Glioblastoma multiforme (GBM) is a common malignant tumor type of the nervous system. The purpose of the present study was to establish a regulatory network of immune-associated genes affecting the prognosis of patients with GBM. The GSE4290, GSE50161 and GSE2223 datasets from the Gene Expression Omnibus database were screened to identify common differentially expressed genes (co-DEGs). A functional enrichment analysis indicated that the co-DEGs were mainly enriched in cell communication, regulation of enzyme activity, immune response, nervous system, cytokine signaling in immune system and the AKT signaling pathway. The co-DEGs accumulated in immune response were then further investigated. For this, the intersection of those co-DEGs and currently known immune-regulatory genes was obtained and a differential expression analysis of these overlapping immune-associated genes was performed. A risk model was established using immune-regulatory genes that affect the prognosis of patients with GBM. The risk score was significantly associated with the prognosis of patients with GBM and had a significant independent predictive value. The risk model had high accuracy in predicting the prognosis of patients with GBM [area under the receiver operating characteristic curve (AUC)=0.764], which was higher than that of a previously reported model of prognosis-associated biomarkers (AUC=0.667). Furthermore, an interaction network was constructed by using immune-regulatory genes and transcription factors affecting the prognosis of patients with GBM and the University of California Santa Cruz database was used to perform a preliminary analysis of the transcription factors and immune genes of interest. The interaction network of immune-regulatory genes constructed in the present study enhances the current understanding of mechanisms associated with poor prognosis of patients with GBM. The risk score model established in the present study may be used to evaluate the prognosis of patients with GBM.
Background Glioblastoma (GBM) is one of the most malignant tumors that can afflict the central nervous system. Previous studies have observed that there are individual differences in the treatment response of immune checkpoint inhibitors in glioblastoma. This study’s aim is to ascertain the factors that may affect the efficacy of immunosuppressant therapy. Methods The clinical data of this study were obtained from a public database. Then, the data was analyzed and processed by R software and corresponding R package. To verify the results of the analysis, information was gathered from 89 GBM patients in our hospital and thereafter the corresponding paraffin sections were stained and quantitatively analyzed by immunohistochemistry. Results From the analysis, it was observed that both CD276 and HAVCR2 were significantly overexpressed in GBM and could be associated with patient prognosis. The analysis of single cell RNA sequencing data and GBM data analysis found an immune subtype with poor prognosis. Further analysis found that the high expression of CD276, HAVCR2 and CD163 was closely related to epithelial-mesenchymal transition (EMT) and could affect the patient prognosis of PD-L1 high expression. GSVA enrichment analysis showed that CD276, HAVCR2 and CD163 might induce EMT by JAK-STAT3 signaling pathway, and RUNX1 and IKZF1 might be transcription factors that regulate CD276/HAVCR2 high expression. Conclusions We found an immune subtype with poor prognosis of GBM, the high expression of CD276, HAVCR2 and CD163 with EMT are closely related and may be one of the factors affecting the efficacy of Anti-PD-L1.
Background Glioblastoma (GBM) is one of the most malignant tumors that can afflict the central nervous system. Previous studies have observed that there are individual differences in the treatment response of immune checkpoint inhibitors in glioblastoma. This study’s aim is to ascertain the factors that may affect the efficacy of immunosuppressant therapy. Methods The clinical data of this study were obtained from a public database. Then, the data was analyzed and processed by R software and corresponding R package. To verify the results of the analysis, information was gathered from 89 GBM patients in our hospital and thereafter the corresponding paraffin sections were stained and quantitatively analyzed by immunohistochemistry. Results From the analysis, it was observed that both CD276 and HAVCR2 were significantly overexpressed in GBM and could be associated with patient prognosis. The analysis of single cell RNA sequencing data and GBM data analysis found an immune subtype with poor prognosis. Further analysis found that the high expression of CD276, HAVCR2 and CD163 was closely related to epithelial-mesenchymal transition (EMT) and could affect the patient prognosis of PD-L1 high expression. GSVA enrichment analysis showed that CD276, HAVCR2 and CD163 might induce EMT by JAK-STAT3 signaling pathway, and RUNX1 and IKZF1 might be transcription factors that regulate CD276/HAVCR2 high expression. Conclusions We found an immune subtype with poor prognosis of GBM, the high expression of CD276, HAVCR2 and CD163 with EMT are closely related and may be one of the factors affecting the efficacy of Anti-PD-L1.
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