Breast Cancer Research and Treatment

, Volume 138, Issue 1, pp 59–67 | Cite as

The detection of ESR1/PGR/ERBB2 mRNA levels by RT-QPCR: a better approach for subtyping breast cancer and predicting prognosis

  • Xin Du
  • Xiao-Qing Li
  • Lin Li
  • Yuan-Yuan Xu
  • Yu-Mei Feng
Preclinical study


The molecular classification of breast cancer mainly focuses on ER, PR, and HER2 status detected by immunohistochemistry (IHC) analysis. To explore the clinical value of breast cancer classification based on gene-based diagnosis of the triple markers, we measured ESR1, PGR, and ERBB2 mRNA levels in 294 breast cancer patients by reverse transcription quantitative polymerase chain reaction (RT-QPCR), and examined their correlation with ER, PR, and HER2 status detected by IHC. We observed a significant positive correlation between the mRNA levels of the triple markers and their protein status (ESR1 vs. ER, Spearman’s ρ = 0.527, P = 2.3 × 10−22; PGR vs. PR, Spearman’s ρ = 0.631, P = 5.1 × 10−34; ERBB2 vs. HER2, Spearman’s ρ = 0.439, P = 3.0 × 10−15). Furthermore, the subtypes determined by mRNA levels of the triple markers were significantly correlated to the subtypes determined based on their protein status (Spearman’s ρ = 0.342, P = 2.0 × 10−8). Kaplan–Meier analysis showed that the subtypes determined by mRNA levels of the triple-marker could predict the disease-free survival (DFS) in breast cancer patients. Multivariate analysis showed that the predictive value of DFS could be confirmed for the subtypes determined by mRNA levels of the triple markers (HR = 2.285, P = 0.008) but not for those determined by their protein status. Taken together, our results suggest that the detection of ESR1/PGR/ERBB2 mRNA levels by RT-QPCR is a better approach for subtyping breast cancer and predicting the prognosis.


RT-QPCR Molecular subtype Breast cancer Prognosis 



This study was supported by the National Natural Science Foundation of China (No. 30872518 and No. 81272357), the Applied Basic Research Projects of Tianjin (No. 06YFJMJC12900 and No. 09JCZDJC19800).

Conflict of interests

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Xin Du
    • 1
  • Xiao-Qing Li
    • 1
    • 2
  • Lin Li
    • 1
  • Yuan-Yuan Xu
    • 1
  • Yu-Mei Feng
    • 1
    • 2
  1. 1.Department of Biochemistry and Molecular BiologyTianjin Medical University Cancer Institute and HospitalTianjinChina
  2. 2.Key Laboratory of Breast Cancer Prevention and Treatment of the Ministry of EducationTianjin Medical University Cancer Institute and HospitalTianjinChina

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