Angiogenesis-Related Gene Signature-Derived Risk Score for Glioblastoma: Prospects for Predicting Prognosis and Immune Heterogeneity in Glioblastoma

Wang, Gang; Hu, Jinqu; Liu, Jiyuan; Zhang, Xiaomei

doi:10.3389/fcell.2022.778286

Cited by 9 publications

(13 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Numerous studies indicate that aberrant angiogenesis is involved in the processes of tumorigenesis, development, invasion, and poor prognosis in glioma ( Tan et al, 2018 ). To date, there are still few studies on ARG in glioma ( Biterge-Sut, 2020 ; Wang et al, 2022 ). Two major aspects of glioma biological processes that contribute to treatment resistance are abnormal formation of new blood vessels via angiogenesis and invasion of glioma cells along white-matter tracts ( Carmeliet, 2005 ; Onishi et al, 2011 ).…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma

Wang

et al. 2022

Front. Genet.

View full text Add to dashboard Cite

Background: Glioma is the most prevalent malignant intracranial tumor. Many studies have shown that angiogenesis plays a crucial role in glioma tumorigenesis, metastasis, and prognosis. In this study, we conducted a comprehensive analysis of angiogenesis-related genes (ARGs) in glioma.Methods: RNA-sequencing data of glioma patients were obtained from TCGA and CGGA databases. Via consensus clustering analysis, ARGs in the sequencing data were distinctly classified into two subgroups. We performed univariate Cox regression analysis to determine prognostic differentially expressed ARGs and least absolute shrinkage and selection operator Cox regression to construct a 14-ARG risk signature. The CIBERSORT algorithm was used to explore immune cell infiltration, and the ESTIMATE algorithm was applied to calculate immune and stromal scores.Results: We found that the 14-ARG signature reflected the infiltration characteristics of different immune cells in the tumor immune microenvironment. Additionally, total tumor mutational burden increased significantly in the high-risk group. We combined the 14-ARG signature with patient clinicopathological data to construct a nomogram for predicting 1-, 3-, and 5-year overall survival with good accuracy. The predictive value of the prognostic model was verified in the CGGA cohort. SPP1 was a potential biomarker of glioma risk and was involved in the proliferation, invasion, and angiogenesis of glioma cells.Conclusion: In conclusion, we established and validated a novel ARG risk signature that independently predicted the clinical outcomes of glioma patients and was associated with the tumor immune microenvironment.

show abstract

Section: Discussionmentioning

confidence: 99%

“…Frontiers in Genetics frontiersin.org glioma (Biterge-Sut, 2020; Wang et al, 2022). Two major aspects of glioma biological processes that contribute to treatment resistance are abnormal formation of new blood vessels via angiogenesis and invasion of glioma cells along white-matter tracts (Carmeliet, 2005;Onishi et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma

Wang

et al. 2022

Front. Genet.

View full text Add to dashboard Cite

show abstract

“…Forty-eight ARGs were derived from the previous study ( 26 ). According to these gene expression profiles, “ConsumusClusterPlus” was constructed for consumes clustering ( 29 ), where patients were divided into various molecular subgroups on the basis of gene expression pattern.…”

Section: Methodsmentioning

confidence: 99%

“…Wang, G., et al. analyzed the molecular subtypes of ARG in Glioblastoma multiforme and established a prognostic model to predict the treatment response of patients ( 26 ). Based on the 48 ARGs provided in their study, we developed a prognosis prediction model in OV, which reveals the significant value in prognosis, tumor microenvironment, and pharmacological sensitivity.…”

Section: Introductionmentioning

confidence: 99%

Molecular subtypes, clinical significance, and tumor immune landscape of angiogenesis-related genes in ovarian cancer

et al. 2022

View full text Add to dashboard Cite

Angiogenesis is a physiological process, where new blood vessels are formed from pre-existing vessels through the mechanism called sprouting. It plays a significant role in supporting tumor growth and is expected to provide novel therapeutic ideas for treating tumors that are resistant to conventional therapies. We investigated the expression pattern of angiogenesis-related genes (ARGs) in ovarian cancer (OV) from public databases, in which the patients could be classified into two differential ARG clusters. It was observed that patients in ARGcluster B would have a better prognosis but lower immune cell infiltration levels in the tumor microenvironment. Then ARG score was computed based on differentially expressed genes via cox analysis, which exhibited a strong correlation to copy number variation, immunophenoscore, tumor mutation load, and chemosensitivity. In addition, according to the median risk score, patients were separated into two risk subgroups, of which the low-risk group had a better prognosis, increased immunogenicity, and stronger immunotherapy efficacy. Furthermore, we constructed a prognostic nomogram and demonstrated its predictive value. These findings help us better understand the role of ARGs in OV and offer new perspectives for clinical prognosis and personalized treatment.

show abstract

“…For example, a prognostic model was developed based on 5 iron death-related genes to predict survival and response to immunotherapy in GBM patients [9]. There is also a prognostic model of GBM constructed based on three angiogenesis-related bases [10]. These prognostic characteristics are based on traditional RNA-seq, and because GBM is a highly heterogeneous tumor, these approaches are unable to detect exact cellular and molecular alterations because bulk RNAseq mostly represents the "average" expression of all cells in the sample [11].…”

Section: Introductionmentioning

confidence: 99%

Expression of hub genes of endothelial cells in glioblastoma-A prognostic model for GBM patients integrating single cell RNA sequencing and bulk RNA sequencing

Zhao

Fan

et al. 2022

Preprint

View full text Add to dashboard Cite

Background：Glioblastoma multiforme (GBM) is one of the most common malignancies in the world and many studies have used traditional high-throughput RNA sequencing (bulk RNA-seq) data to explore its potential prognostic markers. However, it is unable to detect specific cellular and molecular changes in tumour cells. The aim of this study was to use single cell RNA-seq (scRNA-seq) to discover marker genes in endothelial cells and to construct a prognostic model for GBM patients in combination with traditional RNA-seq data.Methods：Bulk RNA-seq data were downloaded from The Cancer Genome Atlas (TCGA) and The China Glioma Genome Atlas (CGGA) databases. 10x scRNA-seq data for GBM were obtained from the Gene Expression Omnibus (GEO) database. The uniform manifold approximation and projection (UMAP) was used for downscaling and cluster identification. Key modules and differentially expressed genes (DEGs) were identified by weighted gene correlation network analysis (WGCNA). Non-negative matrix decomposition (NMF) algorithm was used to identify different subtypes based on DEGS. And Cox regression analysis was used to build prognostic models. Finally, differences in mutational landscape, immune cell abundance, immune checkpoint inhibitors (ICIs)-associated genes, immunotherapy effects and enriched pathways were also investigated between different risk groups.RESULT：The analysis of scRNA-seq data from eight samples revealed 13 clusters and four cell types. After applying differential analysis, endothelial cells were identified as the most important significant cell type. In addition, we explored potential neoangiogenic pathways in GBM after controlling for phenotypic differences between GBM and normal brain tissue ECs at the single cell level. Overall, through differential analysis, WGCNA and screening of endothelial cell marker genes, we identified 157 DEGs for the construction of prognostic models. In addition, based on DEGs,the NMF algorithm identified two clusters with different prognostic and immunological features observed. We finally built a prognostic model based on the expression levels of four of these key genes. Higher risk scores were significantly associated with poorer survival outcomes and were associated with low mutation rates in IDH genes and upregulation of immune checkpoints such as PD-L1 and CD276. The CGGA cohort served as an external validation cohort for our findings.Conclusion：We built and validated a 4-gene signature for GBM using 10 scRNA-seq and bulk RNA-seq data in this work. We believe our findings will provide greater insight into the characteristics of ECs in GBM and provide potential prognostic biomarkers to design rational treatment plans.

show abstract

Angiogenesis-Related Gene Signature-Derived Risk Score for Glioblastoma: Prospects for Predicting Prognosis and Immune Heterogeneity in Glioblastoma

Cited by 9 publications

References 52 publications

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma

Molecular subtypes, clinical significance, and tumor immune landscape of angiogenesis-related genes in ovarian cancer

Expression of hub genes of endothelial cells in glioblastoma-A prognostic model for GBM patients integrating single cell RNA sequencing and bulk RNA sequencing

Contact Info

Product

Resources

About