(0669) Investigating the Circulating Proteome in Plasma of Vestibular Schwannoma Patients and Healthy Controls

Introduction: Identification of plasma biomarkers in patients with difficult-to-access skull base tumors, such as vestibular schwannoma (VS), could improve disease prognostication, optimize management strategies, and guide therapeutic development.

Methods: A high-throughput, DNA aptamer-based proteomic analysis of plasma from 6 patients with sporadic, non-irradiated VS prior to surgical resection and 6 age-and gender-matched healthy controls (HC) was performed to profile over 7,200 circulating proteins. Protein abundance was quantified using log2fold change. Enriched pathways were determined using metascape bioinformatic analysis. Candidate biomarker expression was validated in VS tissue and tumor secretion.

Results: Mean age was 61 years (range, 46 to 71 years) and average tumor size was 25.5 mm (range, 11 to 49 mm). There were 1,499 proteins differentially expressed between VS and HC (padj < 0.05). Of these, 152 (10%) were significantly upregulated in VS (log2fold change > 1.5) and 273 (18%) were downregulated (log2fold change < 0.66). The top 40 differentially expressed proteins, analyzed through principal component analysis, effectively distinguished VS from HC accounting for 84% of the variance (p < 0.05). Bioinformatic analysis revealed enrichment in processes associated with cancer, necrosis, protein catabolism and immune cell activation. Proteins including NF-κB inhibitor alpha, WNT16 and WNT10A, integral to NF-κB and Wnt signaling pathways, were all significantly upregulated (padj < 0.05). Notably, hepcidin (HAMP), a regulator of iron homeostasis and metabolism that may influence tumor growth, was highly upregulated in VS plasma (log2fold change = 3.8, padj < 0.05). HAMP was also highly expressed in VS tissue by immunofluorescence and in secretion from primary tumor culture compared to Schwann cells controls (308 vs 6 pg/mL, p < 0.05).

Conclusions: Our multiplexed, high-throughput proteomic analysis identified several novel biomarkers differentiating VS patients from healthy controls, which may help with disease diagnosis and improve treatment.