RELL1, a novel oncogene, accelerates tumor progression and regulates immune infiltrates in glioma

Jin, Xiaohong; Xie, Huiwen; Liu, Xiaoman; Shen, Qiuyan; Wang, Ziheng; Hao, Haiyan; Gu, Yan

doi:10.1016/j.intimp.2020.106707

Cited by 15 publications

(11 citation statements)

References 25 publications

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“…To complete the pathway analysis, the GSEA software (v4.0.3) was used. Nominal values (NOM) with (p < 0:05) and a false discovery rate (q value < 0.25) were both considered statistically significant [18,19].…”

Section: Gene Set Enrichment Analysis (Gsea)mentioning

confidence: 99%

Identification of Nine M6A-Related Long Noncoding RNAs as Prognostic Signatures Associated with Oxidative Stress in Oral Cancer Based on Data from The Cancer Genome Atlas

Song

et al. 2022

Oxidative Medicine and Cellular Longevity

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Objective. Although the expression of long noncoding RNAs (lncRNAs) and N6-methyladenosine (M6A) is correlated with different tumors, it remains unclear how M6A-related lncRNA functioning affects the initiation and progression of oral squamous cell carcinoma (OSCC). Materials and Methods. Gene expression and clinical data were retrieved from The Cancer Genome Atlas. The prognostic value of M6A-related lncRNAs was determined using univariate Cox regression analyses. Gene set enrichment analysis of OSCC patient clusters revealed the pathways that elucidate the mechanism. Furthermore, a risk-based model was established. The difference in the overall survival (OS) between groups, including low-/high-risk groups, was determined by Kaplan-Meier analysis. Relationships among immune cells, clusters, clinicopathological characteristics, and risk scores were explored. Results. Among 1,080 M6A-related lncRNAs, 36 were prognosis-related. Patients with OSCC were divided into two clusters. T stage and the pathological grade were noticeably lower in cluster 2 than in cluster 1. Epithelial-mesenchymal transition showed greater enrichment in cluster 1. Nine hub M6A-related lncRNAs were identified for the model of risk score for predicting OSCC prognosis. The OS was longer in patients with a low-risk score than in patients with a high-risk score. The risk score was an independent prognostic factor of OSCC and was associated with the infiltration of different immune cells. T stages and the American Joint Committee on Cancer (AJCC) stages were more advanced in the high-risk score group than in the low-risk score group. Finally, expression correlation analysis showed that the risk score is associated with the expression of oxidative stress markers. Conclusion. M6A-related lncRNAs play an important role in OSCC progression. Immune cell infiltration was related to the risk score model in OSCC and could accurately predict OSCC prognosis.

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Section: Gene Set Enrichment Analysis (Gsea)mentioning

confidence: 99%

Identification of Nine M6A-Related Long Noncoding RNAs as Prognostic Signatures Associated with Oxidative Stress in Oral Cancer Based on Data from The Cancer Genome Atlas

Song

et al. 2022

Oxidative Medicine and Cellular Longevity

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“…The mRNA microarray technology based on gene expression profiles has facilitated the detection of a wide range of diseases [ 8 , 9 ]. The expression levels of several thousand genes have been measured simultaneously in these profiles for providing a better prognosis than prior models owing to the fact that they are used as the basis for the feature selection and classification [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Integrated Microarray Analysis to Identify Genes and Small-Molecule Drugs Associated with Stroke Progression

Cui¹,

Zhao

Huang

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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Several blood biomarkers are now considered increasingly important for stratifying risk, monitoring disease progression, and evaluating the response to therapy in ischemic stroke. The purpose of the present study was to identify the key genes associated with ischemic stroke progression and elucidate the potential therapeutic small molecules. Microarray datasets related to stroke for GSE58294, GSE22255, and GSE16561 were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were filtered using the Limma package. DAVID was then searched to perform gene ontology (GO) and pathway enrichment analyses. Based on the DEGs, a protein-protein interaction (PPI) network was developed using Cytoscape, and MCODE was applied to conduct module analysis. Finally, to identify the potential drugs for ischemic stroke, the connectivity map (CMap) database was used. Sixty DEGs were identified after analyzing the three datasets. The GO data analysis revealed that the DEGs were significantly associated with biological processes, including positive regulation of programmed cell death, protein localization in organelles, and positive regulation of apoptosis. KEGG analysis showed that the DEGs were particularly enriched in the Fc epsilon RI signaling pathway, MAPK signaling pathway, and Huntington’s disease. We selected five DEGs with high connectivity (CYBB, SYK, DUSP1, TNF, and SP1) that significantly predicted stroke progression. In addition, CMap prediction showed ten small molecules that could be used as adjuvants when treating ischemic stroke. The outcomes of the present study indicated that the five genes mentioned above can be considered potential targets for developing new medications that can modify the ischemic stroke process, and mycophenolic acid was the most promising small molecule to treat ischemic stroke.

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“…GBM is one of the most commonly seen primary malignant brain tumor in adults with an overall poor prognosis (Ostrom et al, 2018;Zhang et al, 2019;Jin et al, 2020). The recurrence rate of GBM is particularly high.…”

Section: Discussionmentioning

confidence: 99%

NPC2 as a Prognostic Biomarker for Glioblastoma Based on Integrated Bioinformatics Analysis and Cytological Experiments

Shen

Lin

et al. 2021

Front. Genet.

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Glioblastoma (GBM) is one of the most common and fatal malignancies worldwide, while its prognostic biomarkers are still being explored. This study aims to identify potential genes with clinical and prognostic significance by integrating bioinformatics analysis and investigating their function in HNSCC. Based on the Single-cell RNA sequencing (scRNA-seq) results of H3K27M-glioma cells, computational bioinformatics methods were employed for selecting prognostic biomarker for GBM. The protein NPC2 (NPC Intracellular Cholesterol Transporter 2), which has been shown to be related to lipoprotein metabolism and innate immune system, was identified to be upregulated in GBM. NPC2 showed a relatively higher expression in GBM samples, and a negative correlation with tumor purity and tumor infiltrating immune cells. Additionally, NPC2 was knocked down in U87-MG and U251 cells line, and cell proliferation and migration capability were evaluated with CCK-8, scratch and transwell assay, respectively. Cytological experiments has shown that NPC2 overexpression inhibited GBM cells proliferation and migration, indicating its important role in GBM progression. This is the first investigation into the prognostic value of NPC2 interact with GBM. The potential molecular factor NPC2 have been identified as a prognostic biomarker for GBM.

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RELL1, a novel oncogene, accelerates tumor progression and regulates immune infiltrates in glioma

Cited by 15 publications

References 25 publications

Identification of Nine M6A-Related Long Noncoding RNAs as Prognostic Signatures Associated with Oxidative Stress in Oral Cancer Based on Data from The Cancer Genome Atlas

Identification of Nine M6A-Related Long Noncoding RNAs as Prognostic Signatures Associated with Oxidative Stress in Oral Cancer Based on Data from The Cancer Genome Atlas

Integrated Microarray Analysis to Identify Genes and Small-Molecule Drugs Associated with Stroke Progression

NPC2 as a Prognostic Biomarker for Glioblastoma Based on Integrated Bioinformatics Analysis and Cytological Experiments

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