Genome-wide association study of germline variants and breast cancer-specific mortality

NBCS Collaborators

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44 Scopus citations

Abstract

BACKGROUND: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.

METHODS: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).

RESULTS: We did not find any variant associated with breast cancer-specific mortality at P < 5 × 10-8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10-7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10-7, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster.

CONCLUSIONS: We uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.

Original languageEnglish
Pages (from-to)647-657
Number of pages11
JournalBritish Journal of Cancer
Volume120
Issue number6
DOIs
StatePublished - Feb 2019

Keywords

  • Bayes Theorem
  • Breast Neoplasms/genetics
  • Chromosomes, Human, Pair 7
  • Female
  • Genetic Variation
  • Genome-Wide Association Study
  • Humans
  • Prognosis
  • Proportional Hazards Models
  • Receptors, Estrogen/genetics
  • White People/genetics

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