Abstract / Summary
Background and Purpose This study aims to explore the characteristics and potential functions of protein palmitoylation-related genes in glioma multi-omics data. Methods Single-cell transcriptome data from 18 glioma patients (GEO) were scored for protein palmitoylation via GSVA, with pathway enrichment compared by score groups. Multi-omics data (702 patients, UCSC-XENA) enabled tumor subtyping for clinical and immune infiltration analyses. Machine learning identified ZDHHC22 as a prognostic marker; lentiviral knockdown and functional assays confirmed its role, with TP63 validated as its upstream regulator of glioma malignant progression. Results Single-cell sequencing analysis revealed the identification of 11 cell subsets, thereby highlighting the heterogeneity of glioma cells with varying protein palmitoylation levels. Multiple subtyping of glioma indicated that CS1 exhibited poorer survival and higher immune infiltration compared to CS2. Machine learning identified ZDHHC22 as a prognostic marker for gliomas. Upregulation of ZDHHC22 significantly suppressed glioma cell proliferation, migration and invasion. The subcutaneous xenograft tumor experiment confirmed that overexpression of ZDHHC22 markedly suppresses glioma tumor growth, but remains to be validated in orthotopic intracranial glioma models. TP63 directly binds to the promoter region of the ZDHHC22 gene and significantly represses its transcriptional activity. Furthermore, knockdown of ZDHHC22 effectively reverses the inhibitory effect of TP63 knockdown on the malignant phenotype of glioma cells. Conclusion PRGs are pivotal modulators of the glioma immune microenvironment, which can be reliably applied for glioma prognostic prediction, immune infiltration evaluation, and immunotherapy efficacy assessment. ZDHHC22 acts as a critical tumor suppressor in glioma progression.