Abstract
Glioma, the most common primary intracranial tumor, has seen increased scrutiny with the advent of high-throughput detection technologies, yet many aspects of its tumorigenesis and progression remain enigmatic. In this study, we utilized 4D label-free mass quantitative proteomics to analyze glioma protein expression, with a focus on SUMOylated proteins through SUMO peptide enrichment. Bioinformatics analysis was applied to identify differentially expressed proteins (DEPs) and differentially SUMOylated proteins, elucidating their functions and interactions. By integrating proteomics and transcriptomics data, we pinpointed core proteins with consistent upregulation and assessed their potential as drug targets in glioma through virtual screening of eight cytoplasmic proteins with small molecule binding cavities. Our findings reveal that low-grade glioma (LGG) exhibits more DEPs than glioblastoma (GBM) when compared to normal brain tissue, but GBM shows more disrupted functions. LGG is characterized by a higher number of SUMOylated proteins in key processes, whereas GBM has fewer, with these SUMOylated proteins implicated in diverse functions, including RNA and protein regulation, metabolism, and immunity. There is also a significant discrepancy between RNA and protein levels for most molecules. The virtual docking of core oncogenic molecules suggests potential therapeutic targets and transformation opportunities. This study deepens our comprehension of glioma proteomics and SUMOylation, revealing novel pathological mechanisms and laying the groundwork for targeted glioma therapies.