Background: Small-cell lung cancer (SCLC) represents an aggressive malignancy associated with a poor prognosis, underscoring the critical demand for enhanced monitoring methodologies. Circulating tumor DNA (ctDNA) constitutes a promising non-invasive biomarker; however, reports employing highly sensitive tumor-informed assays in SCLC remain scarce. This investigation aimed to assess the clinical utility of a personalized ctDNA monitoring strategy for predicting therapeutic outcomes and resistance in SCLC patients. Methods: This prospective observational study enrolled patients diagnosed with unresectable SCLC. Whole exome sequencing was conducted on baseline tumor specimens to design customized 16-plex multiplex polymerase chain reaction (PCR) panels. Serial blood samples were obtained at baseline, at six-week intervals during treatment, and upon disease progression. Detection of ctDNA-based minimal residual disease (MRD) was performed using a tumor-informed assay (Huajianwei^® bespoke MRD) with ultra-deep sequencing. Results: Among seven evaluable patients, the baseline ctDNA-MRD positivity rate was 100%. A significant positive correlation was observed between the baseline ctDNA levels and radiographic tumor burden (r = 0.821, 95% confidence interval [CI] 0.179–0.973, p = 0.034). Longitudinal analysis indicated that patients exhibiting an early decline in MRD levels demonstrated a non-significant trend toward superior progression-free survival (PFS) compared to those with an MRD increase. Though this between-group difference did not reach conventional statistical significance, it represented a trend-level finding (p = 0.0665, hazard ratio [HR] = 0.24, 95% CI: 0.02–3.19), with no definitive prognostic association confirmed in this pilot cohort. Notably, an elevation in MRD preceded radiographic progression by as much as 135 days in certain instances. Conclusions: This study shows that dynamic tumor-informed ctDNA-based MRD monitoring reflects tumor burden changes and may correlate with clinical outcomes in SCLC, supporting its potential to guide personalized treatment and facilitate earlier therapeutic interventions compared to conventional imaging techniques. Prospective multicenter validation is needed to confirm its clinical utility.

Background: Small-cell lung cancer (SCLC) represents an aggressive malignancy associated with a poor prognosis, underscoring the critical demand for enhanced monitoring methodologies. Circulating tumor DNA (ctDNA) constitutes a promising non-invasive biomarker; however, reports employing highly sensitive, tumor-informed assays in SCLC remain scarce. This investigation aimed to assess the clinical utility of a personalized ctDNA monitoring strategy for predicting therapeutic outcomes and resistance in SCLC patients. Methods: This prospective, observational study enrolled patients diagnosed with unresectable SCLC. Whole exome sequencing was conducted on baseline tumor specimens to design customized 16-plex multiplex PCR panels. Serial blood samples were obtained at baseline, at six-week intervals during treatment, and upon disease progression. Detection of ctDNA-based minimal residual disease (MRD) was performed using a tumor-informed assay (Huajianwei® bespoke MRD) with ultra-deep sequencing. Results: Among seven evaluable patients, the baseline ctDNA-MRD positivity rate was 100%. A significant positive correlation was observed between baseline ctDNA levels and radiographic tumor burden (r = 0.821, P = 0.034). Longitudinal analysis indicated that patients exhibiting an early decline in MRD levels (n=5) demonstrated a trend toward superior progression-free survival (PFS) compared to those with an MRD increase (n=2) (P = 0.0665, hazard ratio (HR) = 0.24 (95% CI: 0.02 - 3.19)). Notably, elevation in MRD preceded radiographic progression by as much as 135 days in certain instances. Conclusions: Tumor-informed ctDNA-MRD monitoring effectively mirrors tumor burden and offers early prediction of treatment response and clinical outcomes in SCLC. ctDNA kinetics may serve as a crucial prognostic indicator, presenting the potential to inform personalized management approaches and facilitate earlier therapeutic interventions compared to conventional imaging techniques.