98%
921
2 minutes
20
HER2-positive and triple-negative breast cancers (TNBC) are difficult to treat and associated with poor prognosis. Despite showing initial response, HER2-positive breast cancers often acquire resistance to HER2-targeted therapies, and TNBC lack effective therapies. To overcome these clinical challenges, we evaluated the therapeutic utility of co-targeting TrkA and JAK2/STAT3 pathways in these breast cancer subtypes. Here, we report the novel combination of FDA-approved TrkA inhibitors (Entrectinib or Larotrectinib) and JAK2 inhibitors (Pacritinib or Ruxolitinib) synergistically inhibited in vitro growth of HER2-positive breast cancer cells and TNBC cells. The Entrectinib-Pacritinib combination inhibited the breast cancer stem cell subpopulation, reduced expression of stemness genes, SOX2 and MYC, and induced apoptosis. The Entrectinib-Pacritinib combination suppressed orthotopic growth of HER2-positive Trastuzumab-refractory breast cancer xenografts and basal patient-derived xenograft (PDXs), reduced tumoral SOX2 and MYC, and induced apoptosis in both mouse models. The Entrectinib-Pacritinib combination inhibited overall metastatic burden, and brain and bone metastases of intracardially inoculated TNBC cells without toxicity. Together, our results demonstrate for the first time that co-inhibition of TrkA and JAK2 synergistically suppresses breast cancer growth and metastasis, thereby providing preclinical evidence that supports future clinical evaluations.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11533721 | PMC |
http://dx.doi.org/10.1016/j.canlet.2024.217023 | 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.
View Article and Find Full Text PDF