Literature DB >> 22127114

BRCA and beyond: a genome-first approach to familial breast cancer risk assessment.

Alison H Trainer1, Ella Thompson, Paul A James.   

Abstract

Breast cancer affects around 12% of women in the Western world, but individual lifetime risks vary significantly within any population. Currently, familial cancer services assess and manage familial breast cancer risk based on the presence of a family history of the condition or the identification of high-risk breast cancer susceptibility alleles. This model of clinical care provides an accurate genetic risk assessment for only the minority of families referred to these services. With increasing access to technologies that interrogate human variation at the genome-wide level, it is envisaged that familial breast cancer risk assessments will in the future assume a genome-first approach. This review discusses and highlights the different components of familial breast cancer risk, which will need to be integrated to make this new model of clinical risk assessment possible.

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Year:  2011        PMID: 22127114

Source DB:  PubMed          Journal:  Discov Med        ISSN: 1539-6509            Impact factor:   2.970


  4 in total

1.  iPrevent®: a tailored, web-based, decision support tool for breast cancer risk assessment and management.

Authors:  Ian M Collins; Adrian Bickerstaffe; Thilina Ranaweera; Sanjaya Maddumarachchi; Louise Keogh; Jon Emery; G Bruce Mann; Phyllis Butow; Prue Weideman; Emma Steel; Alison Trainer; Mathias Bressel; John L Hopper; Jack Cuzick; Antonis C Antoniou; Kelly-Anne Phillips
Journal:  Breast Cancer Res Treat       Date:  2016-02-24       Impact factor: 4.872

2.  Characterization of mutations in BRCA1/2 and the relationship with clinic-pathological features of breast cancer in a hereditarily high-risk sample of chinese population.

Authors:  Min Fang; Li Zhu; Hengyu Li; Xizhou Li; Yanmei Wu; Kainan Wu; Jian Lin; Yuan Sheng; Yue Yu
Journal:  Oncol Lett       Date:  2017-12-29       Impact factor: 2.967

3.  The Clinical and Psychosocial Outcomes for Women Who Received Unexpected Clinically Actionable Germline Information Identified through Research: An Exploratory Sequential Mixed-Methods Comparative Study.

Authors:  Laura E Forrest; Rowan Forbes Shepherd; Erin Tutty; Angela Pearce; Ian Campbell; Lisa Devereux; Alison H Trainer; Paul A James; Mary-Anne Young
Journal:  J Pers Med       Date:  2022-07-07

4.  Prognostic Genes of Breast Cancer Identified by Gene Co-expression Network Analysis.

Authors:  Jianing Tang; Deguang Kong; Qiuxia Cui; Kun Wang; Dan Zhang; Yan Gong; Gaosong Wu
Journal:  Front Oncol       Date:  2018-09-11       Impact factor: 6.244

  4 in total

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