Identification of differentially expressed LncRNA in Uterine Corpus Endometrial Carcinoma (UCEC) with circlncRNAnet and GEPIA
To investigated the roles of lncRNAs in the tumorigenesis, development of UCEC, we first identified differentially expressed lncRNAs in the LncRNA-TCGA module of cirlncRNAnet. A total of 10978 lncRNAs were detected in Uterine Corpus Endometrial Carcinoma (UCEC), of which 121 lncRNAs were dysregulated (77 up-regulated and 44 down-regulated) (|Log2 fold change|>4 and P<0.01)（Supplementary table 1）. We further verified the expression of 121 differentially expressed LncRNAs in UCEC using the GEPIA and found that only RP11-89K21.1 and RP11-357H14.17 were significantly overexpressed in UCEC (P<0.05) (Fig. 1a-b), consistent with the results from cirlncRNAnet. The expression of CTD-2314B22 .1, CTD-2377D24.6, RP11-657O9.1 and LINC00668 were higher in UCEC than those in normal tissues, but the differences were not statistically significant (P>0.05) (Fig. 1c-f). The expression of AP000892.6, ACTA2-AS1 and RP11-867G23.10 was significantly decreased in UCEC compared with normal tissues (P <0.05) (Fig. 1h-i).
Prognostic values of dysregulated LncRNA including RP11-89K21.1 and RP11-357H14.17 in UCEC analyzed by GEPIA.
We further explored the prognostic values of the 121 differentially expressed lncRNAs in UCEC using GEPIA. The results showed that high expressions of RP11-89K21.1, RP11-357H14.17, CTD-2314B22.1, CTD-2377D24.6, RP11-657O9.1 and LINC00668 were significantly correlated with shortened overall survival (OS) in UCEC (P=0.0088, P=0.025, P=0.026, P=0.0013, P=0.021, and P=0.0086, respectively) (Fig. 2a-f, Table 1). Additionally, the expressions of AP000892.6, ACTA2-AS1 and RP11-867G23.10 were decreased in UCEC, while high expressions of AP000892.6, ACTA2-AS1 and RP11-867G23.10 were significantly associated with poor prognosis (all P<0.05) (Fig. 2g-i). Kaplan-Meier plotter showed that high expressions of RP11-89K21.1 (Additional file 1: Figure S1a), LINC00668 (Additional file 1: Figure S1d) and ACTA2-AS1 (Additional file 1: Figure S1e) were also correlated with OS in UCEC (Additional file 1: Table S1), RP11-357H14.17, CTD-2377D24.6 and AP000892.6 were not detected in Kaplan-Meier plotter. The above results suggest that high expression of RP11-89K21.1 and RP11-357H14.17 may play important roles in the occurrence, development and prognosis of UCEC.
The cellular location and co-expressed genes of RP11-89K21.1 and RP11-357H14.17
The cellular localization of lncRNAs played crucial roles in their functions and molecular mechanisms, we explored the subcellular localizations of RP11-89K21.1 and RP11-357H14.17 with lncLocator. The results showed that RP11-89K21.17 was mainly located in cytosol and cytoplasm (score:0.56 and 0.28, respectively), RP11-357H14.17 was mainly located in cytosol and ribosome (score:0.37 and 0.32, respectively) (Fig. 3a). Therefore, it was more likely that RP11-89K21.1 and RP11-357H14.17 exerted their biological functions and potential mechanisms through the ceRNA network. We further explored the co-expression gene of RP11-89K21.1 and RP11-357H14.17 and visualized by Circos map and heat map with circlncRNAnet. The circos maps showed that chromosome distribution of the top 50 co-expressed genes associated with RP11-89K21.1 and RP11-357H14.17, which were mainly localized in the autosomes. There was no particular enrichment in chromosome 2 (where RP11-89K21.1 locates) and 7 (where RP11-357H14.17 locates). The heat map indicated that AC012354.6, RP11-89K21.2, SIX3, SIX3-AS1, and Six3os1_1/2/4/5 were the co-expression gene of RP11-89K21.1, CTD-2377D24.6, HOXB-AS4, HOXB9 and MIR196A1 were the co-expression gene of RP11-357H14.17 (all P<0.05) (Fig. 3b-c, Additional file 2-3).
Transcriptional regulation and protein interaction of RP11-89K21.1 and RP11-357H14.17
Furthermore, we explored the transcriptional factors (TFs) and binding proteins of RP11-89K21.1 and RP11-357H14.17 by AnnoLnc. 31 TFs and 42 TFs were identified to be correlated with RP11-89K21.1 and RP11-357H14.17, respectively. 21 TFs of these two lncRNAs were commonly existed in the database (CEBPB, CHD1, c-Myc, CtBP2, CTCF, Egr-1, EZH2, GABP, Max, NRSF, p300, Pol2, Pol2-4H8, PU.1, Rad21, RBBP5, SUZ12, TCF7L2, YY1, Znf143, ZNF263) (Fig. 4a). We found that the expression of EZH2 in UCEC was significantly overexpressed, while the expression of TCF7L2 in UCEC was significantly decreased (both P<0.05). There was no significant difference in the expression levels of other TFs in UCEC (P>0.05) (Fig. 4b). We further investigated that EZH2 expression was positively correlated with both RP11-89K21.1 and RP11-357H14.17 using starBase (r=0.118, P=5.67e-03 and r=0.103, P=1.57e-02, respectively) (Fig. 4c). Based on the correlation coefficients were too small, we further explored the correlation between EZH2 and RP11-89K21.1, RP11-357H14.17 using GEPIA, the result showed that the expression of EZH2 was positively correlated with both RP11-89K21.1 (R=0.3, P=8.8e-07) and RP11-357H14.17 (R=0.31, P=3.7e-07) (Fig .4d). What’s more, the binding proteins of RP11-89K21.1 included CBWD7, GUSB, ABRA, MTUS2, VAMP4 (top 5) (Fig. 4e), and the binding proteins of RP11-357H14.17 included CLIC1, CNN2, TCTN1, TMEM240, ZNF836 (top 5) (Fig. 4f). The networks of the transcription factors (Fig. 4e) and binding proteins (Fig. 4f) were visualized through GeneMANIA (Additional file 4-7).
Construction of lncRNA–miRNA–mRNA network
The subcellular locations of lncRNAs were closely correlated with their potential functions and mechanisms in tumors. We found that both RP11-89K21.1 and RP11-357H14.17 were mainly located in cytosol, and it was possible that RP11-89K21.1 and RP11-357H14.17 achieved their biological functions through the ceRNA mechanism. Thus, the binding miRNAs of RP11-89K21.1 and RP11-357H14.17 were predicted by AnnoLnc. The expressions of potential miRNAs were further validated by starBase. The results showed that 22 miRNAs families and 10 miRNAs families were associated with RP11-89K21.1 and RP11-357H14.17, respectively. There were 5 miRNAs families overlapped in the lncRNAs binding miRNAs (Fig. 5a, Table 2 and Additional file 1: Table S2), of which the expression of miR-27b, miR-4770, miR-143, miR-204 in UCEC was significantly decreased (all P<0.05) (Fig. 5b-h). The expression of miR-125a-5p, miR-125b-5p, miR-139-5p, miR-670-3p, miR-24-1-5p, miR-503 in UCEC was also significantly decreased (all P<0.05) (Additional file 1: Figure S2 and Additional file 1: Table S2). For RP11-89K21.1, miR-27b, miR-4770, miR-143, miR-204, miR-125a-5p, miR-125b-5p, miR-139-5p and miR-670-3p were regarded as candidate miRNAs. For RP11-357H14.17, miR-27b, miR-4770, miR-143, miR-204, miR-24-1-5p and miR-503 were considered as candidate miRNAs. The targeted mRNAs of the candidate miRNAs were further predicted by miRTarBase. As shown in Fig. 6, lncRNA-miRNA-mRNA regulatory network was constructed by Cytoscape, there were 2 lncRNAs (RP11-89K21.1 and RP11-357H14.17), 11 miRNAs and 183 target genes included in the interaction network. (Fig. 6).
Functional enrichment analysis of lncRNA-related targets
To explore the potential functions and mechanisms of RP11-89K21.1 and RP11-357H14.17 in the development of UCEC, GO and KEGG enrichment analysis of RP11-89K21.1 and RP11-357H14.17 targeted genes were analyzed by Metascape. GO showed that RP11-89K21.1 targeted genes primarily participated in transcription factor complex and perinuclear region of cytoplasm, also regulated proximal promoter sequence-specific DNA binding, phosphotransferase activity, kinase and growth factor binding (Fig. 7a-d, Additional file 1: Table S3-4). The biological processes of RP11-89K21.1 targeted genes mainly involved in blood vessel development, regulation of cell death and differentiation, tissue morphogenesis and response to growth factor (Fig. 7e-f and table 3). RP11-357H14.17 targeted genes were mainly located in perinuclear region of cytoplasm, participated in cyclin-dependent protein kinase holoenzyme complex, adherens junction and transcription factor complex, also regulated protein kinase activity
transcription factor and kinase binding (Fig. 8a-d, Additional file 1: Table S5-6). RP11-89K21.1 targeted genes mainly involved in biological processes such as blood vessel development, regulation of transferase activity, apoptotic signaling pathway, regulation of cell death and cell differentiation, response to oxygen levels (Fig. 8e-f and table 5).
KEGG enrichment analysis showed that RP11-89K21.1 targeted genes were significantly enriched in pathways in cancer, endocrine resistance and microRNAs in cancer, regulated apelin signaling pathway, Th17 cell differentiation and hippo signaling pathway (Fig. 7g-h, table 4). RP11-357H14.17 targeted genes were significantly enriched in pathways in cancer, microRNAs in cancer, PI3K-AKT signaling pathway, AGE-RAGE signaling pathway in diabetic complications, cell cycle and cytokine-mediated signaling pathway (Fig. 8g-h, table 6). These signaling pathways played key roles in the occurrence and development of a variety of tumors, including endometrial carcinoma. Moreover, in order to better understand the relationship between RP11-89K21.1, RP11-357H14.17 and UCEC, we performed protein-protein interaction (PPI) enrichment analysis using Metascape (Fig. 7i and Fig. 8i). The most important 10 and 8 MCODE components in PPI network, pathway and enrichment process analysis were applied to each MCODE component independently.
Correlation between the expression of RP11-89K21.1, RP11-357H14.17 and immune infiltration with ImmucLnc
In order to investigate the relationship between RP11-89K21.1, RP11-357H14.17 and immune infiltration, ImmucLnc database was employed to detect RP11-89K21.1, RP11-357H14.17 correlated immune cell types (CD8_T cell, Macrophage, Dendritic, BMSCs and CD4_T cell, and Neutrophil). We found that the expression of RP11-89K21.1 was negatively correlated with CD8_T cell (Rs Value=-0.159, P=0) and Macrophage (Rs Value=-0.11, P=0.01), and positively correlated with CD4_T cell (Rs Value=0.106, P=0.013) and Neutrophil (Rs Value=0.138, P=0.001) (Table 7). The expression of RP11-357H14.17 was negatively correlated with CD8_T cell (Rs Value=-0.114, P=0.008) and positively correlated with CD4_T cell (Rs Value=0.102, P=0.017) (Table 8)