Prognosis Analysis and Validation of m6A Signature and Tumor Immune Microenvironment in Glioma
| Autor: | Houshi Xu, Shao Jian Lin, Tong Meng, Mingjie Wang, Anke Zhang, Meiqing Lou, Yunjia Ni, Yuanzhi Xu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Cancer Research RNA methylation Human Protein Atlas Biology Genome lcsh:RC254-282 03 medical and health sciences 0302 clinical medicine Immune system Glioma glioma medicine prognostic model Gene PDPN TIMP1 Original Research immune infiltration WGCNA m6A medicine.disease lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens 030104 developmental biology Oncology 030220 oncology & carcinogenesis Cancer research |
| Zdroj: | Frontiers in Oncology Frontiers in Oncology, Vol 10 (2020) |
| ISSN: | 2234-943X |
| Popis: | Glioma is one of the most typical intracranial tumors, comprising about 80% of all brain malignancies. Several key molecular signatures have emerged as prognostic biomarkers, which indicate room for improvement in the current approach to glioma classification. In order to construct a more veracious prediction model and identify the potential prognosis-biomarker, we explore the differential expressed m6A RNA methylation regulators in 665 gliomas from TCGA-GBM and TCGA-LGG. Consensus clustering was applied to the m6A RNA methylation regulators, and two glioma subgroups were identified with a poorer prognosis and a higher grade of WHO classification in cluster 1. The further chi-squared test indicated that the immune infiltration was significantly enriched in cluster 1, indicating a close relation between m6A regulators and immune infiltration. In order to explore the potential biomarkers, the weighted gene co-expression network analysis (WGCNA), along with Least absolute shrinkage and selection operator (LASSO), between high/low immune infiltration and m6A cluster 1/2 groups were utilized for the hub genes, and four genes (TAGLN2, PDPN, TIMP1, EMP3) were identified as prognostic biomarkers. Besides, a prognostic model was constructed based on the four genes with a good prediction and applicability for the overall survival (OS) of glioma patients (the area under the curve of ROC achieved 0.80 (0.76-0.83) and 0.72 (0.68-0.76) in TCGA and Chinese Glioma Genome Atlas (CGGA), respectively). Moreover, we also found PDPN and TIMP1 were highly expressed in high-grade glioma from The Human Protein Atlas database and both of them were correlated with m6A and immune cell marker in glioma tissue samples. In conclusion, we construct a novel prognostic model which provides new insights into glioma prognosis. The PDPN and TIMP1 may serve as potential biomarkers for prognosis of glioma. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|