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. 2020 Sep 4:11:1026.
doi: 10.3389/fgene.2020.01026. eCollection 2020.

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

Affiliations

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

Peitao Zhou et al. Front Genet. .

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.

Keywords: circular RNA; hepatocellular carcinoma; macrophage; non-coding RNAs; regulatory network.

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Figures

FIGURE 1
FIGURE 1
The prognostic value of six cell fractions in HCC patients from TCGA. (A) The composition of six cell fractions in HCC patients (n = 343). (B) The OS analysis of HCC patients with top (n = 86) and bottom 25% (n = 85) infiltration level of six cell fractions.
FIGURE 2
FIGURE 2
The prognostic value of six cell fractions in HCC patients from GSE14520. (A) The composition of six cell fractions in HCC patients (n = 221). (B) The OS analysis of HCC patients with top (n = 55) and bottom 25% (n = 56) infiltration levels of six cell fractions.
FIGURE 3
FIGURE 3
The DEmRNAs, DEmiRNAs, and DEcircRNAs identified from paired tumor and adjacent non-tumor cases. (A) The DEmRNAs were screened out from TCGA and GSE14520. The DEmiRNAs were screened out from TCGA. (B) Identification of DEmRNA-related macrophages from TCGA and GSE14520. (C) The DEcircRNAs were screened out from three GEO data sets.
FIGURE 4
FIGURE 4
Construction of the circRNA-miRNA-mRNA network based on 45 DEmRNAs related to macrophages. The network was constructed after taking the intersection of DEcircRNA-DEmiRNA pairs and DEmiRNA-macrophage-related DEmRNA pairs. The red diamond, yellow rectangle, and light green ellipse indicate circRNA, miRNA, and mRNA, respectively.
FIGURE 5
FIGURE 5
Construction of the hub circRNA-miRNA-mRNA network. (A) PPI network analysis of 45 DEmRNAs related to macrophage. (B) Two subnetworks of PPI network analyzed by the MCODE plugin of cytoscape. (C) Construction of the circRNA-miRNA-mRNA network based on six hub DEmRNAs related to macrophages. (D) Construction of the circRNA-miRNA-mRNA network based on PRC1. PRC1 was identified as the most influential node by the IVI method. The red diamond, yellow rectangle, and light green ellipse indicate circRNA, miRNA, and mRNA, respectively.
FIGURE 6
FIGURE 6
The Kaplan–Meier survival analysis of six hub macrophage-related DEmRNAs in HCC cases from TCGA (A) and GSE14520 (B).
FIGURE 7
FIGURE 7
The macrophage fractions in HCC cases with different expression levels of PRC1 or DTL from TCGA (A) and GSE14520 (B).

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