The lncRNAs, miRNAs and mRNAs expression matrices of the 89 patients (24 normal and 65 with ChRCC) were downloaded from the TCGA dataset. Patients’ clinicopathological characteristics are presented in Table 1.
Table 1
The clinicopathological characteristics of ChRCC patients.
| Total(n = 65) | Alive(n = 55) | Dead(n = 10) |
Gender | | | |
Male | 39 | 32 | 7 |
Female | 26 | 23 | 3 |
Race | | | |
Asian | 2 | 1 | 1 |
White | 57 | 48 | 9 |
Black or african American | 4 | 4 | 0 |
Not reported | 2 | 2 | 0 |
Age at diagnose | | | |
< 60 (years) | 46 | 41 | 5 |
60–80 (years) | 18 | 13 | 5 |
> 80 (years) | 1 | 1 | 0 |
Mean (SD) (days) | 19129.83 (5127.97) | 18493.20 (4978.49) | 22631.30 (4709.89) |
Median [MIN, MAX] (days) | 18502 [6556, 31591] | 17710 [6556, 31591] | 22697 [15045, 28705] |
Tumor clinical stage | | | |
Stage_I | 20 | 19 | 1 |
Stage_II | 25 | 23 | 2 |
Stage_III | 14 | 11 | 3 |
Stage_IV | 6 | 2 | 4 |
Firstly, 1628 DElncRNAs (763/865, up/down), 104 DEmiRNAs (61/43, up/down), and 2619 DEmRNAs (1103/1516, up-/down-DEmRNAs), were elucidated. Their volcano maps and heatmaps are presented in Fig. 2 (A, B, C). GO analysis showed that the top five functions of the 2619 DEmRNAs focused on organic anion transport, regulation of membrane potential, regulation of ion transmembrane transport, modulation of chemical synaptic transmission, and regulation of trans − synaptic signaling (Fig. 3A). Meanwhile, the top five KEGG pathways of these DEmRNAs were enriched in neuroactive ligand − receptor interaction, cAMP signaling pathway, complement and coagulation cascades, retinol metabolism, and chemical carcinogenesis (Fig. 3B). Insulin secretion and connection between pathways were presented in the pathways-pathways network (Fig. 3C). In the pathways-genes network, multiple RNAs were related to five pathways: complement and coagulation cascades, metabolism of xenobiotics by cytochrome P450, neuroactive ligand − receptor interaction, retinol metabolism, and steroid hormone biosynthesis (Fig. 3D).
In the WGCNA, the power of the soft threshold of the lncRNAs-miRNAs matrix was 10 (Fig. 4A), and the miRNAs-mRNAs matrix was 14 (Fig. 4B), both of which achieved the best satisfaction and consistency of the scale-free R-squared value. After calculating their adjacency and connectivity, these lncRNAs-miRNAs were classified into 10 modules (Fig. 4C), and miRNAs-mRNAs were classified into 11 modules (Fig. 4D). Their topological overlap matrix heatmaps are presented in Fig. 4 (E, F). Red, yellow, brown, and grey modules of lncRNAs-miRNAs were found to have significant correlation (Fig. 5A), and greater connections were also observed in green, turquoise, and grey modules of the miRNAs-mRNAs (Fig. 5B). Modules in these two groups included a total of 1534 DElncRNAs, 98 DEmiRNAs, and 2543 DEmRNAs, which were also more closely related to ChRCC than the others (Fig. 5C, D).
When predicting the DElncRNAs and DEmiRNAs of the module genes in miRcode, we identified 116 DElncRNAs (43/73, up/down) and 19 DEmiRNAs (9/10, up/down) and their connective pairs. When using the StarBase, miRTarBase, miRDB, and TargetScan datasets, 512 target mRNAs of the 19 DEmiRNAs were included. Forty-three of them finally coincided with selected module DEmRNAs (Fig. 5E), which corresponded to 113 lncRNAs and 14 miRNAs.
Nine mRNAs (ALPL, ARHGAP29, CADM2, KIT, KLRD1, MYBL1, PSD3, SFRP1, SLC7A11) were identified as prognosis-related genes when an univariate Cox analysis was conducted on the 43 mRNAs, (P < 0.05). Moreover, the results of multivariate Cox proportional hazards regressions indicted that two of the nine mRNAs (CADM2, SFRP1) were independent risk factors for ChRCC (Fig. 6A). The C-index of this model was 0.91, and the 3-and 5-year AUCs (area under receiver operating characteristic curve) were 0.996 and 0.989 (Fig. 6B), which proved the stability and reliability of the model. Finally, six miRNAs (3/3, up/down) corresponded to 79 lncRNAs (31/48, up/down) and were associated with these nine mRNAs (5/4, up/down). The ceRNA network based on their relationship was constructed using the Cytoscape platform (Fig. 7A).
Additionally, Kaplan–Meier analyses for the ceRNA members showed that low expression of KLRD1 and high expression of LINC00520 significantly contributed to worse OS for patients with ChRCC (P < 0.05) (Fig. 7B, C). Meanwhile, the low-risk group also showed obvious superiority over the high-risk group, despite its P value being slightly greater than 0.05 (P = 0.06016) (Fig. 7D).