scholarly journals Association of gene variants in the TGF-beta signalling pathways with invasive breast cancer risk

2008 ◽  
Vol 10 (S2) ◽  
Author(s):  
S Scollen ◽  
AM Dunning ◽  
AC Bradshaw ◽  
R Hesketh ◽  
JC Metcalfe
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Invasive Breast Cancer ◽  
Signalling Pathways ◽  
Gene Variants ◽  
Tgf Beta

scholarly journals Endogenous hormones and risk of invasive breast cancer in pre- and post-menopausal women: findings from the UK Biobank

2021 ◽  
Author(s):  
Sandar Tin Tin ◽  
Gillian K. Reeves ◽  
Timothy J. Key
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Invasive Breast Cancer ◽  
Cox Regression ◽  
Menopausal Status ◽  
Endogenous Hormones ◽  
Uk Biobank ◽  
Menopausal Women ◽  
Post Menopausal

Abstract Background Some endogenous hormones have been associated with breast cancer risk, but the nature of these relationships is not fully understood. Methods UK Biobank was used. Hormone concentrations were measured in serum collected in 2006–2010, and in a repeat subsample (N ~ 5000) in 2012–13. Incident cancers were identified through data linkage. Cox regression models were used, and hazard ratios (HRs) corrected for regression dilution bias. Results Among 30,565 pre-menopausal and 133,294 post-menopausal women, 527 and 2,997, respectively, were diagnosed with invasive breast cancer during a median follow-up of 7.1 years. Cancer risk was positively associated with testosterone in post-menopausal women (HR per 0.5 nmol/L increment: 1.18; 95% CI: 1.14, 1.23) but not in pre-menopausal women (pheterogeneity = 0.03), and with IGF-1 (insulin-like growth factor-1) (HR per 5 nmol/L increment: 1.18; 1.02, 1.35 (pre-menopausal) and 1.07; 1.01, 1.12 (post-menopausal); pheterogeneity = 0.2), and inversely associated with SHBG (sex hormone-binding globulin) (HR per 30 nmol/L increment: 0.96; 0.79, 1.15 (pre-menopausal) and 0.89; 0.84, 0.94 (post-menopausal); pheterogeneity = 0.4). Oestradiol, assessed only in pre-menopausal women, was not associated with risk, but there were study limitations for this hormone. Conclusions This study confirms associations of testosterone, IGF-1 and SHBG with breast cancer risk, with heterogeneity by menopausal status for testosterone.

scholarly journals Relation of Quantitative Histologic and Radiologic Breast Tissue Composition Metrics with Invasive Breast Cancer Risk

2021 ◽  
Author(s):  
Mustapha Abubakar ◽  
Shaoqi Fan ◽  
Erin Aiello Bowles ◽  
Lea Widemann ◽  
Máire A Duggan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Invasive Breast Cancer ◽  
Statistical Tests ◽  
Predictive Biomarkers ◽  
Breast Cancer Diagnosis ◽  
Breast Cancer Risk Factor ◽  
Computer Assisted ◽  
Tissue Composition

Abstract Background Benign breast disease (BBD) is a strong breast cancer risk factor but identifying patients that might develop invasive breast cancer remains a challenge. Methods By applying machine-learning to digitized H&E-stained biopsies and computer-assisted thresholding to mammograms obtained circa BBD diagnosis, we generated quantitative tissue composition metrics and determined their association with future invasive breast cancer diagnosis. Archival breast biopsies and mammograms were obtained for women (18-86 years of age) in a case-control study, nested within a cohort of 15,395 BBD patients from Kaiser Permanente Northwest (1970-2012), followed through mid-2015. Cases (n = 514) who developed incident invasive breast cancer and controls (n = 514) were matched on BBD diagnosis age and plan membership duration. All statistical tests were 2-sided. Results Increasing epithelial area on the BBD biopsy was associated with increasing breast cancer risk (Odds ratio [OR]Q4 vs Q1=1.85, 95% confidence interval [CI] = 1.13-3.04; Ptrend=0.02). Conversely, increasing stroma was associated with decreased risk in non-proliferative, but not proliferative, BBD (Pheterogeneity=0.002). Increasing epithelium-to-stroma proportion [ORQ4 vs Q1=2.06, 95% CI = 1.28-3.33; Ptrend=0.002) and percent mammographic density (MBD) (ORQ4 vs Q1=2.20, 95% CI = 1.20-4.03; Ptrend=0.01) were independently and strongly predictive of increased breast cancer risk. In combination, women with high epithelium-to-stroma proportion/high MBD had substantially higher risk than those with low epithelium-to-stroma proportion/low MBD [OR = 2.27, 95% CI = 1.27-4.06; Ptrend=0.005), particularly among women with non-proliferative (Ptrend=0.01) versus proliferative (Ptrend=0.33) BBD. Conclusion Among BBD patients, increasing epithelium-to-stroma proportion on BBD biopsies and percent MBD at BBD diagnosis were independently and jointly associated with increasing breast cancer risk. These findings were particularly striking for women with non-proliferative disease (comprising approximately 70% of all BBD patients), for whom relevant predictive biomarkers are lacking.

scholarly journals Considerations When Using Breast Cancer Risk Models for Women with Negative BRCA1/BRCA2 Mutation Results

2019 ◽  
Vol 112 (4) ◽  
pp. 418-422
Author(s):  
Robert J MacInnis ◽  
Yuyan Liao ◽  
Julia A Knight ◽  
Roger L Milne ◽  
Alice S Whittemore ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Invasive Breast Cancer ◽  
Disease Incidence ◽  
Brca2 Mutation ◽  
Estimation Algorithm ◽  
Breast Cancers ◽  
Risk Models ◽  
Replication Studies

Abstract The performance of breast cancer risk models for women with a family history but negative BRCA1 and/or BRCA2 mutation test results is uncertain. We calculated the cumulative 10-year invasive breast cancer risk at cohort entry for 14 657 unaffected women (96.1% had an affected relative) not known to carry BRCA1 or BRCA2 mutations at baseline using three pedigree-based models (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, BRCAPRO, and International Breast Cancer Intervention Study). During follow-up, 482 women were diagnosed with invasive breast cancer. Mutation testing was conducted independent of incident cancers. All models underpredicted risk by 26.3%–56.7% for women who tested negative but whose relatives had not been tested (n = 1363; 63 breast cancers). Although replication studies with larger sample sizes are needed, until these models are recalibrated for women who test negative and have no relatives tested, caution should be used when considering changing the breast cancer risk management intensity of such women based on risk estimates from these models.

scholarly journals Recalibration of the Gail model for predicting invasive breast cancer risk in Spanish women: a population-based cohort study

2013 ◽  
Vol 138 (1) ◽  
pp. 249-259 ◽  
Author(s):  
Roberto Pastor-Barriuso ◽  
Nieves Ascunce ◽  
María Ederra ◽  
Nieves Erdozáin ◽  
Alberto Murillo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cohort Study ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Invasive Breast Cancer ◽  
Population Based ◽  
Gail Model ◽  
Spanish Women

Metformin and breast cancer risk: A meta-analysis and critical literature review.

2012 ◽  
Vol 30 (27_suppl) ◽  
pp. 25-25
Author(s):  
Nananda Col ◽  
Leslie Ochs ◽  
Vicky Springmann ◽  
Aaron K Aragaki ◽  
Rowan T. Chlebowski
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Literature Review ◽  
Cancer Incidence ◽  
Invasive Breast Cancer ◽  
Meta Analysis ◽  
Breast Cancer Incidence ◽  
Cochrane Library ◽  
Study Quality

25 Background: Observational studies have suggested that metformin, commonly used for diabetes treatment that increases insulin sensitivity and improves glycemic control, decreases the incidence of several common cancers. However, findings regarding metformin and breast cancer incidence have been mixed. To explore this issue, a systematic literature review and meta-analysis were performed with a focus on potential biases. Methods: We conducted a comprehensive literature search for all pertinent studies addressing metformin use and breast cancer risk by searching Pub Med, Cochrane Library, Scopus (which includes Embase, ISI Web of Science) using the Mesh terms: "metformin" or "biguanides" or "diabetes mellitus, type 2/therapy" and "cancer" or "neoplasms". When multiple hazard ratios (HR) or odds ratio (OR) were reported, the most adjusted estimate was used in the base-case analysis. We pooled the adjusted HR using and performed sensitivity analyses on duration of metformin use (> or < 3 years use), study quality (assessed using the GRADE system), and initial observation year of the cohort (before vs after 1997). Results: From a total of 421 citations, 13 full-text articles were considered, and 7 independent studies were included. All were observational (4 cohort and 3 case control). Our combined OR for metformin association with invasive breast cancer of all 7 studies was 0.83 (95% CI, 0.71-0.97). Funnel plot analyses did not suggest publication bias. Stronger associations were found when analyses were limited to studies estimating the impact of longer metformin duration (OR = 0.75. 95% CI, 0.62-0.91) or among studies that began observing their cohort before 1997 (OR=0.68. 95% CI, 0.55-0.84). Stratification according to study quality did not affect the combined OR but higher quality studies had smaller CI and achieved statistical significance. Interpretation is limited by the observational nature of reports and different comparison groups. Conclusions: Our analyses support a protective effect of metformin on invasive breast cancer incidence among postmenopausal women with diabetes. Clinical trials are needed to determine whether metformin reduces breast cancer risk.

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