High Levels of HIST1H2BK in Low-Grade Glioma Predicts Poor Prognosis: A Study Using CGGA and TCGA Data

Liu, Weidong; Xu, Zhentao; Zhou, Jie; Xing, Shuang; Li, Zhiqiang; Gao, Xu; Feng, Shiyu; Xiao, Yi

doi:10.3389/fonc.2020.00627

Cited by 31 publications

(34 citation statements)

References 42 publications

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“…Bioinformatics analysis using high-throughput sequencing and clinical data is developing rapidly to identify sensitive biomarkers and prognostic factors for a variety of tumors, including gliomas. The acetylation modification and kinase activity of PAK1 were considered to be an instrumental role in hypoxia-induced autophagy initiation and maintaining GBM growth, and PAK1 might represent potential therapeutic targets for GBM treatment (Feng et al, 2020). HIST1H2BK was identified as an indicator of poor prognosis and a promising biomarker for the treatment of low-grade glioma (LGG) (Liu et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

The relationship between PLOD1 expression level and glioma prognosis investigated using public databases

Tian

Zhou

Wang

et al. 2021

PeerJ

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Background Glioma is the most common type of intracranial tumor with high malignancy and poor prognosis despite the use of various aggressive treatments. Targeted therapy and immunotherapy are not effective and new biomarkers need to be explored. Some Procollagen-lysine 2-oxyglutarate 5-dioxygenase (PLOD) family members have been found to be involved in the metastasis and progression of tumors. Both PLOD2 and PLOD3 had been reported to be highly expressed in gliomas, while the prognostic value of PLOD1 remains to be further illustrated, so we want to investigate the PLOD1 expression in glioma and its clinical implication. Methods We collected gene expression and corresponding clinical data of glioma from the Chinese Glioma Genome Atlas (CGGA) database, The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. First, we analyzed the expression and mutation of PLOD1 in gliomas and its relationship with clinicopathologic characteristics. Then, we conducted survival analysis, prognostic analysis and nomogram construction of the PLOD1 gene. Finally, we conducted gene ontology (GO) enrichment analysis and gene set enrichment analysis (GSEA) to explore possible mechanisms and gene co-expression analysis was also be performed. Results The results showed that the expression level of PLOD1 was higher in gliomas than normal tissues, and high expression of PLOD1 was related to poor survival which can serve as an oncogenic factor and an independent prognostic indicator for glioma patients. Both the GO and GSEA analysis showed high expression of PLOD1 were enriched in Extracellular matrix (ECM) related pathways, the co-expression analysis revealed that PLOD1 was positively related to HSPG2, COL6A2, COL4A2, FN1, COL1A1, COL4A1, CD44, COL3A1, COL1A2 and SPP1, and high expression of these genes were also correlated to poor prognosis of glioma. Conclusions The results showed that high expression of PLOD1 leads to poor prognosis, and PLOD1 is an independent prognostic factor and a novel biomarker for the treatment of glioma. Furthermore, targeting PLOD1 is most likely a potential therapeutic strategy for glioma patients.

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Section: Introductionmentioning

confidence: 99%

The relationship between PLOD1 expression level and glioma prognosis investigated using public databases

Tian

Zhou

Wang

et al. 2021

PeerJ

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“…The PTEN gene is known as the tumor suppressor gene, while PTEN mutation can decrease the inhibition of tumorigenesis. In a previous investigation, a patient with LGG recurrence suffered a poor prognosis ( Liu et al, 2020 ). Thus, early treatment may be helpful for precise therapy in LGG patients harboring the PTEN mutation.…”

Section: Resultsmentioning

confidence: 95%

Phosphatase and Tensin Homolog Mutation in Immune Cell Infiltration and Clinicopathological Features of Low-Grade Gliomas

Peng

et al. 2020

Front. Mol. Biosci.

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The mutation of phosphatase and tensin homolog (PTEN) genes frequently occur in low-grade gliomas (LGGs) and are deeply associated with a poor prognosis and survival rate. In order to identify the crucial signaling pathways and genes associated with the PTEN mutation, we performed bioinformatics analysis on the RNA sequencing results, which were obtained from The Cancer Genome Atlas database. A total of 352 genes were identified as differentially expressed genes (DEGs). The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggested that the DEGs were significantly enriched in categories associated with cell division and multiple metabolic progressions. The histological stage was significantly associated with PTEN expression levels. In addition, the PTEN mutation was associated with an abundance of B cells, neutrophils, macrophages, dendritic cells, and CD8+ T cells during tumor infiltration. The results showed that patients with LGGs harboring the PTEN mutation had a poor prognosis and more serious immune cell infiltration occurred depending on the mRNA expression level. These results demonstrated that multiple genes and signaling pathways play a key role in LGG from low grade to high grade, and are associated with PTEN mutations. In this study, we outlined an approach to assess the influence of PTEN mutations on prognosis, overall survival, and messenger RNA (mRNA) expression. Our results provided alternative strategies for the personalized treatment of patients with LGGs harboring the PTEN mutation.

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“…Some of these lncRNAs are reported to take part in regulating tumor immune response. RP5-1119A7.17 is negatively associated with histone 1 ( HIST1 )/histone H2B type 1-K ( H2BK ), which are involved in immune response and cell growth in low-grade glioma [ 51 ]. The immunosuppression of CD39 + Tregs relies on a distinct transcriptional program with a low level of neurofilament light ( NEFL ) [ 52 ].…”

Section: Discussionmentioning

confidence: 99%

Construction of a Prognostic Gene Signature Associated with Immune Infiltration in Glioma: A Comprehensive Analysis Based on the CGGA

Gong

Liu

Xiong

et al. 2021

Journal of Oncology

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Background. Tumor microenvironment (TME) is closely related to the progression of glioma and the therapeutic effect of drugs on this cancer. The aim of this study was to develop a signature associated with the tumor immune microenvironment using machine learning. Methods. We downloaded the transcriptomic and clinical data of glioma patients from the Chinese Glioma Genome Atlas (CGGA) databases (mRNAseq_693). The single-sample Gene Set Enrichment Analysis (ssGSEA) database was used to quantify the relative abundance of immune cells. We divided patients into two different infiltration groups via unsupervised clustering analysis of immune cells and then selected differentially expressed genes (DEGs) between the two groups. Survival-related genes were determined using Cox regression analysis. We next randomly divided patients into a training set and a testing set at a ratio of 7 : 3. By integrating the DEGs into least absolute shrinkage and selection operator (LASSO) regression analysis in the training set, we were able to construct a 15-gene signature, which was validated in the testing and total sets. We further validated the signature in the mRNAseq_325 dataset of CGGA. Results. We identified 74 DEGs associated with tumor immune infiltration, 70 of which were significantly associated with overall survival (OS). An immune-related gene signature was established, consisting of 15 key genes: adenosine triphosphate (ATP)-binding cassette subfamily C member 3 (ABCC3), collagen type IV alpha 1 chain (COL4A1), podoplanin (PDPN), annexin A1 (ANXA1), COL4A2, insulin-like growth factor binding protein 2 (IGFBP2), serpin family A member 3 (SERPINA3), CXXC-type zinc finger protein 11 (CXXC11), junctophilin 3 (JPH3), secretogranin III (SCG3), secreted protein acidic and rich in cysteine (SPARC)-related modular calcium-binding protein 1 (SMOC1), Cluster of Differentiation 14 (CD14), COL1A1, S100 calcium-binding protein A4 (S100A4), and transforming growth factor beta 1 (TGF-β1). The OS of patients in the high-risk group was worse than that of patients in the low-risk group. GSEA showed that interleukin-6 (IL-6)/Janus kinase (JAK)/signal transducer and activator of transcription (STAT3) signaling, interferon gamma (IFN-γ) response, angiogenesis, and coagulation were more highly enriched in the high-risk group and that oxidative phosphorylation was more highly enriched in the low-risk group. Conclusion. We constructed a stable gene signature associated with immune infiltration to predict the survival rates of glioma patients.

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High Levels of HIST1H2BK in Low-Grade Glioma Predicts Poor Prognosis: A Study Using CGGA and TCGA Data

Cited by 31 publications

References 42 publications

The relationship between PLOD1 expression level and glioma prognosis investigated using public databases

The relationship between PLOD1 expression level and glioma prognosis investigated using public databases

Phosphatase and Tensin Homolog Mutation in Immune Cell Infiltration and Clinicopathological Features of Low-Grade Gliomas

Construction of a Prognostic Gene Signature Associated with Immune Infiltration in Glioma: A Comprehensive Analysis Based on the CGGA

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