SDPS-28 THE STUDY OF AN ANOIKIS-RELATED SIGNATURE TO PREDICT GLIOMA PROGNOSIS AND IMMUNE INFILTRATION

BACKGROUND: Gliomas are the most common highly aggressive primary malignant brain tumors in adults with different biological behavior and clinically heterogeneous features. Method: We extracted the anoikis-related genes (ARGs) from GeneCards and obtained differentially expressed genes in normal and glioma tissues from the GSE4290 dataset by differential analysis to obtain intersect differentially expressed ARG in gliomas. KEGG and GO analysis were used to evaluate the potential pathways and molecular processes of these genes. Based on The Cancer Genome Atlas (TCGA) training cohort, we performed the Least Absolute Shrinkage and Selection Operator (LASSO) regression and Cox regression to construct an ARG prognostic model and validated them in the TCGA testing cohort and the Chinese Glioma Genome Atlas (CGGA) validation cohort. Subsequently, we further explored the differences in clinical characteristics, tumor mutation burden(TMB), and the immune microenvironment in the high- and low-risk groups. Univariate and multifactorial regression analyses and nomogram construction were also performed. Moreover, we assessed the expression levels and clinical prognostic value of prognostic key genes. RESULTS: The regulatory model based on quantitative ARG prognostic models showed that patients in the high-risk group were associated with poorer survival prognosis, poorer clinical characteristics, and higher TMB levels. Moreover, the high-risk group had high levels of immune infiltration and upregulated immune checkpoint gene expression. The ARG prognostic model and the Nomogram showed good predictive performance. Expression and survival analysis of five prognostic ARG signatures (ETV4, HMOX1, MYC, NFE2L2, and UBE2C) showed that these genes except MYC were cancer-promoting genes. CONCLUSION: Our constructed ARG prognostic risk model provides a potential therapeutic target and theoretical basis for predicting the prognosis of glioma patients and guiding individualized immunotherapy.