作者
Carsten Denkert,Sivaramakrishna Rachakonda,Thomas Karn,Karsten E. Weber,Miguel Martín,Frederik Marmé,M. Untch,Hervé Bonnefoi,Sungbae Kim,Sabine Seiler,Harry D. Bear,Agnieszka K. Witkiewicz,Seock Ah Im,Angela DeMichele,Anika Pehl,Laura van’t Veer,Nicole McCarthy,Thorsten Stiewe,Paul Jank,Karen A. Gelmon,José A. García-Sáenz,Christina C. Westhoff,Catherine M. Kelly,Toralf Reimer,Bärbel Felder,Mireia Melé,Erik S. Knudsen,Nicholas Turner,Federico Rojo,Wolfgang Schmitt,Peter A. Fasching,Julia Teply‐Szymanski,Zhe Zhang,Masakazu Toi,Hope S. Rugo,Michael Gnant,Andreas Makris,Johannes Holtschmidt,Valentina Nekljudova,S. Loibl
摘要
Highlights•Classical intrinsic subtypes change during neoadjuvant therapy from LumB to LumA•A reverse-transition back to LumB is observed in metastatic disease•Improved dimension reduction by comparison of pre- and post-therapeutic samples•Identification of adaptive prognostic subsets in high-risk luminal breast cancerSummaryWe evaluate therapy-induced molecular heterogeneity in longitudinal samples from high-risk, hormone-receptor positive/HER2-negative breast cancer patients with residual tumor after neoadjuvant chemotherapy from the Penelope-B trial (NCT01864746; EudraCT 2013-001040-62). Intrinsic subtypes are prognostic in pre-therapeutic (Tx) samples (n = 629, p < 0.0001) and post-Tx residual tumors (n = 782, p < 0.0001). After neoadjuvant chemotherapy, a shift of intrinsic subtypes is observed from pre-Tx luminal (Lum) B to post-Tx LumA, with reverse transition back to LumB in metastases. In a combined analysis of 540 paired pre-Tx and post-Tx samples, we identify five adaptive clusters (AC-1–5) based on transcriptomic changes before and after neoadjuvant chemotherapy. These AC-subtypes are prognostic beyond classical intrinsic subtyping, categorizing patients into groups with excellent prognosis (AC-1 and AC-2), poor prognosis (AC-3 and AC-4), and very poor prognosis (AC-5, enriched for basal-like subtype). Our analysis provides a basis for an extended molecular classification of breast cancer patients and improved identification of high-risk patient populations.Graphical abstract