Literature DB >> 36217332

Revealing lncRNA Biomarkers Related to Chronic Obstructive Pulmonary Disease Based on Bioinformatics.

Hui Han1, Lu Hao1.   

Abstract

Background: Chronic obstructive pulmonary disease (COPD) is a common chronic disease of the respiratory tract, with high prevalence, high disability, and poor prognosis. However, the molecular mechanism of COPD needs to be further revealed.
Methods: We obtained the gene expression profile and miRNA expression profile of COPD patients from Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmis) in COPD were identified. Subsequently, the COPD-related ceRNA network was constructed based on the interaction between lncRNA, miRNA, and mRNA using the lncACTdb database. Finally, the Cytoscape software was used to analyze the network topology and COPD-related lncRNAs.
Results: Firstly, the 519 DEGs and 17 DEmis were identified from COPD GEO datasets. GO enrichment showed that leukocyte chemotaxis, cell chemotaxis, and myeloid leukocyte migration were upregulated, and muscle and membrane repolarization-related biological progress were downregulated in COPD. KEGG pathway enrichment shows that the p53 pathway was upregulated in COPD. Hallmark enrichment showed that chronic neutrophil inflammation was a sign of the pathogenesis of COPD. Next, a ceRNA network including 93 DEGs, 2 DEmi, 463 lncRNAs, and 1157 DEG-lncRNA, DEmi-lncRNA, and DEmi-DEG interactions were obtained. The hub-lncRNA (the network is ranked in the top 10) as the core marker of COPD, including SNHG12, SLFNL1-AS1, KCNQ1OT1, XIST, EAF1-AS1, FOXD2-AS1, NORAD, PINK1-AS and RP11-69E11.4. And the cytoHubba analysis identified ATM, SMAD7 and HIF1A as hub genes of ceRNA network.
Conclusion: This study provides a landscape of ceRNA network of COPD, which help to reveal the underlying pathophysiological mechanisms of COPD and shed light on novel therapeutic strategies for COPD.
© 2022 Han and Hao.

Entities:  

Keywords:  bioinformatics; chronic obstructive pulmonary disease; lncRNA; miRNA

Mesh：

Substances：

Year:  2022        PMID： 36217332      PMCID： PMC9547624          DOI： 10.2147/COPD.S354634

Source DB:  PubMed          Journal:  Int J Chron Obstruct Pulmon Dis        ISSN： 1176-9106


Introduction

Chronic obstructive pulmonary disease (COPD) is a common chronic bronchitis or emphysema hallmarked by chronic respiratory symptoms and airflow restriction, which can further develop into common chronic diseases of pulmonary heart disease and respiratory failure.1 The prevalence of COPD is increasingly worldwide, which become a great individual and society burden.2 As the COPD is often punctuated by rhinoviruses (RVs), the acute exacerbations frequently lead to morbidity and mortality of these patients.3 Although smoking and aging are the main causes of COPD.4 However, the pathological mechanism of COPD remains limited. The underlying pathophysiological mechanism is urgent for developing new therapies for COPD. The dysregulation of mRNA and miRNA expression was also observed in COPD.5 A microarray of epithelium from COPD survey the TLR family gene expression and revealed that TLR5 is essential for the activation of innate immune responses in COPD. The aging-related genes were also differently expressed in COPD.6 The distinct miRNA profile was also observed in COPD.7 Moreover, the study showed that MicroRNA-218 regulated the overproduction of MUC5AC and inflammation of COPD by targeting TNFR1-mediated NF-κB pathway. Recently, microRNA-21 was reported to mediate COPD pathogenesis by regulating SATB1/S100A9/NF-κB axis.8 Emerging studies showed that the genetic factors are also important determinants of COPD. Long non-coding RNA (lncRNA) is a type of single-stranded non-coding RNA with the length of longer than 200 nucleotides that participate in various biological processes by manipulating gene expression.9 Recently, lncRNAs have been documented to play a key role in diverse biological functions and be involved in various disease including COPD and airway disease.10 A recent study revealed the significant different lncRNA expression profiles in smokers with or without COPD. Moreover, lncRNAs was reported to perform essential functions in the progression of COPD. lncRNA TUG1 was reported to reduce proliferation in COPD by inducing -β.11 Research by Li et al showed that lncRNA MIR155HG regulates/macrophage polarization in COPD.12 Zheng et al found that lncRNA COPDA1 promotes the proliferation of human bronchial smooth muscle cells in COPD.13 As the key regulator of miRNA, lncRNA was reported to regulate the COPD progression by targeting miRNA and mRNA.14,15 However, the landscape of COPD ceRNA network is limited. In this study, we performed differential analysis of genes and miRNA expression profiles in COPD patients to obtain COPD-related genes and miRNAs, and constructed a COPD ceRNA network based on the interaction between genes, miRNAs and lncRNAs in the lncACTdb database. And then Cytoscape was used to perform topological analysis on the ceRNA network, and we obtained 10 lncRNAs as hub nodes, which were expected to become potential therapeutic targets for COPD.

Materials and Methods

Data Collection

We searched the mRNA and miRNA expression profiles of patients with COPD in the Gene Expression Omnibus (GEO) database based on the keywords “COPD”, “Home sapiens”, “mRNA profiles” and “miRNA profiles”. A total of 16 items were identified. Finally, after screening for the presence or absence of normal samples and the source of the samples, 148 samples from the four studies were used for subsequent analysis. The detailed information of the data set is shown in Table 1.
Table 1

Datasets

AccessionExperimentPlatformCOPDNormalMrna/microRNA
GSE38974ArrayGPL7723198microRNA
GSE38974ArrayGPL4133239mRNA
GSE103174ArrayGPL136673716mRNA
GSE135188RNA-seqGPL212901818mRNA
Datasets

Data Preprocessing and Differential Expression Analysis

The original data was downloaded and the R package “limma” was used for analysis. Firstly, the original data was normalized (log2), and then differently expressed genes between COPD and normal samples were analyzed (lmFit and eBay functions) with the threshold used is fold change (log2) cutoff of 1 and p value cutoff of 0.05. Each data set was analyzed separately. Volcano maps and gene expression heat maps were performed by R package “ggplot2 and pheatmap”.

PPI Network Analysis

The protein–protein interaction (PPI) network can help us identify the key genes for the occurrence and development of COPD from the level of interaction. Get the PPI information of DEGs from the Search tool for the retrieval of Interacting Genes (STRING) database ().10 Then, Cytoscape v3.7.0 software was used to analyze the topology of the PPI network in COPD, and the PPI network was constructed.

GO/KEGG Enrichment Analysis

In order to study the biological functions of DEG, the R package ClusterProfiler was used to analyze and visualize the functional map of DEGs (Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway) and the annotative R package (org.Hs.eg.db) was selected as background. P value <0.05 is statistically significant.

Hallmark Feature Enrichment

In order to explore the enrichment of DEG in the biological state and process, the Hallmark gene set was downloaded from the MsigDB database, and the gene set of each pathway in the hallmark and the overlap of DEG were calculated by hypergeometric analysis. The enrichment threshold is P value <0.05.

Construction of ceRNA Network

The lncACTdb 2.0 () database contained the ceRNA interaction relationships from multiple documents. The DEGs and DEmis were submitted to the database, and then the related lncRNA, the interactions between DEGs and lncRNA, DEmi and lncRNA, and DEG and DEmiRNA were obtained. According to the ceRNA theory, the selected DEmi and DEG, DEmi and lncRNA, and DEG and lncRNA were integrated and interacted with each other, and the DEmi-DEG-lncRNA ceRNA network was constructed using Cytoscape v3.7.0 software.

Statistical Analysis

All data were analyzed using R (v 4.0.3). The different expression analysis was performed using R “limma” packages. Student’s t-tests were used to calculate P-values by t.test function. The heatmaps were generated by pheatmap R package (v 1.0.12).

Result

DEG and DEmi Related to COPD Was Screened

Firstly, the 519 DEGs from the mRNA expression between COPD samples and normal samples from three GEO datasets were obtained with a threshold of p value <0.05 and |logFC|>1. Among them, 233 up-regulated DEGs, 240 down-regulated DEGs were identified in the data set GSE38974; 10 up-regulated DEGs and 12 down-regulated DEGs were identified in the data set GSE103174, and 16 up-regulated DEGs and 31 down-regulated DEGs were identified in the data set GSE135188. The DEGs volcano map of the above three datasets are shown in Figure 1A–C, and the heatmap is shown in Figure 1D–F. In the DEG expression heatmap, there was significant heterogeneity between the expression of DEGs in COPD samples and normal samples. Next, we use all 519 DEGs to construct a PPI network in Figure 1G. In the constructed PPI-DEG network, there were a total of 139 DEGs and 166 interaction relationships. Among them, UBD, H2AFX, BAG3, and CDKN1A were key genes in the network of COPD. Zhang et al determined the modular gene markers containing H2AFX by analyzing the protein interaction network as a marker for distinguishing COPD and NSCLC.16 Sun et al identified 40 potential COPD-related genes through bioinformatics analysis and found that HIF1A, CDKN1A, BAG3, ERBB2, and ATG16L1 may affect the development of COPD by regulating autophagy.17
Figure 1

The DEG in COPD samples and normal samples. (A) The volcano plots of DEGs in COPD using GSE38974 dataset. (B) The volcano plots of DEGs in COPD using GSE103174 dataset. (C) The volcano plots of DEGs in COPD using GSE135188 datasets. The upregulated gene were red and the down-regulated genes were blue. The filter parameter of DEGs were |log2 (FC)|> 1 and P <0.05. (D) The heat maps of DEGs in COPD samples and normal samples using GSE38974. (E) The heat maps of DEGs in COPD samples and normal samples in the GSE103174. (F) The heat maps of DEGs in COPD samples and normal samples in the GSE135188 datasets. (G) The network of DEGs in COPD.

The DEG in COPD samples and normal samples. (A) The volcano plots of DEGs in COPD using GSE38974 dataset. (B) The volcano plots of DEGs in COPD using GSE103174 dataset. (C) The volcano plots of DEGs in COPD using GSE135188 datasets. The upregulated gene were red and the down-regulated genes were blue. The filter parameter of DEGs were |log2 (FC)|> 1 and P <0.05. (D) The heat maps of DEGs in COPD samples and normal samples using GSE38974. (E) The heat maps of DEGs in COPD samples and normal samples in the GSE103174. (F) The heat maps of DEGs in COPD samples and normal samples in the GSE135188 datasets. (G) The network of DEGs in COPD. We next selected 17 DEmis from the data set GSE38974 by using the same threshold as that used to obtain DEGs, including 11 up-regulated DEmis and 6 down-regulated DEmis. The volcano map and heatmap of DEmis are shown in Figure 2A and B, respectively.
Figure 2

The differential microRNAs (DEmi) in COPD samples and normal samples. (A) The volcano plots of DEmi obtained from the data set GSE38974 with P <0.05 and |log2 (FC)|> 1. The small diamond presents the microRNAs. (B) The heat map of DEmis of COPD samples and normal samples in the data set GSE38974.

The differential microRNAs (DEmi) in COPD samples and normal samples. (A) The volcano plots of DEmi obtained from the data set GSE38974 with P <0.05 and |log2 (FC)|> 1. The small diamond presents the microRNAs. (B) The heat map of DEmis of COPD samples and normal samples in the data set GSE38974.

Functional Enrichment of DEG in COPD

In order to explore the biological significance of COPD features, all DEGs from GSE38974, GSE103174 and GSE135188 were used for GO/KEGG analysis using the Hallmark gene sets in MSigDB. As shown in Figure 3A, GO enrichment showed that leukocyte chemotaxis, cell chemotaxis and myeloid leukocyte migration were upregulated, and muscle and membrane repolarization-related biological progresses were downregulated in COPD. The cytokine receptor CXCR2 antagonist (MK-7123) reduced the chemotaxis of neutrophils, which may alleviate the airway inflammation of COPD,18 and aerobic training combined with respiratory muscle stretching improved the functional exercise capacity of COPD patients and reduced dyspnea.19 In Figure 3B, KEGG pathway enrichment shows that p53 pathway was upregulated in COPD. The p53 signaling pathway polymorphism was associated with changes in emphysema in COPD patients,20 and compared with non-smokers, healthy smokers and COPD smokers due to the apoptosis of active pulmonary capillary endothelial cells, the level of circulating endothelial cells increased.21 Dinesh et al also revealed the increased apoptotic cell death in airway epithelial cells in COPD.10 We also found in the Hallmark enrichment results of Figure 3C and D that chronic neutrophil inflammation was a sign of the pathogenesis of COPD, which persists after smoking cessation.22 And COPD patients may be particularly vulnerable to hypoxia-induced autonomic disorders.23
Figure 3

The functional enrichment analysis of DEG in COPD. (A) GO_BP function enrichment of DEG in COPD. (B) KEGG function enrichment of DEG in COPD. The enrichment results of DEG up (C) and down (D) in Hallmark respectively. The abscissa was the number of intersections between DEG and the pathway gene set, and the ordinate was -log10 of the significance p-value of the hypergeometric test.

The functional enrichment analysis of DEG in COPD. (A) GO_BP function enrichment of DEG in COPD. (B) KEGG function enrichment of DEG in COPD. The enrichment results of DEG up (C) and down (D) in Hallmark respectively. The abscissa was the number of intersections between DEG and the pathway gene set, and the ordinate was -log10 of the significance p-value of the hypergeometric test.

lncRNA Marker is Screened Based on DEG and DEmi

We obtained the RNA interaction relationship from the database lncACTdb 2.0, and constructed the interaction relationship network containing 519 DEGs and 17 DEmis. The ceRNA network we obtained (Figure 4) contains 93 DEGs, 2 DEmi, 463 lncRNAs, and 1157 DEG-lncRNA, DEmi-lncRNA, and DEmi-DEG interactions. The network nodedegree is shown in Table 2. In the constructed ceRNA network, we selected hub-lncRNA (the network is ranked in the top 10) as the core marker of COPD, including SNHG12, SLFNL1-AS1, KCNQ1OT1, XIST, EAF1-AS1, FOXD2-AS1, NORAD, PINK1-AS and RP11-69E11.4. Next, basing on the cytoHubba analysis of cytoscape, ATM, SMAD7 and HIF1A were identified as hub genes in this network and are used for the treatment of COPD in the future (Figure 5).
Figure 4

ceRNA network in COPD.

Table 2

The Network Node Degree

GeneRNAUpordownDegree
AADACmRNADown0
ABCG2mRNADown17
AC002117.1lncRNAPlane1
AC002467.7lncRNAPlane1
AC003104.1lncRNAPlane4
AC003991.3lncRNAPlane3
AC004069.2lncRNAPlane1
AC004448.5lncRNAPlane1
AC005154.6lncRNAPlane6
AC005532.5lncRNAPlane2
AC007228.9lncRNAPlane1
AC007292.6lncRNAPlane1
AC008079.10lncRNAPlane2
AC008697.1lncRNAPlane1
AC009133.12lncRNAPlane2
AC009948.5lncRNAPlane5
AC010136.2lncRNAPlane1
AC010226.4lncRNAPlane1
AC012123.1lncRNAPlane1
AC015849.16lncRNAPlane2
AC015933.2lncRNAPlane1
AC016747.3lncRNAPlane1
AC017060.1lncRNAPlane1
AC017101.10lncRNAPlane5
AC018890.6lncRNAPlane2
AC023347.1lncRNAPlane1
AC034220.3lncRNAPlane1
AC058791.1lncRNAPlane2
AC069363.1lncRNAPlane2
AC073254.1lncRNAPlane1
AC073641.2lncRNAPlane3
AC074117.10lncRNAPlane1
AC074286.1lncRNAPlane3
AC074366.3lncRNAPlane2
AC084219.4lncRNAPlane2
AC092066.1lncRNAPlane1
AC093627.10lncRNAPlane1
AC097662.2lncRNAPlane1
AC104134.2lncRNAPlane2
AC107081.5lncRNAPlane2
AC108142.1lncRNAPlane1
AC116366.5lncRNAPlane1
AC139100.4lncRNAPlane1
AC141928.1lncRNAPlane1
ACANmRNADown0
ACSL5mRNAUp0
ACTA2mRNADown12
ACTBL2mRNADown0
ACTG2mRNADown0
ACTN3mRNADown0
ADAMTS4mRNAUp1
ADH1AmRNADown0
ADH1CmRNADown0
ADORA2A-AS1lncRNAPlane1
AF127936.9lncRNAPlane1
AF146191.4lncRNAPlane1
AGBL1mRNADown0
AGBL2mRNADown0
AGERmRNADown0
AGTR2mRNAUp0
AK2P2mRNAUp0
AKAP14mRNADown0
AKIRIN1mRNAUp0
AL133243.1lncRNAPlane1
ALAS2mRNAUp0
ALG6mRNADown0
ALKBH3-AS1lncRNAPlane1
ALMS1-IT1lncRNAPlane1
ALOX12-AS1lncRNAPlane2
AMOTL2mRNADown0
ANKMY2mRNADown0
ANKRD22mRNAUp0
ANO8mRNAUp0
ANXA2P3mRNADown0
ANXA5mRNADown0
ANXA6mRNAUp0
AP001258.4lncRNAPlane1
AP006621.8lncRNAPlane1
APAF1mRNAUp23
APOBEC3AmRNAUp0
APOBEC3CmRNAUp0
ARHGAP26mRNAUp2
ARL4CmRNAUp2
ARNTL2mRNAUp0
ART4mRNADown0
ASPHD1mRNAUp0
ASPNmRNADown0
ATF3mRNAUp5
ATMmRNAUp72
ATP1A2mRNADown0
ATP1B2mRNADown0
AXUD1mRNAUp0
BACE1-ASlncRNAPlane1
BAG3mRNAUp1
BAI3mRNADown0
BAIAP2-AS1lncRNAPlane1
BAXmRNAUp22
BCDIN3D-AS1lncRNAPlane1
BCHEmRNADown0
BCL2A1mRNAUp0
BDKRB1mRNAUp0
BPIFA1mRNADown0
BVES-AS1lncRNAPlane1
C10orf116mRNADown0
C10orf28mRNADown0
C11orf10mRNADown0
C11orf88mRNADown0
C13orf33mRNAUp0
C15orf48mRNAUp0
C17orf102lncRNAPlane1
C18orf32mRNAUp0
C1orf105mRNAUp0
C1orf132lncRNAPlane1
C1orf195lncRNAPlane1
C1QTNF5mRNADown0
C1QTNF7mRNADown0
C1RL-AS1lncRNAPlane4
C20orf46mRNADown0
C20orf85mRNADown0
C2orf40mRNADown0
C2orf54mRNAUp0
C2orf83mRNADown0
C4orf7mRNAUp0
C6mRNADown0
C6orf124mRNAUp0
C6orf192mRNADown0
C7orf23mRNADown0
C9orf117mRNADown0
C9orf171mRNADown0
C9orf24mRNADown0
CABP7mRNADown0
CACNA1EmRNAUp0
CACNA1HmRNADown0
CAPSmRNADown0
CARD8-AS1lncRNAPlane1
CASC2lncRNAPlane3
CASC8lncRNAPlane1
CASK-AS1lncRNAPlane1
CASQ2mRNADown0
CATIP-AS2lncRNAPlane2
CAV1mRNADown25
CBX6mRNADown0
CBY1mRNADown0
CCDC103mRNADown0
CCDC137mRNAUp0
CCDC17mRNADown0
CCDC18-AS1lncRNAPlane10
CCDC19mRNADown0
CCDC3mRNADown0
CCDC37mRNADown0
CCDC48mRNADown0
CCDC77mRNADown0
CCDC81mRNADown0
CCL19mRNAUp0
CCL20mRNAUp4
CCL8mRNAUp2
CCR6mRNAUp0
CD70mRNAUp0
CD86mRNADown4
CDC42EP2mRNAUp0
CDH3mRNAUp0
CDKN1AmRNAUp70
CDKN2B-AS1lncRNAPlane1
CES1mRNADown0
CFLAR-AS1lncRNAPlane6
CGB1mRNADown0
CH25HmRNAUp0
CHI3L1mRNAUp0
CHI3L2mRNAUp0
CHIT1mRNAUp0
CHMP4BmRNAUp0
CHP2mRNAUp0
CHST2mRNAUp0
CKMT2-AS1lncRNAPlane2
CLCmRNAUp0
CLEC4EmRNAUp0
CLUmRNADown20
CMIPmRNAUp0
CNN1mRNADown0
COL21A1mRNADown3
COL4A1mRNADown41
COL4A2-AS1lncRNAPlane7
COX10-AS1lncRNAPlane3
COX5AmRNAUp0
CPA3mRNADown0
CPT2mRNAUp0
CREB3L4mRNADown0
CRNDElncRNAPlane2
CSF3mRNAUp0
CTB-111H14.1lncRNAPlane1
CTC-204F22.1lncRNAPlane6
CTC-351M12.1lncRNAPlane7
CTC-444N24.11lncRNAPlane1
CTC-444N24.7lncRNAPlane4
CTC-459F4.3lncRNAPlane1
CTC-459F4.9lncRNAPlane2
CTC-479C5.10lncRNAPlane4
CTC-487M23.5lncRNAPlane5
CTD-2047H16.3lncRNAPlane2
CTD-2095E4.5lncRNAPlane5
CTD-2292P10.4lncRNAPlane2
CTD-2337I7.1lncRNAPlane1
CTD-2369P2.5lncRNAPlane1
CTD-2410N18.4lncRNAPlane3
CTD-2510F5.4lncRNAPlane3
CTD-2517M22.14lncRNAPlane4
CTD-2587H24.14lncRNAPlane2
CTD-2619J13.14lncRNAPlane1
CTD-2630F21.1lncRNAPlane2
CTD-3032J10.2lncRNAPlane1
CTD-3099C6.9lncRNAPlane1
CTD-3131K8.2lncRNAPlane5
CTGFmRNADown9
CTSSmRNAUp0
CUL2mRNAUp7
CXCL13mRNAUp0
CYorf15BmRNAUp0
CYP1B1mRNAUp3
CYP3A4mRNADown3
CYP3A7mRNADown0
CYTORlncRNAPlane1
DAW1mRNADown0
DDCmRNADown1
DDR2mRNADown0
DENND4BmRNADown0
DESmRNADown0
DGUOK-AS1lncRNAPlane3
DHRS4-AS1lncRNAPlane1
DLEU2LlncRNAPlane1
DLSTmRNAUp0
DLX6-AS1lncRNAPlane5
DNAJC5mRNAUp0
DNAJC7mRNAUp0
DNASE1L3mRNADown0
DOHHmRNAUp10
DPH6-AS1lncRNAPlane2
DPYD-AS1lncRNAPlane5
DUSP15mRNADown0
DUSP2mRNAUp4
DYNC1H1mRNADown0
DYNLRB2mRNADown0
EAF1-AS1lncRNAPlane12
EBLN3PlncRNAPlane8
EEF1A1P11mRNADown0
EFHBmRNADown0
EGFL7mRNADown0
EIF1BmRNAUp0
EIF3J-AS1lncRNAPlane2
ELOA-AS1lncRNAPlane3
EMDmRNAUp0
EML2-AS1lncRNAPlane1
ENPP2mRNADown0
ENPP4mRNADown0
ENTPD1-AS1lncRNAPlane1
ERFmRNAUp0
EXTL3-AS1lncRNAPlane3
F8A1mRNADown0
FAM162BmRNADown0
FAM166BmRNAUp0
FAM183AmRNADown0
FAM201AlncRNAPlane5
FAM5CmRNADown0
FAM95ClncRNAPlane1
FAM96BmRNADown0
FAT4mRNADown0
FENDRRlncRNAPlane3
FGFBP2mRNADown0
FGGmRNAUp2
FHL1mRNADown0
FIBINmRNADown0
FILIP1LmRNADown0
FKBP10mRNAUp0
FLJ21511mRNADown0
FLJ34515mRNADown0
FLJ37453lncRNAPlane3
FLJ46284lncRNAPlane3
FOLR1mRNADown0
FOXD2-AS1lncRNAPlane11
FSTL1mRNADown8
FTXlncRNAPlane9
FUSmRNAUp0
GABBR1mRNADown0
GABREmRNADown0
GADD45BmRNAUp0
GAGE3mRNAUp0
GAS1mRNADown21
GAS5lncRNAPlane2
GBP6mRNADown0
GDE1mRNAUp0
GDF10mRNADown0
GDF15mRNAUp0
GFPT2mRNAUp0
GJB2mRNAUp0
GLT1D1mRNAUp0
GLT25D2mRNADown0
GLYCTK-AS1lncRNAPlane1
GNA11mRNADown0
GNG12-AS1lncRNAPlane2
GNG13mRNADown2
GPC3mRNADown1
GPM6AmRNADown0
GPR172AmRNAUp0
GPR177mRNAUp0
GRB14mRNADown0
GRM8mRNADown0
GSNmRNADown0
GSTA2mRNADown0
GSTA5mRNADown0
GSTM1mRNADown0
GSTT1mRNADown0
GUSBP11lncRNAPlane1
H19lncRNAPlane4
H2AFXmRNAUp29
HAGLRlncRNAPlane3
HAS1mRNAUp0
HCG18lncRNAPlane3
HCRTmRNADown0
HELLPARlncRNAPlane1
HIF1AmRNAUp79
HIRAmRNAUp0
HIST1H2ABmRNADown0
HIST1H4BmRNADown0
HK3mRNAUp0
HLA-UmRNAUp0
HMBOX1mRNADown3
HMGB3L1mRNAUp0
HMOX1mRNAUp5
HNRNPA0mRNAUp0
HNRNPABmRNAUp0
HORMAD2-AS1lncRNAPlane1
HOTAIRM1lncRNAPlane1
HOXA-AS2lncRNAPlane4
HOXA-AS3lncRNAPlane3
HOXA2mRNADown0
HOXC-AS2lncRNAPlane1
HPRmRNAUp0
HRASLS5mRNAUp0
hsa-miR-105miRNAUp0
hsa-miR-10amiRNAUp0
hsa-miR-1274amiRNAUp0
hsa-miR-144miRNAUp0
hsa-miR-148amiRNAUp0
hsa-miR-223miRNAUp0
hsa-miR-25*miRNADown0
hsa-miR-374amiRNAUp0
hsa-miR-422amiRNADown0
hsa-miR-454miRNAUp0
hsa-miR-486-5pmiRNAUp12
hsa-miR-513a-5pmiRNADown3
hsa-miR-576-3pmiRNADown0
hsa-miR-664miRNAUp0
hsa-miR-766miRNAUp0
hsa-miR-923miRNADown0
hsa-miR-937miRNADown0
HSPA2mRNADown0
HSPB3mRNADown0
HSPD1P6mRNAUp0
ID4mRNADown4
IER3mRNAUp0
IFIT1mRNADown4
IFT20mRNAUp0
IGFBP7-AS1lncRNAPlane1
IGHMmRNAUp0
IGSF6mRNAUp0
IL1BmRNAUp1
IL1R2mRNAUp0
IL20RBmRNAUp0
IL33mRNADown0
IL6mRNAUp31
IL8mRNAUp0
INMTmRNADown0
IPO9-AS1lncRNAPlane1
IQCDmRNADown0
IQGAP2mRNAUp0
IRX5mRNADown0
ITGA7mRNADown4
ITGA9-AS1lncRNAPlane4
ITGB2mRNAUp0
ITLN2mRNADown0
ITPKCmRNAUp0
JMJD6mRNAUp0
JPXlncRNAPlane1
JUNBmRNAUp2
KB-1208A12.3lncRNAPlane2
KB-1517D11.4lncRNAPlane1
KB-1572G7.2lncRNAPlane1
KB-1615E4.2lncRNAPlane3
KB-318B8.7lncRNAPlane3
KC6lncRNAPlane1
KCNA5mRNADown0
KCNIP2-AS1lncRNAPlane1
KCNQ1OT1lncRNAPlane16
KDM4A-AS1lncRNAPlane10
KIAA0644mRNADown0
KITmRNADown56
KLK12mRNADown0
KPNA6mRNADown0
KRT17P3mRNAUp0
KRT4mRNADown0
KRT7mRNAUp6
KRT7-ASlncRNAPlane2
L1TD1mRNADown0
LA16c-358B7.3lncRNAPlane1
LACTB2-AS1lncRNAPlane1
LAD1mRNAUp0
LDB2mRNADown0
LEFTY2mRNADown0
LILRB1mRNAUp0
LILRB2mRNAUp0
LIMD1-AS1lncRNAPlane1
LIMK1mRNAUp24
LIMS2mRNADown0
LINC-PINTlncRNAPlane6
LINC00158lncRNAPlane1
LINC00304lncRNAPlane1
LINC00339lncRNAPlane4
LINC00461lncRNAPlane1
LINC00472lncRNAPlane1
LINC00511lncRNAPlane3
LINC00525lncRNAPlane2
LINC00630lncRNAPlane1
LINC00641lncRNAPlane2
LINC00645lncRNAPlane1
LINC00661lncRNAPlane1
LINC00664lncRNAPlane1
LINC00665lncRNAPlane9
LINC00667lncRNAPlane3
LINC00670lncRNAPlane2
LINC00707lncRNAPlane1
LINC00869lncRNAPlane7
LINC00893lncRNAPlane2
LINC00894lncRNAPlane7
LINC00907lncRNAPlane1
LINC00909lncRNAPlane1
LINC00910lncRNAPlane1
LINC00958lncRNAPlane10
LINC00960lncRNAPlane2
LINC00963lncRNAPlane6
LINC01085lncRNAPlane1
LINC01090lncRNAPlane2
LINC01116lncRNAPlane1
LINC01128lncRNAPlane10
LINC01134lncRNAPlane2
LINC01140lncRNAPlane7
LINC01184lncRNAPlane1
LINC01197lncRNAPlane1
LINC01257lncRNAPlane1
LINC01278lncRNAPlane2
LINC01358lncRNAPlane2
LINC01362lncRNAPlane2
LINC01521lncRNAPlane1
LINC01569lncRNAPlane1
LINC01578lncRNAPlane1
LINC01605lncRNAPlane1
LINC01619lncRNAPlane1
LINC01783lncRNAPlane1
LINC01934lncRNAPlane4
LINC01965lncRNAPlane1
LIPE-AS1lncRNAPlane1
LIX1L-AS1lncRNAPlane1
LLNLR-268E12.1lncRNAPlane1
LLNLR-470E3.1lncRNAPlane1
LMCD1mRNADown0
LMNB1mRNAUp0
LMNB2mRNAUp3
LMOD1mRNADown0
LOC100128164mRNADown0
LOC100128178mRNADown0
LOC100128548mRNADown0
LOC100128977mRNAUp0
LOC100131582mRNAUp0
LOC100132247mRNADown0
LOC100134228mRNAUp0
LOC23117mRNADown0
LOC338799mRNADown0
LOC389831mRNADown0
LOC391132mRNAUp0
LOC391532mRNAUp0
LOC402360mRNADown0
LOC51233mRNAUp0
LOC595101mRNAUp0
LOC646909mRNAUp0
LOC646949mRNAUp0
LOC649294mRNAUp0
LOC650392mRNAUp0
LOC728763mRNADown0
LOC728820mRNAUp0
LOC729046mRNAUp0
LOC729259mRNAUp0
LOC729652mRNAUp0
LOC780529mRNAUp0
LRIG1mRNADown9
LRP5LmRNAUp0
LRRC2mRNADown0
LRRC36mRNADown0
LRRC45mRNADown0
LRRC46mRNADown0
LRRC75A-AS1lncRNAPlane2
LTBP2mRNADown0
LTBP4mRNADown0
LTC4SmRNADown0
LTKmRNADown0
MACC1-AS1lncRNAPlane1
MAGOHmRNAUp0
MALAT1lncRNAPlane10
MAOBmRNADown0
MAP4K3mRNADown11
MAPKAPK3mRNAUp0
MATN1-AS1lncRNAPlane1
MBD4mRNAUp0
MBNL1-AS1lncRNAPlane1
MCF2L-AS1lncRNAPlane1
MCM3AP-AS1lncRNAPlane1
MED18mRNAUp2
MELTF-AS1lncRNAPlane1
METTL7AmRNAUp3
MFAP4mRNADown2
MGC70870mRNAUp0
MIR124-2HGlncRNAPlane1
MIR155HGlncRNAPlane1
MIR17HGlncRNAPlane1
MIR22HGlncRNAPlane2
MIR4435-2HGlncRNAPlane2
MIR4458HGlncRNAPlane1
MIR583HGlncRNAPlane1
MIRLET7BHGlncRNAPlane4
MKNK1-AS1lncRNAPlane1
MMP1mRNAUp1
MMP10mRNAUp0
MMP14mRNADown12
MMP19mRNAUp0
MMP9mRNAUp49
MNTmRNADown0
MOP-1mRNAUp0
MRTO4mRNAUp0
MS4A2mRNADown0
MS4A8BmRNADown0
MSCmRNAUp7
MST1mRNADown13
MSTP9mRNADown0
MT1FmRNAUp0
MT1HmRNAUp0
MT1LmRNAUp0
MT1MmRNAUp7
MTND1P23mRNAUp0
MXD1mRNAUp13
MYBmRNADown59
MYH11mRNADown0
MYH2mRNADown1
MYO15BmRNADown0
MYOCmRNADown1
MYOZ1mRNADown0
MYRIPmRNADown0
NBPF14mRNADown0
NBPF20mRNAUp0
NCR2mRNAUp0
NEAT1lncRNAPlane7
NEUROG1mRNAUp0
NFKBIZmRNAUp0
NFYC-AS1lncRNAPlane2
NKILAlncRNAPlane1
NKX2-8mRNADown0
NLRP2mRNAUp0
NMNAT3mRNADown0
NNT-AS1lncRNAPlane1
NORADlncRNAPlane11
NOVmRNADown0
NPHP4mRNAUp0
NPIPmRNADown0
NPM3mRNAUp0
NPNTmRNADown15
NPPA-AS1lncRNAPlane1
NPTNmRNADown0
NR2F1-AS1lncRNAPlane7
NR2F2mRNADown5
NR4A1mRNAUp0
NR4A2mRNAUp18
NSBP1mRNADown0
NTF3mRNADown8
NTMmRNAUp1
NUAK2mRNAUp0
NUTM2A-AS1lncRNAPlane1
NUTM2B-AS1lncRNAPlane2
OGNmRNADown0
OIP5-AS1lncRNAPlane5
OLFML3mRNADown0
OLIG3mRNAUp0
OMDmRNADown0
OPN1LWmRNAUp0
OR2A1-AS1lncRNAPlane2
OSMmRNAUp0
OSTbetamRNADown0
PABPC4LmRNADown0
PADI3mRNAUp0
PAX8-AS1lncRNAPlane1
PCA3lncRNAPlane1
PCBP1-AS1lncRNAPlane5
PCDH18mRNADown0
PCNPmRNADown0
PCOLCE2mRNADown0
PDAP1mRNAUp0
PDCD4-AS1lncRNAPlane1
PF4mRNAUp0
PFDN6mRNAUp0
PHF1mRNADown0
PHF5AmRNAUp0
PHLDA1mRNAUp0
PHLDA2mRNAUp0
PHLDA3mRNADown0
PI16mRNADown0
PI3mRNAUp0
PIK3CD-AS1lncRNAPlane1
PIK3CD-AS2lncRNAPlane1
PIM1mRNAUp19
PINK1-ASlncRNAPlane11
PLA2G1BmRNADown0
PLA2G2AmRNAUp0
PLA2G7mRNAUp0
PLEKHG4mRNAUp0
PLEKHH3mRNADown0
PLNmRNADown0
PMAIP1mRNAUp5
POLR2CmRNAUp0
POLR2J4lncRNAPlane1
POU2AF1mRNAUp0
PPIBmRNAUp0
PPP1R14AmRNADown0
PPP1R3CmRNADown0
PPP3CB-AS1lncRNAPlane5
PRDM6mRNADown0
PRKCBmRNAUp3
PRKYmRNADown0
PROS1mRNADown1
PROSER2-AS1lncRNAPlane1
PRPF19mRNAUp0
PRR13P5mRNAUp0
PRRG4mRNAUp0
PRRT2mRNADown0
PRSS36mRNAUp0
PSMA3-AS1lncRNAPlane7
PTCHD1-ASlncRNAPlane1
PTOV1-AS1lncRNAPlane1
PTPN1mRNAUp2
PTPRDmRNADown12
PTX3mRNAUp3
PVT1lncRNAPlane2
QTRT1mRNAUp0
RAB13mRNAUp3
RAB20mRNAUp0
RAB23mRNADown4
RAET1E-AS1lncRNAPlane1
RANBP6mRNADown0
RAP1GAPmRNADown0
RAPGEF5mRNADown0
RBM26-AS1lncRNAPlane1
RERGmRNADown0
RFX3-AS1lncRNAPlane4
RGL2mRNADown0
RGL4mRNAUp0
RGS1mRNAUp0
RGS22mRNADown0
RND1mRNAUp0
RNF125mRNAUp0
RNF145mRNAUp0
RP1-117O3.2lncRNAPlane1
RP1-118J21.5lncRNAPlane6
RP1-158P9.1lncRNAPlane1
RP1-191J18.66lncRNAPlane10
RP1-193H18.2lncRNAPlane1
RP1-199J3.7lncRNAPlane4
RP1-224A6.9lncRNAPlane1
RP1-253P7.4lncRNAPlane1
RP1-27K12.2lncRNAPlane1
RP1-283E3.8lncRNAPlane2
RP1-37C10.3lncRNAPlane2
RP1-92O14.6lncRNAPlane3
RP11-1000B6.5lncRNAPlane1
RP11-1007O24.3lncRNAPlane4
RP11-106M3.3lncRNAPlane1
RP11-108M9.3lncRNAPlane2
RP11-108M9.6lncRNAPlane2
RP11-10K16.1lncRNAPlane1
RP11-1149O23.2lncRNAPlane1
RP11-120D5.1lncRNAPlane2
RP11-120E11.2lncRNAPlane1
RP11-133K1.11lncRNAPlane1
RP11-140H17.2lncRNAPlane1
RP11-147L13.12lncRNAPlane2
RP11-154D6.1lncRNAPlane1
RP11-156E6.1lncRNAPlane3
RP11-157P1.4lncRNAPlane3
RP11-158K1.3lncRNAPlane1
RP11-160H22.5lncRNAPlane1
RP11-161H23.9lncRNAPlane1
RP11-161M6.2lncRNAPlane3
RP11-16E12.2lncRNAPlane1
RP11-186B7.4lncRNAPlane1
RP11-197N18.2lncRNAPlane1
RP11-197N18.8lncRNAPlane1
RP11-228B15.4lncRNAPlane2
RP11-244H3.1lncRNAPlane1
RP11-267M23.1lncRNAPlane1
RP11-277P12.20lncRNAPlane1
RP11-278C7.3lncRNAPlane3
RP11-288L9.4lncRNAPlane3
RP11-295P9.3lncRNAPlane1
RP11-299J3.8lncRNAPlane3
RP11-29G8.3lncRNAPlane3
RP11-2C24.3lncRNAPlane1
RP11-2C24.4lncRNAPlane2
RP11-303E16.2lncRNAPlane2
RP11-304L19.13lncRNAPlane1
RP11-305E6.4lncRNAPlane7
RP11-314B1.2lncRNAPlane7
RP11-317N8.5lncRNAPlane8
RP11-328C8.4lncRNAPlane7
RP11-334C17.5lncRNAPlane4
RP11-342K2.1lncRNAPlane2
RP11-342M1.3lncRNAPlane2
RP11-345P4.4mRNADown0
RP11-348N5.7lncRNAPlane1
RP11-348P10.2lncRNAPlane1
RP11-352G18.2lncRNAPlane3
RP11-355B11.2lncRNAPlane1
RP11-357H14.17lncRNAPlane5
RP11-359B12.2lncRNAPlane1
RP11-360N9.2lncRNAPlane1
RP11-372K14.2lncRNAPlane4
RP11-373N22.3lncRNAPlane1
RP11-378J18.8lncRNAPlane1
RP11-380L11.4lncRNAPlane1
RP11-381N20.1lncRNAPlane3
RP11-386G11.5lncRNAPlane5
RP11-394O2.3lncRNAPlane1
RP11-395G23.3lncRNAPlane3
RP11-399K21.14lncRNAPlane2
RP11-405O10.2lncRNAPlane1
RP11-412P11.1lncRNAPlane1
RP11-415J8.3lncRNAPlane5
RP11-416N4.4lncRNAPlane2
RP11-421L21.3lncRNAPlane6
RP11-446H18.5lncRNAPlane1
RP11-452F19.3lncRNAPlane1
RP11-45P15.4lncRNAPlane3
RP11-468E2.5lncRNAPlane7
RP11-46O21.2lncRNAPlane1
RP11-477D19.2lncRNAPlane1
RP11-478C19.2lncRNAPlane2
RP11-481C4.2lncRNAPlane1
RP11-493P1.2lncRNAPlane3
RP11-519G16.3lncRNAPlane1
RP11-531A24.7lncRNAPlane1
RP11-539I5.1lncRNAPlane2
RP11-545I5.3lncRNAPlane4
RP11-54O7.1lncRNAPlane1
RP11-54O7.3lncRNAPlane10
RP11-574K11.29lncRNAPlane1
RP11-57H12.5lncRNAPlane5
RP11-588H23.3lncRNAPlane1
RP11-588K22.2lncRNAPlane4
RP11-58K22.5lncRNAPlane1
RP11-5C23.1lncRNAPlane1
RP11-60A24.3lncRNAPlane1
RP11-626G11.5lncRNAPlane1
RP11-631M21.2mRNADown0
RP11-656D10.6lncRNAPlane1
RP11-656D10.7lncRNAPlane2
RP11-65L3.2lncRNAPlane2
RP11-661A12.5lncRNAPlane1
RP11-661A12.8lncRNAPlane1
RP11-677I18.3lncRNAPlane1
RP11-677M14.8lncRNAPlane3
RP11-69E11.4lncRNAPlane11
RP11-69E11.8lncRNAPlane3
RP11-701H24.4lncRNAPlane1
RP11-702F3.1lncRNAPlane1
RP11-714G18.1lncRNAPlane1
RP11-715F3.2lncRNAPlane3
RP11-73M18.8lncRNAPlane1
RP11-77H9.2lncRNAPlane1
RP11-793H13.3lncRNAPlane2
RP11-799B12.4lncRNAPlane1
RP11-802E16.3lncRNAPlane1
RP11-815J21.4lncRNAPlane1
RP11-819C21.1lncRNAPlane2
RP11-81K13.1lncRNAPlane2
RP11-822E23.8lncRNAPlane5
RP11-829H16.3lncRNAPlane1
RP11-834C11.4lncRNAPlane6
RP11-843B15.4lncRNAPlane3
RP11-84G21.1lncRNAPlane1
RP11-861E21.2lncRNAPlane1
RP11-968A15.8lncRNAPlane1
RP11-96D1.10lncRNAPlane2
RP11-983P16.4lncRNAPlane1
RP13-143G15.4lncRNAPlane1
RP13-36C9.6mRNADown0
RP13-39P12.3lncRNAPlane1
RP13-516M14.1lncRNAPlane1
RP3-323N1.2lncRNAPlane1
RP3-467L1.4lncRNAPlane2
RP4-569M23.2lncRNAPlane1
RP4-605O3.4lncRNAPlane1
RP4-613B23.1lncRNAPlane1
RP4-622L5.7lncRNAPlane1
RP4-625H18.2lncRNAPlane1
RP4-635E18.7lncRNAPlane2
RP4-639F20.1lncRNAPlane1
RP4-665N4.8lncRNAPlane2
RP4-669K10.8lncRNAPlane3
RP4-671G15.2lncRNAPlane2
RP4-671O14.6lncRNAPlane3
RP4-758J18.13lncRNAPlane1
RP4-758J18.2lncRNAPlane1
RP4-761J14.8lncRNAPlane1
RP4-794H19.1lncRNAPlane1
RP5-1021I20.5lncRNAPlane1
RP5-1024G6.2lncRNAPlane2
RP5-1024G6.5lncRNAPlane6
RP5-1033H22.2lncRNAPlane1
RP5-1039K5.19lncRNAPlane3
RP5-1071N3.1lncRNAPlane1
RP5-1074L1.4lncRNAPlane3
RP5-1101C3.1lncRNAPlane1
RP5-1126H10.2lncRNAPlane3
RP5-1198O20.4lncRNAPlane8
RP5-864K19.7lncRNAPlane7
RP5-884C9.2lncRNAPlane1
RP5-894A10.6lncRNAPlane1
RP5-899E9.1lncRNAPlane4
RP5-991G20.1lncRNAPlane1
RP5-997D16.2lncRNAPlane1
RP6-24A23.7lncRNAPlane1
RPA4mRNADown0
RPS14P8mRNAUp0
RPS6P1mRNADown0
RRP12mRNAUp0
RSPH10BmRNADown0
S100A12mRNAUp0
S100A8mRNAUp0
S100A9mRNAUp1
S100BmRNAUp3
SAA1mRNAUp0
SAPS1mRNADown0
SCAMP1-AS1lncRNAPlane1
SCN4BmRNADown0
SEC14L3mRNADown0
14-SepmRNAUp0
SERPIND1mRNAUp0
SERTAD1mRNAUp0
SETBP1mRNADown0
SFNmRNAUp0
SFTPA1BmRNADown0
SGCEmRNADown0
SGMS1-AS1lncRNAPlane1
SGPP2mRNAUp5
SH3BP5-AS1lncRNAPlane1
SH3GL3mRNADown0
SHANK3mRNADown0
SHC2mRNADown0
SLAMF7mRNAUp0
SLC16A1-AS1lncRNAPlane1
SLC25A22mRNAUp0
SLC26A4mRNAUp0
SLC2A1-AS1lncRNAPlane3
SLC39A7mRNAUp0
SLC44A5mRNADown0
SLC45A4mRNADown0
SLC6A19mRNAUp0
SLC6A4mRNADown10
SLC7A8mRNAUp0
SLCO4A1mRNAUp0
SLFNL1-AS1lncRNAPlane17
SLIT2mRNADown0
SLITRK6mRNADown0
SMAD7mRNADown75
SMARCAD1mRNADown0
SMG7mRNADown0
SNAI1mRNAUp41
SNHG1lncRNAPlane2
SNHG12lncRNAPlane22
SNHG14lncRNAPlane1
SNHG15lncRNAPlane2
SNHG16lncRNAPlane6
SNHG17lncRNAPlane1
SNHG20lncRNAPlane1
SNHG22lncRNAPlane2
SNHG3lncRNAPlane3
SNHG5lncRNAPlane3
SNHG7lncRNAPlane5
SNORA70mRNADown0
SNTNmRNADown0
SOCS3mRNAUp15
SOD2mRNAUp7
SOSTDC1mRNADown0
SPAG8mRNADown0
SPARCL1mRNADown0
SPEGmRNADown0
SPP1mRNAUp10
SPSB2mRNADown0
SRD5A3-AS1lncRNAPlane1
SRGNmRNAUp0
SSBP3-AS1lncRNAPlane4
SSPNmRNADown0
ST20-AS1lncRNAPlane2
ST6GALNAC3mRNADown0
ST6GALNAC5mRNADown0
STARD13-ASlncRNAPlane3
STARD4-AS1lncRNAPlane4
STC2mRNAUp5
STK32CmRNAUp0
STOML3mRNADown0
STX18-AS1lncRNAPlane1
SULT1A1mRNADown0
SVILmRNADown0
TAF5LmRNAUp0
TARIDlncRNAPlane1
TBC1D9mRNADown1
tcag7.873mRNAUp0
TCEAL4mRNADown0
TCF21mRNADown2
TCTN2mRNADown0
TDRD10mRNADown0
TEP1mRNAUp0
TEX41lncRNAPlane2
THBS1mRNAUp14
THCAT158lncRNAPlane1
THUMPD3-AS1lncRNAPlane5
TLX1NBlncRNAPlane1
TMC3-AS1lncRNAPlane1
TMED9mRNAUp0
TMEM100mRNADown2
TMEM120BmRNAUp0
TMEM147-AS1lncRNAPlane2
TMEM178mRNADown0
TMEM201mRNAUp0
TMEM212mRNADown0
TMEM254-AS1lncRNAPlane1
TNFAIP6mRNAUp3
TNFRSF1AmRNAUp0
TNFRSF6BmRNAUp0
TONSL-AS1lncRNAPlane1
TPTEP1mRNAUp0
TRAM2-AS1lncRNAPlane1
TREM2mRNAUp2
TRG-AS1lncRNAPlane7
TSC22D1-AS1lncRNAPlane1
TSIXlncRNAPlane3
TTMAmRNAUp0
TTN-AS1lncRNAPlane5
TTTY15mRNADown0
TUBA4BmRNADown0
TUFMmRNADown0
TUG1lncRNAPlane6
TXLNGYmRNADown0
TYRP1mRNADown0
UBDmRNAUp5
UNKmRNAUp0
UNQ6494lncRNAPlane1
UNQ9419mRNAUp0
UPF1mRNAUp0
URB2mRNAUp0
USP36mRNAUp0
VCAN-AS1lncRNAPlane3
VLDLR-AS1lncRNAPlane1
VPS18mRNADown1
VPS9D1-AS1lncRNAPlane2
WDR67mRNADown0
WFDC1mRNADown0
WFDC21PlncRNAPlane2
XAGE1DmRNAUp0
XISTlncRNAPlane16
XX-FW83563B9.5lncRNAPlane1
XXbac-B461K10.4lncRNAPlane5
YEATS2-AS1lncRNAPlane1
ZACNmRNADown0
ZBBXmRNADown0
ZBED2mRNADown0
ZBTB20-AS1lncRNAPlane1
ZC3H12AmRNAUp2
ZEB1-AS1lncRNAPlane2
ZFHX2-AS1lncRNAPlane1
ZFP62mRNADown0
ZFPM2-AS1lncRNAPlane7
ZIM2-AS1lncRNAPlane1
ZNF117mRNAUp0
ZNF213-AS1lncRNAPlane2
ZNF264mRNAUp0
ZNF280DmRNADown0
ZNF337-AS1lncRNAPlane4
ZNF426mRNAUp0
ZNF572mRNADown0
ZNF652mRNAUp2
ZNF674-AS1lncRNAPlane3
ZNF675mRNAUp0
ZNF728mRNAUp0
ZNF790-AS1lncRNAPlane8
ZRANB2-AS2lncRNAPlane1
ZSCAN10mRNAUp0
Figure 5

The hub genes of COPD in ceRNA network.

The Network Node Degree ceRNA network in COPD. The hub genes of COPD in ceRNA network.

Discussion

COPD is a chronic progressive inflammatory disease with poor prognosis and low long-term survival rate.24 Pulmonary rehabilitation is traditionally recommended for patients with moderate to severe COPD. Although pulmonary rehabilitation, bronchodilators and anti-inflammatory agents provides the greatest improvement in dyspnea, exercise tolerance, and health-related quality of life,25 it is very difficult to change physical activity and with poor outcome.26 Therefore, COPD is a major heterogeneous disease and one of the world’s leading causes of death, and it is urgent for diagnostic and prognostic biomarkers for COPD. High-throughput sequencing technologies have implied in various disease for detecting potential diagnostic and prognostic biomarkers at the transcriptome level. Accumulation of studies revealed the disease-related RNAs which correlated with disease pathology. lncRNAs and miRNAs regulated mRNAs network implied in the various diseases, and some of them was identified as potentially suitable biomarkers.27 In this study, we identified the differentially expressed RNAs, which have significant associations with immune and cancer-related signaling pathway. Among of these, the cytokine receptor CXCR2 antagonist (MK-7123) reduced the chemotaxis of neutrophils, which may alleviate the airway inflammation of COPD.18 The p53 signaling pathway polymorphism was associated with changes in emphysema in COPD patients.20 In addition, ceRNAs network related to COPD was evaluated, implying new molecular mechanism and potential therapeutic target for COPD. Among of the network genes, 10 lncRNAs might be used as COPD marker including SNHG12, SLFNL1-AS1, KCNQ1OT1, XIST, EAF1-AS1, FOXD2-AS1, NORAD, PINK1-AS and RP11-69E11.4. Among them, SNHG12 participated in the unfolded protein response and function as a potential therapeutic target and biomarker for human cancer.28 Many tumor cells avoided immune-mediated attacks and enhanced the polarization of effector immune cells (such as macrophages and T cells) via SNHG12.29 SNHG12 also actED as a competitive endogenous RNA (ceRNA) by containing multiple miRNA binding sites, thereby “sponging” these miRNAs to regulate its downstream targets.30 Recent studies have described the emerging role of ceRNAs in the etiology of cancer, where various ncRNA molecules including lncRNAs, miRNAs, pseudogenes and circular RNAs (circRNAs) share common miRNA response elements (MREs), thereby passing through complex RNA networks Mutual regulation through cellular processes.31 XIST/miR-200c-3p/EGR3 axis promotes 16HBE cell apoptosis and inflammatory response stimulated by cigarette smoke extract. These findings may provide new insights for the treatment of COPD by reducing lung inflammation.32 In conclusion, our research has revealed the DEGs and DEmis related to COPD, and constructed the ceRNA network in COPD, which may provide potential new insights for the treatment of COPD. However, we have some limitations on the mechanism of action of lncRNA involved in the progression of chronic obstructive pulmonary disease. Next, we will further study the related functions and mechanisms through cell, tissue and animal experiments.
  32 in total

Review 1.  Epidemiology of COPD.

Authors:  C Raherison; P-O Girodet
Journal:  Eur Respir Rev       Date:  2009-12

2.  p53 Signaling Pathway Polymorphisms Associated With Emphysematous Changes in Patients With COPD.

Authors:  Shiro Mizuno; Takeshi Ishizaki; Maiko Kadowaki; Masaya Akai; Kohei Shiozaki; Masaharu Iguchi; Taku Oikawa; Ken Nakagawa; Kazuhiro Osanai; Hirohisa Toga; Jose Gomez-Arroyo; Donatas Kraskauskas; Carlyne D Cool; Herman J Bogaard; Norbert F Voelkel
Journal:  Chest       Date:  2017-03-15       Impact factor: 9.410

3.  Cigarette smoke-induced autophagy impairment accelerates lung aging, COPD-emphysema exacerbations and pathogenesis.

Authors:  Neeraj Vij; Prashanth Chandramani-Shivalingappa; Colin Van Westphal; Rachel Hole; Manish Bodas
Journal:  Am J Physiol Cell Physiol       Date:  2016-07-13       Impact factor: 4.249

4.  CXCR2 Antagonist MK-7123. A Phase 2 Proof-of-Concept Trial for Chronic Obstructive Pulmonary Disease.

Authors:  Stephen I Rennard; David C Dale; James F Donohue; Frank Kanniess; Helgo Magnussen; E Rand Sutherland; Henrik Watz; Susan Lu; Paul Stryszak; Elizabeth Rosenberg; Heribert Staudinger
Journal:  Am J Respir Crit Care Med       Date:  2015-05-01       Impact factor: 21.405

5.  Persistence of circulating endothelial microparticles in COPD despite smoking cessation.

Authors:  Yael Strulovici-Barel; Michelle R Staudt; Anja Krause; Cynthia Gordon; Ann E Tilley; Ben-Gary Harvey; Robert J Kaner; Charleen Hollmann; Jason G Mezey; Hans Bitter; Sreekumar G Pillai; Holly Hilton; Gerhard Wolff; Christopher S Stevenson; Sudha Visvanathan; Jay S Fine; Ronald G Crystal
Journal:  Thorax       Date:  2016-07-26       Impact factor: 9.139

6.  Screening of long non-coding RNA and TUG1 inhibits proliferation with TGF-β induction in patients with COPD.

Authors:  Wenxiang Tang; Zhenyu Shen; Jiang Guo; Shenghua Sun
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2016-11-28

7.  Long non-coding RNA OIP5-AS1 regulates smoke-related chronic obstructive pulmonary disease via targeting micro RNA -410-3p/IL-13.

Authors:  Wenbo Hao; Fei Lin; Hanbing Shi; Zhanjiang Guan; Yunfei Jiang
Journal:  Bioengineered       Date:  2021-12       Impact factor: 3.269

8.  Objective physical activity level is associated with rectus femoris muscle echo-intensity in patients with chronic obstructive pulmonary disease.

Authors:  Kazuki Okura; Masahiro Iwakura; Atsuyoshi Kawagoshi; Keiyu Sugawara; Hitomi Takahashi; Takanobu Shioya
Journal:  Clin Respir J       Date:  2022-07-22       Impact factor: 1.761

9.  Long noncoding RNA IL6-AS1 is highly expressed in chronic obstructive pulmonary disease and is associated with interleukin 6 by targeting miR-149-5p and early B-cell factor 1.

Authors:  Erkang Yi; Jiahuan Zhang; Mengning Zheng; Yi Zhang; Chunxiao Liang; Binwei Hao; Wei Hong; Biting Lin; Jinding Pu; Zhiwei Lin; Peiyu Huang; Bing Li; Yumin Zhou; Pixin Ran
Journal:  Clin Transl Med       Date:  2021-07

Review 10.  SNHG12: An LncRNA as a Potential Therapeutic Target and Biomarker for Human Cancer.

Authors:  Suraksha Tamang; Varnali Acharya; Deepronil Roy; Rinka Sharma; Apeksha Aryaa; Uttam Sharma; Akanksha Khandelwal; Hridayesh Prakash; Karen M Vasquez; Aklank Jain
Journal:  Front Oncol       Date:  2019-09-18       Impact factor: 6.244
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