Parity-related molecular signatures and breast cancer subtypes by estrogen receptor status.
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Embargo End Date
ICR Authors
Authors
Rotunno, M
Sun, X
Figueroa, J
Sherman, ME
Garcia-Closas, M
Meltzer, P
Williams, T
Schneider, SS
Jerry, DJ
Yang, XR
Troester, MA
Sun, X
Figueroa, J
Sherman, ME
Garcia-Closas, M
Meltzer, P
Williams, T
Schneider, SS
Jerry, DJ
Yang, XR
Troester, MA
Document Type
Journal Article
Date
2014-07-08
Date Accepted
2014-06-25
Abstract
INTRODUCTION: Relationships of parity with breast cancer risk are complex. Parity is associated with decreased risk of postmenopausal hormone receptor-positive breast tumors, but may increase risk for basal-like breast cancers and early-onset tumors. Characterizing parity-related gene expression patterns in normal breast and breast tumor tissues may improve understanding of the biological mechanisms underlying this complex pattern of risk. METHODS: We developed a parity signature by analyzing microRNA microarray data from 130 reduction mammoplasty (RM) patients (54 nulliparous and 76 parous). This parity signature, together with published parity signatures, was evaluated in gene expression data from 150 paired tumors and adjacent benign breast tissues from the Polish Breast Cancer Study, both overall and by tumor estrogen receptor (ER) status. RESULTS: We identified 251 genes significantly upregulated by parity status in RM patients (parous versus nulliparous; false discovery rate = 0.008), including genes in immune, inflammation and wound response pathways. This parity signature was significantly enriched in normal and tumor tissues of parous breast cancer patients, specifically in ER-positive tumors. CONCLUSIONS: Our data corroborate epidemiologic data, suggesting that the etiology and pathogenesis of breast cancers vary by ER status, which may have implications for developing prevention strategies for these tumors.
Citation
Breast cancer research : BCR, 2014, 16 (4), pp. R74 - ?
DOI
Source Title
Publisher
BMC
ISSN
1465-5411
eISSN
1465-542X
Collections
Research Team
Molecular Epidemiology