AUTHOR=Li Haonan , Wang Guohui , Wang Wenyan , Pan Jie , Zhou Huandi , Han Xuetao , Su Linlin , Ma Zhenghui , Hou Liubing , Xue Xiaoying 

TITLE=A Focal Adhesion-Related Gene Signature Predicts Prognosis in Glioma and Correlates With Radiation Response and Immune Microenvironment

JOURNAL=Frontiers in Oncology

VOLUME=Volume 11 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.698278

DOI=10.3389/fonc.2021.698278

ISSN=2234-943X

ABSTRACT=Background: Glioma is the most frequent brain malignancy and presents very poor prognosis and high recurrence rates. Focal adhesion complexes play a pivotal role in cell migration and act as hubs of several signaling pathways. 
Methods: We used bioinformatic databases (CGGA, TCGA and GEO) and identified a focal adhesion-related differential gene expression (FADG) signature correlated with patient clinical features was constructed using uniCox and LASSO regression analysis. Patients were given a risk score calculated using the regression coefficient value and expression of each gene. We tested the signature by survival analysis, receiver operating characteristic curve (ROC), principal component analysis (PCA) and stratified the analysis by clinical characteristics. CIBERSORT and ssGSEA were used to explore the tumor microenvironment (TME). A correlation analysis of risk scores and involvement of the immune checkpoint gene levels was performed. We then conducted GSEA to identify signaling pathways related to the FADG signature. 
Results: In total, 1726 (528 patients diagnosed with WHO II, 591 WHO III and 603 WHO IV) patient samples and 23 non-tumor samples were included in our study. We identified 29 prognosis related genes in the LASSO analysis and constructed an eight FADG signature. The results from the survival analysis, stratified analysis, ROC curve, and univariate and multivariate regression analyses revealed that the prognosis of the high-risk group was significantly poorer than that of the low-risk group. Correlation analysis between risk score and genes that resistant to radiation showed that it was positively related with BRCA1, BRCA2, RAD51, TGFB1 and TP53. Besides, we found that the signature could predict the prognosis of patients received radiation therapy. SsGSEA indicated that the high-risk score was positively correlated with the ESTIMATE, immune, stromal scores but negatively correlated with tumor purity. Notably, patients in the high-risk group had high infiltration of Tregs. The correlation analysis revealed that the risk score was positively correlated with genes B7-H3, CTLA4, LAG3, PD-L1, and TIM3 but inversely correlated with PD-1 expression. 
Conclusion: The FADG score we constructed may provide a sensitive prognostic model for patients with glioma and contribute to improve immunotherapy management guidelines.