Identifying novel therapeutic targets for glioblastoma: Insights from plasma proteome analysis

Glioblastoma (GBM) is the most prevalent primary malignant brain tumor, characterized by a poor prognosis and a median survival of less than two years. This underscores the urgent need for the development of more effective therapeutic strategies. The present study aimed to identify potential therapeutic targets for GBM by examining the causal relationships between plasma proteome and GBM. Mendelian randomization (MR) was employed to investigate the association between the plasma proteome and GBM. The inverse variance weighted (IVW) method was the primary analytical method to infer causal relationships. Heterogeneity and pleiotropy tests were also conducted to assess the robustness of the results. Subsequently, the causal proteins were mapped to their encoding genes for functional exploration, enrichment analysis and protein-protein interaction (PPI) network analysis were performed to explore the roles of selected causal proteins. The gene set was submitted to the Enrichr online tool, utilizing the DSigDB database for drug perturbation enrichment analysis. The top 10 significant results were ranked by their combined score. To prioritize compounds with higher drug-likeness and translational potential, these candidates were further filtered based on key Absorption, Distribution, Metabolism, and Excretion (ADME) properties. The key target protein and its top-associated perturbagen that also exhibited favorable ADME profiles were then selected for in silico validation through molecular docking and molecular dynamics (MD) simulations to assess binding stability and mechanism. 19 novel proteins were found to have a causal association with GBM risk. Enrichment analysis revealed that the biological processes were focused on the positive regulation of the MAPK cascade, cellular component analysis highlighted a focus on the nuclear pore outer ring, and molecular function analysis emphasized oxidoreductase activity, specifically acting on NAD(P)H with quinone or similar compounds as acceptors. KEGG pathway analysis was centered on purine metabolism. Critically, DSigDB enrichment analysis pinpointed testosterone as the key bioactive perturbagen most strongly associated with the AKR1C4-centered gene set (P = 0.0066, Combined Score = 912.35), a finding sourced from the therapeutic target database. Molecular docking predicted a stable interaction between testosterone and AKR1C4 with a low binding energy (-10.0 kJ/mol), a prediction further corroborated by MD simulations, which elucidated the dynamic binding mechanism. In summary, AKR1C4 is a novel causal plasma protein influencing GBM risk. The AKR1C4-testosterone-AR axis it delineates thereby provides a mechanistic explanation for the sexual dimorphism observed in GBM and unveils a new therapeutic target.