%0 Journal Article
%A Triulzi, Tiziana
%A Bianchini, Giampaolo
%A Di Cosimo, Serena
%A Pienkowski, Tadeusz
%A Im, Young-Hyuck
%A Bianchi, Giulia Valeria
%A Galbardi, Barbara
%A Dugo, Matteo
%A De Cecco, Loris
%A Tseng, Ling-Ming
%A Liu, Mei-Ching
%A Bermejo, Begoña
%A Semiglazov, Vladimir
%A Viale, Giulia
%A de la Haba-Rodriguez, Juan
%A Oh, Do-Youn
%A Poirier, Brigitte
%A Valagussa, Pinuccia
%A Gianni, Luca
%A Tagliabue, Elda
%T The TRAR gene classifier to predict response to neoadjuvant therapy in HER2-positive and ER-positive breast cancer patients: an explorative analysis from the NeoSphere trial.
%D 2021
%U http://hdl.handle.net/10668/22494
%X As most erb-b2 receptor tyrosine kinase 2 (HER2)-positive breast cancer (BC) patients currently receive dual HER2-targeting added to neoadjuvant chemotherapy, improved methods for identifying individual response, and assisting postsurgical salvage therapy, are needed. Herein, we evaluated the 41-gene classifier trastuzumab advantage risk model (TRAR) as a predictive marker for patients enrolled in the NeoSphere trial. TRAR scores were computed from RNA of 350 pre- and 166 post-treatment tumor specimens. Overall, TRAR score was significantly associated with pathological complete response (pCR) rate independently of other predictive clinico-pathological variables. Separate analyses according to estrogen receptor (ER) status showed a significant association between TRAR score and pCR in ER-positive specimens but not in ER-negative counterparts. Among ER-positive BC patients not achieving a pCR, those with TRAR-low scores in surgical specimens showed a trend for lower distant event-free survival. In conclusion, in HER2-positive/ER-positive BC, TRAR is an independent predictor of pCR and represents a promising tool to select patients responsive to anti-HER2-based neoadjuvant therapy and to assist treatment escalation and de-escalation strategies in this setting.
%K HER2
%K breast cancer
%K gene expression profile
%K pertuzumab
%K predictive biomarker
%K trastuzumab
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