Dataset Information

Construction of a circRNA-miRNA-mRNA Network Related to Macrophage Infiltration in Hepatocellular Carcinoma.

ABSTRACT: Immune cells in the tumor microenvironment play a crucial role in regulating tumor progression. The circular RNA (circRNA) regulatory network involved in immune cell infiltration in hepatocellular carcinoma (HCC) remains largely unknown. In this study, the "estimate the proportion of immune and cancer cells" (EPIC) application is used to evaluate the fractions of immune cells, cancer-associated fibroblasts, and endothelial cells in HCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Patients with a high macrophage fraction have better overall survival, and macrophage fraction is an independent prognostic factor for HCC. Next, the common differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs), and circRNAs (DEcircRNAs) between paired tumor and non-tumor tissues are screened out from the TCGA and/or GEO databases. Through spearman correlation analysis, the macrophage-related DEmRNAs are identified to construct a circRNA-miRNA-mRNA regulatory network, which includes 6 DEcircRNAs, 7 DEmiRNAs, and 45 DEmRNAs. Functional enrichment analysis reveals that these DEmRNAs are mainly involved in immune-related processes. Furthermore, six hub DEmRNAs are identified to establish a hub circRNA regulatory network. Among the DEmRNAs in the network, PRC1 is identified as the most influential node. PRC1 high expression is correlated with poor prognosis and low macrophage infiltration in HCC. Taken together, we identify a certain circRNA regulatory network related to macrophage infiltration and provide novel insight into the mechanism of study and therapeutic targets for HCC.

SUBMITTER: Zhou P

PROVIDER: S-EPMC7500212 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Construction of a circRNA-miRNA-mRNA Network Related to Macrophage Infiltration in Hepatocellular Carcinoma.

Zhou Peitao P Zheng Guanglei G Li Yalin Y Wu Dehua D Chen Yuhan Y

Frontiers in genetics 20200904

Immune cells in the tumor microenvironment play a crucial role in regulating tumor progression. The circular RNA (circRNA) regulatory network involved in immune cell infiltration in hepatocellular carcinoma (HCC) remains largely unknown. In this study, the "estimate the proportion of immune and cancer cells" (EPIC) application is used to evaluate the fractions of immune cells, cancer-associated fibroblasts, and endothelial cells in HCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omni ...[more]

PMID: 33101367

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Project description:BackgroundMacrophage play a crucial role in regulating tumor progression. This study intended to investigate the circular RNA (circRNA) regulatory network associated with macrophage infiltration in hepatocellular carcinoma (HCC).MethodsThe immune cell fractions of HCC from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium were calculated by Estimation of the Proportion of Immune and Cancer cells algorithm. The differentially expressed mRNAs (DEmRNAs), microRNAs (DEmiRNAs) and circRNAs (DEcircRNAs) were identified from HCC and adjacent non-tumor cases of TCGA or Gene Expression Omnibus database. The DEmRNAs related to macrophage were selected by weighted gene co-expression network analysis and then utilized to generate the circRNA-miRNA-mRNA network. A hub circRNA regulatory network was established based on the co-expressed DEmiRNAs and DEmRNAs owning contrary correlation with the clinical characteristics, survival and macrophage infiltration level. A gene signature based on the DEmRNAs in hub network was also generated for further evaluation. The circRNA binding bite for miRNA was detected by luciferase assay.ResultsHigh macrophage fraction predicted good survival for HCC. A circRNA-miRNA-mRNA network was constructed by 27 macrophage related DEmRNAs, 21 DEmiRNAs, and 15 DEcircRNAs. Among this network, the expression of hsa-miR-139-5p was negatively correlated with CDCA8, KPNA2, PRC1 or TOP2A. Hsa-miR-139-5p low or targeted DEmRNA high expression was associated with low macrophage infiltration, high grade, advanced stage and poor prognosis of HCC. Additionally, the risk score generated by 4-DEmRNA signature could reflect the macrophage infiltration status and function as an independent prognostic factor for HCC. Finally, hsa_circ_0007456 acting on hsa-miR-139-5p related network was viewed as the hub circRNA regulatory network. Taken together, some circRNA regulatory networks may be associated with macrophage infiltration, which provides clues for mechanism study and therapeutic strategies of HCC.

Project description: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.

Project description:BackgroundCircular RNAs (circRNAs) have received increasing attention in human tumor research. However, there are still a large number of unknown circRNAs that need to be deciphered. The aim of this study is to unearth novel circRNAs as well as their action mechanisms in hepatocellular carcinoma (HCC).MethodsA combinative strategy of big data mining, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and computational biology was employed to dig HCC-related circRNAs and to explore their potential action mechanisms. A connectivity map (CMap) analysis was conducted to identify potential therapeutic agents for HCC.ResultsSix differently expressed circRNAs were obtained from three Gene Expression Omnibus microarray datasets (GSE78520, GSE94508 and GSE97332) using the RobustRankAggreg method. Following the RT-qPCR corroboration, three circRNAs (hsa_circRNA_102166, hsa_circRNA_100291 and hsa_circRNA_104515) were selected for further analysis. miRNA response elements of the three circRNAs were predicted. Five circRNA-miRNA interactions including two circRNAs (hsa_circRNA_104515 and hsa_circRNA_100291) and five miRNAs (hsa-miR-1303, hsa-miR-142-5p, hsa-miR-877-5p, hsa-miR-583 and hsa-miR-1276) were identified. Then, 1424 target genes of the above five miRNAs and 3278 differently expressed genes (DEGs) on HCC were collected. By intersecting the miRNA target genes and the DEGs, we acquired 172 overlapped genes. A protein-protein interaction network based on the 172 genes was established, with seven hubgenes (JUN, MYCN, AR, ESR1, FOXO1, IGF1 and CD34) determined from the network. The Gene Oncology, Kyoto Encyclopedia of Genes and Genomes and Reactome enrichment analyses revealed that the seven hubgenes were linked with some cancer-related biological functions and pathways. Additionally, three bioactive chemicals (decitabine, BW-B70C and gefitinib) based on the seven hubgenes were identified as therapeutic options for HCC by the CMap analysis.ConclusionsOur study provides a novel insight into the pathogenesis and therapy of HCC from the circRNA-miRNA-mRNA network view.

Project description:Liver hepatocellular carcinoma (LIHC) is one of the major causes of cancer-related death worldwide with increasing incidences, however there are very few studies about the underlying mechanisms and pathways in the development of LIHC. We obtained LIHC samples from The Cancer Genome Atlas (TCGA) to screen differentially expressed mRNAs, lncRNAs, miRNAs and driver mutations. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses and protein-protein interaction (PPI) network were performed. Moreover, we constructed a competing endogenous lncRNAs-miRNAs-mRNAs network. Finally, cox proportional hazards regression analysis was used to identify important prognostic differentially expressed genes. Total of 1284 mRNAs, 123 lncRNAs, 47 miRNAs were identified within different tissues of LIHC patients. GO analysis indicated that upregulated and downregulated differentially expressed mRNAs (DEmRNAs) were mainly associated with cell division, DNA replication, mitotic sister chromatid segregation and complement activation respectively. Meanwhile, KEGG terms revealed that upregulated and downregulated DEmRNAs were primarily involved in DNA replication, Metabolic pathways, cell cycle and Metabolic pathways, chemical carcinogenesis, retinol metabolism pathway respectively. Among the DERNAs, 542 lncRNAs-miRNAs-mRNAs pairs were predicted to construct a ceRNA regulatory network including 35 DElncRNAs, 26 DEmiRNAs and 112 DEmRNAs. In the Kaplan-Meier analysis, total of 43 mRNAs, 14 lncRNAs and 3 miRNAs were screened out to be significantly correlated with overall survival of LIHC. The mutation signatures were analyzed and its correlation with immune infiltrates were evaluated using the TIMER in LIHC. Among the mutation genes, TTN mutation is often associated with poor immune infiltration and a worse prognosis in LIHC. This work conducted a novel lncRNAs-miRNAs-mRNAs network and mutation signatures for finding potential molecular mechanisms underlying the development of LIHC. The biomarkers also can be used for predicting prognosis of LIHC.

Dataset Information

Construction of a circRNA-miRNA-mRNA Network Related to Macrophage Infiltration in Hepatocellular Carcinoma.

Publications

Construction of a circRNA-miRNA-mRNA Network Related to Macrophage Infiltration in Hepatocellular Carcinoma.

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