Construction Of ceRNA Network Research Articles

Identification of Novel Prognostic Signatures for Clear Cell Renal Cell Carcinoma Based on ceRNA Network Construction and Immune Infiltration Analysis.

Objective Clear cell renal cell carcinoma (ccRCC) carries significant morbidity and mortality globally and is often resistant to conventional radiotherapy and chemotherapy. Immune checkpoint blockade (ICB) has received attention in ccRCC patients as a promising anticancer treatment. Furthermore, competitive endogenous RNA (ceRNA) networks are crucial for the occurrence and progression of various tumors. This study was aimed at identifying reliable prognostic signatures and exploring potential mechanisms between ceRNA regulation and immune cell infiltration in ccRCC patients. Methods and Results Gene expression profiling and clinical information of ccRCC samples were obtained from The Cancer Genome Atlas (TCGA) database. Through comprehensive bioinformatic analyses, differentially expressed mRNAs (DEmRNAs; n = 131), lncRNAs (DElncRNAs; n = 12), and miRNAs (DEmiRNAs; n = 25) were identified to establish ceRNA networks. The CIBERSORT algorithm was applied to calculate the proportion of 22 types of tumor-infiltrating immune cells (TIICs) in ccRCC tissues. Subsequently, univariate Cox, Lasso, and multivariate Cox regression analyses were employed to construct ceRNA-related and TIIC-related prognostic signatures. In addition, we explored the relationship between the crucial genes and TIICs via coexpression analysis, which revealed that the interactions between MALAT1, miR-1271-5p, KIAA1324, and follicular helper T cells might be closely correlated with the progression of ccRCC. Ultimately, we preliminarily validated that the potential MALAT1/miR-1271-5p/KIAA1324 axis was consistent with the ceRNA theory by qRT-PCR in the ccRCC cell lines. Conclusion On the basis of the ceRNA networks and TIICs, we constructed two prognostic signatures with excellent predictive value and explored possible molecular regulatory mechanisms, which might contribute to the improvement of prognosis and individualized treatment for ccRCC patients.

Construction of ceRNA networks with different types of IDH1 mutation status in low-grade glioma patients

BackgroundIsocitrate dehydrogenase 1 (IDH1) mutation status is related to the prognosis and immune microenvironment of glioma. Long non-coding ribonucleic acids (lncRNAs) interact with microRNAs (miRNAs), and play roles in the competitive endogenous RNA (ceRNA) network and tumor progression.MethodsData on low-grade glioma (LGG) IDH1 mutation was acquired from The Cancer Genome Atlas (TCGA). An empirical analysis of differential gene expression was conducted to identify differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed lncRNAs (DElncRNAs). Survival-associated genes were identified by a univariate Cox regression analysis. An enrichment analysis was conducted to explore the gene ontology and pathways of the DEmRNAs.ResultsEighty-eight DEIDH1mRNAs, 88 DEIDH1lncRNAs, and 6 DEIDH1miRNAs were identified to construct a ceRNA network of LGG patients. Validated by Chinese Glioma Genome Atlas and our LGG patients of gene expression and survival, and the colorectal neoplasia differentially expressed (CRNDE), HOXA transcript antisense RNA, myeloid-specific 1 (HOTAIRM1)/miRNA-206a/hepatocyte nuclear factor 4 (HNF4G) axis was determined.ConclusionsWe established a ceRNA network by integrating the different IDH1 mutation statuses of LGG patients, and identified HNF4G, CRNDE, and HOTAIRM1 as genes related to the prognosis of and immune infiltration in LGG patients. Our findings suggest that these genes may be targets for LGG treatment, especially for patients with the wild-type IDH1 gene variants.

Integrated Analysis of miR-7-5p-Related ceRNA Network Reveals Potential Biomarkers for the Clinical Outcome of Gastric Cancer.

Gastric cancer (GC) is the second leading cause of tumor-associated death and the fourth most commonly seen tumor across the world. Abnormal ncRNAs have been verified to be involved in potential metastasis via modulating epithelial-to-mesenchymal transition progression and are vital for the progression of cancers. Tumor-infiltrating immune cells (TICs) are a vital indicator of whether cancer patients will benefit from immunotherapy. Nonetheless, the association between ceRNAs and immune cells remained largely unclear. We used the ceRNA network combined with TICs for the prediction of the clinical outcome of GC patients based on TCGA datasets. The percentage of immunocytes in GC was speculated by the use of CIBERSORT. Via Lasso and multivariate assays, prognostic models were established applying survival-related genes and immune cells. Nomograms were developed, and the accuracy of the nomograms was determined using calibration curves. The association between ceRNAs and TICs was validated by the use of integration analysis. In this study, there were 2219 mRNAs (1308 increased and 911 decreased), 171 lncRNAs (51 decreased and 120 increased), and 123 miRNAs (55 decreased and 68 increased) differentially expressed between tumor groups and nontumor groups. Five lncRNAs, six miRNAs, and 64 mRNAs were used for ceRNA network construction. Eight genes including LOX, SPARC, MASTL, PI15, BMPR1B, ANKRD13B, PVT1, and miR-7-5p were applied for the development of the prognostic model. Survival assays suggested that tumor cases with high risk exhibited a shorter overall survival. In addition, we included T-cell CD4 memory activated, monocytes, and neutrophils for the development of a prognosis model. Eventually, our team demonstrated the possible associations between the ceRNA prognosis model and prognostic model based on immune cells. To sum up, the ceRNA network could be used for gene regulation and predict clinical outcomes of GC patients.

Identification of Differentially Expressed and Prognostic lncRNAs for the Construction of ceRNA Networks in Lung Adenocarcinoma.

Background Long noncoding RNAs (lncRNAs) could function as competitive endogenous RNAs (ceRNAs) to competitively adsorb microRNAs (miRNAs), thereby regulating the expression of their target protein-coding mRNAs. In this study, we aim to identify more effective diagnostic and prognostic markers for lung adenocarcinoma (LUAD). Methods We obtained differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) for LUAD by using The Cancer Genomes Atlas (TCGA) portal. Weighted gene coexpression network analysis (WGCNA) was performed to unveil core gene modules associated with LUAD. The Cox proportional hazards model was performed to determine the prognostic significance of DElncRNAs. The diagnostic and prognostic significance of DElncRNAs was further verified based on the receiver operating characteristic curve (ROC). Cytoscape was used to construct the ceRNA networks comprising the lncRNAs-miRNAs-mRNAs axis based on the correlation obtained from the miRcode, miRDB, and TargetScan. Results Compared with normal lung tissues, 2355 DElncRNAs, 820 DEmiRNAs, and 17289 DEmRNAs were identified in LUAD tissues. We generated 8 WGCNA core modules in the lncRNAs coexpression network, 5 modules in the miRNAs, and 12 modules in the mRNAs coexpression network, respectively. One lncRNA module (blue) consisting of 441 lncRNAs, two miRNA modules (blue and turquoise) containing 563 miRNAs, and one mRNA module (turquoise), which consisted of 15162 mRNAs, were mostly significantly related to LUAD status. Furthermore, 67 DEmRNAs were found to be tumor-associated as well as the target genes of the DElncRNAs-DEmiRNAs axis. Survival analyses showed that 6 lncRNAs (LINC01447, WWC2-AS2, OGFRP1, LINC00942, LINC01168, and AC005863.1) were significantly correlated with the prognosis of LUAD patients. Ultimately, the potential ceRNA networks including 6 DElncRNAs, 4 DEmiRNAs, and 22 DEmRNAs were constructed. Conclusion Our study indicated that 6 DElncRNAs had the possibilities as diagnostic and prognostic biomarkers for LUAD. The lncRNA-mediated ceRNA networks might provide novel insights into the molecular mechanisms of LUAD progression.

Construction of ceRNA Network to Reveal Potential Biomarkers in Crohn’s Disease and Validation in a TNBS Induced Mice Model

PurposeWe aimed to construct a competing endogenous RNA (ceRNA) network and explore the potential biomarkers in Crohn’s disease (CD) via bioinformatics analysis. Validation of candidate biomarkers in a 2,4,6-trinitrobenzene sulfonic acid (TNBS) induced experimental colitis model and ceRNA network in an HCT116 cell line was also an aim, along with purposing to reveal the pathogenesis of CD.MethodsGSE102134 and GSE67106 datasets were obtained and used to screen the differentially expressed genes. WCGNA was applied to identify the relative model to construct the ceRNA network. Furthermore, the relationship between candidate gene and immune infiltration was investigated. Then, the expression of potential biomarkers was validated via qRT-PCR in a TNBS induced experimental colitis model. Finally, the ceRNA network was confirmed by RNAi experiments in an HCT116 cell line.ResultsThe ceRNA network, consisting of four lncRNAs, four miRNAs, and eight mRNAs, was constructed and the ROC analysis showed four mRNAs (PTGS2, LPL, STAT1, and TRIB2) had high diagnostic accuracy (AUC>0.9). In addition, upregulated PTGS2 was positively correlated with immune cell infiltration, including Natural killer cells, exhausted T-cells, monocytes, and Dendritic cells. The outcome of this TNBS induced experimental colitis model verified that the expression of PTGS2 and mir-429 was consistent with results of previous bioinformatics analysis. Furthermore, the predicted ceRNA network MIR3142HG/mir-429/PTGS2 were validated via RNA interference. Knockout of MIR3142HG decreased the mRNA level of PTGS2, whereas inhibition of mir-429 increased the mRNA level of PTGS2 in the HCT116 cell line.ConclusionThe exploration of the ceRNA network in this work might contribute to understanding the pathogenesis of CD. The constructed MIR3142HG/mir-429/PTGS2 ceRNA network may play a role in CD, and PTGS2 can be a potential immune-related biomarker in CD.

Screening of cashmere fineness-related genes and their ceRNA network construction in cashmere goats

Competitive endogenous RNA (ceRNA) is a transcript that can be mutually regulated at the post-transcriptional level by competing shared miRNAs. The ceRNA network connects the function of protein-encoded mRNA with the function of non-coding RNA, such as microRNA (miRNA), long non-coding RNA (lncRNA), and circular RNA (circRNA). However, compared with the ceRNA, the identification and combined analysis of lncRNAs, mRNAs, miRNAs, and circRNAs in the cashmere fineness have not been completed. Using RNA-seq technology, we first identified the miRNAs presented in Liaoning Cashmere Goat (LCG) skin, and then analyzed the mRNAs, lncRNAs, circRNAs expressed in LCG and Inner Mongolia cashmere goat (MCG) skin. As a result, 464 known and 45 new miRNAs were identified in LCG skin. In LCG and MCG skin, 1222 differentially expressed mRNAs were identified, 170 differentially expressed lncRNAs and 32 differentially expressed circRNAs were obtained. Then, qRT-PCR was used to confirm further the representative lncRNAs, mRNAs, circRNAs and miRNAs. In addition, miRanda predicted the relationships of ceRNA regulatory network among lncRNAs, circRNAs, miRNAs and mRNAs, the potential regulatory effects were investigated by Go and KEGG analysis. Through the screening and analysis of the results, the ceRNA network regulating cashmere fineness was constructed. LncRNA MSTRG14109.1 and circRNA452 were competed with miRNA-2330 to regulated the expression of TCHH, KRT35 and JUNB, which may provide a potential basis for further research on the process of regulating the cashmere fineness.

Construction of ceRNA network to identify the lncRNA and mRNA related to non-small cell lung cancer.

BackgroundNon-small cell lung cancer (NSCLC) harms human health, but its pathogenesis remains unclear. We wish to provide more molecular therapeutic targets for NSCLC.MethodsThe NSCLC tissue and normal tissue samples were screened for genetic comparison in the TCGA database. The predicted lncRNA and mRNA in BEAS2B and A549 cells were detected.ResultsVolcano plot displayed differentially expressed lncRNAs and mRNAs in adjacent tissues and NSCLC tissues. The survival curve showed that the lncRNA and mRNA had a significant impact on the patient’s survival. The results of GO term enrichment analysis indicated that mRNA functions were enriched in cell cycle-related pathways. In the ceRNA interaction network, 13 lncRNAs and 20 miRNAs were found to have an interactive relationship. Finally, 3 significantly different lncRNAs (LINC00968, lnc-FAM92A-9 and lnc-PTGFR-1) and 6 mRNAs (CTCFL, KRT5, LY6D, TMEM, GBP6, and TMEM179) with potential therapeutic significance were screened out. And the cell experiment verified our results.ConclusionWe screened out clinically significant 3 lncRNAs and 6 mRNAs involved in the ceRNA network, which were the key to our future research on the treatment of NSCLC.

The proliferation role of LH on porcine primordial germ cell-like cells (pPGCLCs) through ceRNA network construction.

BackgroundThe transdifferentiation of skin‐derived stem cells (SDSCs) into primordial germ cell‐like cells (PGCLCs) is one of the major breakthroughs in the field of stem cells research in recent years. This technology provides a new theoretical basis for the treatment of human infertility. However, the transdifferentiation efficiency of SDSCs to PGCLCs is very low, and scientists are still exploring ways to improve this efficiency or promote the proliferation of PGCLCs. This study aims to investigate the molecular mechanism of luteinising hormone (LH) to enhance porcine PGCLCs (pPGCLCs) proliferation.ResultsIn this study, we dissected the proliferation regulatory network of pPGCLCs by whole transcriptome sequencing, and the results showed that the pituitary‐secreted reproductive hormone LH significantly promoted the proliferation of pPGCLCs. We combined whole transcriptome sequencing and related validation experiments to explore the mechanism of LH on the proliferation of pPGCLCs, and found that LH could affect the expression of Hippo signalling pathway‐related mRNAs, miRNAs and lncRNAs in pPGCLCs.ConclusionsFor the first time, we found that LH promotes pPGCLCs proliferation through the competing endogenous RNA (ceRNA) regulatory networks and Hippo signalling pathway. This finding may help to elucidate the molecular mechanism by which LH promotes pPGCLCs proliferation.

Regulation of Long Non-coding RNA KCNQ1OT1 Network in Colorectal Cancer Immunity.

Over the past few decades, researchers have become aware of the importance of non-coding RNA, which makes up the vast majority of the transcriptome. Long non-coding RNAs (lncRNAs) in turn constitute the largest fraction of non-coding transcripts. Increasing evidence has been found for the crucial roles of lncRNAs in both tissue homeostasis and development, and for their functional contributions to and regulation of the development and progression of various human diseases such as cancers. However, so far, only few findings with regards to functional lncRNAs in cancers have been translated into clinical applications. Based on multiple factors such as binding affinity of miRNAs to their lncRNA sponges, we analyzed the competitive endogenous RNA (ceRNA) network for the colorectal cancer RNA-seq datasets from The Cancer Genome Atlas (TCGA). After performing the ceRNA network construction and survival analysis, the lncRNA KCNQ1OT1 was found to be significantly upregulated in colorectal cancer tissues and associated with the survival of patients. A KCNQ1OT1-related lncRNA-miRNA-mRNA ceRNA network was constructed. A gene set variation analysis (GSVA) indicated that the expression of the KCNQ1OT1 ceRNA network in colorectal cancer tissues and normal tissues were significantly different, not only in the TCGA-COAD dataset but also in three other GEO datasets used as validation. By predicting comprehensive immune cell subsets from gene expression data, in samples grouped by differential expression levels of the KCNQ1OT1 ceRNA network in a cohort of patients, we found that CD4+, CD8+, and cytotoxic T cells and 14 other immune cell subsets were at different levels in the high- and low-KCNQ1OT1 ceRNA network score groups. These results indicated that the KCNQ1OT1 ceRNA network could be involved in the regulation of the tumor microenvironment, which would provide the rationale to further exploit KCNQ1OT1 as a possible functional contributor to and therapeutic target for colorectal cancer.

Biomarker Identification in Membranous Nephropathy Using a Long Non-coding RNA-Mediated Competitive Endogenous RNA Network.

This study was aimed to identify biomarker associated with membranous nephropathy (MN) progression by integration of expression profiles and competitive endogenous RNA (ceRNA) network analysis. The gene (GSE108113) and microRNAs (miRNAs) expression profiles (GSE64306) were downloaded to identify the differentially expressed mRNAs, miRNAs and long non-coding RNAs (lncRNAs) between MN and control groups. The functions and pathways enriched by the differentially expressed mRNAs were analyzed. The mRNA-lncRNA co-expression network was constructed followed by and the ceRNA network construction. Total 264 upregulated and 196 downregulated differentially expressed mRNAs, 79 upregulated and 4 downregulated lncRNAs, as well as 115 upregulated and 93 downregulated miRNAs were obtained between MN and control groups. After analysis, the differential mRNAs were significantly involved in multiple immune-related processes, and cell proliferation, apoptosis and differentiation processes, as well as pathways of taste transduction and lysosome. Finally, a ceRNA network consisting of 4 mRNAs (EPB41L5, FAM43A, PRKG1 and TTC14), 3 lncRNAs (LINC00052, LINC00641 and N4BP2L2-IT2) and 5 miRNAs (hsa-miR-145-5p, hsa-miR-3605-5p, hsa-miR-148a-3p, hsa-miR-497-5p and hsa-miR-148b-3p) was constructed. Our study indicated dysregulation of immune- and apoptosis-associated functions and taste transduction and lysosome pathways may play important roles in MN progression. Deregulated ceRNAs, such as LINC00052-hsa-miR-145-5p-EPB41L5, LINC00052-hsa-miR-148a-3p-FAM43A and LINC00641-hsa-497-5p-PRKG1, may be associated with MN development.

Comprehensive analysis of lncRNA and miRNA expression profiles and ceRNA network construction in negative pressure wound therapy.

BackgroundThis study aims to explore the molecular mechanism of negative pressure wound therapy (NPWT) at the transcriptome level through whole transcriptome sequencing and biometric analysis.MethodsA rat skin defect model was constructed and randomly divided into a NPWT group and a gauze group. The tissue in the center of the wound was used for whole transcriptome sequencing, and differentially expressed messenger RNAs (DEmRNAs), long noncoding RNAs (DElncRNAs), and microRNAs (DEmiRNAs) were identified between the two groups. Quantitative real time-polymerase chain reaction (qRT-PCR) analysis was used to verify the sequencing results. Functional enrichment analysis, pathway analysis, and protein-protein interaction (PPI) network analysis of DEmRNAs were conducted. Through bioinformatics analysis, a lncRNA-associated competing endogenous RNA (ceRNA) network was identified and constructed.ResultsWe detected 896 DEmRNAs, 1,471 DElncRNAs, and 20 DEmiRNAs between the two groups. qRT-PCR verified the sequencing results. Functional analysis showed that DEmRNAs were mainly enriched in immune system processes and the Notch signaling pathway. Protein tyrosine phosphatase receptor type C (PTPRC) and signal transducer and activator of transcription 1 (STAT1) were the central hub nodes in the PPI analysis. The ceRNA network contained 11 mRNAs, 15 lncRNAs, and 4 miRNAs.ConclusionsWe identified several DEmRNAs, DElncRNAs, and DEmiRNAs between the NPWT treatment group and the control group. These findings may provide new insights into the pathophysiological mechanism of NPWT and wound healing.

Identification of Potential lncRNAs and miRNAs as Diagnostic Biomarkers for Papillary Thyroid Carcinoma Based on Machine Learning.

Background Papillary thyroid carcinoma (PTC) accounts for most of the proportion of thyroid cancer (TC). The objective of this study was to identify diagnostic, differentially expressed long noncoding RNAs (lncRNAs) and microRNAs (miRNAs), contributing to understanding the epigenetics mechanism of PTC. Methods The data of lncRNA, miRNA, and mRNA were downloaded from the Cancer Genome Atlas (TCGA) dataset, followed by functional analysis of differentially expressed mRNAs. Optimal diagnostic lncRNA and miRNA biomarkers were identified via random forest. The regulatory network between optimal diagnostic lncRNA and mRNAs and optimal diagnostic miRNA and mRNAs was identified, followed by the construction of ceRNA network of lncRNA-mRNA-miRNA. Expression validation and diagnostic analysis of lncRNAs, miRNAs, and mRNAs were performed. Overexpression of ADD3-AS1 was performed in PTC-UC3 cell lines, and cell proliferation and invasion assay were used for investigating the role of ADD3-AS1 in PTC. Results A total of 107 differentially expressed lncRNAs, 81 differentially expressed miRNAs, and 515 differentially expressed mRNAs were identified. 11 lncRNAs and 6 miRNAs were regarded as the optimal diagnostic biomarkers for PTC. The epigenetic modifications via the above diagnostic lncRNAs and miRNAs were identified, including MIR181A2HG-FOXP2-hsa-miR-146b-3p, BLACAT1/ST7-AS1-RPS6KA5-hsa-miR-34a-5p, LBX2-AS1/MIR100HG-CDHR3-hsa-miR-34a-5p, ADD3-AS1-PTPRE-hsa-miR-9-5p, ADD3-AS1-TGFBR1-hsa-miR-214-3p, LINC00506-MMRN1-hsa-miR-4709-3p, and LOC339059-STK32A-hsa-miR-199b-5p. In the functional analysis, MMRN1 and TGFBR1 were involved in cell adhesion and endothelial cell migration, respectively. Overexpression of ADD3-AS1 inhibited cell growth and invasion in PTC cell lines. Conclusion The identified lncRNAs/miRNAs/mRNA were differentially expressed between normal and cancerous tissues. In addition, identified altered lncRNAs and miRNAs may be potential diagnostic biomarkers for PTC. Additionally, epigenetic modifications via the above lncRNAs and miRNAs may be involved in tumorigenesis of PTC.

Comprehensive analysis of lncRNA biomarkers in kidney renal clear cell carcinoma by lncRNA-mediated ceRNA network.

IntroductionKidney renal clear cell carcinoma (KIRC) has a high incidence globally, and its pathogenesis remains unclear. Long non-coding RNA (lncRNA), as a molecular sponge, participates in the regulation of competitive endogenous RNA (ceRNA). We aimed to construct a ceRNA network and screened out possible lncRNAs to predict KIRC prognosis.Material and methodsAll KIRC data were downloaded from the TCGA database and screened to find the possible target lncRNA; a ceRNA network was designed. Next, GO functional enrichment and KEGG pathway of differentially expressed mRNA related to lncRNA were performed. We used Kaplan-Meier curve analysis to predict the survival of these RNAs. We used Cox regression analysis to construct a model to predict KIRC prognosis.ResultsIn the KIRC datasets, 1457 lncRNA, 54 miRNA and 2307 mRNA were screened out. The constructed ceRNA network contained 81 lncRNAs, nine miRNAs, and 17 mRNAs differentially expressed in KIRC. Survival analysis of all differentially expressed RNAs showed that 21 lncRNAs, four miRNAs, and two mRNAs were related to the overall survival rate. Cox regression analysis was performed again, and we found that eight lncRNAs were related to prognosis and used to construct predictive models. Three lnRNAs from independent samples were meaningful.ConclusionThe construction of ceRNA network was involved in the process and transfer of KIRC, and three lncRNAs may be potential targets for predicting KIRC prognosis.

Screening of Biological Target Molecules Related to Glucocorticoid-Induced Cataract (GIC) on the Basis of Constructing ceRNA Network.

Glucocorticoid-induced cataract (GIC)-associated biomarkers were screened by ceRNA network construction. The GIC samples' GSE3040 were obtained from the NCBI-GEO database. R's Limma package was used to identify differentially expressed RNAs (DERs) between the normal and GIC samples group (4- and 16-h). The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis for the mRNAs in the constructed GIC lncRNA-miRNA-mRNA ceRNA regulation network was implemented. A total of 1665 and 1443 DERs were obtained in the 4- and 16-h group, respectively. At two time points, 256 overlapping DERs were identified, of which 210 (17 lncRNAs and 203 mRNAs) had significant differential expression (4 down- and 206 up-regulated). A total of 534 co-expressed ligation pairs (all up-regulated) were obtained. A ceRNA regulation network was constructed. RPS6KA5, GAB1, CCR7, CCL2, COL4A4, and PPARG were obtained and significantly enriched in the 4 KEGG signaling pathways and were featured as GIC target molecules.

Analysis of changes in circular RNA expression and construction of ceRNA networks in human dilated cardiomyopathy.

Dilated cardiomyopathy (DCM) is a severe life‐threatening disease worldwide, and the underlying mechanisms remain unclear. Circular RNAs (circRNAs) have been reported to play important roles in various cardiovascular diseases and can function as competitive endogenous RNAs (ceRNAs). However, their role in human DCM has not been fully elucidated. In the present study, heart samples from DCM patients and healthy controls were used to identify circRNAs by RNA sequencing. Real‐time quantitative reverse transcription‐polymerase chain reaction (qRT‐PCR) was conducted to validate differentially expressed circRNAs and mRNAs. A total of 9585 circRNAs and 22050 mRNAs were detected in the two groups. Overall, 213 circRNAs and 617 mRNAs were significantly up‐regulated in the DCM group compared with the control group. Similarly, 85 circRNAs and 1125 mRNAs were significantly down‐regulated. According to the ceRNA theory, circRNAs can indirectly interact with mRNAs by directly binding to microRNAs (miRNAs), and circRNAs and mRNAs should be concurrently either up‐regulated or down‐regulated. Based on this theory, we constructed two circRNA‐miRNA‐mRNA networks by using the RNA sequencing data and prediction by proprietary software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to probe the potential functions of differentially expressed circRNAs. In conclusion, this study revealed that the expression of cardiac circRNAs was altered in human DCM and explored the potential functions of circRNAs by constructing ceRNA networks. These findings provide a foundation for future studies of circRNAs in DCM.

Identification and analysis of lncRNA, microRNA and mRNA expression profiles and construction of ceRNA network in Talaromyces marneffei-infected THP-1 macrophage

BackgroundCompetitive endogenous RNA (ceRNA) reveals new mechanisms for interactions between RNAs, which have been considered to play a significant role in pathogen-host innate immune response. However, knowledge of ceRNA regulatory networks in Talaromyces marneffei (TM)-macrophages is still limited.MethodsNext-generation sequencing technology (NGS) was used to obtain mRNA, miRNA and lncRNA expression profiles in TM-infected macrophages. The R package DESeq2 was used to identify differentially expressed lncRNA, miRNA and mRNA. The R package GOseq was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and the ceRNA network of lncRNA–miRNA–mRNA interaction was constructed in Cytoscape. Similarly, functional enrichment analysis on mRNA in the ceRNA network. Finally, two mRNAs and four lncRNAs in the ceRNA network were randomly selected to verify the expression using qRT-PCR.ResultsIn total, 119 lncRNAs, 28 miRNAs and 208 mRNAs were identified as differentially expressed RNAs in TM-infected macrophages. The constructed ceRNA network contains 38 lncRNAs, 10 miRNAs and 45 mRNAs. GO and KEGG analysis of mRNA in the ceRNA network indicated that activated pathways in TM-infected macrophages were related to immunity, inflammation and metabolism. The quantitative validation of the expression of four randomly selected differentially expressed lncRNAs, AC006252.1, AC090197.1, IL6R-AS1, LINC02009 and two mRNAs, CSF1, NR4A3 showed that the expression levels were consistent with those in the RNA-sequencing.ConclusionsThe ceRNA network related to immunity, inflammation and metabolism plays an important role in TM-macrophage interaction. This study may provide effective and novel insights for further understanding the underlying mechanism of TM infection.

Identification novel prognostic signatures for Head and Neck Squamous Cell Carcinoma based on ceRNA network construction and immune infiltration analysis

Background: Head and neck squamous cell carcinoma (HNSCC) is a common malignancy with high mortality and morbidity worldwide, but the underlying biological mechanisms of molecules and tumor infiltrating-immune cells (TIICs) are still unknown.Methods and Results: We obtained mRNAs, lncRNAs, and miRNAs expression profiles of 546 HNSCC from The Cancer Genome Atlas (TCGA) database to develop a ceRNA network. CIBERSORT was employed to estimate the fraction of 22 types of TIICs in HNSCC. Univariate and multivariate Cox regression and lasso regression analyses were used to develop prognostic signatures. Then, two novel risk signatures were constructed respectively based on six ceRNAs (ANLN, KIT, PRKAA2, NFIA, PTX3 and has-miR-148a-3p) and three immune cells (naïve B cells, regulatory T cells and Neutrophils). Kaplan-Meier (K-M) analysis and Cox regression analysis further proved that these two signatures were significant prognostic factors independent of multiple clinicopathological characteristics. Two nomograms were built based on ceRNAs-riskScore and TIICs-riskScore that could be used to predict the prognosis of HNSCC. Co-expression analysis showed significant correlations between miR-148a-3p and naive B cells, naive B cells and plasmas cells.Conclusion: Through construction of the ceRNA network and estimation of TIICs, we established two risk signatures and their nomograms with excellent utility, which indicated the potential molecular and cellular mechanisms, and predicted the prognosis of HNSCC.

Long non-coding RNA C5orf64 is a potential indicator for tumor microenvironment and mutation pattern remodeling in lung adenocarcinoma

Understanding the synergistic and antagonistic effects of tumor microenvironment (TME) and tumor mutation pattern on lung adenocarcinoma (LUAD) is urgently needed. Herein, we applied ESTIMATE and CIBERSORT methods to calculate the ratio of immune and stromal components and TIICs proportion of LUAD samples from TCGA database. Immune-related genes were analyzed by Lasso regression analysis and used for ceRNA network construction. A 14-lncRNA immune-related signature was developed, among which C5orf64 was found to be positively correlated with abundances of M2 macrophages, monocytes, eosinophils and neutrophils, but negatively correlated with Tregs and plasma cells. PD-1, PD-L1 and CTLA-4 were demonstrated to be high expressed in high-level C5orf64 groups. However, C5orf64 had a negative correlation with TP53 mutation frequency. A novel model was built based on age, tumor stage and immune-related lncRNA signature. To conclude, lncRNA C5orf64 had potential to be an indicator for TME modulation and tumor mutation pattern remodeling in LUAD.

Abstract 35: Construction of ce-RNA networks and comprehensive analysis with tumor infiltrating immune cells in hepatocellular carcinoma

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide with a high recurrence rate. Although immune-checkpoint treatment provides survival benefits for patients with HCC, the mortality of HCC is still high. Therefore, it is necessary to understand the molecular mechanism, immune microenvironment and related prognostic factors of HCC. Methods: HCC patients with both RNAseq and miRNA expression data and their clinical information were downloaded from the NCI's Genomic Data Commons. Gene expression data were analyzed to identify differentially expressed genes (DEGs). The results were further used to construct the competing endogenous RNA (ceRNA) networks related to HCC. Meanwhile, the proportions of 22 immune cell types in HCC were estimated by using CIBERSORT (https://cibersort.stanford.edu). Subsequently, two nomograms based on the expression value of ceRNAs and the percentage of immune cells were constructed to predict the prognosis of HCC patients, respectively. The calibration and time series ROC curves were used to evaluate these models. Finally, the correlation between ceRNAs and immune cells were explored to reveal the underlying molecular mechanism. Results: Gene expression data and clinical information of 367 primary HCC and 50 adjacent normal samples were downloaded from the TCGA database. These data were used to identify DEGs. A total of 12 lncRNAs, 71 mRNAs and 39 miRNAs were identified to be in ceRNA networks according to starBase v2.0 database. The results showed that stages of cancer, the expression values of CBX2, MAFG, DNM3, BUB1, ARL5B and other 23 genes were important predictors. The AUCs of the constructed nomogram in predicting the 3- and 5-year OS were 0.79 and 0.81 respectively. Stages of cancer, proportions of resting memory CD4+ T cell, M0 macrophages and resting mast cells constructed another nomogram with AUC of 0.79 and 0.81 in predicting the 3- and 5-year OS. CIBERSORT results showed that the proportions of regulatory T cells, CD8+ T cells, follicular helper T cells and M0 macrophages were slightly higher while the proportions of M2 macrophages, monocytes and activated mast cells were slightly lower in HCC than in adjacent normal samples. Integration analysis of CIBERSORT results, ceRNAs and gene set enrichment analysis of immunologic signatures identified BUB1, E2F8, H2AFZ, JPT1, LPCAT1, MAFG and PSMC3IP to be positively related with regulatory T cells, follicular helper T cells, activated memory CD4+ T cells and M0 macrophages. This is consistent with current knowledge that immune activity is suppressed in certain types of cancers. However, the underlying mechanism warrant further exploration. Conclusions: In this study, two nomograms were constructed to predict the prognosis of HCC patients, which might be useful in predicting the prognosis of HCC patients. The results suggest that the immune suppress effect of HCC may be related to BUB1, E2F8, H2AFZ, JPT1, LPCAT1, MAFG and PSMC3IP genes. These genes may serve as potential therapeutic targets. Acknowledgments: This work was supported by the National Science and Technology Major Project of China (2018ZX10302205). Citation Format: Jianxiang Shi, Chi Cui, Yaru Duan, Hua Ye, Peng Wang, Jitian Li, Shuiling Jin, Liping Dai, Jianying Zhang. Construction of ce-RNA networks and comprehensive analysis with tumor infiltrating immune cells in hepatocellular carcinoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 35.

Analysis of exosomal lncRNA, miRNA and mRNA expression profiles and ceRNA network construction in endometriosis.

Aim: To investigate exosomal RNAs (long noncoding RNAs (lncRNAs), microRNAs (miRNAs) and messenger RNAs (mRNAs)) profiling and their related networks in endometriosis (EMs). Materials & methods: RNA sequence was performed in exosomes from ovarian endometriomas (EC), eutopic endometria (EU) and normal endometria (Control) stromal cells. The bioinformatics algorithms evaluated competing endogenous RNA (ceRNA) networks. The top-ranked ceRNA networks were confirmed by RT-PCR. Results: Overlapped differentially expressed 938 lncRNAs, 39 miRNAs and 1449 mRNAs were identified. 13 co-expression modules and 61 ceRNA networks were constructed. Conclusion: This study for the first time shows exosomal RNA biomarkers and lncRNA-related networks in EMs, which reveals a novel molecular mechanism of EMs and provides new resources for EM diagnosis and treatment.