ArticleJournal of clinical bioinformatics2013
High-throughput identification of reference genes for research and clinical RT-qPCR analysis of breast cancer samples.
Article in Journal of clinical bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
- PRR11 expression in early ER+/HER2-low breast cancer: Association with estrogen receptor positivity and exploratory analysis of prognostic significance.Oncology letters · 2026Article
- The Impact of IGFBP6 Knockdown on Cholesterol Metabolism in Breast Cancer Cells.Current medicinal chemistry · 2026Article
- CD44 knockdown alters miRNA expression and their target genes in colon cancer.Frontiers in immunology · 2025Article
- Identification of endogenous reference genes for RT-qPCR analysis in breast cancer and matched adjacent tissues.Frontiers in oncology · 2025Article
- Screening and validating the optimal panel of housekeeping genes for 4T1 breast carcinoma and metastasis studies in mice.Scientific reports · 2024Article
- Spontaneous metastasis xenograft models link CD44 isoform 4 to angiogenesis, hypoxia, EMT and mitochondria-related pathways in colorectal cancer.Molecular oncology · 2024Article
- Effect of IGFBP6 Knockdown on Proteins Regulating Exosome Synthesis and Secretion in MDA-MB-231 Cell Line.Bulletin of experimental biology and medicine · 2023Article
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- Serpin Signatures in Prion and Alzheimer's Diseases.Molecular neurobiology · 2022Article
- Fra-2 overexpression upregulates pro-metastatic cell-adhesion molecules, promotes pulmonary metastasis, and reduces survival in a spontaneous xenograft model of human breast cancer.Journal of cancer research and clinical oncology · 2022Article
- Selection and Validation of Reference Genes for Pan-Cancer in Platelets Based on RNA-Sequence Data.Frontiers in genetics · 2022Article
- Public transcriptome database-based selection and validation of reliable reference genes for breast cancer research.Biomedical engineering online · 2021Article
- Identification of Novel Endogenous Controls for qPCR Normalization in SK-BR-3 Breast Cancer Cell Line.Genes · 2021Article
- Evaluation of Angelica decursiva reference genes under various stimuli for RT-qPCR data normalization.Scientific reports · 2021Article
- Multiple roles of H2A.Z in regulating promoter chromatin architecture in human cells.Nature communications · 2021Article
- Uncovering the stability status of the reputed reference genes in breast and hepatic cancer cell lines.PloS one · 2021Article
- Effect of the Expression ofFrontiers in genetics · 2021Article
- Selecting suitable reference genes for qPCR normalization: a comprehensive analysis in MCF-7 breast cancer cell line.BMC molecular and cell biology · 2020Article
- Conventionally used reference genes are not outstanding for normalization of gene expression in human cancer research.BMC bioinformatics · 2019Article
- The expression signature of cancer-associated KRAB-ZNF factors identified in TCGA pan-cancer transcriptomic data.Molecular oncology · 2019Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundQuantification and normalization of RT-qPCR data critically depends on the expression of so called reference genes. Our goal was to develop a strategy for the selection of reference genes that utilizes microarray data analysis and combines known approaches for gene stability evaluation and to select a set of appropriate reference genes for research and clinical analysis of breast samples with different receptor and cancer status using this strategy.
methodsA preliminary search of reference genes was based on high-throughput analysis of microarray datasets. The final selection and validation of the candidate genes were based on the RT-qPCR data analysis using several known methods for expression stability evaluation: comparative ∆Ct method, geNorm, NormFinder and Haller equivalence test.
resultsA set of five reference genes was identified: ACTB, RPS23, HUWE1, EEF1A1 and SF3A1. The initial selection was based on the analysis of publically available well-annotated microarray datasets containing different breast cancers and normal breast epithelium from breast cancer patients and epithelium from cancer-free patients. The final selection and validation were performed using RT-qPCR data from 39 breast cancer biopsy samples. Three genes from the final set were identified by the means of microarray analysis and were novel in the context of breast cancer assay. We showed that the selected set of reference genes is more stable in comparison not only with individual genes, but also with a system of reference genes used in commercial OncotypeDX test.
conclusionA selection of reference genes for RT-qPCR can be efficiently performed by combining a preliminary search based on the high-throughput analysis of microarray datasets and final selection and validation based on the analysis of RT-qPCR data with a simultaneous examination of different expression stability measures. The identified set of reference genes proved to be less variable and thus potentially more efficient for research and clinical analysis of breast samples comparing to individual genes and the set of reference genes used in OncotypeDX assay.
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