scholarly journals The Genetic and Epigenetic Mechanisms Involved in Irreversible Pulp Neural Inflammation

2021 ◽  
Vol 2021 ◽  
pp. 1-26
Author(s):  
Xiaoxi Xi ◽  
Yihong Ma ◽  
Yuzhen Xu ◽  
Anthony Chukwunonso Ogbuehi ◽  
Xiangqiong Liu ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Noncoding Rna ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Epigenetic Mechanisms ◽  
Cerna Network ◽  
Epigenetic Biomarkers ◽  
Irreversible Pulpitis

Aim. To identify the critical genetic and epigenetic biomarkers by constructing the long noncoding RNA- (lncRNA-) related competing endogenous RNA (ceRNA) network involved in irreversible pulp neural inflammation (pulpitis). Materials and Methods. The public datasets regarding irreversible pulpitis were downloaded from the gene expression omnibus (GEO) database. The differential expression analysis was performed to identify the differentially expressed genes (DEGs) and DElncRNAs. Functional enrichment analysis was performed to explore the biological processes and signaling pathways enriched by DEGs. By performing a weighted gene coexpression network analysis (WGCNA), the significant gene modules in each dataset were identified. Most importantly, DElncRNA-DEmRNA regulatory network and DElncRNA-associated ceRNA network were constructed. A transcription factor- (TF-) DEmRNA network was built to identify the critical TFs involved in pulpitis. Result. Two datasets (GSE92681 and GSE77459) were selected for analysis. DEGs involved in pulpitis were significantly enriched in seven signaling pathways (i.e., NOD-like receptor (NLR), Toll-like receptor (TLR), NF-kappa B, tumor necrosis factor (TNF), cell adhesion molecules (CAMs), chemokine, and cytokine-cytokine receptor interaction pathways). The ceRNA regulatory relationships were established consisting of three genes (i.e., LCP1, EZH2, and NR4A1), five miRNAs (i.e., miR-340-5p, miR-4731-5p, miR-27a-3p, miR-34a-5p, and miR-766-5p), and three lncRNAs (i.e., XIST, MIR155HG, and LINC00630). Six transcription factors (i.e., GATA2, ETS1, FOXP3, STAT1, FOS, and JUN) were identified to play pivotal roles in pulpitis. Conclusion. This paper demonstrates the genetic and epigenetic mechanisms of irreversible pulpitis by revealing the ceRNA network. The biomarkers identified could provide research direction for the application of genetically modified stem cells in endodontic regeneration.

scholarly journals Small Nucleolar RNA and Small Nucleolar RNA Host Gene Signatures as Biomarkers for Pancreatic Cancer

2020 ◽  
Author(s):  
Shuwen Han ◽  
Yangyang Xie ◽  
Xi Yang ◽  
Siqi Dai ◽  
Xiaoyu Dai
Keyword(s):  
Pancreatic Cancer ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Small Nucleolar Rna ◽  
Cerna Network ◽  
Tcga Dataset ◽  
Nucleolar Rna ◽  
Host Genes

Abstract Objective: The objective of this study was to identify key molecules including small nucleolar RNAs (snoRNAs) and small nucleolar RNA host genes (SNHGs) involved in pancreatic cancer.Methods: First, we screened the differentially expressed snoRNAs (DEsnoRNAs) and trend-related snoRNAs based on the cancer genome atlas (TCGA) dataset for pancreatic cancer, and then performed methylation correlation analysis, survival analysis, and extraction of snoRNA host genes for Gene ontology (GO) functional and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Next, DESNHGs and trend-related SNHGs were screened according to the TCGA dataset for pancreatic cancer, and a competing endogenous RNA (ceRNA) network was constructed for pathway and functional enrichment analysis. Results: A total of eight DEsnoRNAs and 93 trend-related snoRNAs were extracted. Then, ten host genes of the snoRNAs were identified. Functional analysis suggested that the ten host genes were significantly enriched in several GO terms including mitotic chromosome condensation and endocytosis pathway. SNORA38B was considered to associate with survival and prognosis. The SNORD17 and SNORA11 were considered to negatively correlate with methylation. In addition, two trend-related SNHGs were extracted. Additionally, a ceRNA network was constructed with 11 miRNAs, one lncRNAs, and one mRNA. SNHG24 mainly correlated with GnRH secretion and neuroactive ligand-receptor interaction in pancreatic cancer. Conclusion: The identified snoRNAs and SNHGs could serve as potential markers for the early detection of pancreatic cancer.

Construction of Long Noncoding RNA-Associated ceRNA Networks Reveals Potential Biomarkers in Alzheimer’s Disease

2021 ◽  
pp. 1-15
Author(s):  
Guan-yong Ou ◽  
Wen-wen Lin ◽  
Wei-jiang Zhao
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Noncoding Rna ◽  
Regulatory Networks ◽  
Enrichment Analysis ◽  
Brain Regions ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Potential Biomarkers

Background: Alzheimer’s disease (AD) is a chronic neurodegenerative disease that seriously impairs both cognitive and memory functions mainly in the elderly, and its incidence increases with age. Recent studies demonstrated that long noncoding RNAs (lncRNAs) play important roles in AD by acting as competing endogenous RNAs (ceRNAs). Objective: In this study, we aimed to construct lncRNA-associated ceRNA regulatory networks composed of potential biomarkers in AD based on the ceRNA hypothesis. Methods: A total of 20 genes (10 upregulated genes and 10 downregulated genes) were identified as the hub differentially expressed genes (DEGs). The functional enrichment analysis showed that the most significant pathways of DEGs involved include retrograde endocannabinoid signaling, synaptic vesicle circle, and AD. The upregulated hub genes were mainly enriched in the cytokine-cytokine receptor interaction pathway, whereas downregulated hub genes were involved in the neuroactive ligand-receptor interaction pathway. After convergent functional genomic (CFG) ranks and expression level analysis in different brain regions of hub genes, we found that CXCR4, GFAP, and GNG3 were significantly correlated with AD. We further identified crucial miRNAs and lncRNAs of targeted genes to construct lncRNA-associated ceRNA regulatory networks. Results: The results showed that two lncRNAs (NEAT1, MIAT), three miRNAs (hsa-miR-551a, hsa-miR-133b and hsa-miR-206), and two mRNA (CXCR4 and GNG3), which are highly related to AD, were preliminarily identified as potential AD biomarkers. Conclusion: Our study provides new insights for understanding the pathogenic mechanism underlying AD, which may potentially contribute to the ceRNA mechanism in AD.

scholarly journals Identification of An Epithelial-Mesenchymal Transition-Related lncRNA Prognostic Signature For Patients With Glioblastoma

2021 ◽  
Author(s):  
XinJie Yang ◽  
Sha Niu ◽  
JiaQiang Liu ◽  
ZeYu Wu ◽  
Shizhang Ling ◽  
...  
Keyword(s):  
High Risk ◽  
Signaling Pathways ◽  
Epithelial Mesenchymal Transition ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Prognostic Signature ◽  
Mesenchymal Transition ◽  
Underlying Mechanisms

Abstract Purpose: Glioblastoma (GBM) is a class of strikingly heterogeneous and lethal brain tumor with very poor prognosis. LncRNAs play critical roles in the tumorigenesis and progression of GBM through regulation of various cancer-related genes and signaling pathways. Here, we aimed to establish an epithelial-mesenchymal transition (EMT)-related lncRNA signature for GBM and explore its underlying mechanisms. Methods: Differential expression analysis and Gene set enrichment analysis (GSEA) were performed to explore key genes and signaling pathways associated with GBM. Spearman correlation analysis, Univariate and multivariate Cox regression analyses were used to construct a lncRNA prognostic signature for GBM patients. Kaplan-Meier analysis and receiver-operating-characteristic (ROC) analysis were applied to assess the performance of the prognostic signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) enrichment analyses were performed to explore the underlying mechanisms of the signature. Single-sample GSEA (ssGSEA) was employed to explore the relationship of the signature and immune activities in GBM.Results: We focused on the essential role of EMT in GBM and identified 78 upregulated EMT-related genes in GBM. A total of 301 EMT-related lncRNAs were confirmed in GBM and a prognostic signature consisting of seven EMT-related lncRNAs (AC012615.1, H19, LINC00609, LINC00634, POM121L9P, SNHG11, and USP32P3) was established, which could divide GBM patients into low- and high-risk subgroups. The accuracy and efficiency of the signature were validated to be satisfactory. Functional enrichment analysis revealed multiple EMT and metastasis-related pathways were associated with the EMT-related lncRNA prognostic signature. In addition, we found the degree of immune cell infiltration and immune responses were significantly increased in high-risk subgroup compared with low-risk subgroup. Conclusion: we established an effective and robust EMT-related lncRNA signature which is expected to predict the prognosis and immunotherapy response for GBM patients.

scholarly journals Identification of Impacted Pathways and Transcriptomic Markers as Potential Mediators of Pulmonary Fibrosis in Transgenic Mice Expressing Human IGFBP5

2021 ◽  
Vol 22 (22) ◽  
pp. 12609
Author(s):  
Xinh-Xinh Nguyen ◽  
Ludivine Renaud ◽  
Carol Feghali-Bostwick
Keyword(s):  
Pulmonary Fibrosis ◽  
Transgenic Mice ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Lung Fibroblasts ◽  
Receptor Interaction ◽  
Receptor Interactions ◽  
Serious Disease

Pulmonary fibrosis is a serious disease characterized by extracellular matrix (ECM) component overproduction and remodeling. Insulin-like growth factor-binding protein 5 (IGFBP5) is a conserved member of the IGFBP family of proteins that is overexpressed in fibrotic tissues and promotes fibrosis. We used RNA sequencing (RNAseq) to identify differentially expressed genes (DEGs) between primary lung fibroblasts (pFBs) of homozygous (HOMO) transgenic mice expressing human IGFBP5 (hIGFBP5) and wild type mice (WT). The results of the differential expression analysis showed 2819 DEGs in hIGFBP5 pFBs. Functional enrichment analysis confirmed the pro-fibrotic character of IGFBP5 and revealed its impact on fundamental signaling pathways, including cytokine–cytokine receptor interaction, focal adhesion, AGE-RAGE signaling, calcium signaling, and neuroactive ligand-receptor interactions, to name a few. Noticeably, 7% of the DEGs in hIGFBP5-expressing pFBs are receptors and integrins. Furthermore, hub gene analysis revealed 12 hub genes including Fpr1, Bdkrb2, Mchr1, Nmur1, Cnr2, P2ry14, and Ptger3. Validation assays were performed to complement the RNAseq data. They confirmed significant differences in the levels of the corresponding proteins in cultured pFBs. Our study provides new insights into the molecular mechanism(s) of IGFBP5-associated pulmonary fibrosis through possible receptor interactions that drive fibrosis and tissue remodeling.

scholarly journals Integrated analysis of ceRNA network in lung adenocarcinoma based on bioinformatics analysis

2021 ◽  
Author(s):  
Huixin Wang ◽  
Qian Li ◽  
Xiaowen Hou ◽  
Xinzhu Shi ◽  
Xu Feng
Keyword(s):  
Cell Proliferation ◽  
Lung Adenocarcinoma ◽  
Signaling Pathways ◽  
Noncoding Rna ◽  
Gene Knockout ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Integrated Analysis ◽  
Invasion And Migration ◽  
Cerna Network

Abstract Background Increasing studies have revealed that long noncoding RNA (lncRNAs) can bind to microRNA (miRNAs) as competitive endogenous RNA (ceRNA), which can affect the expression of mRNAs. These lncRNA related ceRNAs theoretically play an important role in the occurrence and progress of cancer. However, the roles and functions of ceRNA network in lung adenocarcinoma (LUAD) are not completely clear. Methods 1. The chip data were downloaded from the Gene Expression Omnibus (GEO). Different lncRNAs and mRNAs were analyzed by GEO2R, and then the target miRNAs and target mRNAs were predicted. The ceRNA network was constructed and subjected to enrichment analysis. 2. The lncRNA AFAP1-AS1 gene Knockout was constructed. The siRNA was constructed and transfected into LUAD cell A549 by cell transfection. The CCK8, Transwell, scratch assay and flow cytometry were used to gauging the ability of cell proliferation, invasion, migration, and apoptosis. Results In total, 6 lncRNAs and 494 mRNAs were identified as differentially expressed RNAs (DERNAs) in LUAD. A total of 6 DElncRNAs interacted with 22 DEmiRNAs and 22 DEmiRNAs interacted with 55 DEmRNAs were involved in the ceRNA network. These DEmRNAs were found to be related to cancer-related pathways, such as signaling pathways that regulate stem cell pluripotency, TGF-β signaling pathways, and protein digestion and absorption. Knockout of AFAP1-AS1 inhibits cell proliferation, invasion and migration. AFAP1-AS1 promotes apoptosis. Conclusions In this study, we constructed a lncRNA-miRNA-mRNA ceRNA network which may help further research on the mechanism of LUAD. In addition, we identified AFAP1-AS1 as an oncogenic lncRNA in LUAD.

scholarly journals Construction of a Competing Endogenous RNA Network and Identification of Potential Regulatory Axes in Gastric Cancer Chemoresistance

2021 ◽  
Author(s):  
Xian-Zi Yang ◽  
Lei Ma ◽  
Shu-Xian Fang ◽  
Ye Song ◽  
Si-Yu Zhu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cell Line ◽  
Cisplatin Resistance ◽  
Differential Expression Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Continuous Exposure ◽  
Hippo Signaling ◽  
Cerna Network

Abstract Background: The development of chemoresistance is one of the leading causes of chemotherapy failure in gastric cancer (GC). Emerging evidence highlights the multifunctional role of noncoding RNAs (ncRNAs) in GC chemoresistance. However, the comprehensive expression profile and competing endogenous RNAs (ceRNAs) regulatory network between ncRNAs and mRNAs in GC chemoresistance remain unanswered.Methods: GC cell line MGC-803 was employed to create cisplatin-resistant MGC-803/DDP cells by continuous exposure to increasing doses of cisplatin. The whole-transcriptome sequencing (RNA sequencing) was performed to comprehensively analyze the differentially expressed (DE) lncRNAs, miRNAs and mRNAs in MGC-803/DDP and MGC-803 cells. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to investigate the biological functions implicated with the DEncRNAs. Then, the cisplatin-resistant-related ceRNA network and potential regulatory axes were constructed by bioinformatic analysis.Results: We successfully generated cisplatin-resistant GC cell line MGC-803/DDP. Differential expression analysis showed that a total of 1,936 DElncRNAs, 2,194 DEmRNAs and 174 DEmiRNAs were identified. Functional enrichment analysis indicated that those DEncRNAs were mainly involved in neuroactive ligand-receptor interaction, drug metabolism, Hippo signaling pathway, cAMP pathway and P53 pathway. Subsequently, the cisplatin-resistant-related ceRNA network consisting of 71 DElncRNAs, 121 DEmRNAs and 8 DEmiRNAs was constructed with the widely accepted vital chemo-resistant-related genes and signaling pathways. In addition, two constructed regulatory axes (include FAM66C/miR-129-5p/7 mRNAs and SFTA1P/miR-206/FN1 or NRP1) were successfully validated by the Genomic Data Commons (GDC) GC data.Conclusion: Our study has shown that differentially expressed ncRNAs have complex and intricate interactions in the cisplatin resistance of GC. The novel ceRNA network and the potential regulatory axes may provide the most comprehensive view of GC chemoresistance to date. Our findings uncovered potential biomarkers for prognostic prediction and novel therapeutic targets for reversing cisplatin resistance in GC.

scholarly journals Construction and analysis for dys-regulated lncRNAs and mRNAs in LPS-induced porcine PBMCs

2021 ◽  
Vol 27 (2) ◽  
pp. 170-183
Author(s):  
Jing Zhang ◽  
Xin Xu ◽  
Hongbo Chen ◽  
Ping Kang ◽  
Huiling Zhu ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Function Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Lps Challenge ◽  
Tnf Α ◽  
Non Coding Rnas ◽  
And Function

Long non-coding RNAs (lncRNAs) are emerging as key regulators in inflammation. However, their functions and profiles in LPS-induced inflammation in pigs are largely unknown. In this study, we profiled global lncRNA and mRNA expression changes in PBMCs treated with LPS using the lncRNA-seq technique. In total 43 differentially expressed (DE) lncRNAs and 1082 DE mRNAs were identified in porcine PBMCs after LPS stimulation. Functional enrichment analysis on DE mRNAs indicated these genes were involved in inflammation-related signaling pathways, including cytokine–cytokine receptor interaction, TNF-α, NF-κB, Jak-STAT and TLR signaling pathways. In addition, co-expression network and function analysis identified the potential lncRNAs related to inflammatory response and immune response. The expressions of eight lncRNAs (ENSSSCT00000045208, ENSSSCT00000051636, ENSSSCT00000049770, ENSSSCT00000050966, ENSSSCT00000047491, ENSSSCT00000049750, ENSSSCT00000054262 and ENSSSCT00000044651) were validated in the LPS-treated PBMCs by quantitative real-time PCR (qRT-PCR). In LPS-challenged piglets, we identified that expression of three lncRNAs (ENSSSCT00000051636, ENSSSCT00000049770, and ENSSSCT00000047491) was significantly up-regulated in liver, spleen and jejunum tissues after LPS challenge, which indicated that these lncRNAs might be important regulators for inflammation. This study provides the first lncRNA and mRNA transcriptomic landscape of LPS-mediated changes in porcine PBMCs, which might provide potential insights into lncRNAs involved in regulating inflammation in pigs.

Identification of Candidate Genetic Markers and a Novel 4-genes Diagnostic Model in Osteoarthritis through Integrating Multiple Microarray Data

2020 ◽  
Vol 23 (8) ◽  
pp. 805-813
Author(s):  
Ai Jiang ◽  
Peng Xu ◽  
Zhenda Zhao ◽  
Qizhao Tan ◽  
Shang Sun ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Microarray Data ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Functional Enrichment ◽  
Joint Disease ◽  
Support Vector ◽  
Diagnostic Model ◽  
Data Sets

Background: Osteoarthritis (OA) is a joint disease that leads to a high disability rate and a low quality of life. With the development of modern molecular biology techniques, some key genes and diagnostic markers have been reported. However, the etiology and pathogenesis of OA are still unknown. Objective: To develop a gene signature in OA. Method: In this study, five microarray data sets were integrated to conduct a comprehensive network and pathway analysis of the biological functions of OA related genes, which can provide valuable information and further explore the etiology and pathogenesis of OA. Results and Discussion: Differential expression analysis identified 180 genes with significantly expressed expression in OA. Functional enrichment analysis showed that the up-regulated genes were associated with rheumatoid arthritis (p < 0.01). Down-regulated genes regulate the biological processes of negative regulation of kinase activity and some signaling pathways such as MAPK signaling pathway (p < 0.001) and IL-17 signaling pathway (p < 0.001). In addition, the OA specific protein-protein interaction (PPI) network was constructed based on the differentially expressed genes. The analysis of network topological attributes showed that differentially upregulated VEGFA, MYC, ATF3 and JUN genes were hub genes of the network, which may influence the occurrence and development of OA through regulating cell cycle or apoptosis, and were potential biomarkers of OA. Finally, the support vector machine (SVM) method was used to establish the diagnosis model of OA, which not only had excellent predictive power in internal and external data sets (AUC > 0.9), but also had high predictive performance in different chip platforms (AUC > 0.9) and also had effective ability in blood samples (AUC > 0.8). Conclusion: The 4-genes diagnostic model may be of great help to the early diagnosis and prediction of OA.

scholarly journals AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1037.2-1038
Author(s):  
X. Sun ◽  
S. X. Zhang ◽  
S. Song ◽  
T. Kong ◽  
C. Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Shanxi Province ◽  
Receptor Interaction ◽  
Term Therapy ◽  
Pathway Enrichment Analysis ◽  
Key Genes

Background:Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.Objectives:To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.Methods:Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.Results:A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.Conclusion:DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.References:[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

scholarly journals An epithelial–mesenchymal transition-related long noncoding RNA signature correlates with the prognosis and progression in patients with bladder cancer

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Hang Tong ◽  
Tinghao Li ◽  
Shun Gao ◽  
Hubin Yin ◽  
Honghao Cao ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Epithelial Mesenchymal Transition ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Risk Groups ◽  
Functional Enrichment ◽  
Diagnostic Efficacy ◽  
Mesenchymal Transition

Abstract Bladder cancer is a common malignant tumour worldwide. Epithelial–mesenchymal transition (EMT)-related biomarkers can be used for early diagnosis and prognosis of cancer patients. To explore, accurate prediction models are essential to the diagnosis and treatment for bladder cancer. In the present study, an EMT-related long noncoding RNA (lncRNA) model was developed to predict the prognosis of patients with bladder cancer. Firstly, the EMT-related lncRNAs were identified by Pearson correlation analysis, and a prognostic EMT-related lncRNA signature was constructed through univariate and multivariate Cox regression analyses. Then, the diagnostic efficacy and the clinically predictive capacity of the signature were assessed. Finally, Gene set enrichment analysis (GSEA) and functional enrichment analysis were carried out with bioinformatics. An EMT-related lncRNA signature consisting of TTC28-AS1, LINC02446, AL662844.4, AC105942.1, AL049840.3, SNHG26, USP30-AS1, PSMB8-AS1, AL031775.1, AC073534.1, U62317.2, C5orf56, AJ271736.1, and AL139385.1 was constructed. The diagnostic efficacy of the signature was evaluated by the time-dependent receiver-operating characteristic (ROC) curves, in which all the values of the area under the ROC (AUC) were more than 0.73. A nomogram established by integrating clinical variables and the risk score confirmed that the signature had a good clinically predict capacity. GSEA analysis revealed that some cancer-related and EMT-related pathways were enriched in high-risk groups, while immune-related pathways were enriched in low-risk groups. Functional enrichment analysis showed that EMT was associated with abundant GO terms or signaling pathways. In short, our research showed that the 14 EMT-related lncRNA signature may predict the prognosis and progression of patients with bladder cancer.

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