Multidimensional phenotyping of breast cancer cell lines to guide preclinical research
Open accessAbstract
PURPOSE: Cell lines are extremely useful tools in breast cancer research. Their key benefits include a high degree of control over experimental variables and reproducibility. However, the advantages must be balanced against the limitations of modelling such a complex disease in vitro. Informed selection of cell line(s) for a given experiment now requires essential knowledge about molecular and phenotypic context in the culture dish. METHODS: We performed multidimensional profiling of 36 widely used breast cancer cell lines that were cultured under standardised conditions. Flow cytometry and digital immunohistochemistry were used to compare the expression of 14 classical breast cancer biomarkers related to intrinsic molecular profiles and differentiation states: EpCAM, CD24, CD49f, CD44, ER, AR, HER2, EGFR, E-cadherin, p53, vimentin, and cytokeratins 5, 8/18 and 19. RESULTS: This cell-by-cell analysis revealed striking heterogeneity within cultures of individual lines that would be otherwise obscured by analysing cell homogenates, particularly amongst the triple-negative lines. High levels of p53 protein, but not RNA, were associated with somatic mutations (p = 0.008). We also identified new subgroups using the nanoString PanCancer Pathways panel (730 transcripts representing 13 canonical cancer pathways). Unsupervised clustering identified five groups: luminal/HER2, immortalised ('normal'), claudin-low and two basal clusters, distinguished mostly by baseline expression of TGF-beta and PI3-kinase pathway genes. CONCLUSION: These features are compared with other published genotype and phenotype information in a user-friendly reference table to help guide selection of the most appropriate models for in vitro and in vivo studies, and as a framework for classifying new patient-derived cancer cell lines and xenografts.
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The SUM159 cell line harbors activating mutations in HRAS and PIK3CA.
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- Authors
- Saunus, J. M., Smart, C. E., Kutasovic, J. R., Johnston, R. L., Kalita-de Croft, P., Miranda, M., Rozali, E. N., Vargas, A. C., Reid, L. E., Lorsy, E., Cocciardi, S., Seidens, T., McCart Reed, A. E., Dalley, A. J., Wockner, L. F., Johnson, J., Sarkar, D., Askarian-Amiri, M. E., Simpson, P. T., Khanna, K. K., Chenevix-Trench, G., Al-Ejeh, F., & Lakhani, S. R.
- Affiliations
- The University of Queensland (AU)
- Vita-Salute San Raffaele University (IT)
- QIMR Berghofer Medical Research Institute (AU)
- University of Auckland (NZ)
- Corresponding author
- Saunus, Jodi M.
- ORCID
- Venue
- Breast Cancer Research and Treatment
- Published
- 2017-09-09
- Volume
- 167
- Issue
- 1
- Pages
- 289-301
- ISSN
- 0167-6806 (ISSN-L)
- 1573-7217
- OpenAlex
- W2751860027
- Cited by
- 35
- References
- 27
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 2 · 2023: 1 · 2022: 5 · 2021: 8 · 2020: 1 · 2019: 6 · 2018: 5
- FWCI
- 1.10
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Breast Cancer Research and Treatment (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ResearchSpace (University of Auckland) (submittedVersion, cc-by)
- Funders
- National Health and Medical Research Council (APP1017028, APP1113867, APP1082458)
- Australian Research Council (FT130101417)
- National Breast Cancer Foundation (F'ship)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Health Sciences › Medicine › Pathology and Forensic Medicine › Breast Lesions and Carcinomas
- Keywords
- breast cancer cell lines, cell line heterogeneity, breast cancer biomarkers, triple-negative breast cancer, p53 expression, cell-of-origin classification, claudin-low breast cancer, basal-like breast cancer, TGF-beta signaling, PI3K signaling, cell line selection, patient-derived xenografts
- MeSH terms
- Breast Neoplasms, Female, Flow Cytometry, Genotype, Humans, Neoplasm Proteins, Phenotype, Gene Expression Regulation, Neoplastic, Genetic Heterogeneity, Gene Expression Profiling, Cell Line, Tumor
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