Abstract 3236: Analytical validation of a tumor-agnostic DNA methylation-based assay for minimal residual disease detection in lung cancer

Abstract Background: Minimal residual disease (MRD) detection methods are pivotal for non-invasive tumor fraction assessment in lung cancer, enabling disease monitoring and prognosis. Mutation-based assays, such as Signatera and PROPHET [1], have shown favorable performance in detecting MRD. Since DNA methylation can also reflect cancer features, we hereby developed the STELLA, a tumor-agnostic assay leveraging targeted DNA methylation sequencing of cell-free DNA (cfDNA) from blood, to explore the efficacy of DNA methylation in tracking MRD in lung cancer. Methods: To demonstrate proof-of-concept, we designed and validated a STELLA pilot panel, which includes 341 lung-cancer-specific hypermethylated regions with low background noise level (≤1e-5) derived from 2, 485 healthy samples. The ctDNA fraction in plasma samples was quantified using a maximum likelihood method based on the cumulative probability p-values across the selected regions. Results: Analytical validation revealed that our assay can detect tumor fractions as low as 0.02% with a DNA input of 30 ng. In a cohort of 126 PROPHET-positive and 436 PROPHET-negative lung cancer samples, STELLA achieved a PPA of 73.8% and NPA of 97.9% using PROPHET as an orthogonal reference, with tumor fraction measurements strongly correlating with PROPHET (R = 0.73, P < 0.001). Probit regression analysis established a limit of detection (LOD) of 0.019%. In an independent cohort of 87 PROPHET-positive and 338 PROPHET-negative samples from 148 surgically treated lung cancer patients in the MEDAL cohort [1], STELLA demonstrated a PPA of 41.4% and NPA of 98%, using PROPHET as an orthogonal reference relative to PROPHET. In preoperative plasma samples, STELLA detected circulating tumor DNA (ctDNA) with a sensitivity of 32.6%, outperforming a mutation-based tumor-naïve assay (21.7%) but underperforming PROPHET (58.7%). Critically, postoperative STELLA-positive results correlated with significantly shorter disease-free survival (hazard ratio [HR]: 3.98; 95% CI: 1.74-9.13; P < 0.001). Conclusion: These findings underscore the potential of DNA methylation-based, tumor-agnostic cfDNA methods like STELLA to detect MRD in lung cancer with a tumor fraction as low as 0.02% and an NPA of 98%. STELLA offers a promising approach for tumor burden assessment, providing timely insights for treatment decisions and enhancing patient care. Reference: 1. Chen K, Yang F, Shen H, et al. Individualized tumor-informed circulating tumor DNA analysis for postoperative monitoring of non-small cell lung cancer. Cancer Cell. 2023;41(10):1749-1762. Citation Format: Bo Yang, Yuan Sun, Lei Wang, Peiru Liu, Simei Qiu, Lei Chen, Fujun Qiu, Yalan Jin, Shuailai Wu, Yu Xu, Lei Zhang, Zhihong Zhang, Kezhong Chen. Analytical validation of a tumor-agnostic DNA methylation-based assay for minimal residual disease detection in 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 3236.