Abstract
PURPOSE: Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy associated with an exceptionally poor prognosis. A limitation in its standard-of-care management is the absence of practical molecular tools for monitoring disease progression. Circulating tumor DNA (ctDNA) has emerged as a promising biomarker with potential applications in prognostication, early detection of cancer recurrence, refined evaluation of treatment response, and improved disease surveillance. MATERIALS AND METHODS: We analyzed serial plasma samples from 81 patients with SCLC using a 105-gene hybrid capture-based next-generation sequencing liquid biopsy assay at three key time points: diagnosis, postchemotherapy, and clinical relapse. RESULTS: Extensive-stage (ES) patients demonstrated significantly higher median baseline maximum variant allele frequency (VAF(max)) compared with limited-stage cases. Notably, limited-stage patients with VAF(max) >40% experienced outcomes similar to those with ES disease. Across the cohort, median VAF(max) values declined from 53.30% at baseline to 0.15% during remission and then rose to 38.65% at relapse, reflecting initial therapeutic sensitivity followed by disease recurrence that remained unremitting. Baseline VAF(max) correlated with the overall response rate (ORR), progression-free survival (PFS), and overall survival (OS). Moreover, disease-free survival (DFS), defined as the time to relapse from the date of clinical response (evaluated post-4-cycle chemotherapy), was significantly associated with baseline VAF(max) and a decline in VAF(max) of <99.89% at remission. Relapse genomic profiles largely mirrored baseline alterations, although some patients showed novel mutations. CONCLUSION: Median ctDNA VAF(max) was strongly associated with OS, PFS, DFS, and ORR. Importantly, patients with detectable residual alterations at completion of prescribed chemotherapy exhibited a markedly shorter DFS, less than that of patients with lower detectable residual alterations, highlighting the potential utility of ctDNA in risk stratification and the value of early trial enrollment for high-risk subgroups.