566 Background: Endocrine therapy (ET) resistance (ETR) remains a primary challenge in ER+ breast cancer. Analyzing pretreatment tumor transcriptomes across trials with early response endpoints can reveal shared and specific ETR signatures. This study utilizes baseline RNA data from the Phase III ALTERNATE trial (Alliance A011106, NCT01953588; Anastrozole A, Fulvestrant F, or AF) and the ACOSOG Z1031B trial (NCT00824941) to identify predictors of early Ki67 response in postmenopausal ER+/HER2– patients. Methods: ETR was defined as week-4 on-treatment Ki67 >10%. Baseline gene expression from ALTERNATE was analyzed to identify differentially expressed (DE) genes (Wilcoxon test, P0.70). A deep learning model using all protein-coding genes achieved AUC 0.82 (training) and 0.79 (test) in predicting ETR. Cross-trial integration identified ETR-associated PETS, enriched for genomic instability. PETS performed comparably to established signatures and strongly correlated with MYBL2 signature (r=0.93). Top ETR predictors were MYBL2 , AURKB , and EME1 for Arm A and IL4I1 , TNFAIP6 , and ANLN for Arm AF. AF-resistant tumors were enriched for systemic lupus and RIG-I–like receptor signaling; sensitive tumors favored PI3K–AKT, EGFR TKI resistance, AMPK, and insulin signaling. Conclusions: Baseline transcriptomics identify shared and therapy-specific ETR markers. The 15-gene PETS defines a convergent resistance signature, performing similar to established signatures in predicting ETR and correlating with MYBL2. Enrichment of cell-cycle and immune pathways in resistant tumors may suggest patient stratification approach for alternative or combinatorial strategies to overcome early ETR in ER+ breast cancer. Acknowledgement: https://acknowledgments.alliancefound.org. Support: U10CA180821, U10CA180882, U24CA1. Clinical trial information: NCT01953588 .
Anurag et al. (Wed,) studied this question.