Data from A Multiparameter Molecular Classifier to Predict Response to Neoadjuvant Lapatinib plus Trastuzumab without Chemotherapy in HER2&lt;sup&gt;+&lt;/sup&gt; Breast Cancer

Katherine Sanchez,Carmine De Angelis,Mothaffar F Rimawi,Monesh Kapadia,Jamunarani Veeraraghavan,Hiroaki Nitta,Ian E Krop,Britta Weigelt,Rachel Schiff,Andres Forero-Torres,Pier Selenica,Antonio C Wolff,Tao Wang,Aleix Prat,Matthew P Goetz,Anne C Pavlick,Julie R Nangia,Susan G Hilsenbeck,C Kent Osborne,Rita Nanda,Patricia Galván ,Carolina Gutiérrez ,Brent N Rexer ,Jorge S Reis‐Filho ,Tomás Pascual ,Anna Maria Storniolo ,Robert K Davis

doi:10.1158/1078-0432.c.6717737

Abstract

<div>AbstractPurpose:Clinical trials reported 25% to 30% pathologic complete response (pCR) rates in HER2+ patients with breast cancer treated with anti-HER2 therapies without chemotherapy. We hypothesize that a multiparameter classifier can identify patients with HER2-“addicted” tumors who may benefit from a chemotherapy-sparing strategy.Experimental Design:Baseline HER2+ breast cancer specimens from the TBCRC023 and PAMELA trials, which included neoadjuvant treatment with lapatinib and trastuzumab, were used. In the case of estrogen receptor–positive (ER+) tumors, endocrine therapy was also administered. HER2 protein and gene amplification (ratio), HER2-enriched (HER2-E), and PIK3CA mutation status were assessed by dual gene protein assay (GPA), research-based PAM50, and targeted DNA-sequencing. GPA cutoffs and classifier of response were constructed in TBCRC023 using a decision tree algorithm, then validated in PAMELA.Results:In TBCRC023, 72 breast cancer specimens had GPA, PAM50, and sequencing data, of which 15 had pCR. Recursive partitioning identified cutoffs of HER2 ratio ≥ 4.6 and %3+ IHC staining ≥ 97.5%. With PAM50 and sequencing data, the model added HER2-E and PIK3CA wild-type (WT). For clinical implementation, the classifier was locked as HER2 ratio ≥ 4.5, %3+ IHC staining ≥ 90%, and PIK3CA-WT and HER2-E, yielding 55% and 94% positive (PPV) and negative (NPV) predictive values, respectively. Independent validation using 44 PAMELA cases with all three biomarkers yielded 47% PPV and 82% NPV. Importantly, our classifier's high NPV signifies its strength in accurately identifying patients who may not be good candidates for treatment deescalation.Conclusions:Our multiparameter classifier differentially identifies patients who may benefit from HER2-targeted therapy alone from those who need chemotherapy and predicts pCR to anti-HER2 therapy alone comparable with chemotherapy plus dual anti-HER2 therapy in unselected patients.</div>

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