Breast cancer, a formidable global health challenge, needs continuous translational research to understand the complexity of mechanisms and improve therapeutic and diagnostic strategies. Breast cancer cell lines are of paramount importance as they significantly contribute to the initial stage of research to understand cancer biology. This review provides insights into targeted therapies and immunotherapies that have emerged using in vitro models and microbiome analysis. It focuses on therapeutic development using cell lines and the limitations of tumor heterogeneity and microenvironment. We explore the evolving landscape of breast cancer cell lines from two-dimensional (2-D) cultures to patient-derived xenograft (PDX) models advancing both fundamental and translational research. Patient-derived xenografts, cell line-derived xenografts (CDX), three-dimensional (3-D) cultures, organoids, and circulating tumor cells (CTC) models provide promising alternatives that capture the intricacies of the tumor microenvironment. This review bridges the gap between traditional cell lines and newer developments exploring the therapeutic and diagnostic advancements and needs for cell lines to expedite the progress in breast cancer research and treatment.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1002/ijc.34849 | DOI Listing |
Pharm Dev Technol
January 2025
Department of Pharmacy, School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, China.
In this paper, the pH-sensitive targeting functional material NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate (NGR-PEtOz-CHMC, NPC) modified quercetin (QUE) liposomes (NPC-QUE-L) was constructed. The structure of NPC was confirmed by infrared spectroscopy (IR) and nuclear magnetic resonance hydrogen spectrum (H-NMR). Pharmacokinetic results showed that the accumulation of QUE in plasma of the NPC-QUE-L group was 1.
View Article and Find Full Text PDFJ Med Econ
January 2025
UNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.
Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.
Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.
View Article and Find Full Text PDFInt J Gen Med
December 2024
Department of Thyroid and Breast Surgery, Quzhou People's Hospital, Quzhou, 324000, People's Republic of China.
Objective: This study aims to demonstrate the impact of sarcopenia on the prognosis of early breast cancer and its role in early multimodal intervention.
Methods: The clinical data of patients (n=285) subjected to chemotherapy for early-stage breast cancer diagnosed pathologically between January 1, 2016, and December 31, 2020, in our hospital were retrospectively analyzed. Accordingly, the recruited subjects were divided into sarcopenia (n=85) and non-sarcopenia (n=200) groups according to CT diagnosis correlating with single-factor and multifactorial logistic regression analyses.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!