Abstract Treatment options for adult patients with glioma has remained largely unchanged over the past three decades. Targeted inhibitors and immunotherapies have improved outcomes for many cancer types but their relevance in glioma is unclear. The inevitability of glioma disease recurrence demands an understanding of mechanisms driving therapy resistance. The Glioma Longitudinal Analysis (GLASS) Consortium was initiated to establish a definitive portrait of the recurrence process and to discover vulnerabilities that render the tumor sensitive to therapeutic intervention. GLASS is a community-driven effort that seeks to overcome the logistical challenges in constructing adequately powered longitudinal genomic glioma datasets by pooling data from patients treated at institutions worldwide. Currently, the GLASS Data Resource comprises DNA sequencing data (exome and/or whole-genome) from 288 patients of whom high-quality data in at least two time points are present from 222 patients (n = 134 IDHwt, n = 63 IDHmutant-noncodel, n = 25 IDHmutant-codel). We inferred longitudinal mutation, copy number, clonal frequency, and neoantigen profiles and demonstrated that driver genes found at initial disease persisted into recurrence. Treatment with alkylating-agents resulted in a hypermutator phenotype at different rates across glioma subtypes, most frequently among IDHmutant-noncodels, and hypermutation was not associated with differences in overall survival. Acquired aneuploidy was frequently detected in recurrent IDHmutant-noncodel gliomas and further converged with acquired cell cycle pathway alterations and poor outcomes. We showed that the clonal architecture of each tumor remains largely intact over time and that genetic drift was associated with increased survival. Finally, we found that neoantigens were exposed to stable selective pressures throughout a tumor’s progression. Our results collectively suggest that the strongest selective pressures occur early during glioma development and that current therapies shape this evolution in a largely stochastic manner. The GLASS Data Resource provides a genomic reference to study the patterns of glioma evolution.