Abstract LB045: Identification of plasma-derived, EV-based biomarkers for glioblastoma

Abstract Background: Glioblastoma (GBM) is the most malignant and aggressive primary brain cancer in adults, with an incidence of 3.2 per 100,000 people. Currently, diagnosis is only performed via histopathological investigation of a tissue sample from a GBM lesion, complemented with molecular diagnostics for identification of select biomarkers. MRI is the standard of care for follow-up and monitoring of treatment response. Therefore, development of a “liquid biopsy” to obtain disease-relevant information from body fluids is highly desirable.Methods: We present the results from a clinical study in which extracellular vesicle (EV)-derived mRNAs were profiled from the plasma of GBM patients and control individuals for a total of 32 individual RNAseq libraries. Initial biomarker discovery was performed on plasma from 16 patients (8 GBM patients at the time of initial diagnosis and 8 age and sex matched controls). Hybrid capture and RNA-seq were performed via our proprietary pipeline on EV-associated mRNA isolated from 1-2mL plasma. Sequencing data was analyzed for differential gene expression. Validation was done with plasma samples from a new cohort of 8 patients and 8 control individuals.Results: We observed 98 mRNAs as differentially detected between GBM and control samples, with 83 mRNAs enriched in GBM samples and 15 mRNAs decreased (p < 0.05). Correlation based on differentially detected mRNAs separated GBM and control samples into two unique populations. We were able to use the differentially expressed gene signature from the first cohort to separate GBM patients and control individuals in the second cohort. We are currently following up these results with a larger patient population. These data, while preliminary, provide a potential basis for the further development of a GBM gene panel test.Conclusions: We have identified a novel gene signature for GBM in plasma-derived EVs, which differs from previously identified biomarkers isolated from tissue. Further work will refine this signature to enable detection, characterization, and patient monitoring for GBM with less invasive and intensive methods. Citation Format: Yevgenia L. Khodor, Sudipto K. Chakrabortty, Christian Fischer, Martina Rauscher, Leonora Balaj, Bob S. Carter, Seth Yu, Johan Skog. Identification of plasma-derived, EV-based biomarkers for glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB045.