Immunoglobulin G N-glycan signatures as potential diagnostic and predictive biomarkers for non-small-cell lung cancer.

Our previous research revealed aberrant serum N-glycan profiles in non-small-cell lung cancer (NSCLC), but the specific protein sources remain unclear. While immunoglobulin G (IgG) N-glycosylation has been implicated in cancer, its alterations in NSCLC are not well defined. Herein, we profiled the serum IgG N-glycome of 314 NSCLC patients and 364 healthy controls using a high-throughput MALDI-TOF-MS platform. Lectin-based enzyme-linked immunosorbent assay (ELISA) was applied for orthogonal validation. Machine learning was employed to construct a glycan-based diagnostic model. Two-sample Mendelian randomization (MR) analysis was performed to access potential causal relationships. The findings suggested positive correlations between matched IgG and whole-serum N-glycans. Compared with controls, NSCLC patients exhibited distinct IgG glycosylation patterns, including decreased galactosylation, monosialylation, and bisecting N-acetylglucosamine, alongside increased agalactosylation. The lectin-based assay confirmed the reductions in IgG galactosylation and sialylation. An eight-glycan panel demonstrated robust capability for NSCLC discrimination. MR analysis further revealed an inverse association between the IgG FS1/FS2 ratio and NSCLC risk. In conclusion, this study identified dysregulated IgG N-glycan signatures in NSCLC and proposed a pathogenic role for specific glycosylation traits. The findings unveil the potential of IgG glycans as non-invasive biomarkers and provide novel insights into the pathogenesis and therapeutic strategies for NSCLC.