Redefining breast cancer subtypes to guide treatment prioritization and maximize response: Predictive biomarkers across 10 cancer therapies

I-SPY2 Investigators

Research output: Contribution to journalArticlepeer-review

Abstract

Using pre-treatment gene expression, protein/phosphoprotein, and clinical data from the I-SPY2 neoadjuvant platform trial (NCT01042379), we create alternative breast cancer subtypes incorporating tumor biology beyond clinical hormone receptor (HR) and human epidermal growth factor receptor-2 (HER2) status to better predict drug responses. We assess the predictive performance of mechanism-of-action biomarkers from ∼990 patients treated with 10 regimens targeting diverse biology. We explore >11 subtyping schemas and identify treatment-subtype pairs maximizing the pathologic complete response (pCR) rate over the population. The best performing schemas incorporate Immune, DNA repair, and HER2/Luminal phenotypes. Subsequent treatment allocation increases the overall pCR rate to 63% from 51% using HR/HER2-based treatment selection. pCR gains from reclassification and improved patient selection are highest in HR+ subsets (>15%). As new treatments are introduced, the subtyping schema determines the minimum response needed to show efficacy. This data platform provides an unprecedented resource and supports the usage of response-based subtypes to guide future treatment prioritization.

Original languageEnglish (US)
Pages (from-to)609-623.e6
JournalCancer cell
Volume40
Issue number6
DOIs
StatePublished - Jun 13 2022

Keywords

  • breast cancer
  • clinical trial
  • DNA repair
  • Immune
  • immunotherapy
  • Luminal
  • multiple arms
  • platinum
  • response prediction
  • subtyping

ASJC Scopus subject areas

  • Oncology
  • Cell Biology
  • Cancer Research

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