Background: A recent genome-wide association study identified single-nucleotide polymorphism (SNP) 2q35-rs13387042 as a marker of susceptibility to estrogen receptor (ER)-positive breast cancer. We attempted to confirm this association using the Breast Cancer Association Consortium.
Methods: 2q35-rs13387042 SNP was genotyped for 31 510 women with invasive breast cancer, 1101 women with ductal carcinoma in situ, and 35 969 female control subjects from 25 studies. Odds ratios (ORs) were estimated by logistic regression, adjusted for study. Heterogeneity in odds ratios by each of age, ethnicity, and study was assessed by fitting interaction terms. Heterogeneity by each of invasiveness, family history, bilaterality, and hormone receptor status was assessed by subclassifying case patients and applying polytomous logistic regression. All statistical tests were two-sided.
Results: We found strong evidence of association between rs13387042 and breast cancer in white women of European origin (per-allele OR = 1.12, 95% confidence interval [CI] = 1.09 to 1.15; P(trend) = 1.0 x 10(-19)). The odds ratio was lower than that previously reported (P = .02) and did not vary by age or ethnicity (all P > or = .2). However, it was higher when the analysis was restricted to case patients who were selected for a strong family history (P = .02). An association was observed for both ER-positive (OR = 1.14, 95% CI = 1.10 to 1.17; P = 10(-15)) and ER-negative disease (OR = 1.10, 95% CI = 1.04 to 1.15; P = .0003) and both progesterone receptor (PR)-positive (OR = 1.15, 95% CI = 1.11 to 1.19; P = 5 x 10(-14)) and PR-negative disease (OR = 1.10, 95% CI = 1.06 to 1.15; P = .00002).
Conclusion: The rs13387042 is associated with both ER-positive and ER-negative breast cancer in European women.
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http://dx.doi.org/10.1093/jnci/djp167 | DOI Listing |
Biomed Phys Eng Express
January 2025
School of Engineering and Computing, University of the West of Scotland, University of the West of Scotland - Paisley Campus, Paisley PA1 2BE, UK, City, Paisley, PA1 2BE, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.
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New College of Florida, Sarasota, FL, United States.
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View Article and Find Full Text PDFInt J Radiat Biol
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Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei City, Taiwan.
Purpose: Breast cancer ranks as the most prevalent cancer in women, characterized by heightened fatty acid synthesis and glycolytic activity. Fatty acid synthase (FASN) is prominently expressed in breast cancer cells, regulating fatty acid synthesis, thereby enhancing tumor growth and migration, and leading to radioresistance. This study aims to investigate how FASN inhibition affects cell proliferation, migration, and radioresistance in breast cancer, as well as the mechanisms involved.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Pathology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
Triple negative breast cancers often contain higher numbers of tumour-infiltrating lymphocytes compared with other breast cancer subtypes, with their number correlating with prolonged survival. Since little is known about tumour-infiltrating lymphocyte trafficking in triple negative breast cancers, we investigated the relationship between tumour-infiltrating lymphocytes and the vascular compartment to better understand the immune tumour microenvironment in this aggressive cancer type. We aimed to identify mechanisms and signaling pathways responsible for immune cell trafficking in triple negative breast cancers, specifically of basal type, that could potentially be manipulated to change such tumours from immune "cold" to "hot" thereby increasing the likelihood of successful immunotherapy in this challenging patient population.
View Article and Find Full Text PDFPLoS One
January 2025
Biology Department, Faculty of Science, Islamic University of Madinah, Madinah, Saudi Arabia.
This study presents a novel approach to modeling breast cancer dynamics, one of the most significant health threats to women worldwide. Utilizing a piecewise mathematical framework, we incorporate both deterministic and stochastic elements of cancer progression. The model is divided into three distinct phases: (1) initial growth, characterized by a constant-order Caputo proportional operator (CPC), (2) intermediate growth, modeled by a variable-order CPC, and (3) advanced stages, capturing stochastic fluctuations in cancer cell populations using a stochastic operator.
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