Literature DB >> 16563094

Risk prediction models for familial breast cancer.

Antonis C Antoniou1, Douglas F Easton.   

Abstract

A positive family history of breast cancer, reflecting genetic susceptibility, is one of the strongest risk factors for the disease. A number of breast cancer susceptibility genes have been identified to date, with the most important being BRCA1 and BRCA2. Risk prediction models can be used to identify individuals likely to carry BRCA1 and BRCA2 mutations and individuals at high risk of developing the disease. This information can then be used to target genetic testing, screening and interventions more effectively. In this article, the authors review the risk models that have been developed for familial breast cancer and discuss their applicability, strengths and weaknesses, and present examples of classifying women into risk categories according to the predictions by the various models. The review concludes with a discussion of the ways in which risk models could be improved in the immediate- and long-term future.

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Year:  2006        PMID: 16563094     DOI: 10.2217/14796694.2.2.257

Source DB:  PubMed          Journal:  Future Oncol        ISSN: 1479-6694            Impact factor:   3.404


  36 in total

Review 1.  The inherited genetics of ovarian and endometrial cancer.

Authors:  Simon A Gayther; Paul D P Pharoah
Journal:  Curr Opin Genet Dev       Date:  2010-04-24       Impact factor: 5.578

2.  Breast cancer susceptibility variants alter risk in familial ovarian cancer.

Authors:  A Latif; H J McBurney; S A Roberts; F Lalloo; A Howell; D G Evans; W G Newman
Journal:  Fam Cancer       Date:  2010-12       Impact factor: 2.375

3.  A KRAS-variant in ovarian cancer acts as a genetic marker of cancer risk.

Authors:  Elena Ratner; Lingeng Lu; Marta Boeke; Rachel Barnett; Sunitha Nallur; Lena J Chin; Cory Pelletier; Rachel Blitzblau; Renata Tassi; Trupti Paranjape; Pei Hui; Andrew K Godwin; Herbert Yu; Harvey Risch; Thomas Rutherford; Peter Schwartz; Alessandro Santin; Ellen Matloff; Daniel Zelterman; Frank J Slack; Joanne B Weidhaas
Journal:  Cancer Res       Date:  2010-07-20       Impact factor: 12.701

4.  Genetic variation in insulin-like growth factor 2 may play a role in ovarian cancer risk.

Authors:  Celeste Leigh Pearce; Jennifer A Doherty; David J Van Den Berg; Kirsten Moysich; Chris Hsu; Kara L Cushing-Haugen; David V Conti; Susan J Ramus; Aleksandra Gentry-Maharaj; Usha Menon; Simon A Gayther; Paul D P Pharoah; Honglin Song; Susanne K Kjaer; Estrid Hogdall; Claus Hogdall; Alice S Whittemore; Valerie McGuire; Weiva Sieh; Jacek Gronwald; Krzysztof Medrek; Anna Jakubowska; Jan Lubinski; Georgia Chenevix-Trench; Jonathan Beesley; Penelope M Webb; Andrew Berchuck; Joellen M Schildkraut; Edwin S Iversen; Patricia G Moorman; Christopher K Edlund; Daniel O Stram; Malcolm C Pike; Roberta B Ness; Mary Anne Rossing; Anna H Wu
Journal:  Hum Mol Genet       Date:  2011-03-21       Impact factor: 6.150

5.  Association between single-nucleotide polymorphisms in hormone metabolism and DNA repair genes and epithelial ovarian cancer: results from two Australian studies and an additional validation set.

Authors:  Jonathan Beesley; Susan J Jordan; Amanda B Spurdle; Honglin Song; Susan J Ramus; Suzanne Kruger Kjaer; Estrid Hogdall; Richard A DiCioccio; Valerie McGuire; Alice S Whittemore; Simon A Gayther; Paul D P Pharoah; Penelope M Webb; Georgia Chenevix-Trench
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2007-12       Impact factor: 4.254

6.  Role of BRCA1 and BRCA2 gene mutations in epithelial ovarian cancer in Indian population: a pilot study.

Authors:  Shikha Sharma; Shalini Rajaram; Tusha Sharma; Neerja Goel; Sarla Agarwal; Basu Dev Banerjee
Journal:  Int J Biochem Mol Biol       Date:  2014-05-15

7.  A risk prediction algorithm based on family history and common genetic variants: application to prostate cancer with potential clinical impact.

Authors:  Robert J Macinnis; Antonis C Antoniou; Rosalind A Eeles; Gianluca Severi; Ali Amin Al Olama; Lesley McGuffog; Zsofia Kote-Jarai; Michelle Guy; Lynne T O'Brien; Amanda L Hall; Rosemary A Wilkinson; Emma Sawyer; Audrey T Ardern-Jones; David P Dearnaley; Alan Horwich; Vincent S Khoo; Christopher C Parker; Robert A Huddart; Nicholas Van As; Margaret R McCredie; Dallas R English; Graham G Giles; John L Hopper; Douglas F Easton
Journal:  Genet Epidemiol       Date:  2011-07-18       Impact factor: 2.135

8.  Incorporating tumour pathology information into breast cancer risk prediction algorithms.

Authors:  Nasim Mavaddat; Timothy R Rebbeck; Sunil R Lakhani; Douglas F Easton; Antonis C Antoniou
Journal:  Breast Cancer Res       Date:  2010-05-18       Impact factor: 6.466

9.  Tagging single-nucleotide polymorphisms in candidate oncogenes and susceptibility to ovarian cancer.

Authors:  L Quaye; H Song; S J Ramus; A Gentry-Maharaj; E Høgdall; R A DiCioccio; V McGuire; A H Wu; D J Van Den Berg; M C Pike; E Wozniak; J A Doherty; M A Rossing; R B Ness; K B Moysich; C Høgdall; J Blaakaer; D F Easton; B A J Ponder; I J Jacobs; U Menon; A S Whittemore; S Krüger-Kjaer; C L Pearce; P D P Pharoah; S A Gayther
Journal:  Br J Cancer       Date:  2009-02-24       Impact factor: 7.640

10.  Polymorphisms in NF-kappaB inhibitors and risk of epithelial ovarian cancer.

Authors:  Kristin L White; Robert A Vierkant; Catherine M Phelan; Brooke L Fridley; Stephanie Anderson; Keith L Knutson; Joellen M Schildkraut; Julie M Cunningham; Linda E Kelemen; V Shane Pankratz; David N Rider; Mark Liebow; Lynn C Hartmann; Thomas A Sellers; Ellen L Goode
Journal:  BMC Cancer       Date:  2009-06-06       Impact factor: 4.430

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