Dataset Information

Calcium-Related Gene Signatures May Predict Prognosis and Level of Immunosuppression in Gliomas.

ABSTRACT: Gliomas are the most common primary brain cancer. While it has been known that calcium-related genes correlate with gliomagenesis, the relationship between calcium-related genes and glioma prognosis remains unclear. We assessed TCGA datasets of mRNA expressions with differentially expressed genes (DEGs) and enrichment analysis to specifically screen for genes that regulate or are affected by calcium levels. We then correlated the identified calcium-related genes with unsupervised/supervised learning to classify glioma patients into 2 risk groups. We also correlated our identified genes with immune signatures. As a result, we discovered 460 calcium genes and 35 calcium key genes that were associated with OS. There were 13 DEGs between Clusters 1 and 2 with different OS. At the same time, 10 calcium hub genes (CHGs) signature model were constructed using supervised learning, and the prognostic risk scores of the 3 cohorts of samples were calculated. The risk score was confirmed as an independent predictor of prognosis. Immune enrichment analysis revealed an immunosuppressive tumor microenvironment with upregulation of checkpoint markers in the high-risk group. Finally, a nomogram was generated with risk scores and other clinical prognostic independent indicators to quantify prognosis. Our findings suggest that calcium-related gene expression patterns could be applicable to predict prognosis and predict levels of immunosuppression.

SUBMITTER: Liu P

PROVIDER: S-EPMC9136236 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Calcium-Related Gene Signatures May Predict Prognosis and Level of Immunosuppression in Gliomas.

Liu Peidong P Li Yu Y Zhang Yiming Y Choi John J Zhang Jinhao J Shang Guanjie G Li Bailiang B Lin Ya-Jui YJ Saleh Laura L Zhang Liang L Yi Li L Yu Shengping S Lim Michael M Yang Xuejun X

Frontiers in oncology 20220513

Gliomas are the most common primary brain cancer. While it has been known that calcium-related genes correlate with gliomagenesis, the relationship between calcium-related genes and glioma prognosis remains unclear. We assessed TCGA datasets of mRNA expressions with differentially expressed genes (DEGs) and enrichment analysis to specifically screen for genes that regulate or are affected by calcium levels. We then correlated the identified calcium-related genes with unsupervised/supervised lear ...[more]

PMID: 35646664

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Project description:BackgroundCuproptosis is copper-induced cell death. Copper metabolism related genes (CMRGs) were demonstrated that used to assess the prognosis out of tumors. In the study, CMRGs were tested for their effect on TME cell infiltration in Ewing's sarcoma (ES).MethodsThe GEO and ICGC databases provided the mRNA expression profiles and clinical features for downloading. In the GSE17674 dataset, 22prognostic-related copper metabolism related genes (PR-CMRGs) was identified by using univariate regression analysis. Subsequently, in order to compare the survival rates of groups with high and low expression of these PR-CMRGs,Kaplan-Meier analysis was implemented. Additionally, correlations among them were examined. The study employed functional enrichment analysis to investigate probable underlying pathways, while GSVA was applied to evaluate enriched pathways in the ES (Expression Set). Through an unsupervised clustering algorithm, samples were classified into two clusters, revealing significant differences in survival rates and levels of immune infiltration.ResultsUsing Lasso and step regression methods, five genes (TFRC, SORD, SLC11A2, FKBP4, and AANAT) were selected as risk signatures. According to the Kaplan-Meier survival analysis, the high-risk group had considerably lower survival rates than the low-risk group(p=6.013e-09). The area under the curve (AUC) values for the receiver operating characteristic (ROC) curve were 0.876, 0.883, and 0.979 for 1, 3, and 5 years, respectively. The risk model was further validated in additional datasets, namely GSE63155, GSE63156, and the ICGC datasets. To aid in outcome prediction, a nomogram was developed that incorporated risk levels and clinical features. This nomogram's performance was effectively validated through calibration curves.Additionally, the study evaluated the variations in immune infiltration across different risk groups, as well as high-expression and low-expression groups. Importantly, several drugs were identified that displayed sensitivity, offering potential therapeutic options for ES.ConclusionThe findings above strongly indicate that CMRGs play crucial roles in predicting prognosis and immune status in ES.

Dataset Information

Calcium-Related Gene Signatures May Predict Prognosis and Level of Immunosuppression in Gliomas.

Publications

Calcium-Related Gene Signatures May Predict Prognosis and Level of Immunosuppression in Gliomas.

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