Predicting pathological complete response (pCR) to neoadjuvant trastuzumab in patients with breast cancer using HER2 mass spectrometry.

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e12643 Background: Around 40% of HER2-positive (HER2+) breast cancer patients who receive trastuzumab-based neoadjuvant therapy (TNT) achieve pCR (the FDA-recommended outcome measure in this setting). The ability to predict which patients will respond to TNT could support decisions regarding selection neoadjuvant agents or combinations. We previously quantified tumor expression of HER2 with mass spectrometry in archived biopsies of breast cancer patients who received adjuvant trastuzumab; HER2 levels > 2200 amol/ug of tumor protein were associated with superior disease-free and overall survival. We hypothesized that this HER2 protein cutoff would predict pCR in a HER2+ neoadjuvant population treated with TNT. Methods: Formalin-fixed, paraffin-embedded tumor biopsies from patients with breast cancer were microdissected and solubilized for proteomic profiling with multiplexed mass spectrometry. Patients were dichotomized using the pre-specified HER2 cutoff of 2200 amol/ug. Relationships between pre-treatment HER2 expression and pCR following TNT were assessed with Fisher’s exact test. Results: Of 65 evaluable patients, 18 achieved pCR (overall pCR rate 28%). In patients with HER2 expression above the 2200 cutoff (n = 30), the pCR rate was approximately 3 times higher than that of lower HER2 expressors (n = 35) (43% vs. 14%; [odds ratio = 4.47; [95% CI: 1.23-18.94], p = 0.013). Among the lower HER2 expressors, 86% did not achieve pCR. HER3 protein was co-expressed in 29 of 65 patient tumors including 50% of non-pCR samples. Conclusions: In patients diagnosed as HER2+ using standard methods, a quantitative HER2 cutoff identified a subset of low HER2 expressors in which 86% did not achieve pCR on TNT. Quantitative proteomic testing may be more useful than standard HER2 assessment methods in predicting response to TNT. Multiplexed proteomic analysis of HER2 and HER3 co-expression could potentially inform treatment decisions regarding dual therapy with pertuzumab.

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