Integrative bioinformatics analysis unveils neuro-cancer crosstalk-related genes and establishes prognostic risk model in Glioblastoma - PubMed
4 hours ago
- #Bioinformatics
- #Glioblastoma
- #Prognostic Model
- Neuro-cancer crosstalk is important in Glioblastoma (GBM) development but its mechanisms are not fully understood.
- Single-cell RNA-seq identified 15 cell types and increased CD44+ astrocytes and oligodendrocyte progenitor cells in GBM.
- Key intercellular interactions identified include COL6A2-GP6 and L1CAM-ERBB3 between pericytes and excitatory neurons.
- Transcriptomic analysis found 6680 differentially expressed genes and 8636 hub genes from WGCNA.
- Seven key neuro-cancer crosstalk genes were identified, with NGFR and L1CAM selected for a prognostic risk model.
- The NGFR and L1CAM-based model showed good predictive performance for GBM prognosis in training and validation sets.
- High-risk GBM patients had elevated M0 macrophage infiltration and enrichment in axon guidance and RAS-ERK pathways.
- Betamethasone acetate was identified as a potential therapeutic agent through drug sensitivity analysis.
- Molecular docking indicated good binding of betamethasone acetate with L1CAM and NGFR proteins.
- Immunohistochemistry validated high NGFR and low L1CAM expression in GBM tumor samples.