Abstract 3829: Identifying the genetic basis for resistance to aromatase inhibitors (AIs) in metastatic breast cancer (mBC) patients
Authors: Neeraj Singh, Smita Agrawal
Journal: Cancer Research (2024)

Abstract Background: AIs, such as letrozole, anastrozole, and exemestane, are used to treat hormonal receptor positive (HR+) breast cancer (BC) patients. Many patients either respond poorly or relapse on AIs. A comprehensive view of the underlying genomic landscape of such patients may aid in a better understanding of the resistance mechanisms and the development of new targeted therapies. This study leveraged a real-world clinico-genomic dataset of BC patients to identify key biomarkers and the corresponding high frequency mutations in this relapse/refractory patient population. Methods: This retrospective study used ConcertAI’s Genome360TM BC dataset (N=3223). A cohort of HR+/HER2− mBC patients who were either refractory to or relapsed on AIs (N=863) were included. To identify key resistance genes/pathways, only genomic data (from NGS tests) from a biopsy performed after tumor progression on AIs was considered. Prevalence analysis was done only based on known pathogenic/likely pathogenic variants. Pathway analysis of identified biomarkers with the mechanism of action of AIs was performed to identify and validate key resistance pathways. Further, signatures of unique protein alteration were identified within the biomarkers of interest. Results: The median age of patients at the time of diagnosis was 54 years. Adenocarcinoma and Lobular/Ductal carcinoma were the two most prevalent histologies. 51% of patients in this cohort were treated with AIs in the first line. Table 1 lists the 20 most frequently altered genes observed in this cohort. Genes with a potential role in AI resistance based on pathway analysis are indicated. The most common mutations in selected biomarkers are also provided. These biomarkers were observed at a much lower frequency in patients who responded well to AIs. Conclusion: This study provides insights into the genetic basis of resistance to AIs in mBC patients, opening up possibilities for development of new treatments to overcome resistance. Table 1: Top 20 biomarkers and their variants found in AI relapse/refractory mBC Patients. Biomarker Prevalence (%) Potential Role in AI Resistance Key Variants ESR1 37.81 Yes D538G, Y537, Y537N, E380Q, Y537C PIK3CA 37.04 Yes H1047R, E545K, E542K, H1047L, E726K, N345K TP53 35.56 GATA3 14.25 Yes Frameshift Mutation (Mainly) CDH1 11.64 Yes Frameshift Mutation (Mainly) MAP3K1 9.35 KMT2C 9.02 PTEN 8.38 Yes Frameshift Mutation (Mainly) ARID1A 8.17 RB1 7.38 Yes Frameshift Mutation (Mainly) DNMT3A 5.31 ATM 5.30 TBX3 5.10 SPEN 4.90 NF1 4.82 Yes Frameshift Mutation (Mainly) AKT1 4.74 Yes E17K ERBB2 3.21 Yes L755S, V777L, D769Y KRAS 2.74 Yes G12V, G12D, G12A BRCA1/2 2.69 CDKN2A 1.78 Citation Format: Neeraj Singh, Smita Agrawal. Identifying the genetic basis for resistance to aromatase inhibitors (AIs) in metastatic breast cancer (mBC) patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3829.