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Parity-related molecular signatures and breast cancer subtypes by estrogen receptor status.

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.

SUBMITTER: Rotunno M

PROVIDER: S-EPMC4227137 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Parity-related molecular signatures and breast cancer subtypes by estrogen receptor status.

Rotunno Melissa M Sun Xuezheng X Figueroa Jonine J Sherman Mark E ME Garcia-Closas Montserrat M Meltzer Paul P Williams Tyisha T Schneider Sallie Smith SS Jerry D Joseph DJ Yang Xiaohong R XR Troester Melissa A MA

Breast cancer research : BCR 20140708 4

<h4>Introduction</h4>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.<h4>Methods</h4>We developed a parity signature by ...[more]

PMID: 25005139

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Project description:BackgroundTo evaluate the diagnostic performance of radiomic signatures extracted from contrast-enhanced magnetic resonance imaging (CE-MRI) for the assessment of breast cancer receptor status and molecular subtypes.MethodsOne hundred and forty-three patients with biopsy-proven breast cancer who underwent CE-MRI at 3 T were included in this IRB-approved HIPAA-compliant retrospective study. The training dataset comprised 91 patients (luminal A, n = 49; luminal B, n = 8; HER2-enriched, n = 11; triple negative, n = 23), while the validation dataset comprised 52 patients from a second institution (luminal A, n = 17; luminal B, n = 17; triple negative, n = 18). Radiomic analysis of manually segmented tumors included calculation of features derived from the first-order histogram (HIS), co-occurrence matrix (COM), run-length matrix (RLM), absolute gradient (GRA), autoregressive model (ARM), discrete Haar wavelet transform (WAV), and lesion geometry (GEO). Fisher, probability of error and average correlation (POE + ACC), and mutual information coefficients were used for feature selection. Linear discriminant analysis followed by k-nearest neighbor classification (with leave-one-out cross-validation) was used for pairwise radiomic-based separation of receptor status and molecular subtypes. Histopathology served as the standard of reference.ResultsIn the training dataset, radiomic signatures yielded the following accuracies > 80%: luminal B vs. luminal A, 84.2% (mainly based on COM features); luminal B vs. triple negative, 83.9% (mainly based on GEO features); luminal B vs. all others, 89% (mainly based on COM features); and HER2-enriched vs. all others, 81.3% (mainly based on COM features). Radiomic signatures were successfully validated in the separate validation dataset for luminal A vs. luminal B (79.4%) and luminal B vs. triple negative (77.1%).ConclusionsIn this preliminary study, radiomic signatures with CE-MRI enable the assessment of breast cancer receptor status and molecular subtypes with high diagnostic accuracy. These results need to be confirmed in future larger studies.

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Parity-related molecular signatures and breast cancer subtypes by estrogen receptor status.

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Parity-related molecular signatures and breast cancer subtypes by estrogen receptor status.

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