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 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 Identification and Potential Mechanisms of a 7-MicroRNA Signature That Predicts Prognosis in Patients with Lower-Grade Glioma

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhizheng Liu ◽  
Hongliang Meng ◽  
Miaoxian Fang ◽  
Wenlong Guo
Keyword(s):  
Signaling Pathway ◽  
Predictive Accuracy ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Lower Grade ◽  
Clinical Practices ◽  
Lower Grade Glioma ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background. Lower-grade glioma is an intracranial cancer that may develop into glioblastoma with high mortality. The main objective of our study is to develop microRNA for LGG patients which will provide novel prognostic biomarkers along with therapeutic targets. Methods. Clinicopathological data of LGG patients and their RNA expression profile were downloaded through The Cancer Genome Atlas Relevant expression profiles of RNA, and clinicopathological data of the LGG patients had been extracted from the database of “The Cancer Genome Atlas.” Differential expression analysis had been conducted for identification of the differentially expressed microRNAs as well as mRNAs in LGG samples and normal ones. ROC curves and K–M plots were plotted to confirm performance and for predictive accuracy. For the confirmation of microRNAs as an independent prognostic factor, an independent prognosis analysis was conducted. Moreover, target differentially expressed genes of these identified prognostic microRNAs that were extracted and protein-protein interaction networks were developed. Moreover, the biological functions of signature were determined through Genome Ontology analysis, genome pathway analysis, and Kyoto Encyclopedia of Genes. Results. 7-microRNA signature was identified that has the ability of categorization of individuals with LGG into high- and low-risk groups on the basis of significant difference in survival during training and testing cohorts (P < 0.001). The 7-microRNA signature had appeared to be robust in predictive accuracy (all AUC> 0.65). It was also approved with multivariate Cox regression along with some traditional clinical practices that we can use 7-microRNA signature for therapeutic purposes as a self-regulating predictive OS factor (P < 0.001). KEGG and Gene Ontology (GO) analyses reported that 7-microRNAs had mainly developed in important pathways related with glioma, e.g., the “cAMP signaling pathway,” “glutamatergic synapses,” and “calcium signaling pathway”. Conclusion. A newly discovered 7-microRNA signature could be a potential target for the diagnosis and treatment for LGG patients.

Comprehensive assessment of PD-L1 and PD-L2 dysregulation in gastrointestinal cancers

Epigenomics ◽  
2020 ◽  
Author(s):  
Qijie Zhao ◽  
Jinan Guo ◽  
Yueshui Zhao ◽  
Jing Shen ◽  
Parham Jabbarzadeh Kaboli ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Signaling Pathways ◽  
Underlying Mechanism ◽  
Comprehensive Analysis ◽  
The Cancer Genome Atlas ◽  
Gastrointestinal Cancers ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background: PD-L1 and PD-L2 are ligands of PD-1. Their overexpression has been reported in different cancers. However, the underlying mechanism of PD-L1 and PD-L2 dysregulation and their related signaling pathways are still unclear in gastrointestinal cancers. Materials & methods: The expression of PD-L1 and PD-L2 were studied in The Cancer Genome Atlas and Genotype-Tissue Expression databases. The gene and protein alteration of PD-L1 and PD-L2 were analyzed in cBioportal. The direct transcription factor regulating PD-L1/ PD-L2 was determined with ChIP-seq data. The association of PD-L1/PD-L2 expression with clinicopathological parameters, survival, immune infiltration and tumor mutation burden were investigated with data from The Cancer Genome Atlas. Potential targets and pathways of PD-L1 and PD-L2 were determined by protein enrichment, WebGestalt and gene ontology. Results: Comprehensive analysis revealed that PD-L1 and PD-L2 were significantly upregulated in most types of gastrointestinal cancers and their expressions were positively correlated. SP1 was a key transcription factor regulating the expression of PD-L1. Conclusion: Higher PD-L1 or PD-L2 expression was significantly associated with poor overall survival, higher tumor mutation burden and more immune and stromal cell populations. Finally, HIF-1, ERBB and mTOR signaling pathways were most significantly affected by PD-L1 and PD-L2 dysregulation. Altogether, this study provided comprehensive analysis of the dysregulation of PD-L1 and PD-L2, its underlying mechanism and downstream pathways, which add to the knowledge of manipulating PD-L1/PD-L2 for cancer immunotherapy.

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

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Jingwei Zhao ◽  
Le Wang ◽  
Bo Wei
Keyword(s):  
Energy Metabolism ◽  
Risk Score ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Coexpression Network ◽  
Normal Brain ◽  
Lower Grade ◽  
Prognostic Signature ◽  
Lower Grade Glioma ◽  
Genome Atlas

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.

scholarly journals Recurrent Amplification of the Osmotic Stress Transcription Factor NFAT5 in Adrenocortical Carcinoma

2020 ◽  
Vol 4 (7) ◽  
Author(s):  
Taylor C Brown ◽  
Norman G Nicolson ◽  
Jianliang Man ◽  
Courtney E Gibson ◽  
Adam Stenman ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Osmotic Stress ◽  
Protein Expression ◽  
Adrenocortical Carcinoma ◽  
The Cancer Genome Atlas ◽  
Discovery Cohort ◽  
Adrenocortical Adenomas ◽  
Cancer Genome Atlas ◽  
Mrna Expression Levels ◽  
Genome Atlas

Abstract Tumorigenesis requires mitigation of osmotic stress and the transcription factor nuclear factor of activated T cells 5 (NFAT5) coordinates this response by inducing transcellular transport of ions and osmolytes. NFAT5 modulates in vitro behavior in several cancer types, but a potential role of NFAT5 in adrenocortical carcinoma (ACC) has not been studied. A discovery cohort of 28 ACCs was selected for analysis. Coverage depth analysis of whole-exome sequencing reads assessed NFAT5 copy number alterations in 19 ACCs. Quantitative real-time PCR measured NFAT5 mRNA expression levels in 11 ACCs and 23 adrenocortical adenomas. Immunohistochemistry investigated protein expression in representative adrenal samples. The Cancer Genome Atlas database was analyzed to corroborate NFAT5 findings from the discovery cohort and to test whether NFAT5 expression correlated with ion/osmolyte channel and regulatory protein expression patterns in ACC. NFAT5 was amplified in 10 ACCs (52.6%) and clustered in the top 6% of all amplified genes. mRNA expression levels were 5-fold higher compared with adrenocortical adenomas (P &lt; 0.0001) and NFAT5 overexpression had a sensitivity and specificity of 81.8% and 82.7%, respectively, for malignancy. Increased protein expression and nuclear localization occurred in representative ACCs. The Cancer Genome Atlas analysis demonstrated concomitant NFAT5 amplification and overexpression (P &lt; 0.0001) that correlated with increased expression of sodium/myo-inositol transporter SLC5A3 (r2 = 0.237, P &lt; 0.0001) and 14 other regulatory proteins (P &lt; 0.05) previously shown to interact with NFAT5. Amplification and overexpression of NFAT5 and associated osmotic stress response related genes may play an important role adrenocortical tumorigenesis.

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