Unveiling the crucial role of glycosylation modification in lung adenocarcinoma metastasis through artificial neural network-based spatial multi-omics single-cell analysis and Mendelian randomization.

backgroundInvestigations into the intricacies of glycosylation modifications, a prevalent post-translational alteration observed in neoplasms, especially remain elusive in the context of lung adenocarcinoma. Through the integration of multiple omics approaches, the investigation aimed to delineate the significance of glycosylation in lung adenocarcinoma, with an objective to pinpoint viable biological targets.

methodsInitial steps involved the identification of genes differentially expressed in relation to glycosylation at the aggregate transcriptome level within lung adenocarcinoma tissues. This was followed by analyses of localization and function employing both single-cell and spatial transcriptomics to provide a more nuanced understanding. In pursuit of elucidating functional disparities in glycosylation patterns, a predictive framework employing artificial neural networks was constructed. To ascertain causal relationships between specific genes and lung adenocarcinoma, Mendelian randomization was applied, culminating in the experimental validation of these genes' roles.

resultsAnalysis at the single-cell level uncovered marked glycosylation modification expressions in metastatic tissues of lung adenocarcinoma. Moreover, tissues of lung adenocarcinoma with elevated expression of genes associated with glycosylation displayed enhanced differentiation and activation across signaling pathways including TGF-β, oxidative stress, and WNT. Through spatial transcriptomics, zones of intense glycosylation modification were pinpointed within tumor nests and proximate to tumor-associated blood vessels. An artificial neural network-derived prognostic model demonstrated outstanding predictive capability, with AUC scores achieving 0.84, 0.83, and 0.89 for 1, 3, and 5-year forecasts, respectively. The group identified as high-risk was characterized by pronounced immunosuppression and diminished responsiveness to immunotherapy. Mendelian randomization analysis pinpointed GLANT2 (OR = 1.3654, p < 0.05) and GYS1 (OR = 1.2668, p < 0.05) as genes contributing to the pathogenesis of lung adenocarcinoma. Cell assays have reaffirmed that the inhibition of GYS1 significantly reduces proliferation and invasion in lung adenocarcinoma cell lines, while also decreasing glycogen storage and the formation of glycosylation end products, indicating suppression of glycosylation processes. These findings identify GYS1 as a prospective glycosylation-linked biological target for lung adenocarcinoma therapy.