Details

Autor(en) / Beteiligte

• Wolf, Denise M.
• Yau, Christina
• Wulfkuhle, Julia
• Brown-Swigart, Lamorna
• Gallagher, Rosa I.
• Lee, Pei Rong Evelyn
• Zhu, Zelos
• Magbanua, Mark J.
• Sayaman, Rosalyn
• O’Grady, Nicholas
• Basu, Amrita
• Delson, Amy
• Coppé, Jean Philippe
• Lu, Ruixiao
• Braun, Jerome
• Asare, Smita M.
• Sit, Laura
• Matthews, Jeffrey B.
• Perlmutter, Jane
• Hylton, Nola
• Liu, Minetta C.
• Pohlmann, Paula
• Symmans, W. Fraser
• Rugo, Hope S.
• Isaacs, Claudine
• DeMichele, Angela M.
• Yee, Douglas
• Berry, Donald A.
• Pusztai, Lajos
• Petricoin, Emanuel F.
• Hirst, Gillian L.
• Esserman, Laura J.
• van 't Veer, Laura J.

Titel

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

Ist Teil von

• Cancer cell, 2022-06, Vol.40 (6), p.609-623.e6

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2022

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• 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. [Display omitted] •The I-SPY2-990 Data Resource contains mRNA, protein, and response data over 10 drugs•Biomarkers are combined to create breast cancer subtypes to match modern treatments•Best subtyping schemas incorporate Immune, DNA repair, Luminal, and HER2 phenotypes•Treatment assignment using these response predictive subtypes may improve outcomes Wolf et al. use gene expression, protein levels, and response data from 10 drug arms of the I-SPY2 neoadjuvant trial to create new breast cancer subtypes that incorporate tumor biology beyond clinical hormone receptor (HR) and HER2 status. Use of these response-predictive subtypes to guide treatment prioritization may improve patient outcomes.