaluation of polygenic risk scores for breast 599 and ovarian cancer risk prediction in BRCA1 and BRCA2 600 mutation carriers. J Natl Cancer Inst. 2017;109(7):djw302. https://doi.org/10.1093/jnci/djw302.

  23. •• Gao C, Polley EC, Hart SN, Huang H, Hu C, Gnanaolivu R, et al. Risk of breast cancer among carriers of pathogenic variants in breast cancer predisposition genes varies by polygenic risk score. J Clin Oncol. 2021;39(23):2564–73. PRS incorporation into breast cancer risk estimation reclassified over 30% of CHEK2 carriers and nearly half of ATM carriers as having a lifetime risk of breast cancer under 20%, demonstrating the potential clinical utility of PRS in those with moderate penetrance breast cancer susceptibility genes.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Muranen TA, Greco D, Blomqvist C, Aittomaki K, Khan S, Hogervorst F, et al. Genetic modifiers of CHEK2*1100delC-associated breast cancer risk. Genet Med. 2017;19(5):599–603.

    Article  CAS  PubMed  Google Scholar 

  25. Borde J, Ernst C, Wappenschmidt B, Niederacher D, Weber-Lassalle K, Schmidt G, et al. Performance of breast cancer polygenic risk scores in 760 female CHEK2 germline mutation carriers. J Natl Cancer Inst. 2021;113(7):893–9.

    Article  PubMed  Google Scholar 

  26. • Lakeman IMM, van den Broek AJ, Vos JAM, Barnes DR, Adlard J, Andrulis IL, et al. The predictive ability of the 313 variant-based polygenic risk score for contralateral breast cancer risk prediction in women of European ancestry with a heterozygous BRCA1 or BRCA2 pathogenic variant. Genet Med. 2021;23(9):1726–37. This study demonstrated the ability of PRS to predict contralateral breast cancer among those with primary breast cancer and pathogenic mutations in BRCA1/2. This association was stronger for the ER-negative PRS for BRCA1 carriers and stronger for the ER-positive PRS for BRCA2 carriers. The impact on clinical decision-making for this group is yet to be determined.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. •• Hughes E, Wagner S, Pruss D, Bernhisel R, Probst B, Abkevich V, et al. Development and validation of a breast cancer polygenic risk score on the basis of genetic ancestry composition. JCO Precis Oncol. 2022;6:e2200084. This article outlines the development of a multiple-ancestry PRS (MA-PRS) based on genetic information from women of European, East Asian, and African ancestries. This PRS associated with breast cancer risk, both for the entire cohort and within each ancestry group.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Shieh Y, Fejerman L, Lott PC, Marker K, Sawyer SD, Hu D, et al. A polygenic risk score for breast cancer in US Latinas and Latin American women. J Natl Cancer Inst. 2020;112(6):590–8.

    Article  PubMed  Google Scholar 

  29. Ho WK, Tan MM, Mavaddat N, Tai MC, Mariapun S, Li J, et al. European polygenic risk score for prediction of breast cancer shows similar performance in Asian women. Nat Commun. 2020;11(1):3833.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Du Z, Gao G, Adedokun B, Ahearn T, Lunetta KL, Zirpoli G, et al. Evaluating polygenic risk scores for breast cancer in women of african ancestry. J Natl Cancer Inst. 2021;113(9):1168–76.

    Article  PubMed  PubMed Central  Google Scholar 

  31. • Liu C, Zeinomar N, Chung WK, Kiryluk K, Gharavi AG, Hripcsak G, et al. Generalizability of polygenic risk scores for breast cancer among women with European, African, and Latinx ancestry. JAMA Netw Open. 2021;4(8):e2119084. This study analyzed the generalizability of European ancestry-derived PRSs to Latinx and African ancestry populations. While the PRSs generalized well for these groups, the effect size was smaller for those with African ancestry.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Ho WK, Tai MC, Dennis J, Shu X, Li J, Ho PJ, et al. Polygenic risk scores for prediction of breast cancer risk in Asian populations. Genet Med. 2022;24(3):586–600.

    Article  CAS  PubMed  Google Scholar 

  33. • Gao G, Zhao F, Ahearn TU, Lunetta KL, Troester MA, Du Z, et al. Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach. Hum Mol Genet. 2022;31(18):3133–43. A joint PRS, comprised of an African ancestry GWAS-derived PRS and the 313-SNP PRS improved breast cancer risk prediction among women of African ancestry.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Evans DG, van Veen EM, Byers H, Roberts E, Howell A, Howell SJ, et al. The importance of ethnicity: are breast cancer polygenic risk scores ready for women who are not of White European origin? Int J Cancer. 2022;150(1):73–9.

    Article  CAS  PubMed  Google Scholar 

  35. Archer S, Fennell N, Colvin E, et al. Personalised risk prediction in hereditary breast and ovarian cancer: a protocol for a multi-centre randomised controlled trial. Cancers (Basel). 2022;14(11):2716. https://doi.org/10.3390/cancers14112716.

  36. Eklund M, Broglio K, Yau C, Connor JT, Stover Fiscalini A, Esserman LJ. The WISDOM personalized breast cancer screening trial: simulation study to assess potential bias and analytic approaches. JNCI Cancer Spectr. 2018;2(4):pky067.

    Article  PubMed  Google Scholar 

  37. Genetic/familial high-risk assessment: breast, ovarian, and pancreatic: national comprehensive cancer network. 2023. [Available from: https://www.nccn.org/professionals/physician_gls/pdf/genetics_bop.pdf. Accessed 18 Sep 2023.

  38. Sessa C, Balmana J, Bober SL, Cardoso MJ, Colombo N, Curigliano G, et al. Risk reduction and screening of cancer in hereditary breast-ovarian cancer syndromes: ESMO clinical practice guideline. Ann Oncol. 2023;34(1):33–47.

    Article  CAS  PubMed  Google Scholar 

  39. Claus EB, Risch N, Thompson WD. The calculation of breast cancer risk for women with a first degree family history of ovarian cancer. Breast Cancer Res Treat. 1993;28(2):115–20.

    Article  CAS  PubMed  Google Scholar 

  40. McGuigan KA, Ganz PA, Breant C. Agreement between breast cancer risk estimation methods. J Natl Cancer Inst. 1996;88(18):1315–7.

    Article  CAS  PubMed  Google Scholar 

  41. Tischkowitz M, Wheeler D, France E, Chapman C, Lucassen A, Sampson J, et al. A comparison of methods currently used in clinical practice to estimate familial breast cancer risks. Ann Oncol. 2000;11(4):451–4.

    Article  CAS  PubMed  Google Scholar 

  42. McTiernan A, Kuniyuki A, Yasui Y, Bowen D, Burke W, Culver JB, et al. Comparisons of two breast cancer risk estimates in women with a family history of breast cancer. Cancer Epidemiol Biomarkers Prev. 2001;10(4):333–8.

    CAS  PubMed  Google Scholar 

  43. Evans DG, Brentnall A, Byers H, Harkness E, Stavrinos P, Howell A, et al. The impact of a panel of 18 SNPs on breast cancer risk in women attending a UK familial screening clinic: a case-control study. J Med Genet. 2017;54(2):111–3.

    Article  PubMed  Google Scholar 

  44. Sawyer S, Mitchell G, McKinley J, Chenevix-Trench G, Beesley J, Chen XQ, et al. A role for common genomic variants in the assessment of familial breast cancer. J Clin Oncol. 2012;30(35):4330–6.

    Article  PubMed  Google Scholar 

  45. Li H, Feng B, Miron A, Chen X, Beesley J, Bimeh E, et al. Breast cancer risk prediction using a polygenic risk score in the familial setting: a prospective study from the Breast Cancer Family Registry and kConFab. Genet Med. 2017;19(1):30–5.

    Article  CAS  PubMed  Google Scholar 

  46. Husing A, Canzian F, Beckmann L, Garcia-Closas M, Diver WR, Thun MJ, et al. Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status. J Med Genet. 2012;49(9):601–8.

    Article  PubMed  Google Scholar 

  47. Mavaddat N, Pharoah PD, Michailidou K, et al. Prediction of breast cancer risk based on profiling with common genetic variants. J Natl Cancer Inst. 2015;107(5):djv036. https://doi.org/10.1093/jnci/djv036.

  48. Dite GS, MacInnis RJ, Bickerstaffe A, Dowty JG, Allman R, Apicella C, et al. Breast cancer risk prediction using clinical models and 77 independent risk-associated snps for women aged under 50 years: Australian breast cancer family registry. Cancer Epidemiol Biomarkers Prev. 2016;25(2):359–65.

    Article  PubMed  Google Scholar 

  49. Shieh Y, Hu D, Ma L, Huntsman S, Gard CC, Leung JW, et al. Breast cancer risk prediction using a clinical risk model and polygenic risk score. Breast Cancer Res Treat. 2016;159(3):513–25.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Brentnall AR, van Veen EM, Harkness EF, Rafiq S, Byers H, Astley SM, et al. A case-control evaluation of 143 single nucleotide polymorphisms for breast cancer risk stratification with classical factors and mammographic density. Int J Cancer. 2020;146(8):2122–9.

    Article  CAS  PubMed  Google Scholar 

  51. Khera AV, Chaffin M, Aragam KG, Haas ME, Roselli C, Choi SH, et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat Genet. 2018;50(9):1219–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Hughes E, Tshiaba P, Gallagher S, et al. Development and validation of a clinical polygenic risk score to predict breast cancer risk. JCO Precis Oncol. 2020;4:PO.19.00360. https://doi.org/10.1200/PO.19.00360.

  53. van Veen EM, Brentnall AR, Byers H, Harkness EF, Astley SM, Sampson S, et al. Use of single-nucleotide polymorphisms and mammographic density plus classic risk factors for breast cancer risk prediction. JAMA Oncol. 2018;4(4):476–82.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Vachon CM, Scott CG, Tamimi RM, Thompson DJ, Fasching PA, Stone J, et al. Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk. Breast Cancer Res. 2019;21(1):68.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Yiangou K, Hadjisavvas A, Agelaki S, Aggouraki D, Androulakis N, Bozionelou V, et al. 149P associations between the 313-SNP polygenic risk score and breast cancer risk in women from Crete. Ann Oncol. 2022;33:S189.

    Article  Google Scholar 

  56. Shah PD. Polygenic risk scores for breast cancer-can they deliver on the promise of precision medicine? JAMA Netw Open. 2021;4(8):e2119333.

    Article  PubMed  Google Scholar 

  57. Lakeman IMM, Rodriguez-Girondo MDM, Lee A, Celosse N, Braspenning ME, van Engelen K, et al. Clinical applicability of the polygenic risk score for breast cancer risk prediction in familial cases. J Med Genet. 2023;60(4):327–36.

    Article  PubMed  Google Scholar 

  58. Bevers TB, Helvie M, Bonaccio E, Calhoun KE, Daly MB, Farrar WB, et al. Breast cancer screening and diagnosis, version 3.2018, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2018;16(11):1362–89.

    Article  PubMed  Google Scholar 

  59. Shi M, O’Brien KM, Sandler DP, Taylor JA, Zaykin DV, Weinberg CR. Previous GWAS hits in relation to young-onset breast cancer. Breast Cancer Res Treat. 2017;161(2):333–44.

    Article  CAS  PubMed  Google Scholar 

  60. van den Broek JJ, Schechter CB, van Ravesteyn NT, Janssens A, Wolfson MC, Trentham-Dietz A, et al. Personalizing breast cancer screening based on polygenic risk and family history. J Natl Cancer Inst. 2021;113(4):434–42.

    Article  PubMed  Google Scholar 

  61. • Tshiaba PT, Ratman DK, Sun JM, Tunstall TS, Levy B, Shah PS, et al. Integration of a cross-ancestry polygenic model with clinical risk factors improves breast cancer risk stratification. JCO Precis Oncol. 2023;7:e2200447. A cross-ancestry integrated risk score (calRS) combining a cross-ancestry PRS with a clinical estimator for breast cancer risk improved risk stratification for women of multiple ancestries.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Mealiffe ME, Stokowski RP, Rhees BK, Prentice RL, Pettinger M, Hinds DA. Assessment of clinical validity of a breast cancer risk model combining genetic and clinical information. J Natl Cancer Inst. 2010;102(21):1618–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Li SX, Milne RL, Nguyen-Dumont T, et al. Prospective evaluation of the addition of polygenic risk scores to breast cancer risk models. JNCI Cancer Spectr. 2021;5(3):pkab021. https://doi.org/10.1093/jncics/pkab021.

  64. Mars N, Widen E, Kerminen S, Meretoja T, Pirinen M, Della Briotta Parolo P, et al. The role of polygenic risk and susceptibility genes in breast cancer over the course of life. Nat Commun. 2020;11(1):6383.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Opstal-van Winden AWJ, de Haan HG, Hauptmann M, Schmidt MK, Broeks A, Russell NS, et al. Genetic susceptibility to radiation-induced breast cancer after Hodgkin lymphoma. Blood. 2019;133(10):1130–9.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Mills MC, Rahal C. The GWAS diversity monitor tracks diversity by disease in real time. Nat Genet. 2020;52(3):242–3.

    Article  CAS  PubMed  Google Scholar 

  67. Wang S, Qian F, Zheng Y, Ogundiran T, Ojengbede O, Zheng W, et al. Genetic variants demonstrating flip-flop phenomenon and breast cancer risk prediction among women of African ancestry. Breast Cancer Res Treat. 2018;168(3):703–12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Wang L, Desai H, Verma SS, Le A, Hausler R, Verma A, et al. Performance of polygenic risk scores for cancer prediction in a racially diverse academic biobank. Genet Med. 2022;24(3):601–9.

    Article  PubMed  Google Scholar 

  69. Wen W, Shu XO, Guo X, Cai Q, Long J, Bolla MK, et al. Prediction of breast cancer risk based on common genetic variants in women of East Asian ancestry. Breast Cancer Res. 2016;18(1):124.

    Article  PubMed  PubMed Central  Google Scholar 

  70. • Yang Y, Tao R, Shu X, Cai Q, Wen W, Gu K, et al. Incorporating polygenic risk scores and nongenetic risk factors for breast cancer risk prediction among Asian women. JAMA Netw Open. 2022;5(3):e2149030. A 111-SNP PRS derived in this study based on GWAS in Asian ancestry women performed well among Asian ancestry and European-ancestry women. Prediction performance was enhanced by including non-genetic risk factors as well.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Allman R, Dite GS, Hopper JL, Gordon O, Starlard-Davenport A, Chlebowski R, Kooperberg C. SNPs and breast cancer risk prediction for African American and Hispanic women. Breast Cancer Res Treat. 2015;154(3):583–9.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Palmer JR. Polygenic risk scores for breast cancer risk prediction: lessons learned and future opportunities. J Natl Cancer Inst. 2020;112(6):555–6.

    Article  PubMed  Google Scholar 

  73. Shraga R, Yarnall S, Elango S, Manoharan A, Rodriguez SA, Bristow SL, et al. Evaluating genetic ancestry and self-reported ethnicity in the context of carrier screening. BMC Genet. 2017;18(1):99.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Robson ME, Reiner AS, Brooks JD, et al. Association of common genetic variants with contralateral breast cancer risk in the wecare study. J Natl Cancer Inst. 2017;109(10):djx051. https://doi.org/10.1093/jnci/djx051.

  75. Electronic medical records and genomics workgroups. eMERGE Network. 2023. https://emerge-network.org/.

  76. Yanes T, Meiser B, Kaur R, Young MA, Mitchell PB, Scheepers-Joynt M, et al. Breast cancer polygenic risk scores: a 12-month prospective study of patient reported outcomes and risk management behavior. Genet Med. 2021;23(12):2316–23.

    Article  PubMed  Google Scholar 

  77. • Kim JO, Schaid DJ, Vachon CM, Cooke A, Couch FJ, Kim CA, et al. Impact of personalized genetic breast cancer risk estimation with polygenic risk scores on preventive endocrine therapy intention and uptake. Cancer Prev Res (Phila). 2021;14(2):175–84. The incorporation of PRS into breast cancer risk estimation impacted patient intent of taking endocrine therapy for breast cancer prevention.

    Article  PubMed  Google Scholar 

  78. Dixon P, Keeney E, Taylor JC, Wordsworth S, Martin RM. Can polygenic risk scores contribute to cost-effective cancer screening? A systematic review. Genet Med. 2022;24(8):1604–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Das Gupta K, Gregory G, Meiser B, Kaur R, Scheepers-Joynt M, McInerny S, et al. Communicating polygenic risk scores in the familial breast cancer clinic. Patient Educ Couns. 2021;104(10):2512–21.

    Article  PubMed  Google Scholar 

  80. Gregory G, Das Gupta K, Meiser B, Barlow-Stewart K, Geelan-Small P, Kaur R, et al. Polygenic risk in familial breast cancer: changing the dynamics of communicating genetic risk. J Genet Couns. 2022;31(1):120–9.

    Article  PubMed  Google Scholar 

  81. McGuinness M, Fassi E, Wang C, Hacking C, Ellis V. Breast cancer polygenic risk scores in the clinical cancer genetic counseling setting: current practices and impact on patient management. J Genet Couns. 2021;30(2):588–97.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA

    Kaitlin Demarest & Payal D. Shah

  2. Department of Medicine, Perelman Center for Advanced Medicine, 3400 Civic Center Blvd., Philadelphia, PA, 19104, USA

    Kaitlin Demarest

  3. Basser Center for BRCA, Abramson Cancer Center, University of Pennsylvania, Philadelphia, USA

    Payal D. Shah

Authors
  1. Kaitlin Demarest
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Payal D. Shah
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

K.D. and P.D.S. wrote the main manuscript text and P.D.S. prepared the figure. K.D. and P.D.S. reviewed the manuscript.

Corresponding author

Correspondence to Payal D. Shah.

Ethics declarations

Conflict of Interest

Dr. Demarest has nothing to disclose. Dr. Shah reports personal fees from Daiichi Sankyo, Gilead Biosciences, Biotheranostics, and Astra Zeneca for advisory board participation outside the submitted work.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Demarest, K., Shah, P.D. Polygenic Risk Scores for Breast Cancer. Curr Breast Cancer Rep 16, 269–277 (2024). https://doi.org/10.1007/s12609-024-00533-6

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12609-024-00533-6

Keywords

Search

Navigation