Glyco-signatures in patients with advanced lung cancer during anti-PD-1/PD-L1 immunotherapy

Immune checkpoint inhibitors (ICIs) targeting programmed cell death 1/programmed cell death ligand-1 (PD-1/PD-L1) have significantly prolonged the survival of advanced/metastatic patients with lung cancer. However, only a small proportion of patients can benefit from ICIs, and clinical management of the treatment process remains challenging. Glycosylation has added a new dimension to advance our understanding of tumor immunity and immunotherapy. To systematically characterize anti-PD-1/PD-L1 immunotherapy-related changes in serum glycoproteins, a series of serum samples from 12 patients with metastatic lung squamous cell carcinoma (SCC) and lung adenocarcinoma (ADC), collected before and during ICIs treatment, are firstly analyzed with mass-spectrometry-based label-free quantification method. Second, a stratification analysis is performed among anti-PD-1/PD-L1 responders and non-responders, with serum levels of glycopeptides correlated with treatment response. In addition, in an independent validation cohort, a large-scale site-specific profiling strategy based on chemical labeling is employed to confirm the unusual characteristics of IgG N-glycosylation associated with anti-PD-1/PD-L1 treatment. Unbiased label-free quantitative glycoproteomics reveals serum levels' alterations related to anti-PD-1/PD-L1 treatment in 27 out of 337 quantified glycopeptides. The intact glycopeptide EEQFN ¹⁷⁷STYR (H3N4) corresponding to IgG4 is significantly increased during anti-PD-1/PD-L1 treatment (FC=2.65, P=0.0083) and has the highest increase in anti-PD-1/PD-L1 responders (FC=5.84, P=0.0190). Quantitative glycoproteomics based on protein purification and chemical labeling confirms this observation. Furthermore, obvious associations between the two intact glycopeptides (EEQFN ¹⁷⁷STYR (H3N4) of IgG4, EEQYN ²²⁷STFR (H3N4F1) of IgG3) and response to treatment are observed, which may play a guiding role in cancer immunotherapy. Our findings could benefit future clinical disease management.