scholarly journals A Breast Tissue Protein Expression Profile Contributing to Early Parity-Induced Protection Against Breast Cancer

2015 ◽  
Vol 37 (5) ◽  
pp. 1671-1685 ◽  
Author(s):  
Christina Marie Gutierrez ◽  
Rebecca Lopez-Valdez ◽  
Ramadevi Subramani ◽  
Arunkumar Arumugam ◽  
Sushmita Nandy ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Protein Expression ◽  
Breast Tissue ◽  
Expression Profiles ◽  
Genomic Stability ◽  
Protective Effects ◽  
Nulliparous Women ◽  
Protein Expression Profiles

Background/Aims: Early parity reduces breast cancer risk, whereas, late parity and nulliparity increase breast cancer risk. Despite substantial efforts to understand the protective effects of early parity, the precise molecular circuitry responsible for these changes is not yet fully defined. Methods: Here, we have conducted the first study assessing protein expression profiles in normal breast tissue of healthy early parous, late parous, and nulliparous women. Breast tissue biopsies were obtained from 132 healthy parous and nulliparous volunteers. These samples were subjected to global protein expression profiling and immunohistochemistry. GeneSpring and MetaCore bioinformatics analysis software were used to identify protein expression profiles associated with early parity (low risk) versus late/nulliparity (high risk). Results: Early parity reduces expression of key proteins involved in mitogenic signaling pathways in breast tissue through down regulation of EGFR1/3, ESR1, AKT1, ATF, Fos, and SRC. Early parity is also characterized by greater genomic stability and reduced tissue inflammation based on differential expression of aurora kinases, p53, RAD52, BRCA1, MAPKAPK-2, ATF-1, ICAM1, and NF-kappaB compared to late and nulli parity. Conclusions: Early parity reduces basal cell proliferation in breast tissue, which translates to enhanced genomic stability, reduced cellular stress/inflammation, and thus reduced breast cancer risk.

HEIGHT AND WEIGHT, MAMMOGRAPHIC FEATURES OF BREAST TISSUE, AND BREAST CANCER RISK

1984 ◽  
Vol 119 (3) ◽  
pp. 371-381 ◽  
Author(s):  
JACQUES BRISSON ◽  
ALAN S. MORRISON ◽  
DANIEL B. KOPANS ◽  
NORMAN L. SADOWSKY ◽  
LESTER KALISHER ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Breast Tissue

scholarly journals DNA Methylation and Breast Cancer Risk: An Epigenome-Wide Study of Normal Breast Tissue and Blood

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3088 ◽  
Author(s):  
Kaoutar Ennour-Idrissi ◽  
Dzevka Dragic ◽  
Elissar Issa ◽  
Annick Michaud ◽  
Sue-Ling Chang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Breast Tissue ◽  
Normal Breast Tissue ◽  
Normal Breast ◽  
Breast Epithelium ◽  
Normal Breast Epithelium ◽  
Differentially Methylated Genes

Differential DNA methylation is a potential marker of breast cancer risk. Few studies have investigated DNA methylation changes in normal breast tissue and were largely confounded by cancer field effects. To detect methylation changes in normal breast epithelium that are causally associated with breast cancer occurrence, we used a nested case–control study design based on a prospective cohort of patients diagnosed with a primary invasive hormone receptor-positive breast cancer. Twenty patients diagnosed with a contralateral breast cancer (CBC) were matched (1:1) with 20 patients who did not develop a CBC on relevant risk factors. Differentially methylated Cytosine-phosphate-Guanines (CpGs) and regions in normal breast epithelium were identified using an epigenome-wide DNA methylation assay and robust linear regressions. Analyses were replicated in two independent sets of normal breast tissue and blood. We identified 7315 CpGs (FDR < 0.05), 52 passing strict Bonferroni correction (p < 1.22 × 10−7) and 43 mapping to known genes involved in metabolic diseases with significant enrichment (p < 0.01) of pathways involving fatty acids metabolic processes. Four differentially methylated genes were detected in both site-specific and regions analyses (LHX2, TFAP2B, JAKMIP1, SEPT9), and three genes overlapped all three datasets (POM121L2, KCNQ1, CLEC4C). Once validated, the seven differentially methylated genes distinguishing women who developed and who did not develop a sporadic breast cancer could be used to enhance breast cancer risk-stratification, and allow implementation of targeted screening and preventive strategies that would ultimately improve breast cancer prognosis.

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