ctDNA Concentration, MIKI67 Mutations and Hyper-Progressive Disease Related Gene Mutations Are Prognostic Markers for Camrelizumab and Apatinib Combined Multiline Treatment in Advanced NSCLC

Immunotherapy by immune checkpoint inhibitors (ICIs) has showed outstanding efficacy in the treatment of advanced non-small cell lung cancer (NSCLC). The combination of immunotherapy with anti-angiogenic therapy exhibited enhanced efficacy in multiline treatment. However, the potential biomarkers for predicting and monitoring the therapeutic response of the combined therapy remain undefined. In this study, we performed a pilot study by prospectively recruiting 22 advanced NSCLC patients who failed to previous lines of chemotherapy, chemoradiotherapy, TKI therapy, surgery, or any combination of the therapies, and investigated the prognostic factors for patients who received anti-PD-1 (Camrelizumab) and anti-angiogenic (Apatinib) combined therapy. The objective response rate (ORR) assessed by an independent radiology review was 22.7%, and the median progression-free survival (PFS) was 5.25 months. We found that high concentration of circulating-free DNA (cfDNA) (HR = 27.75, P = 0.003), MIKI67 mutation (HR = 114.11, P = 0.009) and gene variations related to hyper-progressive disease (HPD) (HR = 36.85, P = 0.004) were independent risk factors and exhibited significant correlation with PFS. Circulating tumor DNA (ctDNA) mutational status was also a predicting indicator for PFS. In contrast, the blood tumor mutational burden (bTMB) could not stratify the clinical benefit in this combined therapy (HR = 0.81, P = 0.137). Furthermore, we found that the variant allele fraction (VAF) of mutations in ctDNA was sensitive indicators of therapeutic response and therefore can be used to monitor the tumor relief or progression. In conclusion, cfDNA concentration, MIKI67 mutations and HPD-related mutations were independent risk factors and PFS predictors for multiline combined anti-angiogenic/ICI combined therapy. ctDNA may be a novel monitoring biomarker for therapeutic response and predicting biomarker for prognosis in future combined therapy involving PD-1 blockade.