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 language | English (US) |
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Pages (from-to) | 609-623.e6 |
Journal | Cancer cell |
Volume | 40 |
Issue number | 6 |
DOIs | |
State | Published - Jun 13 2022 |
Keywords
- DNA repair
- Immune
- Luminal
- breast cancer
- clinical trial
- immunotherapy
- multiple arms
- platinum
- response prediction
- subtyping
ASJC Scopus subject areas
- Oncology
- Cancer Research