Inflammation has been associated with fatigue during and after various types of breast cancer treatments. We examined whether prior chemotherapy was associated with DNA methylation patterns that could explain persisting inflammation and/or fatigue in women treated for breast cancer. Prior to breast radiation therapy, DNA was extracted from peripheral blood mononuclear cells (PBMCs) of 61 Stage 0-IIIA breast cancer patients who had received partial mastectomy with or without chemotherapy. DNA methylation was assessed at >485,000 CpG sites across the genome along with fatigue and plasma inflammatory markers previously associated with fatigue. Compared to non-chemotherapy-treated, women who had received chemotherapy exhibited significantly decreased methylation at eight CpG sites (p<1.03×10(-7)) including four in exon 11 of transmembrane protein 49 (TMEM49), which demonstrated the largest decreases in methylation. Lower methylation at each identified CpG site was associated with increased plasma soluble tumor necrosis factor receptor 2 (sTNFR2) and interleukin (IL)-6 and mediated the relationship between chemotherapy and increases in these inflammatory biomarkers adjusting for multiple clinical and treatment characteristics. sTNFR2, but not CpG methylation status, was correlated with fatigue. Six months after breast radiation therapy, DNA methylation, inflammatory biomarkers and fatigue assessments were repeated in a subset of subjects (N=39). Reduced methylation in 4 of the 8 identified CpG sites was still observed in chemotherapy versus non-chemotherapy-treated patients, albeit with some decay indicating the dynamic and potentially reversible nature of the changes. Reduced methylation in these 4 CpG sites also continued to correlate with either increased sTNFR2 or IL-6, but not fatigue. In conclusion, prior chemotherapy treatment was associated with decreased methylation of CpG sites in DNA from PBMCs of breast cancer patients, which correlated with increased inflammatory markers prior to and 6months after radiation therapy. Persisting epigenetic changes secondary to chemotherapy may be one factor that contributes to inflammation and its consequences including cancer-related fatigue in vulnerable breast cancer patients.
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http://dx.doi.org/10.1016/j.bbi.2014.02.010 | DOI Listing |
East Mediterr Health J
December 2024
Department of Radiology, King Abdulaziz University, Jeddah, Saudi Arabia.
Background: Breast cancer is often thought to occur at a younger age among Arab women based on the mean or median age at diagnosis, or the proportion of women diagnosed with breast cancer at a young age.
Objective: To compare age-specific breast cancer incidence rates among women from selected Arab countries with selected high- and middle-income countries.
Methods: We examined population-based, age-specific, national or regional breast cancer incidence data for 2008-2012 and 2013-2017 from Australia, Brazil, Canada, Germany, Japan, United Kingdom, and United States of America, and compared them with data from Algeria, Bahrain, Jordan, Kuwait, Morocco, Qatar, and Saudi Arabia.
Pharm Dev Technol
January 2025
Department of Pharmacy, School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, China.
In this paper, the pH-sensitive targeting functional material NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate (NGR-PEtOz-CHMC, NPC) modified quercetin (QUE) liposomes (NPC-QUE-L) was constructed. The structure of NPC was confirmed by infrared spectroscopy (IR) and nuclear magnetic resonance hydrogen spectrum (H-NMR). Pharmacokinetic results showed that the accumulation of QUE in plasma of the NPC-QUE-L group was 1.
View Article and Find Full Text PDFJ Med Econ
January 2025
UNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.
Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.
Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.
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