Abstract 1263: Reconstructing small cell lung cancer evolution using deep whole genome sequencing of circulating tumor DNA

Abstract Background: Small cell lung cancer (SCLC) is the most lethal form of lung cancer. This poor prognosis is due in large part to SCLC’s recalcitrance to therapy. The standard of care for extensive-stage SCLC (ES-SCLC) is chemotherapy with immunotherapy. While most tumors initially respond, responses are transient and >80% of tumors progress within one year of treatment. Seminal studies have shown that sequencing aggressive tumors before and after therapy identifies drivers of resistance. Unfortunately, the aggressive clinical course of ES-SCLC has precluded collection of patient-matched naïve and recurrent tumor tissue traditionally required to study evolution. In lieu of this, other groups have used circulating tumor DNA (ctDNA) to study SCLC evolution. However, these studies used sequencing panels that analyze <0.004% of the SCLC genome. Using new methods to comprehensively trace how SCLCs evolve to therapy resistance is a significant unmet need. Methods: Medical records were reviewed to identify treatment naïve ES-SCLC patients with longitudinal liquid biopsies collected pre- and post-therapy using IRB-approved protocols. ctDNA was isolated from plasma using NucleoSnap cfDNA kits. Germline DNA was extracted from buffy coats using NucleoSpin Blood kits. Whole genome sequencing (WGS) libraries were prepared using Twist cfDNA Library Preparation with UMI Adapter kits. Deep WGS of ctDNA (>100X) and germline DNA (>40X) was performed using an Illumina NovaSeqX sequencer. Reads were aligned to the hg38 reference genome with BWA-mem. Somatic mutations were called using a two-of-three consensus approach and Mutect2, Strelka2, and MuSE. Structural variants were called using a consensus approach with GRIDSS, SvABA, and Manta. Subclonal copy number alterations were identified with Battenberg. Pyclone was used to reconstruct clonal populations. Results: As expected, we identified deleterious genomic alterations impacting TP53 and RB1 tumor suppressor genes, known drivers of SCLC development. COSMIC mutational signature analysis identified high activity of tobacco carcinogen, APOBEC, and replicative-based processes across tumors. We found highly varied patterns of genomic evolution following frontline chemoimmunotherapy across patients. Most ES-SCLC tumors exhibited genomic evolution at recurrence, with evidence of focal amplifications and deletions or whole genome duplication. Some tumors exhibited minimal copy number evolution at relapse, suggesting non-genomic mechanisms driving resistance. We also found that second line therapies forced additional genomic evolution following initial recurrence. Conclusions: Our data demonstrates that deep WGS of ctDNA recapitulates known genetics of ES-SCLC and enables sensitive characterization of resistant clones. Our data highlights the under-appreciated role of genomic evolution in ES-SCLC frontline therapy resistance. Citation Format: Benjamin B. Morris, Zhihui Zhang, Andrew R. Lynch, Simon Heeke, Kyle Concannon, C. Allison Stewart, Runsheng Wang, Alexa Halliday, Waree Rinsurongkawong, Vadeerat Rinsurongkawong, J. Jack Lee, Jianjun Zhang, Don L. Gibbons, Ara A. Vaporciyan, Carl M. Gay, Hai T. Tran, John V. Heymach, Lauren A. Byers, Peter Van Loo. Reconstructing small cell lung cancer evolution using deep whole genome sequencing of circulating tumor DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1263.