The Feasibility of Using Biomarkers Derived from Circulating Tumor DNA Sequencing as Predictive Classifiers in Patients with Small-Cell Lung Cancer

Abstract

Purpose: This study aimed to investigate the feasibility of biomarkers based on dynamic circulating tumor DNA (ctDNA) to classify small cell lung cancer (SCLC) into different subtypes. Materials and Methods: Tumor and longitudinal plasma ctDNA samples were analyzed by next-generation sequencing of 1,021 genes. PyClone was used to infer the molecular tumor burden index (mTBI). Pre-treatment tumor tissues (T1) and serial plasma samples were collected (pre-treatment [B1], after two [B2], six [B3] cycles of chemotherapy and at progression [B4]). Results: Overall concordance between T1 and B1 sequencing (n=30) was 66.5%, and 89.5% in the gene of RB1. A classification method was designed according to the changes of RB1 mutation, named as subtype I (both positive at B1 and B2), subtype II (positive at B1 but negative at B2), and subtype III (both negative at B1 and B2). The median progressive-free survival for subtype I patients (4.5 months [95% confidence interval (CI), 2.6 to 5.8]) was inferior to subtype II (not reached, p < 0.001) and subtype III (10.8 months [95% CI, 6.0 to 14.4], p=0.002). The median overall survival for subtype I patients (16.3 months [95% CI, 5.3 to 22.9]) was inferior to subtype II (not reached, p=0.01) and subtype III (not reached, p=0.02). Patients with a mTBI dropped to zero at B2 had longer median overall survival (not reached vs. 19.5 months, p=0.01). The changes of mTBI from B4 to B1 were sensitive to predict new metastases, with a sensitivity of 100% and a specificity of 85.7%. Conclusion: Monitoring ctDNA based RB1 mutation and mTBI provided a feasible tool to predict the prognosis of SCLC.