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Purpose <p>Quantitative real-time PCR (qRT-PCR) represents a robust methodology to investigate alterations in gene expression patterns during tumorigenesis. The quantification of target gene expression is conventionally standardized through normalization against a stably expressed reference gene. However, the expression profile of a specific reference gene can exhibit variability across different tissue types and diverse physiological conditions. This study aimed to identify a suitable reference gene from a pool of ten potential candidates for the comparison of gene expression profiles between six human breast cell lines, comprising both normal breast (MCF-12A) and breast cancer cells (MCF-7, BT-474, SK-BR-3, MDA-MB-468, MDA-MB-231).</p> Methods <p>Four different mathematical approaches were used to calculate the stability of reference gene expression (comparative ΔCt method, NormFinder, coefficient of variation and RefFinder).</p> Results <p>Stability analysis identified <i>ACTB</i> as a suitable reference gene across all cell lines. As we are specifically interested in studying metabolic adaptation of breast cancer, we applied the same approach to identify a suitable reference gene also after maintaining the cell lines in L-arginine-deficient medium for up to 72&#xa0;h. The stability ranking of reference genes fluctuated after L-arginine was depleted.</p> Conclusion <p>In the context of investigating specific cell lines under certain conditions, we propose the identification of reference genes that exhibit optimal stability and suitability.</p>

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Identification of an appropriate reference gene for normalization of qRT-PCR expression analyses in human breast cancer cell lines: application to L-arginine depletion studies

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月26日

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  • Antonia Röglin,
  • Rainer Böger,
  • Fiona Kleinsang,
  • Juliane Hannemann

摘要

Purpose

Quantitative real-time PCR (qRT-PCR) represents a robust methodology to investigate alterations in gene expression patterns during tumorigenesis. The quantification of target gene expression is conventionally standardized through normalization against a stably expressed reference gene. However, the expression profile of a specific reference gene can exhibit variability across different tissue types and diverse physiological conditions. This study aimed to identify a suitable reference gene from a pool of ten potential candidates for the comparison of gene expression profiles between six human breast cell lines, comprising both normal breast (MCF-12A) and breast cancer cells (MCF-7, BT-474, SK-BR-3, MDA-MB-468, MDA-MB-231).

Methods

Four different mathematical approaches were used to calculate the stability of reference gene expression (comparative ΔCt method, NormFinder, coefficient of variation and RefFinder).

Results

Stability analysis identified ACTB as a suitable reference gene across all cell lines. As we are specifically interested in studying metabolic adaptation of breast cancer, we applied the same approach to identify a suitable reference gene also after maintaining the cell lines in L-arginine-deficient medium for up to 72 h. The stability ranking of reference genes fluctuated after L-arginine was depleted.

Conclusion

In the context of investigating specific cell lines under certain conditions, we propose the identification of reference genes that exhibit optimal stability and suitability.