Projects per year
Abstract
Hypoxia is common in breast tumours and is linked to therapy resistance and advanced disease. To understand hypoxia-driven breast cancer progression, RT-qPCR is a widely used technique to quantify transcriptional changes that occur during malignant transformation. Reference genes (RGs) are endogenous RT-qPCR controls used to normalise mRNA levels, allowing accurate assessment of transcriptional changes. However, hypoxia reprograms transcription and post-transcriptional processing of RNA such that favoured RGs including GAPDH or PGK1 are unsuitable for this purpose. To address the need for robust RGs to study hypoxic breast cancer cell lines, we identified 10 RG candidates by analysing public RNA-seq data of MCF-7 and T-47D (Luminal A), and, MDA-MB-231 and MDA-MB-468 (triple negative breast cancer (TNBC)) cells cultured in normoxia or hypoxia. We used RT-qPCR to determine RG candidate levels in normoxic breast cancer cells, removing TBP and EPAS1 from downstream analysis due to insufficient transcript abundance. Assessing primer efficiency further removed ACTB, CCSER2 and GUSB from consideration. Following culture in normoxia, acute, or chronic hypoxia, we ascertained robust non-variable RGs using RefFinder. Here we present RPLP1 and RPL27 as optimal RGs for our panel of two Luminal A and two TNBC cell lines cultured in normoxia or hypoxia. Our result enables accurate evaluation of gene expression in selected hypoxic breast cancer cell lines and provides an essential resource for assessing the impact of hypoxia on breast cancer progression.
Original language | English |
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Article number | 59 |
Number of pages | 12 |
Journal | BMC Genomics |
Volume | 26 |
DOIs | |
Publication status | Published - 21 Jan 2025 |
Bibliographical note
© The Author(s) 2025Keywords
- Humans
- Cell Line, Tumor
- Breast Neoplasms/genetics
- Female
- Gene Expression Regulation, Neoplastic
- Real-Time Polymerase Chain Reaction/standards
- Reference Standards
- Gene Expression Profiling/standards
- Cell Hypoxia/genetics
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CellPhe 2: Machine learning-based phenotyping to predict cell fate in heterogeneous populations
Brackenbury, W. (Principal investigator), O'Toole, P. J. (Co-investigator) & Wilson, J. C. (Co-investigator)
BBSRC (BIOTECHNOLOGY AND BIOLOGICAL SCIENCES RESEARCH COUNCIL)
1/02/24 → 31/07/25
Project: Research project (funded) › Research
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Targeting sodium signalling to combat the disease-driving effects of tumour hypoxia
Brackenbury, W. (Principal investigator), Bridge, K. (Co-investigator), Duckett, S. B. (Co-investigator) & Holding, A. N. (Co-investigator)
MEDICAL RESEARCH COUNCIL (MRC)
1/10/23 → 30/09/26
Project: Research project (funded) › Research
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Next generation approaches to understand tissue specific regulation of the glucocorticoid response
Holding, A. N. (Principal investigator) & Thomas-Oates, J. E. (Co-investigator)
BBSRC (BIOTECHNOLOGY AND BIOLOGICAL SCIENCES RESEARCH COUNCIL)
17/05/21 → 31/01/25
Project: Research project (funded) › Research
Datasets
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Identification of robust RT-qPCR reference genes for studying changes in gene expression in response to hypoxia in breast cancer cell lines
Mason, J. (Creator), Bridge, K. (Creator), Holding, A. N. (Creator) & Brackenbury, W. (Creator), Zenodo, 7 Jan 2025
Dataset