Citation

Filho OM, Viale G, Stein S, Trippa L, Yardley DA, Mayer IA, Abramson VG, Arteaga CL, Spring LM, Waks AG, Wrabel E, DeMeo MK, Bardia A, Dell'Orto P, Russo L, King TA, Polyak K, Michor F, Winer EP, Krop IE. 2021. Impact of HER2 Heterogeneity on Treatment Response of Early-Stage HER2-Positive Breast Cancer: Phase II Neoadjuvant Clinical Trial of T-DM1 Combined with Pertuzumab. Cancer discovery. 11(10):2474-2487. Pubmed: 33941592 DOI:10.1158/2159-8290.CD-20-1557

Abstract

Intratumor heterogeneity is postulated to cause therapeutic resistance. To prospectively assess the impact of HER2 () heterogeneity on response to HER2-targeted therapy, we treated 164 patients with centrally confirmed HER2-positive early-stage breast cancer with neoadjuvant trastuzumab emtansine plus pertuzumab. HER2 heterogeneity was assessed on pretreatment biopsies from two locations of each tumor. HER2 heterogeneity, defined as an area with amplification in >5% but <50% of tumor cells, or a HER2-negative area by FISH, was detected in 10% (16/157) of evaluable cases. The pathologic complete response rate was 55% in the nonheterogeneous subgroup and 0% in the heterogeneous group ( < 0.0001, adjusted for hormone receptor status). Single-cell FISH analysis of cellular heterogeneity identified the fraction of nonamplified cells as a driver of therapeutic resistance. These data suggest HER2 heterogeneity is associated with resistance to HER2-targeted therapy and should be considered in efforts to optimize treatment strategies. SIGNIFICANCE: HER2-targeted therapies improve cure rates in HER2-positive breast cancer, suggesting chemotherapy can be avoided in a subset of patients. We show that HER2 heterogeneity, particularly the fraction of nonamplified cancer cells, is a strong predictor of resistance to HER2 therapies and could potentially be used to optimize treatment selection...
©2021 American Association for Cancer Research.

Related Faculty

Photo of Franziska Michor

Franziska Michor uses the tools of theoretical evolutionary biology, applied mathematics, statistics, and computational biology to address important questions in cancer research.

Search Menu