Gliomas account for approximately 80% of all malignant intracranial tumors， with strong invasiveness and poor prognosis， posing significant challenges to clinical diagnosis and treatment. Traditional imaging and pathological grading often prove inadequate in addressing the significant intra- and intertumoral heterogeneity. Multi-omics（ such as genomics， transcriptomics， proteomics， metabolomics） provide an integrated perspective for subtyping， risk stratification， and efficacy/recurrence monitoring， thereby accelerating the translation of novel therapies and precision medicine strategies into clinical applications for gliomas. However， challenges such as batch effects in sample preprocessing， inconsistent cross-platform standards， insufficient data integration and interpretability， and the integration of complex results into clinical pathways continue to hinder its implementation. This paper summarizes the key value and limitations of multi-omics testing in the practical context of precision diagnosis and treatment for gliomas， emphasizes standardized sample delivery， quality control， and reporting processes， providing guidance and recommendations for the clinical application of multi-omics testing.