Multi-omic landscape of human gliomas from diagnosis to treatment and recurrence
Hadeesha PiyadasaiD, Benjamin Oberlton, Mikaela K. RibiiD, Ke Xuan Leow, Jolene S. RanekiD, Inna AverbukhiD, Meelad AmouzgariD, Candace C. LiuiD, Davide G. FranchinaiD, Noah F. GreenwaldiD, Erin McCaffreyiD, Rashmi KumariD, Selena FerrianiD, Albert G. TsaiiD, Ferda Filiz, Christine Camacho FullawayiD, Marc MB BosseiD, Sricharan Reddy VarraiD, Alex KongiD, Cameron Sowers, Melanie Hayden GephartiD, Pablo Nunez PereziD, Enjun YangiD, Mike Travers, Michael J. Schachter, , Michael AngeloiD
Abstract
Gliomas are among the most lethal cancers, with limited treatment options. To uncover hallmarks of therapeutic escape and tumor microenvironment (TME) evolution, we applied spatial proteomics, transcriptomics, and glycomics to 670 lesions from 310 adult and pediatric patients. Single-cell analysis shows high B7H3+ tumor cell prevalence in glioblastoma (GBM) and pleomorphic xanthoastrocytoma (PXA), while most gliomas, including pediatric cases, express targetable tumor antigens in less than 50% of tumor cells, potentially explaining trial failures. Longitudinal samples of isocitrate dehydrogenase (IDH)-mutant gliomas reveal recurrence driven by tumor-immune spatial reorganization, shifting from T-cell and vasculature-associated myeloid cell-enriched niches to microglia and CD206+ macrophage-dominated tumors. Multi-omic integration identified N-glycosylation as the best classifier of grade, while the immune transcriptome best predicted GBM survival. Provided as a community resource, this study opens new avenues for glioma targeting, classification, outcome prediction, and a baseline of TME composition across all stages.
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