Prognostic significance of age related genes in patients with lower grade glioma

Wang, Haiwei; Wang, Xinrui; Xu, Liangpu; Zhang, Ji; Cao, Hua

doi:10.7150/jca.41123

Cited by 19 publications

(23 citation statements)

References 44 publications

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“…Epithelial membrane protein 3(EMP3) is considered to be a tumor suppressor, but this article found that this gene is a prognostic risk gene for LGG. Similar to our results, Haiwei Wang et al also found that EMP3 was associated with the worse prognosis of LGG patients [23] and Xiao-Xia Guo et al discovered EMP3 was also a risk gene in the process of developing a prognostic 4-gene panel for glioblastoma patients [24]. WEE1 G2 checkpoint kinase(WEE1) is reported to be an oncogenic nuclear kinase and a regulator of the G2 checkpoint.…”

Section: Discussionsupporting

confidence: 90%

Development of a Prognostic Five-Gene Signature with Radiotherapy Guidance Significance for Diffuse Lower-Grade Glioma Patients Based on Large-Scale Sequencing Data

Zhang¹,

Luo²,

Xie³

et al. 2020

Preprint

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Background: Diffuse lower-grade gliomas (LGGs) are infiltrative and heterogeneous neoplasms. Gene signature including multiple protein coding genes (PCGs) is widely used as tumor markers. This study aimed to construct a multi-PCG signature to predict survival for LGG patients.Methods: LGG data including PCG expression profiles and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Survival analysis, receiver operating characteristic (ROC) analysis and random survival forest algorithm (RSFVH) were used to identify the prognostic PCG signature.Results: From the training (n = 524) and test (n = 431) datasets, a five-PCG signature which can classify LGG patients into low- or high-risk group with significantly different overall survival (Log Rank P < 0.001) was screened out and validated. In terms of prognosis predictive performance, the five-PCG signature is stronger than other clinical variables and IDH mutation status. Moreover, the five-PCG signature could further divide radiotherapy patients into two different risk groups. GO and KEGG analysis found PCGs in the prognostic five-PCG signature were mainly enriched in cell cycle, apoptosis, DNA replication pathways.Conclusions: The new five-PCG signature is a reliable prognostic marker with radiotherapy guidance significance for LGG patients and has a good prospect in clinical application.

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Section: Discussionsupporting

confidence: 90%

Development of a Prognostic Five-Gene Signature with Radiotherapy Guidance Significance for Diffuse Lower-Grade Glioma Patients Based on Large-Scale Sequencing Data

Zhang¹,

Luo²,

Xie³

et al. 2020

Preprint

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“…SERPINE1 was reported to be up-regulated in STAD tissues compared with normal tissues, and the overexpression of SERPINE1 was closely associated with worse prognosis among STAD patients [ 32 ]. In addition, SERPINE1 was reported to have excellent prognostic value among patients with lower grade glioma [ 33 ]. SERPINE1 was observed to be up-regulated in glioma tissues using immunohistochemistry, and high expression of SERPINE1 was associated with reduced DFS and OS in glioma patients [ 34 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of pivotal genes associated with the prognosis of gastric carcinoma through integrated analysis

et al. 2021

Bioscience Reports

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Purpose: Detecting and diagnosing gastric cancer (GC) during its early period remains greatly difficult. Our analysis was performed to detect core genes correlated with GC and explore their prognostic values. Methods: Microarray datasets from the GEO (GSE54129) and TCGA-stomach adenocarcinoma (STAD) datasets were applied for common differentially coexpressed genes using differential gene expression analysis and weighted gene coexpression network analysis (WGCNA). Functional enrichment analysis and protein-protein interaction (PPI) network analysis of differentially coexpressed genes were performed. We identified hub genes via the CytoHubba plugin. Prognostic values of hub genes were explored. Afterward, GSEA was used to analyze survival-related hub genes. Finally, the tumor-infiltrating immune cell (TIC) abundance profiles were estimated. Results: Sixty common differentially co-expressed genes were found. Functional enrichment analysis implied that cell−cell junction organization and cell adhesion molecules were primarily enriched. Hub genes were identified using the degree, edge percolated component (EPC), maximal clique centrality (MCC), and maximum neighborhood component (MNC) algorithms, and SERPINE1 was highly associated with the prognosis of GC patients. Moreover, GSEA demonstrated that ECM receptor interactions and pathways in cancers were correlated with SERPINE1 expression. CIBERSORT analysis of the proportion of TICs suggested that CD8+ T cell and T cell regulation were negatively associated with SERPINE1 expression, showing that SERPINE1 may inhibit the immune-dominant status of the tumor microenvironment in GC. Conclusions: Our analysis shows that SERPINE1 is closely correlated with the tumorigenesis and progression of GC. Furthermore, SERPINE1 acts as a candidate therapeutic target and prognostic biomarker of GC.

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“…This conclusion was also proved by our study (AUC = 0:827 vs. 0.747 for lncRNA alone model and 0.739 for mRNA alone model; C-index = 0:812 vs. 0.702 for lncRNA alone model and 0.737 for mRNA alone model). Furthermore, the poor prognosis of LGG was traditionally determined according to clinical characteristics, including older age [23] and IDH1 nonmutational status [24,25]. Thus, whether the risk score was superior or added additional prognostic value to these current clinical systems for prognosis prediction was also an important focus in the signature studies [10,22,26].…”

Section: Discussionmentioning

confidence: 99%

“…Overexpression of PON2 led to a significant increase in tumor cell proliferation and resistance to oxidative stress [34], while silencing of PON2 expression inhibited cancer cell proliferation, migration, and invasion [24]. Patients with high PON2 expression had shorter OS compared with those having low PON2 expression [23]. These findings indicated that high expression of PON2 may represent a protective stress response.…”

mentioning

confidence: 95%

Identification and Validation of an Energy Metabolism-Related lncRNA-mRNA Signature for Lower-Grade Glioma

Zhao

Wang

Wei

2020

BioMed Research International

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Energy metabolic processes play important roles for tumor malignancy, indicating that related protein-coding genes and regulatory upstream genes (such as long noncoding RNAs (lncRNAs)) may represent potential biomarkers for prognostic prediction. This study will develop a new energy metabolism-related lncRNA-mRNA prognostic signature for lower-grade glioma (LGG) patients. A GSE4290 dataset obtained from Gene Expression Omnibus was used for screening the differentially expressed genes (DEGs) and lncRNAs (DELs). The Cancer Genome Atlas (TCGA) dataset was used as the prognosis training set, while the Chinese Glioma Genome Atlas (CGGA) was for the validation set. Energy metabolism-related genes were collected from the Molecular Signatures Database (MsigDB), and a coexpression network was established between energy metabolism-related DEGs and DELs to identify energy metabolism-related DELs. Least absolute shrinkage and selection operator (LASSO) analysis was performed to filter the prognostic signature which underwent survival analysis and nomogram construction. A total of 1613 DEGs and 37 DELs were identified between LGG and normal brain tissues. One hundred and ten DEGs were overlapped with energy metabolism-related genes. Twenty-seven DELs could coexpress with 67 metabolism-related DEGs. LASSO regression analysis showed that 9 genes in the coexpression network were the optimal signature and used to construct the risk score. Kaplan-Meier curve analysis showed that patients with a high risk score had significantly worse OS than those with a low risk score (TCGA: HR=3.192, 95%CI=2.182‐4.670; CGGA: HR=1.922, 95%CI=1.431‐2.583). The predictive accuracy of the risk score was also high according to the AUC of the ROC curve (TCGA: 0.827; CGGA: 0.806). Multivariate Cox regression analyses revealed age, IDH1 mutation, and risk score as independent prognostic factors, and thus, a prognostic nomogram was established based on these three variables. The excellent prognostic performance of the nomogram was confirmed by calibration and discrimination analyses. In conclusion, our findings provided a new biomarker for the stratification of LGG patients with poor prognosis.

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Prognostic significance of age related genes in patients with lower grade glioma

Cited by 19 publications

References 44 publications

Development of a Prognostic Five-Gene Signature with Radiotherapy Guidance Significance for Diffuse Lower-Grade Glioma Patients Based on Large-Scale Sequencing Data

Development of a Prognostic Five-Gene Signature with Radiotherapy Guidance Significance for Diffuse Lower-Grade Glioma Patients Based on Large-Scale Sequencing Data

Identification of pivotal genes associated with the prognosis of gastric carcinoma through integrated analysis

Identification and Validation of an Energy Metabolism-Related lncRNA-mRNA Signature for Lower-Grade Glioma

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