Integrated analysis of a competing endogenous RNA network reveals a ferroptosis-related 6-lncRNA prognostic signature in clear cell renal cell carcinoma

BACKGROUND

Establishing a robust signature for prognostic prediction and precision treatment is necessary due to the heterogeneous prognosis and treatment response of clear cell renal cell carcinoma (ccRCC).

OBJECTIVES

This study set out to elucidate the biological functions and prognostic role of ferroptosis-related long non-coding RNAs (lncRNAs) based on a synthetic analysis of competing endogenous RNA networks in ccRCC.

MATERIAL AND METHODS

Ferroptosis-related genes were obtained from the FerrDb database. The expression data and matched clinical information of lncRNAs, miRNAs and mRNAs from The Cancer Genome Atlas (TCGA) database were obtained to identify differentially expressed RNAs. The lncRNA-miRNA-mRNA ceRNA network was established utilizing the common miRNAs that were predicted in the RNAHybrid, StarBase and TargetScan databases. Then, using progressive univariate Cox regression, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis of gene expression data and clinical information, a ferroptosis-related lncRNA prognosis signature was constructed based on the lncRNAs in ceRNA. Finally, the influence of independent lncRNAs on ccRCC was explored.

RESULTS

A total of 35 ferroptosis-related mRNAs, 356 lncRNAs and 132 miRNAs were sorted out after differential expression analysis in the TCGA-KIRC. Subsequently, overlapping lncRNA-miRNA and miRNA-mRNA interactions among the RNAHybrid, StarBase and TargetScan databases were constructed and identified; then a ceRNA network with 77 axes related to ferroptosis was established utilizing mutual miRNAs in 2 interaction networks as nodes. Next, a 6-ferroptosis-lncRNA signature including PVT1, CYTOR, MIAT, SNHG17, LINC00265, and LINC00894 was identified in the training set. Kaplan-Meier analysis, PCA, t-SNE analysis, risk score curve, and receiver operating characteristic (ROC) curve were performed to confirm the validity of the signature in the training set and verified in the validation set. Finally, single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) analysis showed that the signature was related to immune cell infiltration.

CONCLUSIONS

Our research underlines the role of the 6-ferroptosis-lncRNA signature as a predictor of prognosis and a therapeutic alternative for ccRCC.

Comprehensive Analysis of a Competing Endogenous RNA Co-Expression Network in Chronic Obstructive Pulmonary Disease

Purpose

Chronic obstructive pulmonary disease (COPD) is the main cause of mortality world widely. Non-coding RNAs (lncRNAs) and associated competitive endogenous RNAs (ceRNAs) networks were recently proved to lead to mRNA gene expression downregulation but were still unclear in COPD. This study aims to investigate and elucidate the mechanisms underlying the involvement of ceRNA co-expression networks in COPD pathogenesis.

Methods

Obtained expression signature of data from the Gene Expression Omnibus database and compared the differentially expression of mRNAs and miRNAs between COPD patients and healthy smokers. Predicted the miRNA-lncRNA and miRNA-mRNA interaction using online library and employed CIBERSORT to measure the proportions of the 22 immune cells in the COPD and control groups.

Results

Established a ceRNA-network comprising 11 lncRNAs, 5 miRNAs, and 16 mRNAs. Using the weighted correlation network analysis method, we identified hub genes and hub miRNAs and obtained one core sub-network, XIST, FGD5-AS1, KCNQ1OT1, HOXA11-AS, LINC00667, H19, PRKCQ-AS1, NUTM2A-AS1/has-mir-454-3p/ZNF678, PRRG4. COPD patients had different proportions of immune cells than controls, and these variations were associated with the magnitude of pulmonary function parameters.

Conclusion

The ceRNA-network, particularly the core sub-network, may be a putative goal for COPD, in which specific immune cells were involved.

Construction of ceRNA regulatory networks for osteoporosis

Osteoporosis increases the risk of fracture. Improving the diagnosis and treatment of osteoporosis has clinical applications. The differentially expressed genes (DEcircRs, DEmRs, DEmiRs) of osteoporotic patients and controls were analyzed using the GEO database, and enrichment analysis of DEmRs was performed. circRNAs and mRNAs, which were predicted to have a target relationship with DEmRs, were obtained to compare competing endogenous RNA (ceRNA) regulatory networks by comparison with differentially expressed genes. Molecular experiments were utilized to validate the expression of genes within the network. The interactions between genes within the ceRNA network were validated by luciferase reporter assays. Following overexpression of circ_0070304 in bone marrow mesenchymal stem cells (BMSCs), the osteogenic differentiation of the cells was assessed by Alizarin Red staining. A total of 110 intersectional DEmRs between patients with osteoporosis and controls from GSE35958 and GSE56815, which were mainly enriched in estrogen, the thyroid hormone signaling pathway, and adherens junctions were identified. A ceRNA network [circ_0070304/miR‑183‑5p/ring finger and CCCH‑type domains 2 (RC3H2)] was then constructed. Circ_0070304 acted as a sponge for miR‑183‑5p and regulated RC3H2 expression. Overexpression of circ_0070304 upregulated ROCK1 and induced osteogenic differentiation. The ceRNA regulatory network that was obtained is expected to be a new target for osteoporosis treatment and to provide new insights into the diagnosis and treatment of osteoporosis in greater depth.

Role of ceRNA network in inflammatory cells of rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease caused by inflammatory cells. Various inflammatory cells involved in RA include fibroblast-like synoviocytes, macrophages, CD4+T-lymphocytes, B lymphocytes, osteoclasts and chondrocytes. The close interaction between various inflammatory cells leads to imbalance of immune response and disorder of the expression of mRNA in inflammatory cells. It helps to drive production of pro-inflammatory cytokines and stimulate specific antigen-specific T- and B-lymphocytes to produce autoantibodies which is an important pathogenic factor for RA. Competing endogenous RNA (ceRNA) can regulate the expression of mRNA by competitively binding to miRNA. The related ceRNA network is a new regulatory mechanism for RNA interaction. It has been found to be involved in the regulation of abnormal biological processes such as proliferation, apoptosis, invasion and release of inflammatory factors of RA inflammatory cells. Understanding the ceRNA network in 6 kinds of RA common inflammatory cells provides a new idea for further elucidating the pathogenesis of RA, and provides a theoretical basis for the discovery of new biomarkers and effective therapeutic targets.

A novel signature based on CeRNA and immune status predicts prognostic risk and drug sensitivity in gastric cancer patients

Background

At present, there is increasing evidence that both competitive endogenous RNAs (ceRNAs) and immune status in the tumor microenvironment (TME) can affect the progression of gastric cancer (GC), and are closely related to the prognosis of patients. However, few studies have linked the two to jointly determine the prognosis of patients with GC. This study aimed to develop a combined prognostic model based on ceRNAs and immune biomarkers.

Methods

First, the gene expression profiles and clinical information were downloaded from TCGA and GEO databases. Then two ceRNA networks were constructed on the basis of circRNA. Afterwards, the key genes were screened by univariate Cox regression analysis and Lasso regression analysis, and the ceRNA-related prognostic model was constructed by multivariate Cox regression analysis. Next, CIBERSORT and ESTIMATE algorithms were utilized to obtain the immune cell infiltration abundance and stromal/immune score in TME. Furthermore, the correlation between ceRNAs and immunity was found out through co-expression analysis, and another immune-related prognosis model was established. Finally, combining these two models, a comprehensive prognostic model was built and visualized with a nomogram.

Results

The (circRNA, lncRNA)-miRNA-mRNA regulatory network of GC was constructed. The predictive power of ceRNA-related and immune-related prognosis models was moderate. Co-expression analysis showed that the ceRNA network was correlated with immunity. The integrated model of combined ceRNAs and immunity in the TCGA training set, the AUC values of 1, 3, and 5-year survival rates were 0.78, 0.76, and 0.78, respectively; in the independent external validation set GSE62254, they were 0.81, 0.79, and 0.78 respectively; in GSE15459, they were 0.84, 0.88 and 0.89 respectively. Besides, the prognostic score of the comprehensive model can predict chemotherapeutic drug resistance. Moreover, we found that plasma variant translocation 1 (PVT1) and infiltrating immune cells (mast cells) are worthy of further investigation as independent prognostic factors.

Conclusions

Two ceRNA regulatory networks were constructed based on circRNA. At the same time, a comprehensive prognosis model was established, which has a high clinical significance for prognosis prediction and chemotherapy drug selection of GC patients.

Mitochondrial Aldehyde Dehydrogenase 2 Represents a Potential Biomarker of Biochemical Recurrence in Prostate Cancer Patients

BACKGROUND

We aimed to explore the role of mitochondrial aldehyde dehydrogenase 2 (ALDH2) in prostate cancer (PCa) patients and provide insights into the tumor immune microenvironment (TME) for those patients undergoing radical radiotherapy.

METHODS

We performed all analyses using R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish network of competing endogenous RNAs (ceRNAs).

RESULTS

Downregulation of ADLH2 was significantly associated with higher risk of BCR-free survival (HR: 0.40, 95%CI: 0.24-0.68, p = 0.001) and metastasis-free survival (HR: 0.21, 95%CI: 0.09-0.49, p = 0.002). Additionally, ALDH2 repression contributed to significantly shorter BCR-free survival in the TCGA database (HR: 0.55, 95%CI: 0.33-0.93, p = 0.027). For immune checkpoints, patients that expressed a higher level of CD96 had a higher risk of BCR than their counterparts (HR: 1.79, 95%CI: 1.06-3.03, p = 0.032), as well as NRP1 (HR: 2.18, 95%CI: 1.29-3.69, p = 0.005). In terms of the TME parameters, the spearman analysis showed that ALDH was positively associated with B cells (r: 0.13), CD8+ T cells (r: 0.19), neutrophils (r: 0.13), and macrophages (r: 0.17). Patients with higher score of neutrophils (HR: 1.75, 95%CI: 1.03-2.95, p = 0.038), immune score (HR: 1.92, 95%CI: 1.14-3.25, p = 0.017), stromal score (HR: 2.52, 95%CI: 1.49-4.26, p = 0.001), and estimate score (HR: 1.81, 95%CI: 1.07-3.06, p = 0.028) had higher risk of BCR than their counterparts. Our ceRNA network found that PART1 might regulate the expression of ALDH via has-miR-578 and has-miR-6833-3p. Besides, PHA-793887, PI-103, and piperlongumine had better correlations with ALDH2.

CONCLUSIONS

We found that ALDH2 might serve as a potential biomarker predicting biochemical recurrence for PCa patients.

Deregulation of ceRNA Networks in Frontal Cortex and Choroid Plexus of Brain during SARS-CoV-2 Infection Aggravates Neurological Manifestations: An Insight from Bulk and Single-Cell Transcriptomic Analyses

Although transcriptomic studies of SARS-CoV-2-infected brains have depicted variability in gene expression, the landscape of deregulated cell-specific regulatory circuits has not been elucidated yet. Hence, bulk and single-cell RNA-seq data are analyzed to gain detailed insights. Initially, two ceRNA networks with 19 and 3 differentially expressed (DE) hub lncRNAs are reconstructed in SARS-CoV-2 infected Frontal Cortex (FC) and Choroid Plexus (CP), respectively. Functional and pathway enrichment analyses of downstream mRNAs of deregulated ceRNA axes demonstrate impairment of neurological processes. Mapping of hub lncRNA-mRNA pairs from bulk RNA-seq with snRNA-seq data has indicated that NORAD, NEAT1, and STXBP5-AS1 are downregulated across 4, 4, and 2 FC cell types, respectively. At the same time, MIRLET7BHG and MALAT1 are upregulated in excitatory neurons of FC and neurons of CP, respectively. Here, it is hypothesized that downregulation of NORAD, NEAT1, and STXBP5-AS1, and upregulation of MIRLET7BHG and MALAT1 might deregulate respectively 51, 6, and 37, and 31 and 19 mRNAs in cell types of FC and CP. Afterward, 13 therapeutic miRNAs are traced that might safeguard against deregulated lncRNA-mRNA pairs of NORAD, NEAT1, and MIRLET7BHG in FC. This study helps to explain the plausible mechanism of post-COVID neurological manifestation and also to devise therapeutics against it.

Identification of the ferroptosis-related ceRNA network related to prognosis and tumor immunity for gastric cancer

Gastric cancer (GC) is a highly invasive course and has a very poor prognosis. Because there are no obvious symptoms in the early stage, most patients with GC are diagnosed in the late stage. The effective diagnosis, prognosis biomarkers and treatment targets of GC can solve this problem to a great extent. Although researchers have done a lot of research on GC in recent years, the relationship between the competing endogenous RNA (ceRNA) network of ferroptosis-related genes and the GC remains to be explored. Therefore, the research done in this paper has become particularly important. Download the expression data and clinical survival data about stomach adenocarcinoma from UCSC Xena and The Cancer Genome Atlas (TCGA) platform. Using bioinformatics tools to screen lncRNAs, miRNAs and mRNAs that are differentially expressed in GC samples and normal samples and related to the prognosis of GC. Then, screening lncRNAs, miRNAs and mRNAs with targeted relationships from the Starbase database. Subsequently, correlation analysis and survival analysis were carried out respectively. Finally, we get a ceRNA network related to the prognosis of GC patients. Cell experiments confirmed the results obtained by bioinformatics. This is critical for the discovery of the diagnosis, prognosis biomarkers and treatment targets.

Comprehensive bioinformatic analyses of lncRNA-mediated ceRNA network for uterine corpus endometrial carcinoma

Background

Given that long non-coding RNAs (lncRNAs) involved in the tumor initiation or progression of the endometrium and that competing endogenous RNA (ceRNA) plays an important role in increasingly more biological processes, lncRNA-mediated ceRNA is likely to function in the pathogenesis of uterine corpus endometrial carcinoma (UCEC). Our present study aimed to explore the potential molecular mechanisms for the prognosis of UCEC through a lncRNA-mediated ceRNA network.

Methods

The transcriptome profiles and corresponding clinical profiles of UCEC dataset were retrieved from Clinical Proteomic Tumor Analysis Consortium (CPTAC) and The Cancer Genome Atlas (TCGA) databases respectively. Differentially expressed genes (DEGs) in UCEC samples were identified via "Edge R" package. Then, an integrated bioinformatics analysis including functional enrichment analysis, tumor infiltrating immune cell (TIIC) analysis, Kaplan-Meier curve, Cox regression analysis were conducted to analyze the prognostic biomarkers.

Results

In the CPTAC dataset of UCEC, a ceRNA network comprised of 36 miRNAs, 123 lncRNAs and 124 targeted mRNAs was established, and 8 of 123 prognostic-related Differentially Expressed long noncoding RNAs (DElncRNAs) were identified. While in the TCGA dataset, a ceRNA network comprised of 38 miRNAs, 83 lncRNAs and 110 targeted mRNAs was established, and 2 of 83 prognostic-related DElncRNAs were identified. After filtered by risk grouping and Cox regression analysis, 10 prognostic-related lncRNAs including LINC00443, LINC00483, C2orf48, TRBV11-2, MEG-8 were identified. In addition, 33 survival-related Differentially Expressed messenger RNA (DEmRNAs) in two ceRNA networks were further validated in the Human Protein Atlas Portal (HPA) database. Finally, six lncRNA/miRNA/mRNA axes were established to elucidate prognostic regulatory roles in UCEC.

Conclusions

Several prognostic lncRNAs are identified and prognostic model of lncRNA-mediated ceRNA network is constructed, which promotes the understanding of UCEC development mechanisms and potential therapeutic targets.

Identification of lncRNA/circRNA-miRNA-mRNA ceRNA Network as Biomarkers for Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) accounts for the majority of liver cancer, with the incidence and mortality rates increasing every year. Despite the improvement of clinical management, substantial challenges remain due to its high recurrence rates and short survival period. This study aimed to identify potential diagnostic and prognostic biomarkers in HCC through bioinformatic analysis.

Methods: Datasets from GEO and TCGA databases were used for the bioinformatic analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were carried out by WebGestalt website and clusterProfiler package of R. The STRING database and Cytoscape software were used to establish the protein-protein interaction (PPI) network. The GEPIA website was used to perform expression analyses of the genes. The miRDB, miRWalk, and TargetScan were employed to predict miRNAs and the expression levels of the predicted miRNAs were explored via OncomiR database. LncRNAs were predicted in the StarBase and LncBase while circRNA prediction was performed by the circBank. ROC curve analysis and Kaplan-Meier (KM) survival analysis were performed to evaluate the diagnostic and prognostic value of the gene expression, respectively.

Results: A total of 327 upregulated and 422 downregulated overlapping DEGs were identified between HCC tissues and noncancerous liver tissues. The PPI network was constructed with 89 nodes and 178 edges and eight hub genes were selected to predict upstream miRNAs and ceRNAs. A lncRNA/circRNA-miRNA-mRNA network was successfully constructed based on the ceRNA hypothesis, including five lncRNAs (DLGAP1-AS1, GAS5, LINC00665, TYMSOS, and ZFAS1), six circRNAs (hsa_circ_0003209, hsa_circ_0008128, hsa_circ_0020396, hsa_circ_0030051, hsa_circ_0034049, and hsa_circ_0082333), eight miRNAs (hsa-miR-150-5p, hsa-miR-19b-3p, hsa-miR-23b-3p, hsa-miR-26a-5p, hsa-miR-651-5p, hsa-miR-10a-5p, hsa-miR-214-5p and hsa-miR-486-5p), and five mRNAs (CDC6, GINS1, MCM4, MCM6, and MCM7). The ceRNA network can promote HCC progression via cell cycle, DNA replication, and other pathways. Clinical diagnostic and survival analyses demonstrated that the ZFAS1/hsa-miR-150-5p/GINS1 ceRNA regulatory axis had a high diagnostic and prognostic value.

Conclusion: These results revealed that cell cycle and DNA replication pathway could be potential pathways to participate in HCC development. The ceRNA network is expected to provide potential biomarkers and therapeutic targets for HCC management, especially the ZFAS1/hsa-miR-150-5p/GINS1 regulatory axis.

Construction and analysis of a competing endogenous RNA network associated with circRNAs dysregulated in medial temporal lobe epilepsy

The aetiology and pathogenesis of medial temporal lobe epilepsy (MTLE) remain unclear, and effective treatments are lacking. The involvement of a dysregulated competing endogenous RNA (ceRNA) network in MTLE is only partially understood. The purpose of this study was to investigate MTLE regulatory networks composed of messenger RNAs (mRNAs), circular RNAs (circRNAs), long non-coding RNAs (lncRNAs), and microRNAs (miRNAs) through a ceRNA network map. RNA sequencing (RNA-seq) and small RNA-seq were used to detect mRNAs, circRNAs, miRNAs, and lncRNAs differentially expressed between post-operation hippocampal tissues of MTLE patients (n = 3) and paracancer tissues (n = 3). We performed bioinformatics analysis to identify differentially expressed RNAs and construct the corresponding ceRNA network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of differentially expressed RNAs were conducted to explore the biological processes and pathways involved in MTLE. We identified 352 differentially expressed mRNAs, 179 circRNAs, and 42 miRNAs in MTLE. A ceRNA network composed of mRNAs, circRNAs, and miRNAs was constructed. GO and KEGG analysis of the network suggested a key role of synapses and mTOR, cAMP, ErbB, FoxO, and HIF-1 signalling pathways in MTLE. We identify a new circRNA-miRNA-mRNA ceRNA network in MTLE. These results can help clarify the aetiology of MTLE and identify targeted molecular therapies.

Analyses of circRNA and mRNA Profiles in Vogt-Koyanagi-Harada Disease

Recent studies revealed that circular RNAs (circRNAs) are important in numerous biological process and involved in autoimmune diseases. However, their role in Vogt-Koyanagi-Harada (VKH) disease, a classical autoimmune disease, is not yet known. This research aimed to study the expression profile of mRNAs, microRNAs (miRNAs) and circRNAs and investigate the influence of circRNAs on the pathogenesis of VKH disease. We identified circRNAs, miRNAs, and mRNAs expression profiles in CD4⁺ T cells between 4 VKH patients and 3 healthy controls using the whole-transcriptome sequencing (RNA-seq) technique. We discovered that a total of 5088 mRNAs, 451 circRNAs and 433 miRNAs were differently expressed. The GO and KEGG pathway enrichment analyses were performed for significantly differentially expressed circRNAs and mRNAs. GSEA was conducted for all mRNAs. The functional enrichment suggested that the inflammatory response, the adaptive immune response, NF-kappa B signaling pathway, Th17 cell differentiation, Th1 and Th2 cell differentiation and T cell receptor signaling pathway were associated with VKH disease. In addition, based on the immune-related genes we screened, the circRNA-miRNA-mRNA ceRNA network was analyzed and constructed. Ten differently expressed mRNAs (LAT, ZAP70, ITK, ICOS, RASGRP1, PAG1, PLCG1, PRKCQ, LCK, CARD11) and 5 differently expressed circRNAs (hsa_circ_0033144, hsa_circ_0000233, hsa_circ_0000396, hsa_circ_0001924, hsa_circ_0001320) were selected to be validated by Real-time qPCR (RT-qPCR). The results of RT-qPCR turned out to be consistent with RNA-seq data. Further analysis showed that hsa_circ_0001320 and hsa_circ_0001924 may serve as crucial candidate marker genes of VKH disease. These results reveal that circRNAs may have a crucial immunomodulatory function in the pathophysiological process of VKH disease.

Susceptibility Modules and Genes in Hypertrophic Cardiomyopathy by WGCNA and ceRNA Network Analysis

Background: We attempted to identify a regulatory competing endogenous RNA (ceRNA) network and a hub gene of Hypertrophic Cardiomyopathy (HCM). Methods: Microarray datasets of HCM tissue were obtained from NCBI Gene Expression Omnibus (GEO) database. The R package "limma" was used to identify differentially expressed genes. Online search databases were utilized to match the relation among differentially expressed long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and mRNAs. Weighted correlation network analysis (WGCNA) was used to identify the correlations between key modules and HCM. STRING database was applied to construct PPI networks. Gene Set Enrichment Analysis (GSEA) was used to perform functional annotations and verified the hub genes. Results: A total of 269 DE-lncRNAs, 63 DE-miRNAs and 879 DE-mRNAs were identified in myocardial tissues from microarray datasets GSE130036, GSE36946 and GSE36961, respectively. According to online databases, we found 1 upregulated miRNA hsa-miR-184 that was targeted by 2 downregulated lncRNAs (SNHG9, AC010980.2), potentially targeted 2 downregulated mRNAs (LRRC8A, SLC7A5). 3 downregulated miRNAs (hsa-miR-17-5p, hsa-miR-876-3p, hsa-miR-139-5p) that were targeted by 9 upregulated lncRNAs, potentially targeted 21 upregulated mRNAs. Black and blue modules significantly related to HCM were identified by WGCNA. Hub gene IGFBP5 regulated by hsa-miR-17-5p, AC007389.5, AC104667.1, and AC002511.2 was identified. GSEA indicated that IGFBP5 might involve in the synthesis of myosin complex, participate in kinesin binding, motor activity and function via the regulation of actin cytoskeleton. Conclusion: The results provide a potential molecular regulatory mechanism for the diagnosis and treatment of HCM. IGFBP5 might play an important role in the progression of HCM.

Identification and Validation of a Potent Multi-lncRNA Molecular Model for Predicting Gastric Cancer Prognosis

Gastric cancer (GC) remains the third deadliest malignancy in China. Despite the current understanding that the long noncoding RNAs (lncRNAs) play a pivotal function in the growth and progression of cancer, their prognostic value in GC remains unclear. Therefore, we aimed to construct a polymolecular prediction model by employing a competing endogenous RNA (ceRNA) network signature obtained by integrated bioinformatics analysis to evaluate patient prognosis in GC. Overall, 1,464 mRNAs, 14,376 lncRNAs, and 73 microRNAs (miRNAs) were found to be differentially expressed in GC. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that these differentially expressed RNAs were mostly enriched in neuroactive ligand–receptor interaction, chemical carcinogenesis, epidermis development, and digestion, which were correlated with GC. A ceRNA network consisting of four lncRNAs, 21 miRNAs, and 12 mRNAs were constructed. We identified four lncRNAs (lnc00473, H19, AC079160.1, and AC093866.1) as prognostic biomarkers, and their levels were quantified by qRT-PCR in cancer and adjacent noncancerous tissue specimens. Univariable and multivariable Cox regression analyses suggested statistically significant differences in age, stage, radiotherapy, and risk score groups, which were independent predictors of prognosis. A risk prediction model was created to test whether lncRNAs could be used as an independent risk predictor of GC or not. These novel lncRNAs’ signature independently predicted overall survival in GC (p < 0.001). Taken together, this study identified a ceRNA and protein–protein interaction networks that significantly affect GC, which could be valuable for GC diagnosis and therapy.

The Construction and Analysis of Infiltrating Immune Cell and ceRNA Networks in Diabetic Foot Ulcer

BACKGROUND

Diabetic foot ulcer (DFU) is a severe complication characterized by low-grade infectious inflammation and probably associated with specific competitive endogenous RNAs (ceRNAs) and infiltrating immune cells. Nonetheless, no reliable biomarkers are used for detecting infectious inflammation in DFU. Therefore, it is essential to explore potential biomarkers for the accurate diagnosis and treatment of DFU.

METHODS

The gene expression profile was retrieved from Gene Expression Omnibus (GEO) database and divided into two groups, namely, standard samples and DFU samples. To establish the ceRNA networks, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were utilized to analyze differential expression genes (DEGs). The cell type identification was achieved by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm to screen-specific immune-infiltrating cells associated with DFU.

RESULTS

A ceRNA network was constructed with 20 differential expression circRNA (DEcircRNAs), 11 differential expression microRNAs (DEmiRNAs), and 9 differential expression mRNAs (DEmRNAs). Functional enrichment analysis demonstrated that DFU was mainly enriched in vascular endothelial growth factor (VEGF) and T-cell receptor signaling. In addition, CIBERSORT estimation indicated that CD8⁺ T cells and Monocytes were significantly related to the expression of IL-6, a DFU-specific infectious inflammation factor.

CONCLUSION

This study identified that some significant ceRNAs (JUNB, GATA3, hsa-circ-0049271 and hsa-circ-0074559) and infiltrating immune cells (CD8⁺ T cells and monocytes) might be related to DFU infectious inflammation.

Long Non-Coding RNA-Mediated Competing Endogenous RNA Networks in Ischemic Stroke: Molecular Mechanisms, Therapeutic Implications, and Challenges

Ischemic stroke (IS) is a disease that is characterized by high mortality and disability. Recent studies have shown that LncRNA-mediated competing endogenous RNA (ceRNA) networks play roles in the occurrence and development of cerebral I/R injury by regulating different signaling pathways. However, no systematic analysis of ceRNA mechanisms in IS has been reported. In this review, we discuss molecular mechanisms of LncRNA-mediated ceRNA networks under I/R injury. The expression levels of LncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) and their effects in four major cell types of the neurovascular unit (NVU) are also involved. We further summarize studies of LncRNAs as biomarkers and therapeutic targets. Finally, we analyze the advantages and limitations of using LncRNAs as therapeutics for IS.

Construction of a ceRNA Network and Analysis of Tumor Immune Infiltration in Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is characterized by high malignancy, frequent metastasis, and recurrence with an unfavorable prognosis. This study is aimed at constructing a prognostic model for tumor-infiltrating immune cells and a competing endogenous RNA (ceRNA) network in PAAD and analyzing susceptibilities of chemotherapy and immunotherapy of PAAD. Gene expression profiles and clinical information of PAAD were downloaded from The Cancer Genome Atlas (TCGA) database and divided into the tumor group and the normal group. A total of five PAAD survival-related key genes in the ceRNA network and three survival-related immune infiltrating cells were uncovered, and two survival risk models and nomograms were constructed. The efficiency and performance of the two models were verified using multi-index area under the curve analysis at different time points, decision curve analysis, and calibration curves. Co-expression analysis showed that LRRC1, MIR600HG, and RNF166 in the ceRNA network and tumor-infiltrating immune cells including CD8 T cells and M1 macrophages were likely related to the PAAD prognosis, and the expression of key ceRNA-related genes was experimently validated in tissues and cell lines by RT-qPCR. Patients with low risk scores for key genes in the ceRNA network displayed a positive response to anti-programmed death-1 (PD-1) treatment and greater sensitivity to chemotherapeutic drugs such as docetaxel, lapatinib, and paclitaxel. More importantly, our results suggested that the IC50 values of gemcitabine in PAAD were not significantly different between the high and low risk groups. The expression levels of immune checkpoints were significantly different in the high-risk and low-risk groups. The prognostic model, nomogram, and drug analysis may provide an essential reference for PAAD patient management in the clinic.

The Construction and Analysis of ceRNA Network and Immune Infiltration in Kidney Renal Clear Cell Carcinoma

Background: Kidney renal clear cell carcinoma (KIRC) has the highest invasion, mortality and metastasis of the renal cell carcinomas and seriously affects patient’s quality of life. However, the composition of the immune microenvironment and regulatory mechanisms at transcriptomic level such as ceRNA of KIRC are still unclear.

Methods: We constructed a ceRNA network associated with KIRC by analyzing the long non-coding RNA (lncRNA), miRNA and mRNA expression data of 506 tumor tissue samples and 71 normal adjacent tissue samples downloaded from The Cancer Genome Atlas (TCGA) database. In addition, we estimated the proportion of 22 immune cell types in these samples through “The Cell Type Identification by Estimating Relative Subsets of RNA Transcripts.” Based on the ceRNA network and immune cells screened by univariate Cox analysis and Lasso regression, two nomograms were constructed to predict the prognosis of patients with KIRC. Receiver operating characteristic curves (ROC) and calibration curves were employed to assess the discrimination and accuracy of the nomograms. Consequently, co-expression analysis was carried out to explore the relationship between each prognostic gene in a Cox proportional hazards regression model of ceRNA and each survival-related immune cell in a Cox proportional hazards regression model of immune cell types to reveal the potential regulatory mechanism.

Results: We established a ceRNA network consisting of 12 lncRNAs, 25 miRNAs and 136 mRNAs. Two nomograms containing seven prognostic genes and two immune cells, respectively, were successfully constructed. Both ROC [area under curves (AUCs) of 1, 3, and 5-year survival in the nomogram based on ceRNA network: 0.779, 0.747, and 0.772; AUCs of 1, 3, and 5-year survivals in nomogram based on immune cells: 0.603, 0.642, and 0.607] and calibration curves indicated good accuracy and clinical application value of both models. Through co-correlation analysis between ceRNA and immune cells, we found both LINC00894 and KIAA1324 were positively correlated with follicular helper T (Tfh) cells and negatively correlated with resting mast cells.

Conclusion: Based on the ceRNA network and tumor-infiltrating immune cells, we constructed two nomograms to predict the survival of KIRC patients and demonstrated their value in improving the personalized management of KIRC.

AC016405.3 functions as an oncogenic long non-coding RNA by regulating ERBB3 via sponging miR-22-3p in breast cancer

Background

Increasing studies reported that long non‐coding RNAs are involved in regulating breast cancer (BRCA) progression. However, the specific roles and mechanisms of lncRNAs in BRCA remain largely unknown. Here, we sought to explore the functions and mechanisms of AC016405.3 in BRCA progression.

Methods

Bioinformatic analysis for AC016405.3, miR‐22‐3p, and ERBB3 were performed on starBase. The expressions of AC016405.3, miR‐22‐3p, and ERBB3 were examined by RT‐qPCR. The functions of AC016405.3 on the proliferation, migration, and invasion of cells were evaluated by conducting CCK‐8, colony formation, wound‐healing, and Transwell assays. The subcellular distribution of AC016405.3 in BRCA cells was identified by performing fluorescence in situ hybridization (FISH) and subcellular fractionation techniques. Dual‐luciferase assay was applied to validate the interactions of miR‐22‐3p with AC016405.3 or ERBB3. The interaction between ERBB3 and miR‐22‐3p was also tested by Anti‐Ago2 RNA immunoprecipitation (RIP) assay.

Results

The results showed that AC016405.3 is highly expressed in BRCA tissues as well as cells and positively correlated with poor prognosis in BRCA patients. Silencing AC016405.3 obviously repressed the malignant behaviors of BRCA cells. Mechanistically, AC016405.3 functioned as a competing endogenous RNA (ceRNA) for miR‐22‐3p in the cytoplasm and sponged miR‐22‐3p to release its suppression of ERBB3. Rescue experiments revealed that the suppression role induced by AC016405.3 depletion on malignant behaviors of BRCA cells could be obviously counter by inhibiting miR‐22‐3p or overexpressing ERBB3.

Conclusion

AC016405.3 promotes BRCA progression by the derepression of ERBB3 via sponging miR‐22‐3p, which may represent a potential target for BRCA treatment.

MicroRNA-490-3p and -490-5p in carcinogenesis: Separate or the same goal?

MicroRNA (miR)-490-3p and miR-490-5p, located on chromosome 7q33, are two independent mature products of miR-490 exerting distinct effects on tumor progression. miR-490-3p and miR-490-5p possess antitumor properties. miR-490-3p dysfunction has been associated with malignancies including colorectal cancer, while the abnormal function of miR-490-5p has been more considerably associated with bladder cancer (for example). At present, there are 30 and 11 target genes of miR-490-3p and miR-490-5p, respectively, that have been experimentally verified, of which the cyclin D1 (CCND1) gene is a common target. Through these target genes, miR-490-3p and miR-490-5p are involved in 7 and 3 signaling pathways, respectively, of which only 2 are shared regulatory signaling pathways. The present review introduces two competing endogenous RNA (ceRNA) regulatory networks centered on miR-490-3p and miR-490-5p. These networks may be important promoters of tumor cell proliferation, invasiveness, metastatic potential and apoptosis. Unlike miR-490-5p, miR-490-3p plays a unique role in promoting cancer. However, both are promising molecular markers for early cancer diagnosis and prognosis. In addition, miR-490-3p was also found to be associated with the chemical resistance of cisplatin and paclitaxel. The present review focuses on the abnormal expression of miR-490-3p and miR-490-5p in different tumor types, and their complex ceRNA regulatory networks. The clinical value of miR-490-3p and miR-490-5p in cancer diagnosis, prognosis and treatment is also clarified, and an explanation for the opposing effects of miR-490-3p in tumor research is provided.

Prediction of a Competing Endogenous RNA Co-expression Network by Comprehensive Methods in Systemic Sclerosis-Related Interstitial Lung Disease

Systemic sclerosis (SSc) is an immune-mediated connective tissue disease characterized by fibrosis of multi-organs, and SSc-related interstitial lung disease (SSc-ILD) is a leading cause of morbidity and mortality. To explore molecular biological mechanisms of SSc-ILD, we constructed a competing endogenous RNA (ceRNA) network for prediction. Expression profiling data were obtained from the Gene Expression Omnibus (GEO) database, and differential expressed mRNAs and miRNAs analysis was further conducted between normal lung tissue and SSc lung tissue. Also, the interactions of miRNA–lncRNA, miRNA–mRNA, and lncRNA–mRNA were predicted by online databases including starBase, LncBase, miRTarBase, and LncACTdb. The ceRNA network containing 11 lncRNAs, 7 miRNAs, and 20 mRNAs were constructed. Based on hub genes and miRNAs identified by weighted correlation network analysis (WGCNA) method, three core sub-networks—SNHG16, LIN01128, RP11-834C11.4(LINC02381)/hsa-let-7f-5p/IL6, LINC01128/has-miR-21-5p/PTX3, and LINC00665/hsa-miR-155-5p/PLS1—were obtained. Combined with previous studies and enrichment analyses, the lncRNA-mediated network affected LPS-induced inflammatory and immune processes, fibrosis development, and tumor microenvironment variations. The ceRNA network, especially three core sub-networks, may be served as early biomarkers and potential targets for SSc, which also provides further insights into the occurrence, progression, and accurate treatment of SSc at the molecular level.

Transcriptomic analysis and competing endogenous RNA network in the human endometrium between proliferative and mid-secretory phases

Successful embryo implantation is the first step for establishing natural pregnancy and is dependent on the crosstalk between the embryo and a receptive endometrium. However, the molecular signaling events for successful embryo implantation are not entirely understood. To identify differentially expressed transcripts [long-noncoding RNAs (lncRNAs), microRNAs (miRNAs) and mRNAs] and competing endogenous RNA (ceRNA) networks associated with endometrial receptivity, the current study analyzed gene expression profiles between proliferative and mid-secretory endometria in fertile women. A total of 247 lncRNAs, 67 miRNAs and 2,154 mRNAs were identified as differentially expressed between proliferative and mid-secretory endometria. Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that these differentially expressed genes were significantly enriched for 'cell adhesion molecules.' Additionally, 98 common mRNAs were significantly involved in tryptophan metabolism, metabolic pathways and FoxO signaling. From the differentially expressed lncRNA/miRNA/mRNA ceRNA network, hub RNAs that formed three axes were identified: The DLX6-AS1/miR-141 or miR-200a/OLFM1 axis, the WDFY3-AS2/miR-135a or miR-183/STC1 axis, and the LINC00240/miR-182/NDRG1 axis. These may serve important roles in the regulation of endometrial receptivity. The hub network of the current study may be developed as a candidate marker for endometrial receptivity.

Identification of Prognostic Biomarkers and Correlation With Immune Infiltrates in Hepatocellular Carcinoma Based on a Competing Endogenous RNA Network

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Recently, competing endogenous RNAs (ceRNA) have revealed a significant role in the progression of HCC. Herein, we aimed to construct a ceRNA network to identify potential biomarkers and illustrate its correlation with immune infiltration in HCC.

Methods

RNA sequencing data and clinical traits of HCC patients were downloaded from TCGA. The limma R package was used to identify differentially expressed (DE) RNAs. The predicted prognostic model was established using univariate and multivariate Cox regression. A K-M curve, TISIDB and GEPIA website were utilized for survival analysis. Functional annotation was determined using Enrichr and Reactome. Protein-to-protein network analysis was implemented using SRTNG and Cytoscape. Hub gene expression was validated by quantitative polymerase chain reaction, Oncomine and the Hunan Protein Atlas database. Immune infiltration was analyzed by TIMMER, and Drugbank was exploited to identify bioactive compounds.

Results

The predicted model that was established revealed significant efficacy with 3- and 5-years of the area under ROC at 0.804 and 0.744, respectively. Eleven DEmiRNAs were screened out by a K-M survival analysis. Then, we constructed a ceRNA network, including 56 DElncRNAs, 6 DEmiRNAs, and 28 DEmRNAs. The 28 DEmRNAs were enriched in cancer-related pathways, for example, the TNF signaling pathway. Moreover, six hub genes, CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1, were all overexpressed in HCC tissues and independently correlated with survival rate. Furthermore, expression of hub genes was related to immune cell infiltration in HCC, including B cells, CD8⁺ T cells, CD4⁺ T cells, monocytes, macrophages, neutrophils, and dendritic cells.

Conclusion

The findings from this study demonstrate that CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1 are closely associated with prognosis and immune infiltration, representing potential therapeutic targets or prognostic biomarkers in HCC.

Roles of the SNHG7/microRNA‑9‑5p/DPP4 ceRNA network in the growth and 131I resistance of thyroid carcinoma cells through PI3K/Akt activation

Radioactive iodine (RAI, ¹³¹I) therapy is the main treatment for thyroid carcinoma (TC). Long noncoding RNA (lncRNA)/microRNA (miR) competing endogenous RNA (ceRNA) networks have aroused great interest for their roles in gene expression. The present study aimed to investigate the effect of lncRNA SNHG7 on the growth and ¹³¹I resistance of TC. Differentially expressed lncRNAs in TC and paracancerous tissues were analyzed. The binding of miR-9-5p with small nucleolar RNA host gene 7 (SNHG7) and dipeptidyl-peptidase 4 (DPP4) was identified. Gain- and loss-of-function analyses of SNHG7 and miR-9-5p were performed to determine their effects on the growth and ¹³¹I resistance of TC cells. The activity of the PI3K/Akt pathway was evaluated. Consequently, upregulated SNHG7 was revealed in TC tissues and correlated with ¹³¹I resistance. Silencing of SNHG7 or overexpressing miR-9-5p inhibited the growth and ¹³¹I resistance of TC cells. SNHG7 acted as a ceRNA of miR-9-5p to enhance DPP4 expression. Overexpressed SNHG7 increased DPP4 expression and activated the PI3K/Akt signaling pathway by sponging miR-9-5p. The in vitro results were reproduced in vivo. In summary, the present study provided evidence that the SNHG7/miR-9-5p/DPP4 ceRNA network could promote the growth and ¹³¹I resistance of TC cells via PI3K/Akt activation. The present study may offer novel options for TC treatment.

Circular RNA and Messenger RNA Expression Profile and Competing Endogenous RNA Network in Subchondral Bone in Osteonecrosis of the Femoral Head

Osteonecrosis of the femoral head (ONFH) is a common and destructive orthopedic disease, of which the pathogenesis mechanism remains elusive. Limited studies have been conducted to investigate the role of circular RNAs (circRNAs) in subchondral bone in ONFH. This study aimed to profile differential expression of circRNAs and messenger RNAs (mRNAs) in subchondral bone obtained from ONFH patients by next-generation sequencing, and explore the potential regulatory relationship of these molecules in ONFH by bioinformatics analysis. As a result, we detected 74 aberrantly expressed circRNAs and 121 differentially expressed mRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses indicated several vital biological processes and signaling pathways, which are primarily related to osteogenic capacity influenced by osteoblasts and osteoclasts. Furthermore, attempting construction of protein-protein interaction network with 57 aberrant genes and competing endogenous RNA network with 3 selected circRNAs preliminarily revealed the regulatory roles and the relationships of these molecules in ONFH. In addition, the potential association of circRNAs in our networks with the molecular mechanism of ONFH was validated by real time-quantitative PCR. In conclusion, our findings may promote understanding the mechanism of ONFH, and offer a novel insight into early diagnosis and intervention of ONFH.

Development and validation of a novel prognostic signature in gastric adenocarcinoma

Competing endogenous RNA networks have attracted increasing attention in gastric adenocarcinoma (GA). The current study aimed to explore ceRNA-based prognostic biomarkers for GA. RNA expression profiles were downloaded from TCGA and GEO databases. A ceRNA network was constructed based on the most relevant modules in the weighted gene coexpression network analysis. Kaplan-Meier (KM) survival analysis revealed prognosis-related RNAs, which were subjected to the multivariate Cox regression analysis. The predictive accuracy and discriminative ability of the signature were determined by KM analyses, receiver operating characteristic curves and area under the curve values. Ultimately, we constructed a ceRNA network consisting of 55 lncRNAs, 17 miRNAs and 73 mRNAs. Survival analyses revealed 3 lncRNAs (LINC01106, FOXD2-AS1, and AC103702.2) and 3 mRNAs (CCDC34, ORC6, and SOX4) as crucial prognostic factors; these factors were then used to construct a survival specific ceRNA network. Patients with high risk scores exhibited significantly worse overall survival than patients with low risk scores, and the AUC for 5-year survival was 0.801. A total of 112 GA specimens and the GSE84437 dataset were used to successfully validate the robustness of our signature by qRT-PCR. In summary, we developed a prognostic signature for GA, that shows better accuracy than the traditional TNM pathological staging system.

Identification of RNA Transcript Makers Associated With Prognosis of Kidney Renal Clear Cell Carcinoma by a Competing Endogenous RNA Network Analysis

Objective

This study aims to identify several RNA transcripts associated with the prognosis of kidney renal clear cell carcinoma (KIRC).

Methods

The differentially expressed mRNAs, lncRNAs, and miRNAs (DEmRNAs, DElncRNAs, and DEmiRNAs) between KIRC cases and controls were screened based on an RNA-seq dataset from The Cancer Genome Atlas (TCGA) database. Subsequently, miRcode, miRDB, and TargetScan database were used to predict interactions between lncRNAs, miRNAs and target mRNAs. Then, a ceRNA network was built using miRNAs-mRNAs and lncRNAs-miRNAs pairs. Functional analysis of mRNAs in ceRNA was performed. Finally, the survival analysis of RNA transcripts in ceRNA network and correlation analysis for key RNA regulators were carried out.

Results

There were 1527 DElncRNAs, 54 DEmiRNAs, and 2321 DEmRNAs. A ceRNA network was constructed among 81 lncRNAs, 9 miRNAs, and 197 mRNAs. Functional analysis showed that numerous mRNAs were significantly associated with regulation of cellular glucuronidation. In addition, 35 lncRNAs, 84 mRNAs and two miRNAs were significantly corelated to the survival of patients with KIRC (P < 0.05). Among them, miRNA-21 and miRNA-155 were negatively related to three lncRNAs (LINC00472, SLC25A5.AS1, and TCL6). Seven mRNA targets of miRNA-21 (FASLG, FGF1, TGFBI, ALX1, SLC30A10, ADCY2, and ABAT) and 12 mRNAs targets of miRNA-155 (STXBP5L, SCG2, SPI1, C12orf40, TYRP1, CTHRC1, TDO2, PTPRQ, TRPM8, ERMP1, CD36, and ST9SIA4) also acted as prognostic biomarkers for KIRC patients.

Conclusion

We screened numerous novel prognosis-related RNA markers for KIRC patients by a ceRNA network analysis, providing deeper understandings of prognostic values of RNA transcripts for KIRC.

Comprehensive Construction of a Circular RNA-Associated Competing Endogenous RNA Network Identified Novel Circular RNAs in Hypertrophic Cardiomyopathy by Integrated Analysis

Hypertrophic cardiomyopathy (HCM), the most common heritable cardiomyopathy, is associated with a high risk of sudden cardiac death. The complexity and behavior of the circular RNA (circRNA)-associated competing endogenous RNA (ceRNA) network in HCM have not been thoroughly elucidated. Plasma circRNA and messenger RNA (mRNA) expression profiles were acquired by using a microarray. Weighted correlation network analysis (WGCNA) and linear models for microarray data (Limma) were used to analyze microarray data. Gene modules, consisting of genes with high correlations, were detected and represented by a designated color. The ceRNA network, including circRNA, microRNA (miRNA), and mRNA, was constructed based on the “ceRNA hypothesis” using an integrated systems biology method. By WGCNA, two modules, namely magenta and red modules, were identified as being positively correlated with HCM. In the combined analysis of WGCNA and Limma, 36 hub circRNAs in the magenta module and 83 hub circRNAs in the red module were significantly upregulated compared with the controls. By coexpression analysis, 270 circRNA–mRNA pairs were identified with a coefficient ≥0.9 and p < 0.05. With Starbase and miRWalk tools, circRNA–miRNA pairs and miRNA–mRNA pairs were predicted. Once these pairs were combined, the ceRNA network with 6 circRNAs, 29 miRNAs, and 6 mRNAs was constructed. Functional analysis demonstrated that these circRNAs in the ceRNA network were associated with calcium-release channel activity and muscle filament sliding. Our study provided a global perspective and systematic analysis of the circRNA-associated ceRNA network in HCM. The identified circRNAs hsa_circ_0043762, hsa_circ_0036248, and hsa_circ_0071269 may be key regulators involved in HCM pathogenesis.

Integrated Analysis of a Risk Score System Predicting Prognosis and a ceRNA Network for Differentially Expressed lncRNAs in Multiple Myeloma

Long non-coding RNAs (lncRNAs) are non-protein-coding RNAs longer than 200 nucleotides. Accumulating evidence demonstrates that lncRNA is a potential biomarker for cancer diagnosis and prognosis. However, there are no prognostic biomarkers and lncRNA models for multiple myeloma (MM). Hence, it is necessary to screen novel lncRNA that can potentially participate in the initiation and progression of MM and consequently construct a risk score system for the disease. Raw microarray datasets were obtained from the Gene Expression Omnibus website. Weighted gene co-expression network analysis and principal component analysis identified 12 lncRNAs of interest. Then, univariate, least absolute shrinkage and selection operator Cox regression and multivariate Cox hazard regression analysis identified two lncRNAs (LINC00996 and LINC00525) that were formulated to construct a risk score system to predict survival. Receiver operating characteristic analysis certificated the superior performance in predicting 3-year overall survival (area under the curve = 0.829). The similar prognostic values of the two-lncRNA signature were also observed in the tested The Cancer Genome Atlas dataset. Furthermore, two other lncRNAs (LINC00324 and LINC01128) were differentially expressed between CD138+ plasma cells from normal donors and MM patients and were verified to be associated with cancer stage in the Gene Expression Omnibus dataset. A lncRNA-mediated competing endogenous RNA network, including 2 lncRNAs, 12 mitochondrial RNAs, and 103 target messenger RNAs, was constructed. In conclusion, we developed a two-lncRNA expression signature to predict the prognosis of MM and constructed a key lncRNA-based competing endogenous RNA network in MM. These lncRNAs were associated with survival and are probably involved in the occurrence and progression of MM.

A Novel Immune-Related Competing Endogenous RNA Network Predicts Prognosis of Acute Myeloid Leukemia

Background

Acute myeloid leukemia (AML) is a genetically, biologically and clinically heterogeneous hematopoietic malignancy that is highly dependent on the bone marrow (BM) microenvironment. Infiltrated immune cells and stromal cells are an important part of the BM microenvironment and significantly affect the progression of AML. Recently, the competing endogenous RNA hypothesis has gained great interests in the study of molecular and biological mechanisms of tumor occurrence and progression. However, research on how competing endogenous RNA relates to leukemia tumor microenvironment remains uninvestigated.

Methods

In this study, mRNA, miRNA and lncRNA data and clinical information of the AML cohort were obtained from The Cancer Genome Atlas (TCGA) database, and the immune and stromal scores were calculated using the ESTIMATE algorithm.

Results

We found that immune scores were significantly correlated with cytogenetic risk and overall survival, and also identified microenvironment-related mRNAs, miRNAs, and lncRNAs based on the immune and stromal scores. Differentially expressed mRNAs and lncRNAs were applied to weighted correlation network analysis (WGCNA) to identify the modules most relevant to the immune microenvironment of AML. Using miRNA database to predict miRNA-targeted genes, we established the immune-related competing endogenous RNA network consisting of 33 lncRNAs, 21 miRNAs and 135 mRNAs. Prognostic analysis was performed on the genes in the immune-related competing endogenous RNA network to screen out 15 lncRNAs, 2 miRNAs and 31 mRNAs with prognostic values.

Conclusion

In summary, we identified a novel immune-related mRNA-miRNA-lncRNA competing endogenous RNA network associated with the prognosis of AML, which may contribute to better understanding of the development and progression of AML and to serve as novel therapeutic targets.

The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration in Colon Adenocarcinoma Metastasis

BACKGROUND

Colon adenocarcinoma (COAD) is a malignant and lethal tumor in digestive system and distance metastasis lead to poor prognosis. The metastasis-specific ceRNAs (competitive endogenous RNAs) and tumor-infiltrating immune cells might associate with tumor prognosis and distance metastasis. Nonetheless, few studies have concentrated on ceRNAs and Immune cells in COAD.

METHODS

The gene expression profile and clinical information of COAD were downloaded from TCGA and divided into two groups: primary tumors with or without distance metastasis. We applied comprehensive bioinformatics methods to analyze differential expression genes (DEGs) related to metastasis and establish the ceRNA networks. The Cox analysis and Lasso regression were utilized to screen the pivotal genes and prevent overfitting. Based on them, the prognosis prediction nomograms were established. The cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was then applied to screen significant tumor immune-infiltrating cells associated with COAD metastasis and established another prognosis prediction model. Ultimately, co-expression analysis was applied to explore the relationship between key genes in ceRNA networks and significant immune cells. Multiple databases and preliminary clinical specimen validation were used to test the expressions of key biomarkers at the cellular and tissue levels.

RESULTS

We explored 1 significantly differentially expressed lncRNA, 1 significantly differentially expressed miRNA, 8 survival-related immune-infiltrating cells, 5 immune cells associated with distance metastasis. Besides, 3 pairs of important biomarkers associated with COAD metastasis were also identified: T cells follicular helper and hsa-miR-125b-5p (R = -0.200, P < 0.001), Macrophages M0 and hsa-miR-125b-5p (R = 0.170, P < 0.001) and Macrophages M0 and FAS (R = -0.370, P < 0.001). Multidimensional validation and preliminary clinical specimen validation also supported the results.

CONCLUSION

In this research, we found some significant ceRNAs (FAS and hsa-miR-125b-5p) and tumor-infiltrating immune cells (T cells follicular helper and Macrophages M0) might related to distance metastasis and prognosis of COAD. The nomograms could assist scientific and medical researchers in clinical management.

Development and validation of a four-microRNA signature for placenta accreta spectrum: an integrated competing endogenous RNA network analysis

Background

Placenta accreta spectrum (PAS) is a major cause of maternal morbidity and mortality in modern obstetrics, however, few studies have explored the underlying molecular mechanisms and biomarkers. In this study, we aimed to elucidate the regulatory RNA network contributing to PAS, comprising long non-coding (lnc), micro (mi), and messenger (m) RNAs, and identify biomarkers for the prediction of intraoperative blood volume loss.

Methods

Using RNA sequencing, we compared mRNA, lncRNA, and miRNA expression profiles between five PAS and five normal placental tissues. Furthermore, the miRNA expression profiles in maternal plasma samples from ten PAS and ten control participants were assessed. The data and clinical information were analyzed using R language and GraphPad Prism 7 software.

Results

Upon comparing PAS and control placentas, we identified 8,806 lncRNAs, 128 miRNAs, and 1,788 mRNAs that were differentially expressed. Based on a lasso regression analysis and correlation predictions, we developed a competing endogenous (ce) RNA network comprising 20 lncRNAs, 4 miRNAs, and 19 mRNAs. This network implicated a reduced angiogenesis pathway in PAS, and correlation analyses indicated that two miRNAs (hsa-miR‐490-3p and hsa-miR-133a-3p) were positively correlated to operation-related blood volume loss.

Conclusions

We identified a ceRNA regulatory mechanism in PAS, and two miRNAs that may potentially serve as biomarkers of PAS prognosis.

Construction of a Competitive Endogenous RNA Network for Pancreatic Adenocarcinoma Based on Weighted Gene Co-expression Network Analysis and a Prognosis Model

Pancreatic adenocarcinoma (PAAD) is a pancreatic disease with considerable mortality worldwide. Because of a lack of obvious symptoms at the early stage, most PAAD patients are diagnosed at the terminal stage and prognosis is usually poor. In this study, we firstly obtained RNA sequencing data of 181 patients with PAAD from The Cancer Genome Atlas (TCGA) database to identify early diagnostic biomarkers for PAAD. Survival-related mRNAs were identified using a weighted gene co-expression network analysis (WGCNA), and then a linear prognostic model of seven long non-coding RNAs (lncRNAs) was established using univariate and multivariate Cox proportional hazards regression analyses, which is verified using a time-dependent receiver operating characteristic (ROC) curve analysis. Finally, according to the survival analysis, we constructed a survival-related competing endogenous RNA (ceRNA) network. Our results showed that: (1) The upregulated genes related to cell cycle-related pathway (including homologous recombination, DNA replication and mismatch repair) in PAAD can increase the proliferation ability of cancer cells; (2) The 7-lncRNA signature can predict the overall survival (OS) of PAAD patients; and (3) The key mRNAs and lncRNAs are involved in mutual regulation in the ceRNA network.

Long non-coding RNA LINC00460 predicts poor survival and promotes cell viability in pancreatic cancer

Emerging evidence has demonstrated that long non-coding RNAs (lncRNAs) possess great potential as vital biomarkers and powerful therapeutic targets in various diseases. In the present study, differentially expressed transcripts in pancreatic cancer (PC) were identified, and a competing endogenous RNA (ceRNA) network was constructed using The Cancer Genome Atlas database. An independent cohort consisting of 59 patients with PC was used to validate the clinical value of the identified lncRNA. Cell viability and colony formation assays were used to evaluate the biological functions of the lncRNA in PC cells. The present bioinformatic analysis revealed that LINC00460 was upregulated in PC samples with a prognostic significance. In the ceRNA network, it potentially targeted the microRNA-503/cyclin D1 axis. The results of real-time quantitative PCR confirmed that LINC00460 was significantly upregulated in cancer tissues and was associated with poor survival of patients with PC. The expression levels of LINC00460 were significantly associated with tumor size, but not with age, sex, differentiation, lymph node metastasis, vascular invasion and tumor stage. Through univariate and multivariate analysis, LINC00460 was characterized as an independent prognostic biomarker for PC. Further in vitro experiments demonstrated that suppressing LINC00460 using small interfering RNA inhibited viability and colony formation of PC cells. In summary, LINC00460 may be an independent prognostic biomarker for PC and may serve as an oncogenic lncRNA that promotes PC cell growth. Further in-depth exploration is required to reveal the specific biological mechanism of LINC00460 in PC cells.

RNA-Seq Revealed a Circular RNA-microRNA-mRNA Regulatory Network in Hantaan Virus Infection

Hantaan virus (HTNV), a Hantavirus serotype that is prevalent in Asia, causes hemorrhagic fever with renal syndrome (HFRS) with high mortality in human race. However, the pathogenesis of HTNV infection remains elusive. Circular RNAs (circRNAs), a new type of non-coding RNAs, play a crucial role in various pathogenic processes. Nevertheless, circRNA expression profiles and their effects on pathogenesis of HTNV infection are still completely unknown. In the present study, RNA sequencing was performed to analyze the circRNA, microRNA (miRNA), and mRNA expression profiles in HTNV-infected and mock-infected human umbilical vein endothelial cells (HUVECs). A total of 70 circRNAs, 66 miRNAs, and 788 mRNAs were differently expressed. Several differentially expressed RNAs were validated by RT-qPCR. Moreover, we verified that some differentially expressed RNAs, such as circ_0000479, miR-149-5p, miR-330-5p, miR-411-3p, RIG-I, CMPK2, PARP10, and GBP1, promoted or inhibited HTNV replication. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis demonstrated that the host genes of differentially expressed circRNAs were principally involved in the innate immune response, the type I interferon (IFN) signaling pathway, and the cytokine-mediated signaling pathway. Additionally, the circRNA-miRNA-mRNA regulatory network was integrally analyzed. The data showed that there were many circRNA-miRNA-mRNA interactions in HTNV infection. By dual-luciferase reporter assay, we confirmed that circ_0000479 indirectly regulated RIG-I expression by sponging miR-149-5p, hampering viral replication. This study for the first time presents a comprehensive overview of circRNAs induced by HTNV and reveals that a network of enriched circRNAs and circRNA-associated competitive endogenous RNAs (ceRNAs) is involved in the regulation of HTNV infection, thus offering new insight into the mechanisms underlying HTNV-host interaction.

Analysis of lncRNA, miRNA and mRNA-associated ceRNA networks and identification of potential drug targets for drug-resistant non-small cell lung cancer

Background: Drug resistance to chemotherapeutic drugs or targeted medicines is an obstacle encountered in the treatment of non-small-cell lung cancer (NSCLC). However, the mechanisms of competing endogenous RNA (ceRNA) on the drug resistance in NSCLC are rarely reported. In this paper, the comprehensive expression profiles of lncRNAs and mRNAs in drug-resistant NSCLC cells were obtained by RNA sequencing.

Methods: The dysregulated lncRNAs, miRNAs and mRNAs in drug-resistant NSCLC cell lines were identified by RNA-sequencing and bioinformatics methods.

Results: A total of 39 dysregulated lncRNAs and 650 dysregulated mRNAs were identified between drug-resistant NSCLC cell lines and their parental cell lines. Additionally, 33 lncRNA-miRNA-mRNA pathways in the ceRNA network in drug-resistant NSCLC were constructed through bioinformatics methods and ceRNA regulatory rules. These comprised 12 dysregulated lncRNAs, five dysregulated miRNAs, and eight dysregulated mRNAs. In addition, lncRNA ATP2B1/miR-222-5p/TAB2 and lncRNA HUWE1/miR-222-5p/TAB2 were identified as potential ceRNA networks involved in drug resistance to NSCLC.

Conclusions: The current study provides a promising therapeutic strategy against the lncRNA-miRNA-mRNA ceRNA regulatory network for NSCLC treatment and deepens our comprehension of the ceRNA regulatory mechanisms related to drug resistance to NSCLC.

Investigation of circRNA Expression Profiles and Analysis of circRNA-miRNA-mRNA Networks in an Animal (Mouse) Model of Age-Related Macular Degeneration

PURPOSES

To (i) identify dysregulated circular RNAs (circRNAs) and (ii) elucidate their potential functions in an animal (mouse) model of choroidal neovascularization (CNV), a prominent feature of neovascular age-related macular degeneration (AMD).

METHODS

Expression profiles for circRNA were identified by microarray analysis. Selected circRNAs were confirmed by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). Bioinformatic analyses of identified circRNAs were performed to predict (i) circRNA/microRNA interactions and (ii) occurrence of competing endogenous RNA (ceRNA) networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were applied to predict both the biological functions and potential pathways of the altered parental genes involved in CNV.

RESULTS

Microarray analysis indicated that 100 circRNAs in RPE-choroid-sclera complexes from CNV mice were significantly altered compared with those from control mice (fold change≥1.5, p < .05). Of these, six were validated by qRT-PCR, and included up-regulated mmu_circRNA_20332 and mmu_circRNA_19388, and down-regulated mmu_circRNA_36481, mmu_circRNA_006555, mmu_circRNA_012588, and mmu_circRNA_005578. GO analysis revealed that the altered parental genes involved in ceRNA networks were mostly enriched in immune system processes and portions of neurons. KEGG analysis revealed that these altered parental genes were also amplified in extracellular matrix (ECM)-receptor interactions, chemokine signaling pathways, and advanced glycation end-product (AGE)-receptors for advanced glycation end-product (RAGE) signaling pathways in diabetic complications.

CONCLUSION

The study identified statistically significant differences between CNV-mouse circRNAs and control mouse circRNAs, suggesting that circRNAs play vital roles in the pathogenesis of CNV. It is, therefore, reasonable to consider circRNAs as potential therapeutic targets for regulating CNV in AMD patients.

LncRNA-Associated ceRNA Network Reveals Novel Potential Biomarkers of Laryngeal Squamous Cell Carcinoma

OBJECTIVE

This study aims to construct a systematic mRNA-miRNA-lncRNA network to identify novel lncRNAs and miRNAs biomarkers for laryngeal squamous cell carcinoma (LSCC).

METHODS

The mRNA, miRNA and lncRNA expression profiles of LSCC were obtained from Gene Expression Omnibus (GEO) database. The differentially expressed mRNAs, miRNAs and lncRNAs (DEmRNAs, DEmiRNAs and DElncRNAs) were screened between LSCC tissues and controls. Functional analysis of DEmRNAs, DEmRNAs targeted by DEmiRNAs and DEmRNAs targeted by DElncRNAs were respectively performed. The miRWalk, starbase and DIANA-LncBase were respectively used to predict DEmiRNAs-DEmRNAs, DElncRNAs-DEmRNAs and DElncRNAs-DEmiRNAs pairs. ceRNA network was built by DEmiRNAs-DEmRNAs and DElncRNAs-DEmiRNAs pairs. LncRNA subcellular localization was predicted using lncLocator. Using published The Cancer Genome Atlas (TCGA) and external datasets (GSE127165 and GSE133632), we also validated the expression of key DElncRNAs and DEmiRNAs in ceRNA network. The diagnostic and prognostic value of candidate genes was evaluated by ROC curve analysis and survival analysis, respectively.

RESULTS

There were 5 mRNA datasets, 3 miRNA datasets and 2 lncRNA datasets in this study. Totally, 2957 DEmRNAs, 61 DElncRNAs and 23 DEmiRNAs were identified. Functional analysis of DEmRNAs shows that they were significantly enriched in cancer-related pathways, such as DNA replication and extracellular matrix organization. There were 11 DEmiRNAs, 17 DElncRNAs and 967 DEmRNAs in the ceRNA network. Notably, up-regulated lncRNA DGCR5-down-regulated has-miR-338-3p/has-miR-139-5p pairs in this network were experimentally validated. Moreover, down-regulated AL121839.2, down-regulated LINC02147, up-regulated AC079328.2, up-regulated AC004943.2 and up-regulated HMGA2-AS1 were located in the cytoplasm. AL121839.2 and LINC02147 interacted with has-miR-1246. AC004943.2, AC079328.2 and HMGA2-AS1 targeted has-miR-3185, has-miR-3137 and has-miR-582-5p, respectively. Based on the TCGA and external datasets (GSE127165 and GSE133632), DGCR5 and AC004943.2 were significantly up-regulated while AL121839.2 and LINC02147, has-miR-338-3p, has-miR-139-5p and has-miR-582-5p were significantly down-regulated, which were consistent with our integration analysis. DGCR5, AL121839.2, LINC02147, AC004943.2, has-miR-338-3p, has-miR-139-5p and has-miR-582-5p could predict the occurrence of LSCC. Survival analysis suggested that only, AL121839.2 has potential prognostic value for LSCC.

CONCLUSION

This study provided novel insights into the ceRNA network and uncovered novel lncRNAs and miRNAs with diagnostic value in LSCC.

Comprehensive Characterization of Circular RNAs in Neuroblastoma Cell Lines

Neuroblastoma (NB) is a rare type of cancer but frequently occurred in children. However, it is still unclear whether circular RNAs (circRNAs) play key roles in NB tumorigenesis or progression. In this study, we identified 39,022 circRNAs across the 39 neuroblastoma and 2 normal cell lines. With the gene and circRNA expression data, we classified the NB cell lines, identified and characterized the functional circRNAs in the 3 NB classes. Specifically, 29 circRNAs were found to be dysregulated in the NB classes. Notably, 7 circRNAs located within MYCN-amplified regions were upregulated in cell lines with the high activities of MYC targets and MYCN amplification, and were highly correlated with expression of their parental gene, NBAS. Subsequently, we constructed ceRNA networks for the functional circRNAs. Specifically, hsa_circ_0005379 was identified as a critical regulator in the ceRNA networks because of targeting 13 genes, which formed a complex competing endogenous RNA (ceRNA) network. Moreover, hsa_circ_0002343, which was connected with few genes, might regulate the PI3K/Akt/mTOR signaling via RAC1. Furthermore, 3 genes, including NOTCH2, SERPINH1, and LAMC1, involved in epithelial mesenchymal transition (EMT) were observed to connect with hsa_circ_0001361, suggesting that this circRNA was closely associated with EMT. Consequently, 7 genes, such as DAD1, PPIA, NOTCH2, PGK1, BUB1, EIF2S1, and TCF7L2, were found to be closely associated with both event-free survival (EFS) and overall survival (OS). In conclusion, the present study identified functional circRNAs and predicted their functionality in neuroblastoma cell lines, which not only improved the understanding of circRNAs in neuroblastoma, but also provided the evidences for the related researchers.

Comprehensive Analysis of lncRNA-miRNA- mRNA Network Ascertains Prognostic Factors in Patients with Colon Cancer

Background:

Non-coding RNAs are competing endogenous RNAs in the occurrence and development of tumorigenesis; numerous microRNAs are aberrantly expressed in colon cancer tissues and play significant roles in oncogenesis development and metastasis. However, large clinical and RNA data are lacking to further confirm the exact role of these RNAs in tumors. This study aimed to ascertain differential RNA expression between colon cancer and normal colon tissues.

Materials and Methods:

RNA sequencing and clinical data of patients with colon cancer were procured from The Cancer Genome Atlas database; differentially expressed long non-coding RNA, differentially expressed messenger RNAs, and differentially expressed microRNAs were achieved using the limma package in edgeR to generate competing endogenous RNAs networks. Then, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were conducted with ggplot2 package, the Kaplan-Meier survival method was used to predict survival in patients with colon cancer.

Results:

In total, 1174 differentially expressed long non-coding RNAs, 2068 differentially expressed messenger RNAs, and 239 differentially expressed microRNAs were generated between 480 colon cancer and 41 normal colon tissue samples. Three competing endogenous RNA networks were established. Gene Ontology analysis indicated that the genes of the up-regulated microRNA network were involved in negative regulation of transcription, DNA-template, and those of down-regulated microRNA network were involved in transforming growth factor β receptor signaling pathways, response to hypoxia, cell migration, while Kyoto Encyclopedia of Genes and Genomes analyses of these networks turned out to be negative. Three long non-coding RNAs (AP004609.1, ARHGEF26-AS1, and LINC00491), 3 microRNAs (miRNA-141, miRNA-216a, and miRNA-193b) and 3 RNAs (ULBP2, PHLPP2, and TPM2) were detected to be associated with prognosis by the Kaplan-Meier survival analysis. Additionally, univariate and multivariate Cox regression analyses showed that the microRNA-216a of the competing endogenous RNA might be an independent prognostic factor in colon cancer.

Conclusions:

This study constructed the non-coding RNA-related competing endogenous RNA networks in colon cancer and sheds lights on underlying biomarkers for colon cancer cohorts.

Long non-coding RNA expression identified by microarray analysis: Candidate biomarkers in human acral lentiginous melanoma

Melanoma is a rare but fatal form of skin cancer and acral lentiginous melanoma (ALM) is one of its most common types. Long non-coding RNA (lncRNA) has emerged as a crucial molecule in the development and progression of human cancers, and several studies have revealed that lncRNAs may be associated with the pathogenesis, progression and metastasis of melanoma. To demonstrate the association between ALM and lncRNAs, microarray analysis was performed in tumor and adjacent non-tumor tissues. A total of 4,488 lncRNAs and 3,913 mRNAs were identified to be differentially expressed in these samples. Among them, 2,211 and 2,277 lncRNAs were upregulated and downregulated in the ALM samples compared with adjacent tissues, respectively. In addition, 1,191 and 2,722 mRNAs were upregulated and downregulated, respectively. Additionally, five randomly selected lncRNAs (fold-change >2; P<0.05) were validated by reverse transcription-quantitative PCR. An lncRNA and mRNA co-expression network and competing endogenous network analysis were also constructed. In summary, the results of the present study may reveal a novel mechanism associated with the pathogenesis and malignant biological processes of ALM and indicate that lncRNAs may serve as potential targets for the treatment of ALM.

[Long non-coding RNAs show different expression profiles and display competing endogenous RNA potential in placenta accreta spectrum disorders]

OBJECTIVE

To investigate the expression profile of long non-coding RNAs (lncRNA) and identify potential lncRNA-related competing endogenous RNAs (ceRNA) in placenta accrete spectrum disorders (PAS).

METHODS

Five tissue specimens of placental implantation and 5 adjacent normal placental tissues were collected from cesarean section deliveries complicated by PAS in our hospital between December, 2017 and June, 2018. Human microarrays were used to identify the lncRNAs that were differentially expressed in PAS, and 5 of the identified lncRNAs were further validated using qRT-PCR. GO and KEGG pathway analyses were performed to indentify the most significant enrichment functions. A ceRNA network was constructed based on ENST00000511361 (RP5-875H18.4), NR_027457 (LINC00221) and NR_126415 (FOXP4-AS1) to pinpoint the potential lncRNAs-related ceRNA.

RESULTS

A total of 329 lncRNAs and 179 mRNAs were identified to have differential expression in PAS. The results of qRT-PCR were consistent with the human microarrays results. Transforming growth factor-β (TGF-β) signaling pathway was the most significantly enriched pathway. The constructed ceRNA network suggested that RP5-875H18.4--miRNA-218--SLIT2 had a potential ceRNA regulatory mechanism in PAS.

CONCLUSIONS

The differentially expressed lncRNAs are involved in the occurrence and progression of PAS possibly by regulating the TGF-β signaling pathway. The ceRNA network of RP5-875H18.4--miRNA-218--SLIT2 may play a role in the occurrence of PAS.

Identifying prognostic biomarkers in endometrial carcinoma based on ceRNA network

PURPOSE

Endometrial carcinoma (EC), a common gynecological malignancy with high incidence, affects the mental and physical health of women. Mounting evidence shows that long noncoding RNAs (lncRNAs), messenger RNAs (mRNAs), and microRNAs (miRNAs) have instrumental roles in various biological processes associated with the pathogenesis of EC. In this research, we intend to further study the mechanism of EC and the potential predictive markers of EC.

METHODS

First, we obtained original data of EC RNA transcripts from The Cancer Genome Atlas database and performed differential analysis. Subsequently, according to the miRcode online software, relationship pairs of lncRNA-miRNA were constructed, and miRNA-mRNA pairs were established based on miRDB, TargetScan, and miRTarBase. Then, we constructed the competing endogenous RNA (ceRNA) network based on lncRNA-miRNA and miRNA-mRNA pairs. To further explain the function of the ceRNA network and explore the potential prognostic markers, functional enrichment analysis, and survival analysis were carried out.

RESULTS

The research showed that there were 744 differential expression lncRNAs (DElncRNAs), 164 differential expression miRNAs (DEmiRNAs), and 2447 differential expression mRNAs (DEmRNAs) between EC tissues and normal tissues. Subsequently, we built 103 DEmiRNA-DEmRNA interaction pairs and 369 DElncRNA-DEmiRNA pairs. Then, we established the ceRNA network of EC, including 62 DElncRNAs, 26 DEmiRNAs, and 70 DEmRNAs. Moreover, 10 of 62 lncRNAs, 19 of 70 mRNAs, and 4 of 26 miRNAs that closely related to the survival of EC with P < .05 were obtained. Notably, based on this network, it was found that LINC00261-hsa-mir-31 pair and LINC00261-hsa-mir-211 target pairs could be used as the potential prognostic markers of EC.

CONCLUSION

This research recommended an available basis for the molecular mechanism of EC and prognosis prediction, which could help guide the subsequent treatments and predict the prognosis for patients with EC.

TOB1-AS1 suppresses non-small cell lung cancer cell migration and invasion through a ceRNA network

Non-small cell lung cancer (NSCLC) is the leading cause of lung cancer-associated mortality. Recent studies revealed that long non-coding (lnc)RNAs have crucial roles in human cancers. The present study was the first, to the best of our knowledge, to indicate that the lncRNA transducer of ERBB2, 1-antisense 1 (TOB1-AS1) acts as a tumor suppressor in NSCLC. Knockdown of TOB1-AS1 significantly induced NSCLC cell migration, invasion and proliferation. It was also demonstrated that the higher expression of TOB1-AS1 in NSCLC samples was associated with longer overall survival time. Furthermore, a TOB1-AS1-mediated competing endogenous RNA network in NSCLC was constructed, including Homo sapiens (hsa)-microRNA (miR)-27a-3p, hsa-miR-23a-3p, hsa-miR-23b-3p, hsa-miR-27b-3p, hsa-miR-23c, dynein cytoplasmic 2 light intermediate chain 1, E4F transcription factor 1, TSPY-like 4, component of oligomeric Golgi complex 7, inositol hexakisphosphate kinase 2 and deltex E3 ubiquitin ligase 3. Of note, dysregulation of targets of TOB1-AS1 was associated with the prognosis of NSCLC patients. The present study suggested that TOB1-AS1 may serve as a novel biomarker for NSCLC.

Identification of Long Non-Coding RNA-Associated Competing Endogenous RNA Network in the Differentiation of Chicken Preadipocytes

Emerging evidence indicates that long noncoding RNAs (lncRNAs) play important roles in the regulation of cell differentiation by acting as competing endogenous RNA (ceRNA). However, the regulatory mechanisms of lncRNA and the lncRNA-associated ceRNA network involved in adipogenic differentiation of chicken preadipocytes remain elusive. Here, we first constructed the chicken preadipocyte in vitro induction model. Then, we identified differentially expressed lncRNAs (DELs), miRNAs (DEMis), and mRNAs (DEMs) between differentiated and undifferentiated preadipocytes. Furthermore, we constructed the lncRNA associated ceRNA network by gene expression correlation analysis and target prediction of DELs, DEMis, and DEMs. Finally, we determined twelve candidate lncRNA-miRNA-mRNA interactions from the lncRNA associated ceRNA network. Eight out of the twelve interactions were validated by RT-qPCR, indicating their potential role in the regulation of chicken preadipocytes differentiation. Among the eight interactions, TCONS_00026544-gga-miR-128-1-5p-RASD1, TCONS_00055280-gga-miR-135a-5p-JAM3, TCONS_00055280-gga-miR-135a-5p-GPR133, TCONS_00055280-gga-miR-135a-5p-CLDN1, and TCONS_00055280-gga-miR-135a-5p-TMEM123 may promote adipogenic differentiation of chicken preadipocytes while TCONS_00057272-gga-miR-146a-3p-FOXO6, TCONS_00057242-gga-miR-6615-3p-FOXO6, and TCONS_00057242-gga-miR-6615-3p-ENSGALT00000043224 have the opposite effects. Our results not only provide novel insights into ceRNA roles of lncRNAs in chicken preadipocytes differentiation and but also contribute to a better understanding of chicken fat deposition.

Systematic analysis identifies three-lncRNA signature as a potentially prognostic biomarker for lung squamous cell carcinoma using bioinformatics strategy

Background

Lung squamous cell carcinoma (LUSC) is the second most common histological subtype of lung cancer (LC), and the prognoses of most LUSC patients are so far still very poor. The present study aimed at integrating lncRNA, miRNA and mRNA expression data to identify lncRNA signature in competitive endogenous RNA (ceRNA) network as a potentially prognostic biomarker for LUSC patients.

Methods

Gene expression data and clinical characteristics of LUSC patients were retrieved from The Cancer Genome Atlas (TCGA) database, and were integratedly analyzed using bioinformatics methods including Differentially Expressed Gene Analysis (DEGA), Weighted Gene Co-expression Network Analysis (WGCNA), Protein and Protein Interaction (PPI) network analysis and ceRNA network construction. Subsequently, univariate and multivariate Cox regression analyses of differentially expressed lncRNAs (DElncRNAs) in ceRNA network were performed to predict the overall survival (OS) in LUSC patients. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of multivariate Cox regression model. Gene expression profiling interactive analysis (GEPIA) was used to validate key genes.

Results

WGCNA showed that turquoise module including 1,694 DElncRNAs, 2,654 DEmRNAs as well as 113 DEmiRNAs was identified as the most significant modules (cor=0.99, P<1e-200), and differentially expressed RNAs in the module were used to subsequently analyze. PPI network analysis identified FPR2, GNG11 and ADCY4 as critical genes in LUSC, and survival analysis revealed that low mRNA expression of FPR2 and GNG11 resulted in a higher OS rate of LUSC patients. A lncRNA-miRNA-mRNA ceRNA network including 121 DElncRNAs, 18 DEmiRNAs and 3 DEmRNAs was established, and univariate and multivariate Cox regression analysis of those 121 DElncRNAs showed a group of 3 DElncRNAs (TTTY16, POU6F2-AS2 and CACNA2D3-AS1) had significantly prognostic value in OS of LUSC patients. ROC analysis showed that the area under the curve (AUC) of the 3-lncRNA signature associated with 3-year survival was 0.629.

Conclusions

The current study provides novel insights into the lncRNA-related regulatory mechanisms underlying LUSC, and identifying 3-lncRNA signature may serve as a potentially prognostic biomarker in predicting the OS of LUSC patients.

The Construction and Comprehensive Analysis of ceRNA Networks and Tumor-Infiltrating Immune Cells in Bone Metastatic Melanoma

Background/Aims: As a malignant and melanocytic tumor, cutaneous melanoma is the devastating skin tumor with high rates of recurrence and metastasis. Bone is the common metastatic location, and bone metastasis may result in pathologic fracture, neurologic damage, and severe bone pain. Although metastatic melanoma was reported to get benefits from immunotherapy, molecular mechanisms and immune microenviroment underlying the melanoma bone metastasis and prognostic factors are still unknown.

Methods: Gene expression profiling of 112 samples, including 104 primary melanomas and 8 bone metastatic melanomas from The Cancer Genome Atlas database, was assayed to construct a ceRNA network associated with bone metastases. Besides, we detected the fraction of 22 immune cell types in melanoma via the algorithm of “cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT).” Based on the significant ceRNAs or immune cells, we constructed nomograms to predict the prognosis of patients with melanoma. Ultimately, correlation analysis was implemented to discover the relationship between the significant ceRNA and immune cells to reveal the potential signaling pathways.

Results: We constructed a ceRNA network based on the interaction among 8 pairs of long noncoding RNA–microRNA and 15 pairs of microRNA–mRNA. CIBERSORT and ceRNA integration analysis discovered that AL118506.1 has both significant prognostic value (P = 0.002) and high correlation with T follicular helper cells (P = 0.033). Meanwhile, T cells CD8 and macrophages M2 were negatively correlated (P < 0.001). Moreover, we constructed two satisfactory nomograms (area under curve of 3-year survival: 0.899; 5-year survival: 0.885; and concordance index: 0.780) with significant ceRNAs or immune cells, to predict the prognosis of patients.

Conclusions: In this study, we suggest that bone metastasis in melanoma might be related to AL118506.1 and its role in regulating thrombospondin 2 and T follicular helper cells. Two nomograms were constructed to predict the prognosis of patients with melanoma and demonstrated their value in improving the personalized management.

Investigation of miRNA- and lncRNA-mediated competing endogenous RNA network in cholangiocarcinoma

Cholangiocarcinoma (CCA) is a biliary malignancy which is prone to lymphatic metastasis and has a high mortality rate. This disease lacks effective therapeutic targets and prognostic molecular biomarkers. The aim of the current study was to investigate differentially expressed genes and elucidate their association with CCA and the underlying mechanisms of action. mRNAs, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) obtained from 36 CCA samples and nine normal samples from The Cancer Genome Atlas were integrated. Subsequently, 1,095 differentially expressed (DE) mRNAs and 75 DE miRNAs were identified using a threshold of |log2 fold change|>2 and an adjusted P<0.01. Weighted gene co-expression network analysis was used to identify the DEmRNAs that could be key target genes in CCA. A total of 12 hub DEmRNAs were identified as targetable genes. Furthermore, the hub DEmRNAs-DElncRNAs pairs were identified using the miRTarBase and miRcode databases. Cytoscape software was used to construct and visualize the protein-protein interactions and the competing endogenous RNA network. Survival time analysis and correlation analysis were used to further evaluate the hub genes. The results obtained in the current study suggested that spalt like transcription factor 3 and OPCML intronic transcript 1 may serve an important role in the development and progression of CCA.

Construction and Investigation of a lncRNA-Associated ceRNA Regulatory Network in Cholangiocarcinoma

Background/Aims: As a type of malignant tumor commonly found in the bile duct, cholangiocarcinoma (CCA) has a poor prognosis. Long non-coding RNA (lncRNA) has recently drawn increasing attention because it functions as a competing endogenous RNA (ceRNA) to hinder miRNA functions that participate in posttranscriptional regulatory networks in tumors. Therefore, to investigate the mechanisms of CCA carcinogenesis and to enhance treatment efficiency, the expression profiles, including lncRNA, miRNA, and mRNA data, were comprehensively integrated and analyzed in this study.

Methods: A comprehensive comparison was performed on the RNA-sequencing and miRNA profiles data of 36 CCA samples and 9 normal samples from The Cancer Genome Atlas (TCGA) database. Then, a dysregulated lncRNA-related ceRNA network was established by using four public databases.

Results: In summary, 1,410 lncRNAs, 64 miRNAs, and 3,494 mRNAs appeared as genes that were aberrantly expressed in CCA. Then, a dysregulated ceRNA network related to the lncRNAs was constructed. The network included 116 lncRNAs, 13 miRNAs and 60 mRNAs specific to CCA. The survival analysis showed that, among them, 26 lncRNAs, 3 miRNAs, and 13 mRNAs were prognostic biomarkers for patients with CCA. Finally, three mRNAs were selected for validation of their expression levels in the Gene Expression Omnibus (GEO) database. The results indicated that the expression of those genes was highly consistent between the TCGA and GEO databases.

Conclusions: The findings in this study provide a better understanding of the ceRNA network involved in CCA biology and lay a solid foundation for improving CCA diagnosis and prognosis.