scholarly journals Clinical Significance and Systematic Expression Analysis of the Thyroid Receptor Interacting Protein 13 (TRIP13) as Human Gliomas Biomarker

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2338
Author(s):  
Ssu-Han Chen ◽  
Hong-Han Lin ◽  
Yao-Feng Li ◽  
Wen-Chiuan Tsai ◽  
Dueng-Yuan Hueng
Keyword(s):  
Clinical Significance ◽  
Expression Analysis ◽  
Expression Profiles ◽  
Malignant Gliomas ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Lower Grade ◽  
Interacting Protein ◽  
Thyroid Receptor ◽  
Genome Atlas

The prognosis of malignant gliomas such as glioblastoma multiforme (GBM) has remained poor due to limited therapeutic strategies. Thus, it is pivotal to determine prognostic factors for gliomas. Thyroid Receptor Interacting Protein 13 (TRIP13) was found to be overexpressed in several solid tumors, but its role and clinical significance in gliomas is still unclear. Here, we conducted a comprehensive expression analysis of TRIP13 to determine the prognostic values. Gene expression profiles of the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA) and GSE16011 dataset showed increased TRIP13 expression in advanced stage and worse prognosis in IDH-wild type lower-grade glioma. We performed RT-PCR and Western blot to validate TRIP13 mRNA expression and protein levels in GBM cell lines. TRIP13 co-expressed genes via database screening were regulated by essential cancer-related upstream regulators (such as TP53 and FOXM1). Then, TCGA analysis revealed that more TRIP13 promoter hypomethylation was observed in GBM than in low-grade glioma. We also inferred that the upregulated TRIP13 levels in gliomas could be regulated by dysfunction of miR-29 in gliomas patient cohorts. Moreover, TRIP13-expressing tumors not only had higher aneuploidy but also tended to reduce the ratio of CD8+/Treg, which led to a worse survival outcome. Overall, these findings demonstrate that TRIP13 has with multiple functions in gliomas, and they may be crucial for therapeutic potential.

scholarly journals A comprehensive analysis of the angiogenesis-related genes in glioblastoma multiforme vs. brain lower grade glioma

2020 ◽  
Vol 78 (1) ◽  
pp. 34-38
Author(s):  
Burcu BITERGE-SUT
Keyword(s):  
Glioblastoma Multiforme ◽  
Malignant Gliomas ◽  
Genetic Alterations ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Lower Grade ◽  
Nonsense Mutations ◽  
Lower Grade Glioma ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Abstract Brain tumors are one of the most common causes of cancer-related deaths around the world. Angiogenesis is critical in high-grade malignant gliomas, such as glioblastoma multiforme. Objective: The aim of this study is to comparatively analyze the angiogenesis-related genes, namely VEGFA, VEGFB, KDR, CXCL8, CXCR1 and CXCR2 in LGG vs. GBM to identify molecular distinctions using datasets available on The Cancer Genome Atlas (TCGA). Methods: DNA sequencing and mRNA expression data for 514 brain lower grade glioma (LGG) and 592 glioblastoma multiforme (GBM) patients were acquired from The Cancer Genome Atlas (TCGA), and the genetic alterations and expression levels of the selected genes were analyzed. Results: We identified six distinct KDR mutations in the LGG patients and 18 distinct KDR mutations in the GBM patients, including missense and nonsense mutations, frame shift deletion and altered splice region. Furthermore, VEGFA and CXCL8 were significantly overexpressed within GBM patients. Conclusions: VEGFA and CXCL8 are important factors for angiogenesis, which are suggested to have significant roles during tumorigenesis. Our results provide further evidence that VEGFA and CXCL8 could induce angiogenesis and promote LGG to progress into GBM. These findings could be useful in developing novel targeted therapeutics approaches in the future.

scholarly journals Clinical characterization, genetic profiling, and immune infiltration of TOX in diffuse gliomas

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Hao Zhang ◽  
Fan Fan ◽  
Yuanqiang Yu ◽  
Zeyu Wang ◽  
Fangkun Liu ◽  
...  
Keyword(s):  
Immune Cell ◽  
Malignant Gliomas ◽  
Leading Edge ◽  
Cell Types ◽  
Tumour Microenvironment ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Lymphocyte Migration ◽  
Who Grade ◽  
Genome Atlas

Abstract Background Immunotherapies targeting glioblastoma (GBM) have led to significant improvements in patient outcomes. TOX is closely associated with the immune environment surrounding tumors, but its role in gliomas is not fully understood. Methods Using data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), we analyzed the transcriptomes of 1691 WHO grade I-IV human glioma samples. The R language was used to perform most of the statistical analyses. Somatic mutations and somatic copy number variation (CNV) were analyzed using GISTIC 2.0. Results TOX was down-regulated in malignant gliomas compared to low grade gliomas, and upregulated in the proneural and IDH mutant subtypes of GBM. TOXlow tumours are associated with the loss of PTEN and amplification of EGFR, while TOXhigh tumours harbor frequent mutations in IDH1 (91%). TOX was highly expressed in leading edge regions of tumours. Gene ontology and pathway analyses demonstrated that TOX was enriched in multiple immune related processes including lymphocyte migration in GBM. Finally, TOX had a negative association with the infiltration of several immune cell types in the tumour microenvironment. Conclusion TOX has the potential to be a new prognostic marker for GBM.

scholarly journals Clinical characterization, genetic profiling, and immune infiltration of TOX in diffuse gliomas

2020 ◽  
Author(s):  
Zhang Hao ◽  
Fan Fan ◽  
Yu Yuanqiang ◽  
Wang Zeyu ◽  
Liu Fangkun ◽  
...  
Keyword(s):  
Immune Cell ◽  
Malignant Gliomas ◽  
Leading Edge ◽  
Cell Types ◽  
Tumour Microenvironment ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Lymphocyte Migration ◽  
Who Grade ◽  
Genome Atlas

Abstract Background: Immunotherapies targeting glioblastoma (GBM) have led to significant improvements in patient outcomes. TOX is closely associated with the immune environment surrounding tumors, but its role in gliomas is not fully understood. Methods: Using data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), we analyzed the transcriptomes of 1691 WHO grade I-IV human glioma samples. The R language was used to perform most of the statistical analyses. Somatic mutations and somatic copy number variation (CNV) were analyzed using GISTIC 2.0. Results: TOX was down-regulated in malignant gliomas compared to low grade gliomas, and upregulated in the proneural and IDH mutant subtypes of GBM. TOXlow tumours are associated with the loss of PTEN and amplification of EGFR, while TOXhigh tumours harbor frequent mutations in IDH1 (91%). TOX was highly expressed in leading edge regions of tumours. Gene ontology and pathway analyses demonstrated that TOX was enriched in multiple immune related processes including lymphocyte migration in GBM. Finally, TOX had a negative association with the infiltration of several immune cell types in the tumour microenvironment. Conclusion: TOX has the potential to be a new prognostic marker for GBM.

scholarly journals The Cancer Genome Atlas expression profiles of low-grade gliomas

2014 ◽  
Vol 36 (4) ◽  
pp. E23 ◽  
Author(s):  
David D. Gonda ◽  
Vincent J. Cheung ◽  
Karra A. Muller ◽  
Amit Goyal ◽  
Bob S. Carter ◽  
...  
Keyword(s):  
Cpg Island ◽  
Expression Profiles ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Molecular Characteristics ◽  
Low Grade ◽  
Cpg Island Methylator Phenotype ◽  
Low Grade Gliomas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Differentiating between low-grade gliomas (LGGs) of astrocytic and oligodendroglial origin remains a major challenge in neurooncology. Here the authors analyzed The Cancer Genome Atlas (TCGA) profiles of LGGs with the goal of identifying distinct molecular characteristics that would afford accurate and reliable discrimination of astrocytic and oligodendroglial tumors. They found that 1) oligodendrogliomas are more likely to exhibit the glioma-CpG island methylator phenotype (G-CIMP), relative to low-grade astrocytomas; 2) relative to oligodendrogliomas, low-grade astrocytomas exhibit a higher expression of genes related to mitosis, replication, and inflammation; and 3) low-grade astrocytic tumors harbor microRNA profiles similar to those previously described for glioblastoma tumors. Orthogonal intersection of these molecular characteristics with existing molecular markers, such as IDH1 mutation, TP53 mutation, and 1p19q status, should facilitate accurate and reliable pathological diagnosis of LGGs.

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

2020 ◽  
Author(s):  
Qiang Zhang ◽  
Shun-Bin Luo ◽  
Fu-Chen Xie ◽  
Xiao-Jun Liu ◽  
Ren-ai Xu
Keyword(s):  
Large Scale ◽  
Expression Profiles ◽  
Predictive Performance ◽  
Gene Signature ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Lower Grade ◽  
Good Prospect ◽  
Sequencing Data ◽  
Genome Atlas

Abstract 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.

scholarly journals Development of a Prognostic Five-Gene Signature for Diffuse Lower-Grade Glioma Patients

2021 ◽  
Vol 12 ◽  
Author(s):  
Qiang Zhang ◽  
Wenhao Liu ◽  
Shun-Bin Luo ◽  
Fu-Chen Xie ◽  
Xiao-Jun Liu ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Clinical Information ◽  
Predictive Performance ◽  
Risk Groups ◽  
Gene Signature ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Lower Grade ◽  
Good Prospect ◽  
Genome Atlas

Background: Diffuse lower-grade gliomas (LGGs) are infiltrative and heterogeneous neoplasms. Gene signature including multiple protein-coding genes (PCGs) is widely used as a tumor marker. 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 a significantly different overall survival (log rank P &lt; 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 that 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 for LGG patients and has a good prospect in clinical application.

scholarly journals Prognostic Model and Nomogram Construction Based on a Novel Ferroptosis-Related Gene Signature in Lower-Grade Glioma

2021 ◽  
Vol 12 ◽  
Author(s):  
Junsheng Zhao ◽  
Zhengtao Liu ◽  
Xiaoping Zheng ◽  
Hainv Gao ◽  
Lanjuan Li
Keyword(s):  
Risk Model ◽  
Survival Curve ◽  
External Validation ◽  
Enrichment Analysis ◽  
Predictive Performance ◽  
The Cancer Genome Atlas ◽  
Survival Prediction ◽  
Low Grade ◽  
Lower Grade ◽  
Genome Atlas

Background: Low-grade glioma (LGG) is considered a fatal disease for young adults, with overall survival widely ranging from 1 to 15 years depending on histopathologic and molecular subtypes. As a novel type of programmed cell death, ferroptosis was reported to be involved in tumorigenesis and development, which has been intensively studied in recent years.Methods: For the discovery cohort, data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were used to identify the differentially expressed and prognostic ferroptosis-related genes (FRGs). The least absolute shrinkage and selection operator (LASSO) and multivariate Cox were used to establish a prognostic signature with the above-selected FRGs. Then, the signature was developed and validated in TCGA and Chinese Glioma Genome Atlas (CGGA) databases. By combining clinicopathological features and the FRG signature, a nomogram was established to predict individuals’ one-, three-, and five-year survival probability, and its predictive performance was evaluated by Harrell’s concordance index (C-index) and calibration curves. Enrichment analysis was performed to explore the signaling pathways regulated by the signature.Results: A novel risk signature contains seven FRGs that were constructed and were used to divide patients into two groups. Kaplan–Meier (K−M) survival curve and receiver-operating characteristic (ROC) curve analyses confirmed the prognostic performance of the risk model, followed by external validation based on data from the CGGA. The nomogram based on the risk signature and clinical traits was validated to perform well for predicting the survival rate of LGG. Finally, functional analysis revealed that the immune statuses were different between the two risk groups, which might help explain the underlying mechanisms of ferroptosis in LGG.Conclusion: In conclusion, this study constructed a novel and robust seven-FRG signature and established a prognostic nomogram for LGG survival prediction.

scholarly journals Prognostic Value of an Autophagy-Related Five-Gene Signature for Lower-Grade Glioma Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Jin-Cheng Guo ◽  
Qing-Shuang Wei ◽  
Lei Dong ◽  
Shuang-Sang Fang ◽  
Feng Li ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Cox Regression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Molecular Characteristics ◽  
Lower Grade ◽  
Cox Regression Analysis ◽  
Tcga Dataset ◽  
Genome Atlas

Background: Molecular characteristics can be good indicators of tumor prognosis and have been introduced into the classification of gliomas. The prognosis of patients with newly classified lower-grade gliomas (LGGs, including grade 2 and grade 3 gliomas) is highly heterogeneous, and new molecular markers are urgently needed.Methods: Autophagy related genes (ATGs) were obtained from Human Autophagy Database (HADb). From the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), gene expression profiles including ATG expression information and patient clinical data were downloaded. Cox regression analysis, receiver operating characteristic (ROC) analysis, Kaplan–Meier analysis, random survival forest algorithm (RSFVH) and stratification analysis were performed.Results: Through univariate Cox regression analysis, we found a total of 127 ATGs associated with the prognosis of LGG patients from TCGA dataset and a total of 131 survival-related ATGs from CGGA dataset. Using TCGA dataset as the training group (n = 524), we constructed a five-ATG signature (including BAG1, BID, MAP1LC3C, NRG3, PTK6), which could divide LGG patients into two risk groups with significantly different overall survival (Log Rank P &lt; 0.001). Then we confirmed in the independent CGGA dataset that the five-ATG signature had the ability to predict prognosis (n = 431, Log Rank P &lt; 0.001). We further discovered that the predictive ability of the five-ATG signature was better than the existing clinical indicators and IDH mutation status. In addition, the five-ATG signature could further classify patients after receiving radiotherapy or chemotherapy into groups with different prognosis.Conclusions: We identified a five-ATG signature that could be a reliable prognostic marker and might be therapeutic targets for autophagy therapy for LGG patients.

scholarly journals RUNX1 and REXO2 are associated with the heterogeneity and prognosis of IDH wild type lower grade glioma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Ji Zhang ◽  
Hua Cao
Keyword(s):  
Transcription Factor ◽  
Low Frequency ◽  
Tumor Grade ◽  
The Cancer Genome Atlas ◽  
Lower Grade ◽  
Wild Type ◽  
Lower Grade Glioma ◽  
Cancer Genome Atlas ◽  
Worse Prognosis ◽  
Genome Atlas

AbstractBased on isocitrate dehydrogenase (IDH) alterations, lower grade glioma (LGG) is divided into IDH mutant and wild type subgroups. However, the further classification of IDH wild type LGG was unclear. Here, IDH wild type LGG patients in The Cancer Genome Atlas and Chinese Glioma Genome Atlas were divided into two sub-clusters using non-negative matrix factorization. IDH wild type LGG patients in sub-cluster2 had prolonged overall survival and low frequency of CDKN2A alterations and low immune infiltrations. Differentially expressed genes in sub-cluster1 were positively correlated with RUNX1 transcription factor. Moreover, IDH wild type LGG patients with higher stromal score or immune score were positively correlated with RUNX1 transcription factor. RUNX1 and its target gene REXO2 were up-regulated in sub-cluster1 and associated with the worse prognosis of IDH wild type LGG. RUNX1 and REXO2 were associated with the higher immune infiltrations. Furthermore, RUNX1 and REXO2 were correlated with the worse prognosis of LGG or glioma. IDH wild type LGG in sub-cluster2 was hyper-methylated. REXO2 hyper-methylation was associated with the favorable prognosis of LGG or glioma. At last, we showed that, age, tumor grade and REXO2 expression were independent prognostic factors in IDH wild type LGG.

scholarly journals Investigation of Genetic Determinants of Glioma Immune Phenotype by Integrative Immunogenomic Scale Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Binghao Zhao ◽  
Yuekun Wang ◽  
Yaning Wang ◽  
Congxin Dai ◽  
Yu Wang ◽  
...  
Keyword(s):  
Immune Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Clinicopathological Characteristics ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Immune Phenotype ◽  
Immune Phenotypes ◽  
Glioma Microenvironment ◽  
Genome Atlas

The immunosuppressive mechanisms of the surrounding microenvironment and distinct immunogenomic features in glioblastoma (GBM) have not been elucidated to date. To fill this gap, useful data were extracted from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), GSE16011, GSE43378, GSE23806, and GSE12907. With the ssGSEA method and the ESTIMATE and CIBERSORT algorithms, four microenvironmental signatures were used to identify glioma microenvironment genes, and the samples were reasonably classified into three immune phenotypes. The molecular and clinical features of these phenotypes were characterized via key gene set expression, tumor mutation burden, fraction of immune cell infiltration, and functional enrichment. Exhausted CD8+ T cell (GET) signature construction with the predictive response to commonly used antitumor drugs and peritumoral edema assisted in further characterizing the immune phenotype features. A total of 2,466 glioma samples with gene expression profiles were enrolled. Tumor purity, ESTIMATE, and immune and stromal scores served as the 4 microenvironment signatures used to classify gliomas into immune-high, immune-middle and immune-low groups, which had distinct immune heterogeneity and clinicopathological characteristics. The immune-H phenotype had higher expression of four immune signatures; however, most checkpoint molecules exhibited poor survival. Enriched pathways among the subtypes were related to immunity. The GET score was similar among the three phenotypes, while immune-L was more sensitive to bortezomib, cisplatin, docetaxel, lapatinib, and rapamycin prescriptions and displayed mild peritumor edema. The three novel immune phenotypes with distinct immunogenetic features could have utility for understanding glioma microenvironment regulation and determining prognosis. These results contribute to classifying glioma subtypes, remodeling the immunosuppressive microenvironment and informing novel cancer immunotherapy in the era of precision immuno-oncology.

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