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Real-time RT-PCR: a complementary method to detect HER-2 status in breast carcinoma
Céline Bossard1, Ivan Bieche, Viviane Le Doussal
1Département de Pathologie, Centre René Huguenin, Saint-Cloud, France. u539@nantes.inserm.fr
Anticancer Research
|December 13, 2005
Summary
Quantitative real-time RT-PCR (Q-RT-PCR) accurately determines HER-2 status in breast cancer. This method shows high concordance with immunohistochemistry (IHC), offering a valuable complementary tool for treatment decisions.
Area of Science:
- Oncology
- Molecular Biology
- Biochemistry
Background:
- Accurate HER-2 status determination is crucial for treating HER-2 overexpressed invasive breast carcinoma with Herceptin.
- Immunohistochemistry (IHC) is a common method, but quantitative mRNA expression analysis offers complementary insights.
Purpose of the Study:
- To retrospectively evaluate HER-2 mRNA expression levels using quantitative real-time RT-PCR (Q-RT-PCR).
- To compare Q-RT-PCR results with IHC for HER-2 status determination in primary breast carcinomas.
- To establish cut-off values for altered mRNA expression using normal breast tissue samples.
Main Methods:
- Quantitative real-time RT-PCR (Q-RT-PCR) was performed on 44 primary breast carcinoma tissue samples.
- HER-2 mRNA expression levels were normalized using 20 normal breast tissue RNA samples to define expression categories.
- Results were compared with conventional immunohistochemistry (IHC) staining.
Main Results:
- HER-2 gene expression was categorized into normal, moderate, and strong overexpression groups.
- Overexpression was observed in a significant portion of samples: 38% strong, 25% moderate, and 36.3% normal expression.
- A high concordance rate of 84% was found between Q-RT-PCR and IHC, with only minor discordances in 7 cases.
Conclusions:
- Q-RT-PCR is a reliable and complementary method for quantifying HER-2 mRNA expression.
- The high concordance with IHC supports its utility in determining HER-2 status for treatment selection.
- This quantitative approach provides valuable data for personalized breast cancer therapy.

