Germinoma tissue sample

Negative tumor markers were initially effective in distinguishing germinomas from non-germ cell tumors (NGGCT) but not non-intracranial germ cell tumors (non-iGCT). Accurate and non-invasive diagnostic markers are crucial to reduce surgery risks. Metabolites that respond to real-time pathophysiological changes present a promising avenue for advancing germinoma diagnosis. Using metabolomics and a multi-step machine learning approach, potential diagnostic metabolic biomarkers in the cerebrospinal fluid of 65 patients (26 germinoma, 31 non-iGCT, 8 NGGCT) were identified. A subset of these samples (13 plus 8/9 random samples) was used as test data to evaluate classification models. Additionally, a comprehensive multi-omics strategy was applied to investigate germinoma pathogenesis using various tissue samples, including transcriptome, metabolome, and DNA methylation data, focusing on dysregulated metabolic pathways and immune cell infiltration. The multi-omics approach highlighted activated nicotinamide metabolism in germinomas, accompanied by a distinct immune cell profile characterized by fewer immune-suppressing cells and increased anti-tumor immune cells compared to NGGCT. The study underscores the unique tumor pathogenesis of germinomas compared to NGGCT, offering novel insights into therapeutic approaches for intracranial germ cell tumors.