Literature DB >> 25342391

The role of genome sequencing in personalized breast cancer prevention.

Weiva Sieh1, Joseph H Rothstein1, Valerie McGuire1, Alice S Whittemore2.   

Abstract

BACKGROUND: There is uncertainty about the benefits of using genome-wide sequencing to implement personalized preventive strategies at the population level, with some projections suggesting little benefit. We used data for all currently known breast cancer susceptibility variants to assess the benefits and harms of targeting preventive efforts to a population subgroup at highest genomic risk of breast cancer.
METHODS: We used the allele frequencies and effect sizes of 86 known breast cancer variants to estimate the population distribution of breast cancer risks and evaluate the strategy of targeting preventive efforts to those at highest risk. We compared the efficacy of this strategy with that of a "best-case" strategy based on a risk distribution estimated from breast cancer concordance in monozygous twins, and with strategies based on previously estimated risk distributions.
RESULTS: Targeting those in the top 25% of the risk distribution would include approximately half of all future breast cancer cases, compared with 70% captured by the best-case strategy and 35% based on previously known variants. In addition, current evidence suggests that reducing exposure to modifiable nongenetic risk factors will have greatest benefit for those at highest genetic risk.
CONCLUSIONS: These estimates suggest that personalized breast cancer preventive strategies based on genome sequencing will bring greater gains in disease prevention than previously projected. Moreover, these gains will increase with increased understanding of the genetic etiology of breast cancer. IMPACT: These results support the feasibility of using genome-wide sequencing to target the women who would benefit from mammography screening. ©2014 American Association for Cancer Research.

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Year:  2014        PMID: 25342391      PMCID: PMC4221442          DOI: 10.1158/1055-9965.EPI-14-0559

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  18 in total

1.  Polygenic susceptibility to breast cancer and implications for prevention.

Authors:  Paul D P Pharoah; Antonis Antoniou; Martin Bobrow; Ron L Zimmern; Douglas F Easton; Bruce A J Ponder
Journal:  Nat Genet       Date:  2002-03-04       Impact factor: 38.330

2.  MutYH mutation carriers have increased breast cancer risk.

Authors:  Gad Rennert; Flavio Lejbkowicz; Ilana Cohen; Mila Pinchev; Hedy S Rennert; Ofra Barnett-Griness
Journal:  Cancer       Date:  2011-09-22       Impact factor: 6.860

3.  Polygenes, risk prediction, and targeted prevention of breast cancer.

Authors:  Paul D P Pharoah; Antonis C Antoniou; Douglas F Easton; Bruce A J Ponder
Journal:  N Engl J Med       Date:  2008-06-26       Impact factor: 91.245

Review 4.  Genetic polymorphisms and breast cancer risk: evidence from meta-analyses, pooled analyses, and genome-wide association studies.

Authors:  Sihua Peng; Bingjian Lü; Wenjing Ruan; Yimin Zhu; Hongqiang Sheng; Maode Lai
Journal:  Breast Cancer Res Treat       Date:  2011-03-29       Impact factor: 4.872

5.  The predictive capacity of personal genome sequencing.

Authors:  Nicholas J Roberts; Joshua T Vogelstein; Giovanni Parmigiani; Kenneth W Kinzler; Bert Vogelstein; Victor E Velculescu
Journal:  Sci Transl Med       Date:  2012-04-02       Impact factor: 17.956

Review 6.  Genetic susceptibility to breast cancer.

Authors:  Nasim Mavaddat; Antonis C Antoniou; Douglas F Easton; Montserrat Garcia-Closas
Journal:  Mol Oncol       Date:  2010-05-21       Impact factor: 6.603

7.  Germline mutations in breast and ovarian cancer pedigrees establish RAD51C as a human cancer susceptibility gene.

Authors:  Alfons Meindl; Heide Hellebrand; Constanze Wiek; Verena Erven; Barbara Wappenschmidt; Dieter Niederacher; Marcel Freund; Peter Lichtner; Linda Hartmann; Heiner Schaal; Juliane Ramser; Ellen Honisch; Christian Kubisch; Hans E Wichmann; Karin Kast; Helmut Deissler; Christoph Engel; Bertram Müller-Myhsok; Kornelia Neveling; Marion Kiechle; Christopher G Mathew; Detlev Schindler; Rita K Schmutzler; Helmut Hanenberg
Journal:  Nat Genet       Date:  2010-04-18       Impact factor: 38.330

8.  Analysis of RAD51C germline mutations in high-risk breast and ovarian cancer families and ovarian cancer patients.

Authors:  Ella R Thompson; Samantha E Boyle; Julie Johnson; Georgina L Ryland; Sarah Sawyer; David Y H Choong; Georgia Chenevix-Trench; Alison H Trainer; Geoffrey J Lindeman; Gillian Mitchell; Paul A James; Ian G Campbell
Journal:  Hum Mutat       Date:  2011-11-04       Impact factor: 4.878

9.  Public health genomics and personalized prevention: lessons from the COGS project.

Authors:  N Pashayan; A Hall; S Chowdhury; T Dent; P D P Pharoah; H Burton
Journal:  J Intern Med       Date:  2013-11       Impact factor: 8.989

10.  Common polygenic variation contributes to risk of schizophrenia and bipolar disorder.

Authors:  Shaun M Purcell; Naomi R Wray; Jennifer L Stone; Peter M Visscher; Michael C O'Donovan; Patrick F Sullivan; Pamela Sklar
Journal:  Nature       Date:  2009-07-01       Impact factor: 49.962

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  8 in total

Review 1.  Optimizing mouse models for precision cancer prevention.

Authors:  Clémentine Le Magnen; Aditya Dutta; Cory Abate-Shen
Journal:  Nat Rev Cancer       Date:  2016-02-19       Impact factor: 60.716

Review 2.  Primary care providers' cancer genetic testing-related knowledge, attitudes, and communication behaviors: A systematic review and research agenda.

Authors:  Jada G Hamilton; Ekland Abdiwahab; Heather M Edwards; Min-Lin Fang; Andrew Jdayani; Erica S Breslau
Journal:  J Gen Intern Med       Date:  2016-12-19       Impact factor: 5.128

3.  Information Topics of Greatest Interest for Return of Genome Sequencing Results among Women Diagnosed with Breast Cancer at a Young Age.

Authors:  Joann Seo; Jennifer Ivanovich; Melody S Goodman; Barbara B Biesecker; Kimberly A Kaphingst
Journal:  J Genet Couns       Date:  2016-08-20       Impact factor: 2.537

4.  Acceptability of electronic healthcare predictive analytics for HIV prevention: a qualitative study with men who have sex with men in New York City.

Authors:  Jennifer J Mootz; Henry Evans; Jack Tocco; Christian Vivar Ramon; Peter Gordon; Milton L Wainberg; Michael T Yin
Journal:  Mhealth       Date:  2020-04-05

Review 5.  Do Health Professionals Need Additional Competencies for Stratified Cancer Prevention Based on Genetic Risk Profiling?

Authors:  Susmita Chowdhury; Lidewij Henneman; Tom Dent; Alison Hall; Alice Burton; Paul Pharoah; Nora Pashayan; Hilary Burton
Journal:  J Pers Med       Date:  2015-06-09

Review 6.  Cancer prevention: state of the art and future prospects.

Authors:  I Valle; D Tramalloni; N L Bragazzi
Journal:  J Prev Med Hyg       Date:  2015-06-10

7.  How, who, and when: preferences for delivery of genome sequencing results among women diagnosed with breast cancer at a young age.

Authors:  Kimberly A Kaphingst; Jennifer Ivanovich; Ashley Elrick; Rebecca Dresser; Cindy Matsen; Melody S Goodman
Journal:  Mol Genet Genomic Med       Date:  2016-10-24       Impact factor: 2.183

8.  Polygenic prediction of breast cancer: comparison of genetic predictors and implications for risk stratification.

Authors:  Kristi Läll; Maarja Lepamets; Marili Palover; Tõnu Esko; Andres Metspalu; Neeme Tõnisson; Peeter Padrik; Reedik Mägi; Krista Fischer
Journal:  BMC Cancer       Date:  2019-06-10       Impact factor: 4.430

  8 in total

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