Objective: To explore the molecular mechanism underlying the inhibitory effects of aspirin against human breast cancer cell proliferation through bioinformatics analysis.
Methods: Drug Bank 5.1.3 was searched to identify direct protein targets (DPTs) of aspirin, and the protein-protein interaction (PPI) network of the DPTs was constructed online using STRING and the signaling pathways involved were identified. The genetic alterations of 6 DPTs associated with human breast cancer was analyzed and visualized by cBio Portal and OncoPrint, respectively. The transcriptomic data of breast cancer and normal tissues were downloaded from TCGA database, and the overexpressed genes were analyzed by DECenter. The intersection between the genes associated with the DPTs obtained by STRING analysis and the differentially over-expressed genes in TCGA was determined to confirm the candidate DPTs as a potential target of aspirin, and GO functional enrichment analysis was performed using Gene Ontology. The potential targets of aspirin against the proliferation of human breast cancer cells were verified by Western blotting.
Results: Eleven DPTs of aspirin were identified. KEGG pathway enrichment indicated that 6 genes (EDNRA, IKBKB, NFKB2, NFKBIA, PTGS2 and TP53) were associated with the occurrence and development of cancer. A total of 10 220 differentially expressed genes were identified from the TCGA database, and among them 4 genes (, , , ) were found to be the potential targets for aspirin. These genes were involved mostly in the regulation of cell cycle and cell division. Western blotting showed that aspirin could down-regulate the expression levels of several pivotal proteins that regulated cell cycle and cell division, including , , and .
Conclusions: , , and may be potential targets for aspirin to inhibit the proliferation of human breast cancer cells, by affecting the progress of cell cycle and cell division.
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http://dx.doi.org/10.12122/j.issn.1673-4254.2019.10.02 | DOI Listing |
J Med Internet Res
January 2025
Cancer Screening, American Cancer Society, Atlanta, GA, United States.
Background: The online nature of decision aids (DAs) and related e-tools supporting women's decision-making regarding breast cancer screening (BCS) through mammography may facilitate broader access, making them a valuable addition to BCS programs.
Objective: This systematic review and meta-analysis aims to evaluate the scientific evidence on the impacts of these e-tools and to provide a comprehensive assessment of the factors associated with their increased utility and efficacy.
Methods: We followed the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted a search of MEDLINE, PsycINFO, Embase, CINAHL, and Web of Science databases from August 2010 to April 2023.
Cien Saude Colet
January 2025
Universidade Federal do Ceará. R. Alexandre Baraúna 1115, Rodolfo Teófilo. 60430-160 Fortaleza CE Brasil.
Mammography is one of the main methods available for breast cancer screening in Brazil. However, differences in timely access and performance of the exam can be highlighted based on social determinants of health, considered relevant due to their influence on the health situation of a population. Thus, the present study aimed to identify the social determinants of health associated with access to and performance of mammography in Brazilian women.
View Article and Find Full Text PDFCien Saude Colet
January 2025
Instituto René Rachou, Fundação Oswaldo Cruz (Fiocruz Minas). Av. Augusto de Lima 1715, Barro Preto. 30190-002 Belo Horizonte MG Brasil.
This article aims to identify the relationship between material deprivation and mortality from breast, cervical, and prostate neoplasms in the Brazilian adult population and the relationship between ethnicity/skin color and material deprivation. This cross-sectional ecological study calculated the mean mortality rate per 100,000 inhabitants, and deaths were standardized by age and gender and redistributed per to ill-defined causes, stratified by age group and ethnicity/skin color. We applied the Negative Binomial model, containing the interaction between ethnicity/skin color and the Brazilian Deprivation Index (IBP).
View Article and Find Full Text PDFBrief Bioinform
November 2024
Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC 27101, United States.
Pathway analysis plays a critical role in bioinformatics, enabling researchers to identify biological pathways associated with various conditions by analyzing gene expression data. However, the rise of large, multi-center datasets has highlighted limitations in traditional methods like Over-Representation Analysis (ORA) and Functional Class Scoring (FCS), which struggle with low signal-to-noise ratios (SNR) and large sample sizes. To tackle these challenges, we use a deep learning-based classification method, Gene PointNet, and a novel $P$-value computation approach leveraging the confusion matrix to address pathway analysis tasks.
View Article and Find Full Text PDFCancer Res
January 2025
INSERM U1194, Montpellier Cedex 05, Occitanie, France.
BRCA1 deficiency is observed in approximately 25% of triple-negative breast cancer (TNBC). BRCA1, a key player of homologous recombination (HR) repair, is also involved in stalled DNA replication fork protection and repair. Here, we investigated the sensitivity of BRCA1-deficient TNBC models to the frequently used replication chain terminator gemcitabine, which does not directly induce DNA breaks.
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