Literature DB >> 25727315

From candidate gene studies to GWAS and post-GWAS analyses in breast cancer.

Laura Fachal1, Alison M Dunning2.   

Abstract

There are now more than 90 established breast cancer risk loci, with 57 new ones, revealed through genome-wide-association studies (GWAS) during the last two years. Established high, moderate and low penetrance genetic variants currently explain ∼49% of familial breast cancer risk. GWAS-discovered variants account for 14%, and it is estimated that another 1000 yet-to-be-discovered loci could contribute an additional ∼14% of familial risk. Polygenic risk scores can already be used to stratify breast cancer risk in the female population and could improve the targeting of mammographic screening programmes, which are at present largely based on age-specific risks. Fine-scale mapping and functional analyses are revealing candidate causal variants and the molecular mechanisms by which GWAS-hits may act. Better-powered GWAS and genome-wide sequencing projects are likely to continue identifying new breast cancer causal variants.
Copyright © 2015 Elsevier Ltd. All rights reserved.

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Year:  2015        PMID: 25727315     DOI: 10.1016/j.gde.2015.01.004

Source DB:  PubMed          Journal:  Curr Opin Genet Dev        ISSN: 0959-437X            Impact factor:   5.578


  36 in total

1.  Genetic variants demonstrating flip-flop phenomenon and breast cancer risk prediction among women of African ancestry.

Authors:  Shengfeng Wang; Frank Qian; Yonglan Zheng; Temidayo Ogundiran; Oladosu Ojengbede; Wei Zheng; William Blot; Katherine L Nathanson; Anselm Hennis; Barbara Nemesure; Stefan Ambs; Olufunmilayo I Olopade; Dezheng Huo
Journal:  Breast Cancer Res Treat       Date:  2018-01-04       Impact factor: 4.872

2.  ERα Binding by Transcription Factors NFIB and YBX1 Enables FGFR2 Signaling to Modulate Estrogen Responsiveness in Breast Cancer.

Authors:  Thomas M Campbell; Mauro A A Castro; Kelin Gonçalves de Oliveira; Bruce A J Ponder; Kerstin B Meyer
Journal:  Cancer Res       Date:  2017-11-27       Impact factor: 12.701

3.  [Leukocyte count of puerperal sows].

Authors:  D Mäde; G Wujanz
Journal:  Berl Munch Tierarztl Wochenschr       Date:  1996-09       Impact factor: 0.328

4.  Breast Cancer-Related Low Penetrance Genes.

Authors:  Daehee Kang; Ji-Yeob Choi
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

5.  Recommendations on breast cancer screening and prevention in the context of implementing risk stratification: impending changes to current policies.

Authors:  J Gagnon; E Lévesque; F Borduas; J Chiquette; C Diorio; N Duchesne; M Dumais; L Eloy; W Foulkes; N Gervais; L Lalonde; B L'Espérance; S Meterissian; L Provencher; J Richard; C Savard; I Trop; N Wong; B M Knoppers; J Simard
Journal:  Curr Oncol       Date:  2016-12-21       Impact factor: 3.677

6.  MCF-7 as a Model for Functional Analysis of Breast Cancer Risk Variants.

Authors:  Alix Booms; Gerhard A Coetzee; Steven E Pierce
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-07-10       Impact factor: 4.254

7.  Omics, big data and machine learning as tools to propel understanding of biological mechanisms and to discover novel diagnostics and therapeutics.

Authors:  Nikolaos Perakakis; Alireza Yazdani; George E Karniadakis; Christos Mantzoros
Journal:  Metabolism       Date:  2018-08-08       Impact factor: 8.694

8.  Individual patient data meta-analysis shows a significant association between the ATM rs1801516 SNP and toxicity after radiotherapy in 5456 breast and prostate cancer patients.

Authors:  Christian Nicolaj Andreassen; Barry S Rosenstein; Sarah L Kerns; Harry Ostrer; Dirk De Ruysscher; Jamie A Cesaretti; Gillian C Barnett; Alison M Dunning; Leila Dorling; Catharine M L West; Neil G Burnet; Rebecca Elliott; Charlotte Coles; Emma Hall; Laura Fachal; Ana Vega; Antonio Gómez-Caamaño; Christopher J Talbot; R Paul Symonds; Kim De Ruyck; Hubert Thierens; Piet Ost; Jenny Chang-Claude; Petra Seibold; Odilia Popanda; Marie Overgaard; David Dearnaley; Matthew R Sydes; David Azria; Christine Anne Koch; Matthew Parliament; Michael Blackshaw; Michael Sia; Maria J Fuentes-Raspall; Teresa Ramon Y Cajal; Agustin Barnadas; Danny Vesprini; Sara Gutiérrez-Enríquez; Meritxell Mollà; Orland Díez; John R Yarnold; Jens Overgaard; Søren M Bentzen; Jan Alsner
Journal:  Radiother Oncol       Date:  2016-07-18       Impact factor: 6.280

9.  Population-level diversity in the association of genetic polymorphisms of one-carbon metabolism with breast cancer risk.

Authors:  Shaik Mohammad Naushad; Chandrasekhar Divya; M Janaki Ramaiah; Tajamul Hussain; Salman A Alrokayan; Vijay Kumar Kutala
Journal:  J Community Genet       Date:  2016-08-19

10.  Evaluation of potential regulatory function of breast cancer risk locus at 6q25.1.

Authors:  Yaqiong Sun; Chuanzhong Ye; Xingyi Guo; Wanqing Wen; Jirong Long; Yu-Tang Gao; Xiao Ou Shu; Wei Zheng; Qiuyin Cai
Journal:  Carcinogenesis       Date:  2015-12-08       Impact factor: 4.944

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