Circulating Tumor DNA-Based Stratification Strategy for Chemotherapy Plus PD-1 Inhibitor in Advanced Non-Small-Cell Lung Cancer

Medical Laboratory Science Oncology Life Sciences Immunology Medicine
circulating tumor DNA chemotherapy PD-1 inhibitor non-small-cell lung cancer personalized treatment

Exploration of a Chemotherapy and PD-1 Inhibitor Personalized Stratification Strategy Based on Circulating Tumor DNA in Advanced Non-Small Cell Lung Cancer

Background and Significance of the Study

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths globally. In the treatment of advanced NSCLC, the combination of immune checkpoint inhibitors (ICIs) and chemotherapy has become the standard first-line therapy, particularly for patients with a programmed death ligand-1 (PD-L1) expression of less than 50%. However, not all patients benefit from this combined therapy, resulting in unnecessary adverse events and wasted medical resources. Therefore, there is an urgent need for an effective stratification strategy to identify patients who can benefit from the combination therapy of PD-1 inhibitors and chemotherapy to optimize personalized treatment plans.

Circulating tumor DNA (ctDNA) shows promise in predicting tumor characteristics, allowing for the evaluation of tumor immune response potential and prognosis by detecting genetic features such as tumor mutation burden and intratumor heterogeneity. This study is based on a multicenter randomized controlled phase III clinical trial (Choice-01), where ctDNA samples were prospectively collected and analyzed from patients with advanced NSCLC. The goal was to develop a ctDNA-based stratification strategy to identify patient groups that could benefit from the combination of chemotherapy and PD-1 inhibitors, ultimately proposing a potential personalized immunochemotherapy model.

Methods

The study involved 460 patients with advanced NSCLC participating in the Choice-01 trial. High-throughput gene sequencing and low-depth whole-genome sequencing were conducted on their blood samples to identify biomarkers predictive of the treatment efficacy of chemotherapy combined with PD-1 inhibitors. These biomarkers included ctDNA status and genomic features such as blood-based tumor mutational burden (BTMB), intratumor heterogeneity (ITH), and chromosomal instability (CIN). The specific process included:

  1. Sample Collection and Processing: Baseline plasma samples from 460 patients were collected. All samples underwent deep sequencing using the OncoScreen 520 gene panel and low-depth whole-genome sequencing (LPWGS).
  2. Experimental Design and Grouping: Patients were grouped based on PD-L1 expression, tumor type, and smoking status and were randomly assigned in a 2:1 ratio to either a chemotherapy combined with PD-1 inhibitor group or a chemotherapy-only group.
  3. Genomic Analysis: The ctDNA-positive and negative states were defined using maximum somatic allele frequency (MSAF), and the impact of baseline ctDNA status on the effect of combined therapy was further analyzed.

Results

1. Prognostic Analysis of Baseline ctDNA Status

The study showed that patients with baseline ctDNA-negative status usually had better survival prognosis, and no significant additional survival benefit was observed in the chemotherapy combined with PD-1 inhibitor group. In contrast, ctDNA-positive patients demonstrated a significant advantage in objective response rate (ORR) and progression-free survival (PFS) with the combined treatment. Therefore, the study suggests prioritizing ctDNA-positive patients for further stratification.

2. Predictive Effect of Genomic Features

In ctDNA-positive patients, BTMB, ITH, and CIN as genomic markers showed inconsistent potential in predicting survival benefits. Notably, high BTMB levels were associated with significantly prolonged PFS, while patients with low ITH and CIN demonstrated better overall survival (OS) under the chemotherapy combined with PD-1 inhibitor treatment. Comprehensive analysis of these indicators further confirmed the limitations of relying on a single genomic marker to accurately predict clinical outcomes, highlighting the importance of integrating multi-dimensional markers.

3. Genomic Immune Subtype Stratification Strategy Based on ctDNA

Based on the genomic features of ctDNA-positive patients, a blood-based genomic immune subtype (BGIS) stratification scheme was proposed, classifying patients into three subtypes: - BGIS-1: Patients with baseline ctDNA-negative status, showing generally good prognosis. - BGIS-2: Patients carrying any ICI favorable characteristics (e.g., high BTMB or low ITH/CIN), who exhibited significant survival benefits from the combined treatment. - BGIS-3: Patients without ICI favorable characteristics, who did not demonstrate significant survival advantages with the combined treatment.

The study indicates that only BGIS-2 subtype patients experienced significantly prolonged PFS and OS under chemotherapy combined with PD-1 inhibitors, suggesting this subtype as the primary target population for the combined treatment, while new treatment strategies should be explored for BGIS-3 subtype patients.

Clinical Application Value and Future Outlook

The main innovation of this study lies in the proposal of a ctDNA-based stratification strategy. By integrating different levels of genomic markers, it promises to realize personalized treatment for NSCLC patients. The study demonstrates that the BGIS stratification strategy can assist in first-line treatment selection and dynamically monitor treatment effects, providing an effective stratification tool for clinical practice. Additionally, the strategy’s reliability and reproducibility were validated in two independent phase III trials, showcasing its broad application potential.

In practice, for BGIS-1 subtype patients, considering their better survival prognosis, more personalized first-line treatment options could be considered. For BGIS-2 subtype patients, it is recommended to prioritize chemotherapy combined with PD-1 inhibitors. For BGIS-3 subtype patients, since the current combined treatment model is not significantly effective, further exploration of new treatment schemes or sensitization methods is needed.

Discussion and Limitations

The study compared whole-exome sequencing data of patients’ blood and tissue samples, identifying differences in tumor characteristics and immune response potential across BGIS subtypes, providing theoretical support for the rationality of the stratification strategy. However, because this study was the first to provide blood WGS data in such a patient population, an ideal external validation cohort with CIN data is currently lacking, with verification results partially relying on surrogate indicators such as BTMB and ITH. Moreover, due to the risk of false negatives brought by low ctDNA concentration, some results need cautious interpretation, emphasizing the need for prospective studies to further validate these findings.

Conclusions

Through an in-depth study of the panoramic and longitudinal genomic characteristics of ctDNA in the Choice-01 trial patients, a ctDNA-based stratification strategy (BGIS) was proposed and validated for its predictive value in immunochemotherapy for advanced NSCLC patients, offering new insights for personalized treatment management. The BGIS stratification strategy not only guides patients’ first-line treatment choices but also shows promising prospects in dynamically monitoring treatment effects, providing essential references for future prospective study designs.