Glioblastoma multiforme (GBM) is an aggressive brain cancer closely linked to hypoxic conditions and altered lactate metabolism. This study aims to investigate the prognostic factors of GBM by developing models that integrating hypoxia and lactate metabolism, and to leverage bioinformatics techniques to gain deeper insights in this process. Publicly available GBM datasets identified hypoxia-lactate metabolism-related prognostic genes. Bioinformatics analyses included differential expression, functional enrichment, consensus clustering, immune profiling, and prognostic risk modeling. PPBP expression was validated via ELISA, Western blot, and RT-qPCR. Functional effects of PPBP knockdown/overexpression were assessed using CCK-8, EdU, wound healing, and Transwell assays under normoxia/hypoxia. Molecular mechanisms were explored with ChIP, dual-luciferase reporter, Co-IP, and pathway inhibition assays. Xenograft models evaluated in vivo tumor growth and survival. Virtual screening and SPR identified PPBP-targeting compounds, validated pharmacologically in vitro and in vivo. Integrated bioinformatics and experimental research identified 165 hypoxia-lactate metabolism-related genes in GBM. A seven-gene prognostic signature was established, with PPBP validated as a key hypoxia-induced oncogene. PPBP knockdown suppressed malignant phenotypes and glycolysis under hypoxia via CXCR2/PI3K/AKT signaling. HIF-1α transcriptionally activated PPBP through direct promoter binding. The natural compound Oenothein B targeted PPBP, inhibiting tumor growth and lactate metabolism in vitro and in vivo. This research develops a hypoxia-lactate metabolism-related gene signature to predict GBM prognosis, identifies PPBP as a key driver of hypoxic tumor progression via HIF-1α transcription and CXCR2/PI3K/AKT signaling, and shows that the natural compound Oenothein B targets PPBP to suppress glioma growth, offering a potential GBM therapy.
Cao et al. (Sat,) studied this question.