PATH-42. UNCOVERING AN ASSOCIATION BETWEEN OLIGODENDROGLIOMA AND THE HUMAN PAPILLOMAVIRUS (HPV) THROUGH MOLECULAR SUBPOPULATION ANALYSIS USING NETRAAI

Abstract

Abstract Oligodendrogliomas (OGs) are a rare subset of primary brain tumors, accounting for approximately 5% of all brain tumors. While the etiology of OG has yet to be fully characterized, genomic heterogeneity is linked to clinical heterogeneity with variability in progression and survival. Currently, OGs are stratified into three molecular subtypes based on IDH mutation and 1p/19q co-deletion with additional molecular heterogeneity related to EGFR, PTEN, 10q deletion, and several other markers observed among 1p/19q co-deleted OGs. Using a public OG dataset, we assembled a set consisting of 156 primary OG tumors, 14 primary glioma samples, and 9 normal samples profiled using mRNA expression arrays. Using NetraAI, a novel machine learning platform, we identified three OG patient subpopulations based on survival and differentially expressed genes. Examining low- versus high-grade OG, we identified two subpopulations: (1) 26 low-grade and 21 high-grade OGs characterized by higher RPS6KV1 expression, and (2) 6 low-grade and 61 high-grade OGs characterized by higher LFNG expression. A third subpopulation emerged examining 1p/19p co-deletion, consisting of 60 no co-deletion and 3 co-deletion OGs characterized by higher HDAC1 expression. These driving genes have a common link to human papillomavirus (HPV) infection based on functional genomic analysis. HDAC1 is a histone deacetylase involved in gene expression regulation, LFNG is implicated in the Notch signaling pathway, and RPS6KB1 is a kinase regulating protein synthesis and cell growth. We hypothesize that concomitant HPV infection may negatively impact OG prognosis, warranting further investigation into the precise molecular interactions linking HPV infection to clinical outcomes. Furthermore, exploring the link between HPV infection and vaccination to OG outcomes on a population basis may provide valuable insights. The identification of these subpopulations, not previously described by other groups, demonstrates the utility of the NetraAI approach in uncovering subpopulations with potential implications in developing targeted therapies for OG.