Abstract
BACKGROUND: Glioblastoma multiforme (GBM) is an exceedingly aggressive tumor subtype, comprising 60% of high-grade gliomas and 54% of all gliomas. GBM has poor survival rates despite current treatments, with less than 5% of patients surviving beyond five years. Long Non-coding RNAs (LncRNAs) are essential in gene regulation and tumor advancement. The dysregulation of lncRNAs in GBM suggests their potential as prognostic biomarkers and therapeutic targets, providing insights for personalized treatment strategies. This study aims to evaluate the prognostic significance of lncRNA expression in GBM to enhance the understanding of the disease and inform therapeutic strategies. METHOD: This study complied with PRISMA principles, with the protocol registered in PROSPERO. A comprehensive search across PubMed, Scopus, Web of Science, and Embase (2000-2023) identified cohort studies on lncRNA dysregulation and GBM prognosis. Two independent researchers screened and extracted relevant data, resolving discrepancies through a third reviewer. The QUIPS tool assessed bias risk, and statistical analysis employed a random-effects model. Sensitivity analysis, assessment of publication bias (Begg's test, funnel plots), and subgroup analyses were performed to investigate heterogeneity. The reliability of the evidence was evaluated using the modified GRADE technique. RESULT: This meta-analysis assessed five lncRNAs with prognostic relevance in GBM patients, revealing that their dysregulated expression correlated with reduced overall survival (HR: 1.37). Dysregulation of MALAT1 had the strongest association with reduced OS (HR: 2.50). Other lncRNAs showed significant associations as follows: HOTAIR (HR: 1.26), NEAT1 (HR: 1.28), H19 (HR: 1.42), and HOTAIRM1 (HR: 1.29). Subgroup analysis indicated stronger prognostic value in low-bias studies (HR: 1.51) and hospital-derived data (HR: 2.51). CONCLUSION: Our study examined the expression of five lncRNAs and identified their potential as prognostic markers for GBM patients. However, evaluating the prognostic value of additional lncRNAs and integrating these into prognostic models alongside other significant GBM biomarkers is recommended for future research.