Development of an Immune-Related LncRNA Prognostic Signature for Glioma

Cao, Yudong; Zhu, Hecheng; Tan, Jun; Wu, Yin; Zhou, Quanwei; Xin, Zhaoqi; Wu, Zhaoping; Jiang, Zhipeng; Guo, Youwei; Kuang, Yirui; Li, Can; Zhao, Ming; Jiang, Xingjun; Peng, Jian; Ren, Chao

doi:10.3389/fgene.2021.678436

Cited by 11 publications

(10 citation statements)

References 48 publications

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“…Some other SE-lncRNAs, including CCAT1, LINC00152, and NEAT1, may also facilitate the malignant phenotype of gliomas [39]. Recently, researchers have developed some lncRNA signatures that have shown predictive effects in the prognosis and treatment of glioma patients, including the pyroptosis-related lncRNA signature [40] and immune-related lncRNA signature [41]. Herein, we explored the predictive value of SE-lncRNAs in glioma prognosis and treatment.…”

Section: Discussionmentioning

confidence: 99%

Integrative analysis of a novel super-enhancer-associated lncRNA prognostic signature and identifying LINC00945 in aggravating glioma progression

Yang

Zheng

et al. 2023

Hum Genomics

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Background Super-enhancers (SEs), driving high-level expression of genes with tumor-promoting functions, have been investigated recently. However, the roles of super-enhancer-associated lncRNAs (SE-lncRNAs) in tumors remain undetermined, especially in gliomas. We here established a SE-lncRNAs expression-based prognostic signature to choose the effective treatment of glioma and identify a novel therapeutic target. Methods Combined analysis of RNA sequencing (RNA-seq) data and ChIP sequencing (ChIP-seq) data of glioma patient-derived glioma stem cells (GSCs) screened SE-lncRNAs. Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets served to construct and validate SE-lncRNA prognostic signature. The immune profiles and potential immuno- and chemotherapies response prediction value of the signature were also explored. Moreover, we verified the epigenetic activation mechanism of LINC00945 via the ChIP assay, and its effect on glioma was determined by performing the functional assay and a mouse xenograft model. Results 6 SE-lncRNAs were obtained and identified three subgroups of glioma patients with different prognostic and clinical features. A risk signature was further constructed and demonstrated to be an independent prognostic factor. The high-risk group exhibited an immunosuppressive microenvironment and was higher enrichment of M2 macrophage, regulatory T cells (Tregs), and Cancer-associated fibroblasts (CAFs). Patients in the high-risk group were better candidates for immunotherapy and chemotherapeutics. The SE of LINC00945 was further verified via ChIP assay. Mechanistically, BRD4 may mediate epigenetic activation of LINC00945. Additionally, overexpression of LINC00945 promoted glioma cell proliferation, EMT, migration, and invasion in vitro and xenograft tumor formation in vivo. Conclusion Our study constructed the first prognostic SE-lncRNA signature with the ability to optimize the choice of patients receiving immuno- and chemotherapies and provided a potential therapeutic target for glioma.

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Section: Discussionmentioning

confidence: 99%

Integrative analysis of a novel super-enhancer-associated lncRNA prognostic signature and identifying LINC00945 in aggravating glioma progression

Yang

Zheng

et al. 2023

Hum Genomics

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“…The risk score in the model was calculated by the following formula: riskScore = ∑ x =1 n (coef mRNA × Expr mRNA). The risk score for each sample was calculated using this formula, and the low- and high-risk groups were divided by the median [ 25 ]. Through “survival” and “timeROC” package in R, the Kaplan-Meir (K-M) survival curve and ROC curve were, respectively, plotted to determine the efficacy of the model.…”

Section: Methodsmentioning

confidence: 99%

Prognostic Model and Immune Infiltration of Ferroptosis Subcluster-Related Modular Genes in Gastric Cancer

Deng

Lin

Gan

et al. 2022

Journal of Oncology

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Background. Gastric cancer (GC) is one of the gastrointestinal tumors with the highest mortality rate. The number of GC patients is still high. As a way of iron-dependent programmed cell death, ferroptosis activates lipid peroxidation and accumulates large reactive oxygen species. The role of ferroptosis in GC prognosis was underrepresented. The objective was to investigate the role of ferroptosis-related genes (FRGs) in the prognosis and development of GC. Methods. Datasets of GC patients were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database that include clinical information and RNA seq data. Through nonnegative matrix factorization (NMF) clustering, we identified and unsupervised cluster analysis of the expression matrix of FRGs. And we constructed the co-expression network between genes and clinical characteristics by consensus weighted gene co-expression network analysis (WGCNA). The prognostic model was constructed by univariate and multivariate regression analysis. The potential mechanisms of development and prognosis in GC were explored by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, gene ontology (GO), tumor immune microenvironment (TIME), and tumor mutation burden (TMB). Results. Two molecular subclusters with different expression patterns of FRGs were identified, which have significantly different survival states. Ferroptosis subcluster-related modular genes were identified by WGCNA. Based on 8 ferroptosis subcluster-related modular genes (collagen triple helix repeat containing 1 (CTHRC1), podoplanin (PDPN), procollagen-lysine,2-oxoglutarate 5-dioxygenase 2 (PLOD2), glutamine-fructose-6-phosphate transaminase 2 (GFPT2), ATP-binding cassette subfamily A member 1 (ABCA1), G protein-coupled receptor 176 (GPR176), serpin family E member 1 (SERPINE1), dual specificity phosphatase 1 (DUSP1)) and clinicopathological features, a nomogram was constructed and validated for their predictive efficiency on GC prognosis. Through receiver operating characteristic (ROC) analysis, the results showed that the area under the curve (AUC) of 1-, 3-, and 5-year survival were 0.721, 0.747, and 0.803, respectively, indicating that the risk-scoring model we constructed had good prognosis efficacy in GC. The degree of immune infiltration in high-risk group was largely higher than low-risk group. It indicated that the immune cells have a good response in high-risk group of GC. The TMB of high-risk group was higher, which could generate more mutations and was more conducive to the body’s resistance to the development of cancer. Conclusion. The risk-scoring model based on 8 ferroptosis subcluster-related modular genes has shown outstanding advantages in predicting patient prognosis. The interaction of ferroptosis in GC development may provide new insights into exploring molecular mechanisms and targeted therapies for GC patients.

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“…LncRNA HAR1A is explicitly expressed in Cajal–Retzius cells (CRs), which are well-known for controlling nerve cell migration during brain development, suggesting that HAR1A is important in brain development ( Cao et al, 2021 ; Lee et al, 2021 ). In addition, the expression of lncRNA HAR1A affects the occurrence and development of many brain diseases, including Huntington’s disease and glioma ( Chen et al, 2018 ; Wei et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Effects of HAR1 on cognitive function in mice and the regulatory network of HAR1 determined by RNA sequencing and applied bioinformatics analysis

Zhang

Lin²,

Huang³

et al. 2023

Front. Genet.

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Background:HAR1 is a 118-bp segment that lies in a pair of novel non-coding RNA genes. It shows a dramatic accelerated change with an estimated 18 substitutions in the human lineage since the human–chimpanzee ancestor, compared with the expected 0.27 substitutions based on the slow rate of change in this region in other amniotes. Mutations of HAR1 lead to a different HAR1 secondary structure in humans compared to that in chimpanzees.Methods: We cloned HAR1 into the EF-1α promoter vector to generate transgenic mice. Morris water maze tests and step-down passive avoidance tests were conducted to observe the changes in memory and cognitive abilities of mice. RNA-seq analysis was performed to identify differentially expressed genes (DEGs) between the experimental and control groups. Systematic bioinformatics analysis was used to confirm the pathways and functions that the DEGs were involved in.Results: Memory and cognitive abilities of the transgenic mice were significantly improved. The results of Gene Ontology (GO) analysis showed that Neuron differentiation, Dentate gyrus development, Nervous system development, Cerebral cortex neuron differentiation, Cerebral cortex development, Cerebral cortex development and Neurogenesis are all significant GO terms related to brain development. The DEGs enriched in these terms included Lhx2, Emx2, Foxg1, Nr2e1 and Emx1. All these genes play an important role in regulating the functioning of Cajal–Retzius cells (CRs). The DEGs were also enriched in glutamatergic synapses, synapses, memory, and the positive regulation of long-term synaptic potentiation. In addition, “cellular response to calcium ions” exhibited the second highest rich factor in the GO analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the DEGs showed that the neuroactive ligand–receptor interaction pathway was the most significantly enriched pathway, and DEGs also notably enriched in neuroactive ligand–receptor interaction, axon guidance, and cholinergic synapses.Conclusion:HAR1 overexpression led to improvements in memory and cognitive abilities of the transgenic mice. The possible mechanism for this was that the long non-coding RNA (lncRNA) HAR1A affected brain development by regulating the function of CRs. Moreover, HAR1A may be involved in ligand–receptor interaction, axon guidance, and synapse formation, all of which are important in brain development and evolution. Furthermore, cellular response to calcium may play an important role in those processes.

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Development of an Immune-Related LncRNA Prognostic Signature for Glioma

Cited by 11 publications

References 48 publications

Integrative analysis of a novel super-enhancer-associated lncRNA prognostic signature and identifying LINC00945 in aggravating glioma progression

Integrative analysis of a novel super-enhancer-associated lncRNA prognostic signature and identifying LINC00945 in aggravating glioma progression

Prognostic Model and Immune Infiltration of Ferroptosis Subcluster-Related Modular Genes in Gastric Cancer

Effects of HAR1 on cognitive function in mice and the regulatory network of HAR1 determined by RNA sequencing and applied bioinformatics analysis

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