Purpose: Expression-based classifiers to predict complete pathological response (pCR) after neoadjuvant chemotherapy (NACT) are not routinely used in the clinic. We aimed to build and validate a classifier for pCR after NACT. Experimental Design: We performed a prospective multicenter study (EXPRESSION) including 114 patients treated with anthracycline/taxane-based NACT. Pretreatment core-needle biopsies from 91 patients were used for gene expression analysis and classifier construction, followed by validation in five external cohorts (n=619). Results: A 20-gene classifier established in the EXPRESSION cohort using a Youden's index-based cutpoint predicted pCR in the validation cohorts with an accuracy, area under the curve (AUC), negative predictive value (NPV), positive predictive value (PPV), sensitivity and specificity of 0.811, 0.768, 0.829, 0.587, 0.216 and 0.962, respectively. Alternatively, aiming for a high NPV by defining the cutpoint for classi fication based on the complete responder with the lowest predicted probability of pCR in the EXPRESSION cohort led to an NPV of 0.960 upon external validation. With this extreme-low cutpoint, a recommendation to not treat with anthracycline/taxane-based NACT would be possible for 121 of 619 unselected patients (19.5%) and 112 of 322 luminal breast cancer patients (34.8%). The analysis of the molecular subtypes showed that the identification of patients who do not achieve a pCR by the 20 gene classifier was particularly relevant in luminal breast cancer. Conclusions: The novel 20 gene classifier reliably identifies patients who do not achieve a pCR in about one third of luminal breast cancer in both the EXPRESSION and the combined validation cohort.
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