Microsatellite polymorphism in the EGFR, NOTCH4 and E2F4 genes and their association with breast cancer risk

2012 ◽  
Vol 27 (3) ◽  
pp. 219-226 ◽  
Author(s):  
Ana González-Hernández ◽  
Luis Alberto Henríquez-Hernández ◽  
Antonio Cabrera De León ◽  
M. del Cristo Rodríguez-Pérez ◽  
Adolfo Murias-Rosales ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Breast Cancer Risk ◽  
General Population ◽  
Cancer Risk ◽  
Control Sample ◽  
Control Group ◽  
Polymorphic Microsatellites ◽  
Human Genes ◽  
Allelic Distribution

Background The sequences of many human genes that encode proteins involved in cancer contain polymorphic microsatellites. Variations in microsatellite length may constitute risk factors in several human diseases, a possibility that has been little explored in breast cancer. Among the genes that contain polymorphic microsatellites are EGFR, NOTCH4 and E2F4. The length of some of these microsatellites has been associated with breast cancer risk. Purpose and methods To determine whether the length of the microsatellites (CA)n in EGFR, (CTG)n in NOTCH4 and (AGC)n in E2F4 was associated with breast cancer risk, we genotyped these 3 microsatellites in 212 women with breast cancer and a control group of 308 women from the general population who did not have this disease. Results and conclusions The allelic distribution observed for the 3 microsatellites matched that found in other white populations, with the exception of some (AGC)n alleles in E2F4, which have not been described previously. The length of (CA)n in EGFR and (CTG)n in NOTCH4 was not associated with breast cancer (OR=0.99; 95% CI 0.59–1.37; p=0.619 and OR=1.08; 95% CI 0.71–1.65; p=0.725, respectively). Short alleles (<13 repeats) of (AGC)n in E2F4 were less frequent in women with cancer than in the control sample.

scholarly journals Asymmetric Dense Breast is an Independent Breast Cancer Risk Factor

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Alikhassi A ◽  
◽  
Shariatalavi R ◽  
Moradi B ◽  
◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Risk Factor ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Breast Cancer Risk Factor ◽  
Control Group ◽  
Control Groups ◽  
Cancer Risk Factor ◽  
And Control

Objectives: There are multiple known breast cancer risk factors, but most women with breast cancer do not have any of them, so there should be some other unknown risk factors. We hypothesized that asymmetric breast densities could be another breast cancer risk factor. Method: In this study, we defined two case and control groups with 136 women with breast cancer and 136 who did not have breast cancer, respectively. Any different type of asymmetry in either breast was recorded in both groups. Result: The frequency of focal asymmetry in cases was 47 (34.6%), which was statistically more significant than in the control group (28 (20.6%)) (p=0.010). There were three (2.9%) and five (3.7%) global asymmetries in the case and control groups, respectively (p=0.735). The frequency of one view asymmetry in the case and control groups was not significant (16 (11.8%) and 9 (6.6%) respectively) (p=0.142). In the case group, 59 (43.4%) women had at least one type of asymmetry, compared to 41 (30.1%) in the control group (p=0.02). We identify focal asymmetries (likelihood ratio, 1.215; p=0.027) is risk factors for breast cancer. Conclusion: Breast density asymmetry is a breast cancer risk factor that could be scored, thus enhancing risk stratification for screening and prevention.

Breast cancer risk factors and circulating anti-Müllerian hormone concentration in healthy premenopausal women

2021 ◽  
Author(s):  
Tess V Clendenen ◽  
Wenzhen Ge ◽  
Karen L Koenig ◽  
Yelena Afanasyeva ◽  
Claudia Agnoli ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Breast Cancer Risk ◽  
General Population ◽  
Cancer Risk ◽  
Breast Biopsy ◽  
Premenopausal Women ◽  
Inverse Association ◽  
Cancer Risk Factors ◽  
Breast Cancer Risk Factors

Abstract Context In a previous study we reported that anti-Müllerian hormone (AMH), a marker of ovarian reserve, is positively associated with breast cancer risk, consistent with other studies. Objective Assess whether risk factors for breast cancer are correlates of AMH concentration Design Cross-sectional Participants 3831 healthy premenopausal women (aged 21-57, 87% aged 35-49) Setting Ten cohort studies, general population Results Adjusting for age and cohort, we observed positive associations of AMH with age at menarche (p&lt;0.0001) and parity (p=0.0008), and an inverse association with hysterectomy/partial oophorectomy (p=0.0008). Compared to women of normal weight (BMI 18.5-24.9 kg/m 2, AMH was lower (relative geometric mean difference 27%, p&lt;0.0001) among women who were obese (BMI&gt;30). Current oral contraceptive use and current/former smoking were associated with lower AMH concentration than never use (40% and 12% lower, respectively, p&lt;0.0001). We observed higher AMH concentrations among women who had had a benign breast biopsy (15% higher, p=0.03), a surrogate for benign breast disease, an association that has not been reported. In analyses stratified by age (&lt;40/≥40), associations of AMH with BMI and oral contraceptives were similar in younger and older women, while associations with the other factors (menarche, parity, hysterectomy/partial oophorectomy, smoking, and benign breast biopsy) were limited to women ≥40 (p-interaction&lt;0.05). Conclusion This is the largest study of AMH and breast cancer risk factors among women from the general population (not presenting with infertility), and suggests that most of the associations are limited to women over 40, who are approaching menopause and whose AMH concentration is declining.

Potential breast cancer risk factors among Saudi women aged 19–50 years in Jeddah

2013 ◽  
Vol 88 (3) ◽  
pp. 165-170 ◽  
Author(s):  
Sulafa T. Al-Qutub ◽  
Rajaa M. Al-Raddadi ◽  
Bakr M. Bin Sadiq ◽  
Wafa Sait ◽  
Aboelkhair Al-Gahmi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Cancer Risk Factors ◽  
Saudi Women ◽  
Breast Cancer Risk Factors

scholarly journals A Metabolomics Analysis of Postmenopausal Breast Cancer Risk in the Cancer Prevention Study II

Metabolites ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 95
Author(s):  
Steven C. Moore ◽  
Kaitlyn M. Mazzilli ◽  
Joshua N. Sampson ◽  
Charles E. Matthews ◽  
Brian D. Carter ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Conditional Logistic Regression ◽  
Postmenopausal Breast Cancer ◽  
Sex Steroid ◽  
Birth Date ◽  
Blood Draw ◽  
Metabolomics Analysis

Breast cancer is the most common cancer in women, but its incidence can only be partially explained through established risk factors. Our aim was to use metabolomics to identify novel risk factors for breast cancer and to validate recently reported metabolite-breast cancer findings. We measured levels of 1275 metabolites in prediagnostic serum in a nested case-control study of 782 postmenopausal breast cancer cases and 782 matched controls. Metabolomics analysis was performed by Metabolon Inc using ultra-performance liquid chromatography and a Q-Exactive high resolution/accurate mass spectrometer. Controls were matched by birth date, date of blood draw, and race/ethnicity. Odds ratios (ORs) and 95% confidence intervals (CIs) of breast cancer at the 90th versus 10th percentile (modeled on a continuous basis) of metabolite levels were estimated using conditional logistic regression, with adjustment for age. Twenty-four metabolites were significantly associated with breast cancer risk at a false discovery rate <0.20. For the nine metabolites positively associated with risk, the ORs ranged from 1.75 (95% CI: 1.29–2.36) to 1.45 (95% CI: 1.13–1.85), and for the 15 metabolites inversely associated with risk, ORs ranged from 0.59 (95% CI: 0.43–0.79) to 0.69 (95% CI: 0.55–0.87). These metabolites largely comprised carnitines, glycerolipids, and sex steroid metabolites. Associations for three sex steroid metabolites validated findings from recent studies and the remainder were novel. These findings contribute to growing data on metabolite-breast cancer associations by confirming prior findings and identifying novel leads for future validation efforts.

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