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Multilevel classification framework for breast cancer cell selection and its integration with advanced disease models

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Název: Multilevel classification framework for breast cancer cell selection and its integration with advanced disease models
Autoři: Catarina Franco Jones, Diogo Dias, Ana C. Moreira, Gil Gonçalves, Stefano Cinti, Mustafa B.A. Djamgoz, Frederico Castelo Ferreira, Paola Sanjuán-Alberte, Rosalia Moreddu
Zdroj: iScience, Vol 28, Iss 10, Pp 113579- (2025)
Informace o vydavateli: Elsevier, 2025.
Rok vydání: 2025
Sbírka: LCC:Science
Témata: Technical aspects of cell biology, Cancer, Biological sciences research methodologies, Science
Popis: Summary: Breast cancer cell lines are indispensable tools for unraveling disease mechanisms, enabling drug discovery, and developing personalized treatments, yet their heterogeneity and inconsistent classification pose significant challenges in model selection and data reproducibility. This review aims at providing a comprehensive and user-friendly framework for broadly mapping the features of breast cancer types and commercially available human breast cancer cell lines, defining absolute criteria, i.e., objective features such as origin (e.g., MDA-MB, MCF), histological subtype (ductal, lobular), hormone receptor status (ER/PR/HER2), and genetic mutations (BRCA1, TP53), and relative criteria, which contextualize functional behaviors such as metastatic potential, drug sensitivity, and genomic instability. It then examines how the proposed framework could be applied to cell line screening in advanced and emerging disease models. By supporting better informed choices, this work aims to improve experimental design and strengthen the connection between in vitro breast cancer studies and their clinical translation.
Druh dokumentu: article
Popis souboru: electronic resource
Jazyk: English
ISSN: 2589-0042
Relation: http://www.sciencedirect.com/science/article/pii/S2589004225018401; https://doaj.org/toc/2589-0042
DOI: 10.1016/j.isci.2025.113579
Přístupová URL adresa: https://doaj.org/article/0d2a84bc0d9e4d8e9283f9c46d48c545
Přístupové číslo: edsdoj.0d2a84bc0d9e4d8e9283f9c46d48c545
Databáze: Directory of Open Access Journals
Popis
Abstrakt:Summary: Breast cancer cell lines are indispensable tools for unraveling disease mechanisms, enabling drug discovery, and developing personalized treatments, yet their heterogeneity and inconsistent classification pose significant challenges in model selection and data reproducibility. This review aims at providing a comprehensive and user-friendly framework for broadly mapping the features of breast cancer types and commercially available human breast cancer cell lines, defining absolute criteria, i.e., objective features such as origin (e.g., MDA-MB, MCF), histological subtype (ductal, lobular), hormone receptor status (ER/PR/HER2), and genetic mutations (BRCA1, TP53), and relative criteria, which contextualize functional behaviors such as metastatic potential, drug sensitivity, and genomic instability. It then examines how the proposed framework could be applied to cell line screening in advanced and emerging disease models. By supporting better informed choices, this work aims to improve experimental design and strengthen the connection between in vitro breast cancer studies and their clinical translation.
ISSN:25890042
DOI:10.1016/j.isci.2025.113579