Abstract 7043: Genomic profiling of DLL3-positive and negative CTCs in small cell lung cancer

Abstract BACKGROUND: Delta-like ligand 3 (DLL3), an atypical Notch family protein implicated in neuroendocrine tumorigenesis, has emerged as a promising therapeutic target in small cell lung cancer (SCLC), prompting numerous clinical trials investigating DLL3-targeted treatments. Exploring DLL3 in circulating tumor cells (CTCs) through liquid biopsy, coupled with comprehensive genomic analysis, presents an invaluable and minimally-invasive avenue for monitoring disease progression. This approach holds the potential to tailor personalized treatment strategies, emphasizing the critical need for in-depth investigations into both DLL3-positive and negative cell genomic compositions. METHODS: This study examined blood collected in CellSave preservative tubes from stage I (n=17) and stage IV (n=12) SCLC patients, as well as healthy donors (n=10). The CELLSEARCH® platform was employed to count EpCAM-enriched CTCs and evaluate DLL3 protein expression. Subsequently, individual CTCs were isolated based on the presence and absence of DLL3 expression using the DEPArray™ PLUS. The isolated DLL3-negative and positive CTCs were subjected to low-pass sequencing using the Ampli1™ LowPass Kit to uncover genomic aberrations. RESULTS: CTCs were absent in the healthy control group. In stage I patients, CTCs were identified in 5. 8% of blood samples, while in stage IV patients, they were present in 50% of samples, with an average CTC count of 148 in stage IV. Among a total of 2074 detected CTCs, 460 were DLL3-positive, accounting for 6-28% of EpCAM-enriched CTCs in individual patients. Analysis of 300 copy number alteration (CNA) profiles of sorted single cells revealed considerable inter-patient and intra-patient heterogeneity, delineating recurrent clonality and specific genomic alterations in DLL3-negative CTCs. In contrast, DLL3-positive cells showed more stochastic CNA profiles, suggestive of apoptosis-related DNA fragmentation. CONCLUSIONS: Integrating CellSearch, DEPArray, and low-pass sequencing provides a minimally-invasive approach to compare genomic characteristics in DLL3-positive and negative CTCs from SCLC patients. Extension of this approach to a larger patient cohort and employing machine learning algorithms will facilitate identification of patterns within diverse CNA profiles, improving patient stratification and predicting treatment responses for personalized therapeutic strategies in SCLC. Citation Format: Zoltan Simandi, Thai Bui, Alberto Ferrarini, Steven Hepburn, Richard G. Del Mastro. Genomic profiling of DLL3-positive and negative CTCs in small cell lung cancer 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 (6Suppl): Abstract nr 7043.