Real-World Clinical Genomics Study of HR+/HER2- Metastatic Breast Cancers Treated by CDK4/6i plus Endocrine Therapies Revealed a Drug Resistant Tumor Segment Characterized by ER Independence

SABCS 2023 Presentation
Authors Zhengyan Kan, Ji Wen, Jen Webster, Vinicius Bonato, Whijae Roh, Xinmeng Jasmine Mu, Paul Rejto, and Jadwiga Bienkowska


CDK4/6 inhibitors (CDK4/6i) plus endocrine therapies (ET) are the standard-of-care for hormone receptor–positive/human epidermal receptor 2–negative metastatic breast cancer (HR+/HER2− mBC). However, drug resistance remains a major unmet need. Investigations of drug resistance mechanisms has been hampered by a dearth of tumor molecular profiling data from the post-treatment setting. To address this challenge, we have conducted a real- world clinical genomics study to better understand the molecular mechanism of CDK4/6i resistance as well as to stratify patients based on integrated multi-omics profiles.


We retrospectively analyzed a multi-omics dataset of 400 HR+/HER2- mBC patients who had received CDK4/6i plus ET and developed progressive disease (PD) from the de-identified Tempus database. Pre-treatment and post-progression biopsies were taken 1 year prior to starting the CDK4/6i treatment or following PD respectively. Tempus xT next-generation sequencing (DNA-seq of 648 genes) and RNA sequencing assays were performed on 427 tumor FFPE samples, including 200 pre-treatment, 227 post-progression and 26 longitudinal pairs.


The median age of the patients was 57 (54.9-57.4) and median progression free survival (PFS) is 379 (341-433) days. Two genes were found to harbor a significant increase in genomic alteration frequencies (GAF) after adjusting for FDR at post-progression vs. pre- treatment – ESR1 (41.9% vs. 15%, p=5.4e-10), RB1 (13.2% vs. 3%, p=8.5e-05). ESR1 and RB1 also harbored high frequencies of acquired genomic alterations among 26 paired samples at 34.6% and 11.5% respectively. TP53 mutation at baseline was significantly associated with shorter PFS at baseline (p=4.23e-05, HR=2.081) and TP53 GAF significantly increased after PD (37% vs. 28.5%, p=0.039). BRCA1/2 pathogenic mutations (p=1.63e-04, HR=3.066), APOBEC mutation signature S13 (p=0.0125, HR=1.55) and CCNE1 gene expression (p=0.024, HR=1.46) were significantly associated with shorter PFS. APOBEC signature (p=0.0035) and CCNE1 expression (p=1.33e-06) also significantly increased post-progression. Among the top molecular features associated with longer PFS were markers of estrogen signaling such as PGR gene expression (p=6.76e-04, HR=0.565) and the Hallmark estrogen response signature (p=0.021, HR=0.679). Applying a multi-omics pattern recognition algorithm, we identified a molecularly distinct cluster (IC1) characterized by down-regulation of estrogen signaling. IC1 is significantly associated with shorter PFS (p=3.72e-05, HR=0.22) and increased from 4% pre-treatment to 23% post-progression (p=7.3e-08). Further, IC1 is strongly enriched in markers previously implicated in CDK4/6i resistance including CCNE1 expression, RB1 mutation and MYC/E2F activation. We then developed machine learning models to predict gene-level dependency trained on cancer cell line expression and CRISPR-KO screen data. These models predicted decreased dependency on ESR1 and CDK4 and increased dependency on CDK2 in IC1, strengthening the association between ER independence and CDK4/6i resistance.


Our real-world clinical genomics study identified a comprehensive list of biomarkers associated with resistance to CDK4/6i plus ET and estimated patient prevalence for these markers in the post-treatment setting. Integrated and machine-learning analyses identified a subset of aggressive tumors with estrogen independence characteristics that are implicated in CDK4/6i resistance and suggested new therapeutic strategies.