Multiomic profiling of glioblastoma metabolic lesions reveals complex intratumoral genomic evolution and dipeptidase-1-driven vascular proliferation
Glioblastoma undergoes a complex and dynamic evolution involving genetic and epigenetic changes. Understanding the mechanisms behind this evolution is vital for effective therapies. While treatment resistance is associated with glioblastoma's intratumoral heterogeneity, it remains uncertain if hypometabolic and hypermetabolic lesions observed through PET imaging are influenced by spatial intratumoral genomic evolution. In this study, we precisely isolated autologous hypometabolic and hypermetabolic lesions from glioblastoma using advanced neurosurgical and brain imaging technologies, followed by comprehensive whole-genome/exome and transcriptome analysis. Our findings reveal that hypermetabolic lesions evolve from hypometabolic lesions, harbor shrewd focal amplifications and deletions, and exhibit a higher frequency of critical genomic alterations linked to increased aggressiveness. We also found gene signatures in hypermetabolic lesions, including upregulated APOBEC3, hypoxic genes, and downregulated putative tumor suppressors. This study highlights a spatial genomic evolution with diagnostic implications and unveils obstacles and possibilities that should be considered in the development of novel therapeutic strategies. Overall design: We embark on making a comprehensive analysis of genomic alterations in glioblastoma of kryo, zesto, and akri samples by performing exome and genome sequencing of tissue and blood samples to identify critical copy number variations, single nucleotide variants, gene fusions, somatic variants as well as RNA sequencing for functional analysis. By conducting these multi-omics analyses on multisectoral paired biopsies from the same patients with glioblastoma, allowing us to investigate intratumoral alterations, we identified a set of molecular alterations that may influence the regulation of glioblastoma biology and contribute to its heterogeneity and therapeutic resistance. This is the first study to perform a thorough genomic analysis on predetermined multi-regional metabolic tumor lesions from patients with glioblastoma, with an ideal experimental control setup.