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

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.

Keywords

• breast cancer
• gene expression profile
• HER2
• pertuzumab
• predictive biomarker
• trastuzumab