RNA Expression Signatures in Glioblastoma: A Systematic Review of Tumour Biology and Therapeutic Targets

Glioblastoma (GBM) remains the most aggressive primary brain tumour in adults, marked by pronounced cellular heterogeneity, diffuse infiltration, and resistance to conventional treatment. In recent years, transcriptomic profiling has provided valuable insights into the molecular mechanisms that govern the progression of glioblastoma. This systematic review aims to synthesise the current literature on dysregulated gene expression in GBM, focusing on gene signatures associated with stemness, immune modulation, extracellular matrix remodelling, metabolic adaptation, and therapeutic resistance.

We conducted a systematic search of PubMed, The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and the GlioVis portal for studies published between January 2005 and April 2025, limited to English-language reports. Studies were eligible if they included adult glioblastoma tissue or patient-derived datasets and reported gene-level expression or clinical associations. Reviews, commentaries, and studies on non-GBM gliomas were excluded. Screening followed the PRISMA 2020 checklist, with 410 records initially identified, 90 duplicates removed, and 125 studies retained after full-text review. Data were synthesised descriptively, and findings were validated against TCGA/CGGA expression datasets to ensure consistency across cohorts.

We categorised recurrently dysregulated genes by their biological function, including transcription factors (SOX2, ZEB2), growth factor receptors (EGFR, PDGFRA), immune-related markers (PD-L1, TAP1, B2M), extracellular matrix regulators (MMP2, LAMC1, HAS2), and metabolic genes (SLC7A11, PRMT5, NRF2). For each group, we examine the functional consequences of transcriptional alterations and their role in driving key glioblastoma phenotypes, including angiogenesis, immunosuppression, invasiveness, and recurrence.

We further discuss the prognostic implications of these gene signatures and evaluate their potential utility in precision medicine, including current clinical trials that target molecular pathways identified through transcriptomic data. This review highlights the power of gene expression profiling to stratify glioblastoma subtypes and improve personalised therapeutic strategies.