Systems of markers for the diagnosis of breast cancer based on DNA methylation of a group of suppressor protein-coding genes, hypermethylated microRNA genes, and their combinations were compiled. On a representative sample of 70 paired breast cancer specimens (tumor/normal), MS-PCR analysis revealed a significant increase in the methylation frequency of 5 protein-coding genes: RASSF1A suppressor and apoptosis genes APAF1, BAX, BIM/BCL2L11, and DAPK1 (34-61% vs. 4-24%) and 6 microRNA genes: MIRG124G1, MIRG125bG1, MIRG129G2, MIRG148a, MIRG34b/c, and MIRG9G3 (36-76% vs. 6-27%). ROC-analysis showed that a combination of 4 genes (APAF1, BAX, BIM/BCL2L11, and DAPK1) and MIRG125bG1 gene constitute a highly efficient 5-marker system with 100% specificity and sensitivity of 94-96% at AUC=0.98-0.97, suitable also for patients with stage I and II breast cancer. Detection of methylation of at least one gene in this system in biopsy or postoperative material is sufficient to refer the sample to breast cancer.
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http://dx.doi.org/10.1007/s10517-020-04710-2 | 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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