Background: Duration and type of menopausal hormone therapy (HT) has been associated with increased breast cancer risk and the development of estrogen receptor (ER)-positive tumors. The effect of HT dose on breast cancer tumor characteristics remains undefined. We sought to determine if HT dosing regimens influence breast cancer phenotype.
Methods: We conducted a retrospective review of incident female breast cancers occurring in the year 2003 listed in the Kaiser Permanente Northern California Cancer Registry. Type of HT, dose, number of tablets dispensed, tumor phenotype, stage, grade, and histology were obtained from electronic records for women aged >/=50 years who had more than 1 year of uninterrupted pharmacy data (n = 1701). A dose index of HT exposure was created and odds ratios were used to determine if tumor phenotype varied between exposure groups. These results were compared with a previously published analysis of HT duration on tumor phenotype conducted with the same dataset.
Results: The cumulative effect of estrogen and progesterone hormone therapy as calculated by factoring both dose and duration of HT use prior to breast cancer diagnosis did not reveal any new associations that were not previously identified by analysis of HT duration of exposure alone. Low-dose-index combination-HT users were less likely to have tumors with an ER-positive phenotype. An overall trend developed in which low- and high-dose-index exposed women had the lowest rates of ER- and progesterone receptor (PR) -positive tumors.
Conclusion: Duration of use is an adequate surrogate for determining overall exposure to HT when considering the effect of HT on breast cancer phenotype.
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http://dx.doi.org/10.1245/s10434-008-0019-7 | 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.
Cancer grade classification is a challenging task identified from the cell structure of healthy and abnormal tissues. The partitioner learns about the malignant cell through the grading and plans the treatment strategy accordingly. A major portion of researchers used DL models for grade classification.
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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
January 2025
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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