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Quantifying the effects of co-expressing EGFR and HER2 on HER activation and trafficking.

ABSTRACT: The human epidermal growth factor receptor (HER) system is an intricately regulated system that plays critical roles in development and tumorigenesis. Here, we apply integrated experimentation and modeling to analyze HER receptor activation in a panel of cell lines expressing endogenous levels of EGFR/HER1 and different levels of HER2. A mathematical model that includes the fundamental processes involved in receptor activation and trafficking was used to fit the experimental data, and values of the independent parameters for active receptor dimer formation affinities, trafficking rates and relative phosphorylation levels were estimated. Obtained parameter values quantitatively support the existing ideas on the effect of HER2 on EGFR dynamics, and enable us to predict the abundances of various phosphorylated receptor dimers in the cell lines.

SUBMITTER: Shankaran H

PROVIDER: S-EPMC2864016 | biostudies-literature | 2008 Jun

REPOSITORIES: biostudies-literature

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Quantifying the effects of co-expressing EGFR and HER2 on HER activation and trafficking.

Shankaran Harish H Zhang Yi Y Opresko Lee L Resat Haluk H

Biochemical and biophysical research communications 20080418 2

The human epidermal growth factor receptor (HER) system is an intricately regulated system that plays critical roles in development and tumorigenesis. Here, we apply integrated experimentation and modeling to analyze HER receptor activation in a panel of cell lines expressing endogenous levels of EGFR/HER1 and different levels of HER2. A mathematical model that includes the fundamental processes involved in receptor activation and trafficking was used to fit the experimental data, and values of ...[more]

PMID: 18424261

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Project description:ErbB signaling serves essential roles in invasive ductal carcinoma (IDC). The aim of the present study was to assess gene amplification in ErbB family members in IDC with clinical implications. Quantitative polymerase chain reaction and fluorescence in situ hybridization were performed on formalin-fixed paraffin-embedded tumor samples for gene amplification detection. The clinical and histopathological characteristics, as well as the prognostic significance, were analyzed. Among the 119 IDC patients evaluated, epidermal growth factor receptor [EGFR; also known as human epidermal growth factor receptor (HER)1], HER2, HER3 and HER4 gene amplification was observed in 30 (25.2%), 44 (36.9%), 0 (0.0%) and 1 (0.8%) patients, respectively. EGFR amplification was associated with estrogen receptor status (P=0.028) and higher possibilities of recurrence (P=0.015) and distant metastasis (following initial surgery) (P=0.011). In survival analysis, EGFR amplification was also associated with disease-free survival (DFS) (P=0.001) and overall survival (OS) (P=0.003). HER2 amplification was associated with larger tumor size (P=0.006), later clinical stage (P=0.003) and distant metastasis (following initial surgery) (P=0.006). In survival analysis, HER2 amplification was also associated with DFS (P=0.011). Notably, the present study identified a group of patients in whom EGFR and HER2 were co-amplified. This group of patients appeared to have a higher possibility of metastasis (when diagnosed) (P=0.014) and distant metastasis (following initial surgery) (P<0.001). In survival analysis, these patients were noticed to be associated with DFS (P<0.001) and OS (P=0.002). With respect to treatment regimen, this was also true for the DFS association with chemotherapy (P<0.001), radiotherapy (P<0.001) and hormonal therapy (P=0.001). The present results suggest that EGFR and HER2 amplification favor distant metastasis following initial surgery and are significantly associated with poor clinical outcome in breast cancer patients.

Dataset Information

Quantifying the effects of co-expressing EGFR and HER2 on HER activation and trafficking.

Publications

Quantifying the effects of co-expressing EGFR and HER2 on HER activation and trafficking.

Similar Datasets

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