Epidemiological studies have found obesity to be a risk factor for women's breast cancer. The present study was to investigate whether there is a relationship between serum levels of leptin, insulin, and lipids and breast cancer incidence, in order to find experimental evidence that would be helpful in the diagnosis and prevention of breast cancer. Blood samples were collected from 130 patients with mammary disease and 103 healthy control subjects. Serum leptin, insulin, and lipids were determined by radioimmunoassay (RIA), enzyme-linked immunosorbent assays (ELISA), and Biochemistry Auto-analyzer, respectively. The data analysis was performed by use of the SPSS10.0 computer software. We found that the serum levels of leptin, insulin, and triglyceride (TG) were clearly higher in patients with breast cancer than in patients with benign breast disease and healthy controls, while serum HDL-C levels were lower in breast cancer patients (p < 0.03). Moreover, serum leptin levels were significantly correlated with BMI (body mass index) among three groups, whereas serum insulin levels were unrelated to BMI among three groups. Furthermore, the serum levels of leptin and insulin were not associated with menopausal status in patients with mammary disease (p > 0.05); however, the serum levels of F-Chol, T-Chol, TG, LDL-C, and APOB were significant higher in postmenopausal cases than those in premenopausal cases (p < 0.025). Interestingly, logistic regression analysis showed that subjects with elevated serum levels of leptin, insulin, TG, APOA1, and reduced level of serum HDL-C displayed increased risk of developing breast cancer than those with the normal levels, respectively. In conclusion, the present study suggested that aberrant serum levels of leptin, insulin, and lipids might play an important role in carcinogenesis of breast cancer. The elevated serum levels of leptin, insulin, TG, APOA1, and reduced level of serum HDL-C may be correlated with increased risk of breast cancer, suggesting that one way of preventing breast cancer would be carried out by controlling the intake of food.
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http://dx.doi.org/10.1385/ENDO:26:1:019 | 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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