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Purpose: HER2(+) metastatic breast cancer (mBC) is one of the most aggressive and lethal cancer types among females. While initially effective, targeted therapeutic approaches with trastuzumab and pertuzumab antibodies and antibody-drug conjugates (ADC) lack long-term efficacy against HER2(+) mBC and can cause severe systemic toxicity due to off-target effects. Therefore, the development of novel targeted delivery platforms that minimize toxicity and increase therapeutic efficacy is critical to the treatment of HER2(+) breast cancer (BC). A pretargeting delivery platform can minimize the non-specific accumulation and off-target toxicity caused by traditional one-step delivery method by separating the single delivery step into a pre-targeting step with high-affinity biomarker binding ligand followed by the subsequent delivery step of therapeutic component with fast clearance. Each delivery component is functionalized with bioorthogonal reactive groups that quickly react , forming cross-linked clusters on the cell surface, which facilitates rapid internalization and intracellular delivery of therapeutics.
Procedures: We have successfully developed a click chemistry-based pretargeting platform for HER2(+) BC enabling PET-MR image guidance for reduced radiation dose, high sensitivity, and good soft tissue contrast. Radiolabeled trastuzumab and superparamagnetic iron-oxide carriers (uSPIO) were selected as pretargeting and delivery components, respectively. HER2(+) BT-474 cell line and corresponding xenografts were used for and studies.
Results: An enhanced tumor accumulation as well as tumor-to-organ accumulation ratio was observed in pretargeted mice up to 24 h post uSPIO injection. A 40% local T decrease in the pretargeted mice tumor was observed within 4 h, and an overall 15% T drop was retained for 24 h post uSPIO injection.
Conclusions: Prolonged tumor retention and increased tumor-to-organ accumulation ratio provided a solid foundation for pretargeted image-guided delivery approach for applications.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10925432 | PMC |
http://dx.doi.org/10.21203/rs.3.rs-3974001/v1 | 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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