Back to Search Start Over

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

Authors :
Tiziana Triulzi
Giampaolo Bianchini
Serena Di Cosimo
Tadeusz Pienkowski
Young‐Hyuck Im
Giulia Valeria Bianchi
Barbara Galbardi
Matteo Dugo
Loris De Cecco
Ling‐Ming Tseng
Mei‐Ching Liu
Begoña Bermejo
Vladimir Semiglazov
Giulia Viale
Juan de laHaba‐Rodriguez
Do‐Youn Oh
Brigitte Poirier
Pinuccia Valagussa
Luca Gianni
Elda Tagliabue
Source :
Molecular Oncology, Vol 16, Iss 12, Pp 2355-2366 (2022)
Publication Year :
2022
Publisher :
Wiley, 2022.

Abstract

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.

Details

Language :
English
ISSN :
18780261 and 15747891
Volume :
16
Issue :
12
Database :
Directory of Open Access Journals
Journal :
Molecular Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.04d4128992ee4c3590607960b247f2b8
Document Type :
article
Full Text :
https://doi.org/10.1002/1878-0261.13141