[Progress on PD-1/PD-L1 Checkpoint Inhibitors in Lung Cancer]

Partial Least-Squares Discriminant Analysis and Ensemble-Based Flexible Docking of PD-1/PD-L1 Inhibitors: A Pilot Study

Although mAbs targeting the programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) pathway have achieved remarkable therapeutic potential against multiple types of cancer, it is still of great interest for researchers to develop small-molecule PD-1/PD-L1 inhibitors without the mAb-related disadvantages of no oral bioavailability and poor solid tumor penetration. However, targeting the PD-1/PD-L1 pathway with small molecules is normally considered challenging because of the flat and large interaction surface of the PD-1/PD-L1 complex. In this paper, a total of 2558 PD-1/PD-L1 inhibitors were compiled from recent patents and literatures and then used for exploring the chemical space and structural features of PD-1/PD-L1 inhibitors by partial least-squares discriminant analysis. The results showed that intramolecular H bond, amphotericity indices, radius of gyration, nonbond electrostatic energy, fractional van der Waals surface area of H-bond donors, octanol-water partition coefficient, and molecular weight are the seven key features discriminating the PD-1/PD-L1 inhibitors from noninhibitors, with the prediction accuracy larger than 0.90. Based on the seven crystal structures of the PD-L1 dimer complexed with the patent Bristol Myers Squibb (BMS) inhibitors, the feasibility of molecular docking for this unconventional binding pocket was further investigated. The results showed that the ensemble-based flexible docking protocol can reproduce the near-native binding conformations of the BMS inhibitors with a strong correlation between the IC₅₀ values and ligand-receptor interaction energies (R = 0.81). In general, this paper delineates, for the first time, the characteristic features of the PD-1/PD-L1 inhibitors as well as a high-quality flexible docking strategy for the unconventional binding pocket of the PD-L1 dimer.

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.