A Multiparameter Molecular Classifier to Predict Response to Neoadjuvant Lapatinib plus Trastuzumab without Chemotherapy in HER2+ Breast Cancer

Authors

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

Publication Date

8-15-2023

Journal

Clinical Cancer Research

Abstract

PURPOSE: 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.

Keywords

Female, Humans, Antineoplastic Combined Chemotherapy Protocols, Biomarkers, Tumor, Breast Neoplasms, Class I Phosphatidylinositol 3-Kinases, Lapatinib, Neoadjuvant Therapy, Quinazolines, Receptor, ErbB-2, Trastuzumab, Treatment Outcome

Comments

Supplementary Materials

PMID: 37195235