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The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.

Choosing the right cell line for breast cancer research

Open access
Holliday, Deborah L, Speirs, Valerie·2011·Breast Cancer Research

Abstract

Breast cancer is a complex and heterogeneous disease. Gene expression profiling has contributed significantly to our understanding of this heterogeneity at a molecular level, refining taxonomy based on simple measures such as histological type, tumour grade, lymph node status and the presence of predictive markers like oestrogen receptor and human epidermal growth factor receptor 2 (HER2) to a more sophisticated classification comprising luminal A, luminal B, basal-like, HER2-positive and normal subgroups. In the laboratory, breast cancer is often modelled using established cell lines. In the present review we discuss some of the issues surrounding the use of breast cancer cell lines as experimental models, in light of these revised clinical classifications, and put forward suggestions for improving their use in translational breast cancer research.

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Crossref · 10.1186/bcr2889

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Metadata

Authors
Holliday, D. L., & Speirs, V.
Venue
Breast Cancer Research
Published
2011-08
Volume
13
Issue
4
Pages
215-215
ISSN
  • 1465-5411 (ISSN-L)
  • 1465-542X
OpenAlex
W1994930469
Cited by
1,541
References
65
FWCI
7.26
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Choosing the right cell line for breast cancer research. https://app.cochat.ai/papers/10.1186/bcr2889
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Holliday, D. L., & Speirs, V. (2011). Choosing the right cell line for breast cancer research. Breast Cancer Research. https://doi.org/10.1186/bcr2889

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.