Abstract 788: Leveraging multi omics approach to examine the potential role of causative viruses in glioblastoma

Abstract Glioblastoma (GB), a grade IV brain cancer, has the lowest survival rate. Despite aggressive and targeted therapies, patients remain to have the worst prognosis. More than 16% of cancer incidence worldwide has been attributed to infectious agents, raising uncertainties about the role of infections in the development of brain cancer. While numerous studies have suggested potential viral involvement in GB pathogenesis, a common limitation is the reliance on a singular technology, such as DNA/RNA sequencing or immunohistochemistry, within each study. This approach may restrict the comprehensive exploration of viral contributions, as different technologies offer distinct insights into the complex mechanisms underlying GB development. Utilizing a combination of techniques could provide a more holistic understanding, enhancing the robustness of findings and potentially uncovering nuanced aspects of viral influence that a single technology might overlook. To clarify the role of viruses in GB pathology, our study employs a comprehensive approach integrating three distinct research methods. We screened 178 publicly accessible raw mass spectrometry (MS) data of GB tumors from three independent publications (PMID: 31331834, 31154438, 36720864) by employing our internally developed data identification pipeline. The pipeline transforms raw MS data for downstream analysis, conducts database searches against the latest viral protein databases and undergoes peptide validation for enhanced robustness. Subsequent analysis filters duplicate hits and consolidates nested peptides. The final protein list includes only those identified with two or more peptides of over eight amino acids. The pipeline concludes by inferring and listing the corresponding viruses, ensuring a comprehensive and refined approach to the identification and analysis of viral proteins in the context of MS data. To enhance this dataset, we incorporated whole-genome metagenomics and MS-based proteomics, examining a preliminary cohort of15 GB tumor tissues. This approach explored a wide range of viral encoded proteins. Our comprehensive analysis, integrating bioinformatics, genomics, and proteomics, identified multiple herpesvirus species across our cohorts. This potential identification of viruses within GB has the capacity to redefine the stratification of tumor types in GB patients, signaling a significant development in our understanding of the disease. Citation Format: Bavani Gunasegaran, Aziz Abdullah A Alnakli, Gilles J. Guillemin4, Seong Beom Ahn, Benjamin Heng. Leveraging multi omics approach to examine the potential role of causative viruses in glioblastoma abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 788.