Abstract 5909: MRD as a predictive biomarker in patients with small cell lung cancer

Abstract Background: Despite the high response rate to initial treatment, the clinical outcomes of small cell lung cancer (SCLC) remain challenging. Tumor-informed minimal residual disease (MRD) assessments, leveraging circulating tumor DNA (ctDNA) detection, offer a promising approach for early detection and personalized treatment guidance in SCLC. However, their full potential is yet to be demonstrated. Objective: This study aims to investigate the predictive value of a plasma-based personalized MRD monitoring assay in SCLC patients. Methods: We conducted a prospective study, collected clinical data and performed high-throughput whole-exome sequencing (WES) on baseline tumor tissue from SCLC patients. Personalized panels were constructed based on WES data to dynamically monitor MRD through ctDNA extracted from plasma. To evaluate the correlation between MRD dynamics and treatment outcomes, peripheral blood samples were collected at baseline, every 6 weeks ±7 days during treatment, and at disease progression. Results: Seven SCLC patients with consent were recruited for the study, including those with limited stage (n=2) and with extensive stage (n=5). One patient was diagnosed with combined SCLC. Five patients received platinum-based combination regimens, and the other two received monotherapy irinotecan and anlotinib hydrochloride, respectively. The median age was 60 years (range, 68 to 74 years), and all patients had a smoking history. The MRD positive rate at baseline was 100%. TP53 and RB1 genes were the most frequently mutated genes, at 100% and 85.7%, respectively. The MRD elevated up to 48 days prior to disease progression. Patients in the MRD increase group (n=5) experienced progressive disease (PD) finally and the other in the MRD decrease group (n=2) maintained stable disease (SD) or partial response (PR), with one achieving durable MRD clearance after three cycles of sequential chemoradiotherapy. At the end of follow-up, the PFS analysis between the MRD increase and decrease cohorts revealed a clear trend of separation, despite the lack of statistical significance (p=0.06, 95% CI: 1.09-42.81). Moreover, MRD dynamics were more pronounced than the traditional cancer markers, neuron-specific enolase (NSE) and progastrin-releasing peptide (ProGRP), highlighting its high sensitivity and clinical applicability. WES analysis revealed a diverse landscape of genetic alterations, with prevalent missense mutations in genes such as TTN, MUC2, and ZNF676, alongside coding-synonymous variations. Conclusion: Our study indicates that MRD could predict clinical outcomes and surpass traditional biomarkers, presenting its potential as a biomarker for the management of SCLC patients. Personalized MRD monitoring may provide valuable insights into treatment response and disease progression in SCLC. Further validation with a larger sample size is ongoing. Citation Format: Jianhua Chang, Qiuyi Zhang, Die Dai, Binbin Chen, Meng Zhang, Zongyou Cai, Lihong Guo, Suni Huang, Shiqi Lyu. MRD as a predictive biomarker in patients with small cell lung cancer [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 5909.