作者
Kezhong Chen,Chenyang Wang,Haifeng Shen,Xi Li,Yichen Jin,Shuailai Wu,Fujun Qiu,Qiang Lü,Di Peng,Shuai Fang,Bing Li,Juan Lv,Jinlei Song,Yang Wang,Shannon Chuai,Zhihong Zhang
摘要
Abstract Background: Through parallel testing and comparison of personalized and fixed panel minimal residual disease (MRD) assays, to establish the best technique and application strategy of dynamic MRD detection for prognosis prediction and disease assessment among non-small cell lung cancer (NSCLC) patients. Method: We analyzed 760 plasma samples from prospectively enrolled 181 patients with NSCLC recruited to the MEDAL study (NCT03634826), with disease stage I (63%), II (19%) and III (18%). 80% were adenocarcinomas. Plasma samples were collected at baseline (n=157), landmark 3-day and 1-month (n=334), and longitudinal points (n=248) were analyzed. Additional plasma was collected after relapse for 14 patients (n=21). Median follow-up was 1092 days, and 48 patients progressed. We employed a novel personalized tumor-informed technology named PROPHET using deep sequencing of 50 patient-specific variants. The PROPHET was developed to detect MRD with a limit of detection (LoD) of 0.004% and sample-level specificity of greater than 99% in the analytical validation. Detection and quantification of MRD through tumor-informed (TI) and tumor-agnostic (TA) fixed panel assays in the same samples were conducted for a head-to-head comparison. Results: ctDNA was detected by PROPHET prior to treatment in 45% of samples (83%, 75% and 23% for disease stage III, II and I), and showed a higher positive rate than the TI and TA assays (22% and 19%). PROPHET identified 30 more ctDNA positive patients with a median ctDNA fraction of 0.01% at baseline. From the landmark single test, the sensitivity was 45%; integrating longitudinal time points increased the sensitivity to 85%. Landmark PROPHET status was the only risk factor other than clinical features to predict the clinical relapse (p<0.001, multivariate Cox model). MRD positive patients defined by non-canonical variants (n=8) had similar disease-free survival (DFS) as MRD positive patients defined by canonical variants (n=9). Landmark PROPHET-based MRD status combined with clinical TNM stage outperformed TNM stage for prediction of prognosis (p<0.001). Longitudinal MRD achieved negative predictive value (NPV) of 99% with an interval of 150 days, and demonstrated 299 days of longer lead-time than other state-of-the-art fixed-panel assays. Among 16 patients with equivocal radiological diagnosis, all the MRD positive patients relapsed (n=6). Among relapsed patients received next-line treatments, 7 ctDNA negative patients survived or died other disease, 67% (2/3) ctDNA positive patients died from cancer. Sensitivity for bone and brain metastasis was 100% (11/11) and 50% (2/4), respectively. Conclusion: The sensitive tumor-informed personalized MRD approach could provide advantages in prognosis prediction at landmark and disease assessment during surveillance for NSCLC patients. Citation Format: Kezhong Chen, Chenyang Wang, Haifeng Shen, Xi Li, Yichen Jin, Shuailai Wu, Fujun Qiu, Qiang Lu, Di Peng, Shuai Fang, Bing Li, Juan Lv, Jinlei Song, Yang Wang, Shannon Chuai, Zhihong Zhang. Individualized tumor-informed circulating tumor DNA (ctDNA) analysis for postoperative monitoring of non-small cell lung cancer (NSCLC) - the MEDAL study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1039.