Abstract 5400: Predicting disease progression in inoperable localized NSCLC patients using cfDNA fragmentomics assay
Authors: Yang Yin , Zhang Tao , Wang Jingbo , Wang Jianyang , Tang Wanxiangfu , Bao Hua , Tang Haimeng , Wu Xue , Shao Yang , Wang Xin , Wu Yuqi , Wu Linfang , Xu Xin , Xu Kunpeng , Zhao Jingjing , Wang Luhua , Bi Nan 
Published: June 2023

Background: There is an urgent clinical need to accurately predict the risk for disease progression in post-treatment NSCLC patients. However, the current ctDNA mutation profiling approaches were limited by low sensitivity, while the cfDNA fragmentomics profiling has shown an excellent capability for cancer early detection in NSCLC and therefore exhibits great potential for predicting disease progression. In this retrospective study, we aim to develop a non-invasive liquid biopsy assay utilizing cfDNA fragmentomics profiling for predicting disease progression in inoperable localized NSCLC patients.

Methods: The study cohort retrospectively enrolled 44 patients diagnosed with inoperable localized NSCLC who received first-line chemoradiotherapy/radiotherapy (including 23 disease progression during follow-up). Plasma samples were collected during or post-treatments, including 39 at the fourth week of treatment (TP1), 33 and 25 at 1 (TP2) and 3 (TP3) months post-treatment, respectively. cfDNA fragmentomic profiling, generated based on target sequencing data, was used to fit Regularized Cox Regression models. For each time point, a leave-one-out cross-validation (LOOCV) was performed to evaluate the models’ predictive performances, which was subsequently compared against the ctDNA status determined by the mutation-based method.

Results: Our cfDNA fragmentomics assay showed excellent performance detecting patients with a high risk for disease progression. At TP1, the high-risk patients detected by our model showed an increased risk of 3.62 times (hazard ratio [HR] = 3.62, p = 0.0026) for disease progression, compared to 3.91 times (HR = 3.91, p = 0.0022) and 4.00 times (HR = 4.00, p = 0.019) for TP2 and TP3, respectively. These fragmentomics determined HRs were higher compared to the ctDNA mutation-based results (HR = 2.08, p = 0.074; HR = 1.49, p = 0.61) at TP1 and TP3, albeit being lower at TP2 (HR = 9.47, p &lt; 0.0001). At TP1, the predictive model reached 40% sensitivity at 92.9% specificity, which was higher than the mutation-based method (40% sensitivity at 78.6% specificity), while the combination of the two methods reached a higher sensitivity (60%). Finally, a subset of the cohort (N = 19) with data for all three time points (TP1, TP2 and TP3) was examined, and the patients were labelled as high-risk for having a positive prediction or ctDNA status at any time point. The combined methods could predict disease progression with an excellent sensitivity of 88.9% at 80% specificity.

Conclusions: We developed a cfDNA fragmentomics assay for predicting disease progression in inoperable NSCLC patients. This assay showed increased predicting power during and post treatment compared to the ctDNA mutation-based method, thus illustrating a great clinical potential to guide treatment decisions in inoperable NSCLC patients.

Citation Format: Yin Yang, Tao Zhang, Jingbo Wang, Jianyang Wang, Wanxiangfu Tang, Hua Bao, Haimeng Tang, Xue Wu, Yang Shao, Xin Wang, Yuqi Wu, Linfang Wu, Xin Xu, Kunpeng Xu, Jingjing Zhao, Luhua Wang, Nan Bi. Predicting disease progression in inoperable localized NSCLC patients using cfDNA fragmentomics assay. [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 5400.