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Currently, the spatiotemporal evolution of ecDNA remains poorly understood. In this study, we integrate computational modeling with samples from 94 treatment-naive human glioblastomas (GBM) to investigate the spatiotemporal evolution of ecDNA. We observe oncogene-specific patterns of ecDNA spatial heterogeneity, emerging from random ecDNA segregation and differing fitness advantages. Unlike PDGFRA-ecDNAs, EGFR-ecDNAs often accumulate prior to clonal expansions, conferring strong fitness advantages and reaching high abundances. In corroboration, we observe pretumor ecDNA accumulation in vivo in genetically engineered mouse neural stem cells. Variant and wild-type EGFR-ecDNAs often coexist in GBM. Those variant EGFR-ecDNAs, most commonly EGFRvIII-ecDNA, always derive from preexisting wild-type EGFR-ecDNAs, occur early, and reach high abundance. Our results suggest that the ecDNA oncogenic makeup determines unique evolutionary trajectories. New concepts such as ecDNA clonality and heteroplasmy require a refined evolutionary interpretation of genomic data in a large subset of GBMs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Significance:<\/jats:title>\n                    <jats:p>We study spatial patterns of ecDNA-amplified oncogenes and their evolutionary properties in human GBM, revealing an ecDNA landscape and ecDNA oncogene\u2013specific evolutionary histories. ecDNA accumulation can precede clonal expansion, facilitating the emergence of EGFR oncogenic variants, reframing our interpretation of genomic data in a large subset of GBMs.<\/jats:p>\n                    <jats:p>See related commentary by Korsah et al., p. 1979<\/jats:p>\n                  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