BIOM-80. SEX-ASSOCIATED BIOMARKER SIGNATURES IN MALIGNANT GLIOMA: INSIGHTS FROM A PROTEOMICS STUDY

Abstract Malignant gliomas, including glioblastomas (GBM), are aggressive brain tumors with limited tools for diagnosis, prognosis, treatment, and monitoring. Despite advances in glioma research, the role of sex-associated molecular differences in incidence, progression and treatment response remains largely underexplored. Therefore, identifying sex-associated biomarkers may be beneficial for better understanding the molecular mechanisms of disease to develop more precise and effective diagnostic and therapeutic strategies for gliomas. Here we employed an innovative liquid biopsy approach utilizing extracellular vesicles (EVs) to identify and compare novel sex-associated plasma biomarkers for malignant glioma detection. Utilizing FYR’s proprietary SPARCs technology, tumor-associated and neuro-associated EV subpopulations were isolated from plasma. Proteomics profiles generated from the isolated tumor-associated EVs revealed sex-associated signatures in both male (n=23) and female (n=29) malignant glioma patients. In the female cohort, an L1-penalized logistic regression model employed on proteomics data achieved high classification performance, with an area under the curve (AUC) value of 1. In the female cohort, the models utilized proteins predominantly associated with immune regulation and metabolic processes. In the male cohort, an L1-penalized logistic regression model achieved an AUC value of 0.975, and the model utilized proteins associated with inflammatory signaling and vesicle trafficking. Only two biomarkers overlapped between the sex-specific models, underscoring distinct sex-based molecular profiles in glioma patients. Our study reveals robust sex-associated differences in plasma EV subpopulation biomarkers among malignant glioma patients. These findings reveal valuable insights into sex-associated molecular processes in malignant gliomas and support the integration of sex as a biological variable in biomarker discovery and detection for personalized diagnostic strategies.