Multilevel classification framework for breast cancer cell selection and its integration with advanced disease models
Multilevel classification framework for breast cancer cell selection and its integration with advanced disease models
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.
Biological sciences research methodologies, Cancer, Technical aspects of cell biology
113579
Franco Jones, Catarina
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Dias, Diogo
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Moreira, Ana C
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Gonçalves, Gil
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Cinti, Stefano
d24fc475-fd02-4c21-bd5f-3979fa1bf0a9
Djamgoz, Mustafa B A
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Castelo Ferreira, Frederico
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Sanjuán-Alberte, Paola
07fec7ca-0446-4c4f-a42e-cd6d466f8e16
17 October 2025
Franco Jones, Catarina
c88ddcff-5d51-4d84-b884-ca6b7f31fa07
Dias, Diogo
baf28e3a-d9c9-4623-9b6c-49b7b1d76f20
Moreira, Ana C
3e488089-d0a4-4d34-9633-49e1ff0fa658
Gonçalves, Gil
72476a09-5757-45fd-a3a6-2e8d470b5148
Cinti, Stefano
d24fc475-fd02-4c21-bd5f-3979fa1bf0a9
Djamgoz, Mustafa B A
ec67858f-5dc6-45c3-9747-ded3788d4df5
Castelo Ferreira, Frederico
c5a83f99-59f5-4e98-bd26-ee630505a83b
Sanjuán-Alberte, Paola
07fec7ca-0446-4c4f-a42e-cd6d466f8e16
Franco Jones, Catarina, Dias, Diogo, Moreira, Ana C, Gonçalves, Gil, Cinti, Stefano, Djamgoz, Mustafa B A, Castelo Ferreira, Frederico, Sanjuán-Alberte, Paola and Moreddu, Rosalia
(2025)
Multilevel classification framework for breast cancer cell selection and its integration with advanced disease models.
iScience, 28 (10), , [113579].
(doi:10.1016/j.isci.2025.113579).
Abstract
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.
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e-pub ahead of print date: 16 September 2025
Published date: 17 October 2025
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© 2025 The Authors
Keywords:
Biological sciences research methodologies, Cancer, Technical aspects of cell biology
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Local EPrints ID: 506186
URI: http://eprints.soton.ac.uk/id/eprint/506186
ISSN: 2589-0042
PURE UUID: e99349b5-26ff-4ebb-8977-a4bd34968097
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Date deposited: 29 Oct 2025 17:45
Last modified: 30 Oct 2025 17:35
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Author:
Catarina Franco Jones
Author:
Diogo Dias
Author:
Ana C Moreira
Author:
Gil Gonçalves
Author:
Stefano Cinti
Author:
Mustafa B A Djamgoz
Author:
Frederico Castelo Ferreira
Author:
Paola Sanjuán-Alberte
Author:
Rosalia Moreddu
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