Breast cancer is the second leading cause of cancer mortality among women. Given its important role in DNA methylation and synthesis, one-carbon metabolism may affect breast cancer mortality. We used a population-based cohort of 1,508 women with breast cancer to investigate possible associations of dietary intake of B vitamins before diagnosis as well as nine polymorphisms of one-carbon metabolizing genes and subsequent survival. Women newly diagnosed with a first primary breast cancer in 1996 to 1997 were followed for vital status for an average of 5.6 years. Kaplan-Meier survival and Cox proportional hazard regression analyses were used to evaluate the association between dietary intakes of B vitamins (1,479 cases), genotypes ( approximately 1,065 cases), and all-cause as well as breast cancer-specific mortality. We found that higher dietary intake of vitamin B(1) and B(3) was associated with improved survival during the follow-up period (P(trend) = 0.01 and 0.04, respectively). Compared with the major genotype, the MTHFR 677 T allele carriers have reduced all-cause mortality and breast cancer-specific mortality in a dominant model [hazard ratio (95% confidence interval): 0.69 (0.49-0.98) and 0.58 (0.38-0.89), respectively]. The BHMT 742 A allele was also associated with reduced all-cause mortality [hazard ratio, 0.70 (0.50-1.00)]. Estrogen receptor/progesterone receptor status modified the association between the MTHFR C677T polymorphism and survival (P = 0.05). The survival associations with one-carbon polymorphisms did not differ with the use of chemotherapy, although study power was limited for examining such effect modification. Our results indicate that one-carbon metabolism may be an important pathway that could be targeted to improve breast cancer survival.
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http://dx.doi.org/10.1158/1055-9965.EPI-07-2900 | DOI Listing |
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.
View Article and Find Full Text PDFInt J Gen Med
December 2024
Department of Thyroid and Breast Surgery, Quzhou People's Hospital, Quzhou, 324000, People's Republic of China.
Objective: This study aims to demonstrate the impact of sarcopenia on the prognosis of early breast cancer and its role in early multimodal intervention.
Methods: The clinical data of patients (n=285) subjected to chemotherapy for early-stage breast cancer diagnosed pathologically between January 1, 2016, and December 31, 2020, in our hospital were retrospectively analyzed. Accordingly, the recruited subjects were divided into sarcopenia (n=85) and non-sarcopenia (n=200) groups according to CT diagnosis correlating with single-factor and multifactorial logistic regression analyses.
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