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Updated: May 8, 2026
Building Up a High-throughput Screening Platform to Assess the Heterogeneity of HER2 Gene Amplification in Breast Cancers
Published on: December 5, 2017
HER3, p95HER2, and HER2 protein expression levels define multiple subtypes of HER2-positive metastatic breast cancer
Allan Lipton1, Laurie Goodman, Kim Leitzel
1Breast Oncology Research, Division of Hematology/Oncology, Department of Medicine, Penn State Hershey Medical Center, 500 University Drive, Hershey, PA 17033, USA. alipton@hmc.psu.edu
Abstract:
Trastuzumab is effective in the treatment of HER2/neu over-expressing breast cancer, but not all patients benefit from it. In vitro data suggest a role for HER3 in the initiation of signaling activity involving the AKT–mTOR pathway leading to trastuzumab insensitivity. We sought to investigate the potential of HER3 alone and in the context of p95HER2 (p95), a trastuzumab resistance marker, as biomarkers of trastuzumab escape. Using the VeraTag® assay platform, we developed a dual antibody proximity-based assay for the precise quantitation of HER3 total protein (H3T) from formalin-fixed paraffin-embedded (FFPE) breast tumors. We then measured H3T in 89 patients with metastatic breast cancer treated with trastuzumab-based therapy, and correlated the results with progression-free survival and overall survival using Kaplan–Meier and decision tree analyses that also included HER2 total (H2T) and p95 expression levels. Within the sub-population of patients that over-expressed HER2, high levels of HER3 and/or p95 protein expression were significantly associated with poor clinical outcomes on trastuzumab-based therapy. Based on quantitative H3T, p95, and H2T measurements, multiple subtypes of HER2-positive breast cancer were identified that differ in their outcome following trastuzumab therapy. These data suggest that HER3 and p95 are informative biomarkers of clinical outcomes on trastuzumab therapy, and that multiple subtypes of HER2-positive breast cancer may be defined by quantitative measurements of H3T, p95, and H2T.
Insights
HER3 and p95 protein expression levels can predict trastuzumab treatment outcomes in HER2-positive breast cancer. These biomarkers help identify patient subtypes and guide therapy decisions for improved clinical outcomes.
Area of Science:
- Oncology
- Molecular Biology
- Biomarker Discovery
Background:
- Trastuzumab is a targeted therapy for HER2-positive breast cancer, but treatment resistance limits its effectiveness.
- In vitro studies suggest HER3 signaling contributes to trastuzumab insensitivity via the AKT-mTOR pathway.
- p95HER2 (p95) is a known marker associated with trastuzumab resistance.
Purpose of the Study:
- To investigate HER3 and p95 as biomarkers for predicting trastuzumab resistance in breast cancer.
- To develop a precise assay for quantifying HER3 total protein (H3T) in FFPE tumor samples.
- To correlate H3T, p95, and HER2 total (H2T) expression with clinical outcomes in metastatic breast cancer patients treated with trastuzumab.
Main Methods:
- Development of a dual antibody proximity-based assay (VeraTag®) for precise H3T quantitation in FFPE tissues.
- Measurement of H3T, H2T, and p95 expression levels in 89 metastatic breast cancer patients.
- Kaplan–Meier and decision tree analyses to correlate biomarker expression with progression-free and overall survival.
Main Results:
- High HER3 and/or p95 protein expression significantly correlated with poor clinical outcomes in HER2-overexpressing patients receiving trastuzumab.
- Quantitative H3T, p95, and H2T measurements identified distinct subtypes of HER2-positive breast cancer with varying responses to trastuzumab.
- Biomarker levels provided predictive information regarding patient survival on trastuzumab-based therapy.
Conclusions:
- HER3 and p95 serve as informative biomarkers for predicting clinical outcomes in patients treated with trastuzumab.
- Quantitative assessment of H3T, p95, and H2T enables the definition of multiple subtypes of HER2-positive breast cancer.
- These findings support the use of HER3 and p95 as predictive biomarkers to personalize trastuzumab therapy.
