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Breast cancer is a highly heterogeneous disease; hence, it is crucial to understand its biology and identify new targets for the development of effective treatments. Galectin-1 is known to play an oncogenic role in breast cancer progression. It is known that oncogenic factors can influence cancer progression through interactions with miRNAs. The purpose of this study is to identify the clinical significance and biological role of galectin-1 and miR-22-3p in cancer progression according to the molecular subtype of breast cancer. We analyzed the expression of galectin-1 and miR-22-3p using cancer tissues and the correlation with clinical pathological characteristics. In addition, we investigated the regulation of the cell cycle and EMT processes of cancer progression through the galectin-1/miR-22-3p axis using cell lines of different breast cancer subtypes. miR-22-3p negatively regulates galectin-1 expression and the two molecules have opposite patterns of oncogenic and tumor-suppressive functions, respectively; furthermore, these two molecules are associated with metastasis-free survival. Cell experiments showed that miR-22-3p overexpression and galectin-1 knockdown inhibited the proliferation and invasion of breast cancer cells. Galectin-1 regulates different cancer progression pathways depending on the molecular subtype. In hormone receptor-positive breast cancer cells, galectin-1 knockdown mainly inhibited cell cycle-related substances and induced G0/G1 arrest, whereas in triple-negative breast cancer cells, it suppressed molecules related to the epithelial-mesenchymal transition pathway. In conclusion, the miR-22-3p/galectin-1 axis regulates different cancer metastasis mechanisms depending on the specific molecular subtype of breast cancer, and miR-22-3p/galectin-1 axis modulation may be a novel target for molecular subtype-specific personalized treatment.
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http://dx.doi.org/10.3390/cells14040310 | DOI Listing |
EBioMedicine
September 2025
Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, PR China; Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, PR China. Electronic address:
JMIR Cancer
September 2025
Cancer Patients Europe, Rue de l'Industrie 24, Brussels, 1000, Belgium.
Background: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, radiation exposure, and accessibility issues. Thermography, particularly when driven by artificial intelligence (AI), is being explored as a noninvasive, radiation-free alternative.
View Article and Find Full Text PDFEpidemiol Serv Saude
September 2025
Universidade Estadual do Norte do Paraná, Programa de Pós-Graduação em Enfermagem em Atenção Primária à Saúde Bandeirantes, PR, Brazil.
Objectives: To analyze the temporal trend and identify spatial clusters of breast cancer mortality in Paraná state between 2012 and 2021.
Methods: This was a time series study, with spatial analysis of breast cancer mortality rates in the 399 municipalities of Paraná. Data were selected from the Mortality Information System.
Cien Saude Colet
August 2025
Faculdade de Medicina da Universidade Federal de Pelotas. Pelotas RS Brasil.
The objective of this study was to analyze the characteristics of avoidable mortality in the population aged five to 69 years living in the city of Pelotas/RS, comparing it with the rest of the state of Rio Grande do Sul, from 2000 to 2021. An ecological study was conducted analyzing avoidable mortality coefficients according to sex and age, from 2000 to 2021. The data source was the Mortality Information System, and the trend analysis was performed using Prais-Winsten regression, with standardization of coefficients.
View Article and Find Full Text PDFCien Saude Colet
August 2025
Programa de Pós-Graduação em Nutrição e Saúde, Universidade Estadual do Ceará. R. Betel 1958, Itaperi. 60714-230 Fortaleza CE Brasil.
This study aimed to evaluate mortality due to female breast cancer attributable to overweight and obesity and to estimate the number of preventable deaths with a reduction in the Body Mass Index in Brazil. An ecological study was carried out with investigation of information on overweight, obesity, sociodemographic characteristics based on a national survey carried out in 2013-14; breast cancer mortality rate in 2019 using the Online Atlas of Mortality and Relative Risk Meta-Analyses. The Potential Impact Fraction analysis was carried out, considering the following counterfactual scenarios related to the reduction in BMI: Scenario A - population contingent of women that make up the prevalence of overweight and obesity now composes the prevalence of eutrophy; Scenario B - population contingent of women that make up the prevalence of overweight starts to make up the prevalence of eutrophy; Scenario C - population contingent of women that make up the prevalence of obesity becomes part of the prevalence of overweight.
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