SYT16 is a prognostic biomarker and correlated with immune infiltrates in glioma: A study based on TCGA data
Autor: | Jinbiao Xue, Lin Zhong, Hualin Wei, Chenlin Zhang, Ziheng Wang, Tao Jiang, Jianfeng Chen, Wei Wang, Shiqi Ren |
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Rok vydání: | 2019 |
Předmět: |
0301 basic medicine
Support Vector Machine Immunology Biology 03 medical and health sciences Synaptotagmins 0302 clinical medicine Lymphocytes Tumor-Infiltrating Glioma Databases Genetic medicine Biomarkers Tumor Leukocytes Tumor Microenvironment Immunology and Allergy Data Mining Humans KEGG Mononuclear Phagocyte System Pharmacology Gated channel activity Tumor microenvironment Brain Neoplasms Gene Expression Profiling Cancer Computational Biology medicine.disease Prognosis Neoplasm Proteins Gene expression profiling Ligand-gated channel activity Gene Expression Regulation Neoplastic 030104 developmental biology 030220 oncology & carcinogenesis Cancer research Biomarker (medicine) Software |
Zdroj: | International immunopharmacology. 84 |
ISSN: | 1878-1705 |
Popis: | Background Glioma is the most lethal primary brain tumor. Lower-grade glioma (LGG) is the crucial pathological type of Glioma. Immune-infiltration of the tumor microenvironment positively associated with overall survival in LGG. SYT16 is a gene has not been reported in cancer. We assess the role of SYT16 in LGG, via the publicly available TCGA database. Methods Gene Expression Profiling Interactive Analysis (GEPIA) was used to analyze the expression of SYT16 in LGG. We evaluated the influence of SYT16 on survival of LGG patients by survival module. Then, datasets of LGG were downloaded from TCGA. The correlations between the clinical information and SYT16 expression were analyzed using logistic regression. Univariable survival and Multivariate Cox analysis was used to compare several clinical characteristics with survival. we also explore the correlation between SYT16 and cancer immune infiltrates using CIBERSORT and correlation module of GEPIA. Gene set enrichment analysis (GSEA) was performed using the TCGA dataset. In addition, we use TIMER to explore the collection of SYT16 Expression and Immune Infiltration Level in LGG and to explore cumulative survival in LGG. Results The univariate analysis using logistic regression, indicated that increased SYT16 expression significantly correlated with the tumor grade. Moreover, multivariate analysis revealed that the up-regulated SYT16 expression is an independent prognostic factor for good prognosis. Specifically, SYT16 expression level has significant negative correlations with infiltrating levels of B cell, CD4+ T cells, Macrophages, Neutrophils and DCs in LGG. In addition, GSEA identified ingle organism behavior, gated channel activity, cognition, transporter complex and ligand gated channel activity in Gene Ontology (GO) were differentially enriched in the high SYT16 expression phenotype pathway. Neuroactive ligand receptor interaction, calcium signaling pathway, long term potentiation, type II diabetes mellitus and long term depression were identified as differentially enriched pathway in Kyoto Encyclopedia of Genes and Genomes (KEGG). Conclusion SYT16 is a Prognostic Biomarker and Correlated with Immune Infiltrates in LGG. |
Databáze: | OpenAIRE |
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