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Updated: Oct 10, 2025
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Public transcriptome database-based selection and validation of reliable reference genes for breast cancer research
Qiang Song1, Lu Dou1, Wenjin Zhang1
1Department of Central Laboratory, Chongqing University Three Gorges Hospital, School of Medicine, Chongqing University, Chongqing, 404000, China.
Reliable reference genes (RGs) are crucial for accurate gene expression analysis in breast cancer. This study identified optimal RG combinations, SF1+TRA2B+THRAP3 and THRAP3+RHOA+QRICH1, for normalizing quantitative reverse transcription-polymerase chain reaction (qRT-PCR) in breast cancer tissues and cell lines.
Area of Science:
- Molecular Biology
- Genomics
- Cancer Research
Background:
- Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) is essential for gene expression analysis.
- Accurate normalization of qRT-PCR data relies on selecting stable reference genes (RGs).
- Reliable RGs for breast cancer research remain unidentified, hindering accurate gene expression studies.
Purpose of the Study:
- To identify and validate reliable reference genes for breast cancer tissues and cell lines.
- To establish optimal RG combinations for normalizing qRT-PCR data in breast cancer research.
Main Methods:
- Utilized RNA-sequencing data from the TCGA database (1217 samples) to identify novel candidate RGs.
- Performed qRT-PCR on 87 breast cancer samples (66 tissues, 21 cell lines) to assess RG expression stability.
- Applied five algorithms (geNorm, NormFinder, ΔCt, BestKeeper, ComprFinder) to evaluate RG expression stability.
Main Results:
- Identified RG combinations SF1+TRA2B+THRAP3 for breast cancer tissues and THRAP3+RHOA+QRICH1 for breast cancer cell lines.
- These novel triplet RG combinations demonstrated stable expression and good interchangeability.
- Proposed these combinations as optimal for breast cancer research normalization.
Conclusions:
- Successfully identified novel and reliable reference gene combinations for breast cancer research using public RNA-seq data.
- These findings provide a robust foundation for accurate normalization of qRT-PCR results in diverse breast cancer contexts.
- The validated RG combinations will enhance the reliability of gene expression studies in breast cancer.
