Increasing evidence shows that lncRNAs and miRNAs were differentially expressed and implicated in series of molecular processes, including differentiation, proliferation, metastasis, and transcriptional regulation in sarcomas (29, 30). While the whole regulatory network that links the functions of coding and non-coding RNAs has not been extensively discussed. In the present study, bioinformatics analysis was utilized to integrate available sequencing data sets of sarcoma and 1296 DEGs were identified in sarcoma samples by combining the GO and pathway enrichment analysis, 338 DELs were discovered after the probes were re-annotated, and 36 DEMs were ascertained through intersecting two different expression miRNAs sets. Further, 448 miRNA-mRNA interactions and 454 miRNA-lncRNA interactions were obtained through target gene prediction, and then, we constructed a lncRNA-miRNA-mRNA ceRNA network that contained 29 miRNAs, 69 lncRNAs and 113 mRNAs.
The ceRNA network identified in our study provided useful clues for further study. According to DEGs in the ceRNA network, we constructed PPI network which showed the up-regulated hub nodes including IGF1, PRKCB and GNAI3, and the down-regulated hub nodes including AR, CYCS and PPP1CB. In addition, there were twelve RNAs in the ceRNA network associated with prognosis of sarcomas based on the TCGA database. Among the seven overall survival associated mRNAs, the high expression levels of SMARCC1, SRSF10, PRPF38A, JARID2 and GNAI3 were significantly associated with shorter overall survival in sarcomas (P = 0.0018, P = 0.037, P = 0.0058, P = 0.0093, P = 0.0234, respectively). While the high expression of ARF3 and PRKCB were significantly associated with longer overall survival (P = 0.0018 and P = 0.0162), indicating that ARF3 and PRKCB overexpression could be positive prognostic factors in sarcoma patients. In these overall survival associated mRNAs, GNAI3 and PRKCB with the highest degree of connectivity, were hubs and tended to be essential (31). Moreover, PPI network showed that GNAI3 and PRKCB interacted with each other. The protein encoded by PRKCB is one of the PKC family members that has been reported to be involved in many different cellular functions. Surdez et al.’s study showed that PRKCB is strongly overexpressed in Ewing sarcoma. PRKCB inhibition significantly increased apoptosis in Ewing sarcoma cells and prevented tumor growth in vivo (32). GNAI3 encodes an alpha subunit of Guanine nucleotide-binding proteins and involves in various transmembrane signaling pathways. While their function and role in the prognosis of sarcoma patients remain to be further defined. Besides, in the ceRNA network, both GNAI3 and ARF3 can be regulated by miR-133b and miR-133a-3p, which are located in the center of regulatory network and interact with lncRNAs, including NONHSAT001973.2, NONHSAT203034.1, SNHG12 and ZNF37BP. Recent researches have demonstrated that SNHG12 was significantly over-expressing in osteosarcoma and high expression of SNHG12 tended to have a poor prognosis of osteosarcoma patients. Researchers further confirmed that SNHG12 promoted tumorigenesis and metastasis by activating the Notch signaling pathway, which functioned as a ceRNA, and modulated Notch2 expression of Notch2 by competing with miR-195-5p (33). Therefore, the interaction of SNHG12, miR-133a-3p/miR-133b and GNAI3 in sarcoma was deserved to be explored. Additionally, ARF3 also could be regulated by miR-378a-3p and miR-422a. Among them, miR-378a-3p target with LINC01296, and the high expression of LINC01229 showed a significant shorter overall survival of sarcoma patients (p = 0.0297).
The high expression of miRNA-301a-3p, miRNA-106b-5p, miRNA-130b-3p, and miRNA-423-3p were significantly associated with shorter overall survival of sarcoma patients (P < 0.0001, P = 0.0046, P = 0.0128, P = 0.0147, respectively). Overexpression of miR-301a was showed in Ewing sarcoma cell lines. Additionally, transfection of anti-miR-301a inhibited the proliferation and cell cycle progression of Ewing sarcoma cell (34). In the ceRNA network, the NEAT1/miR-301a-3p, XIST/miR-301a-3p, miR-301a-3p/NR3C2, miR-301a-3p/AR interactions were identified. XIST was significantly up-regulated in osteosarcoma tissues and cell lines, and increased XIST expression was associated with poor overall survival of patients (35). Nakatani et al. have defined miR-130b as an independent predictor of risk for disease progression and survival by Microarray analysis (36). Up to now, there is no study reporting that miRNA-423-3p and miRNA-106b-5p have association with sarcomas. NEAT1/miR-301a-3p/AR, XIST/miR-301a-3p/AR, NEAT1/miR-301a-3p/NR3C2, XIST/miR-301a-3p/AR axis predicted by the construction of ceRNA network may provide a more precise research direction for exploring biological mechanisms extending from this ceRNA network.
However, there are several limitations in the present study. Sarcomas contain multiple distinct subtypes and only two subtypes were involved in our study. More RNAs sequencing datasets of all subtypes of sarcomas were required for the construction of ceRNA network. Furthermore, regulatory ways of ceRNA network are very complex and ceRNA activity is influenced by multiple factors such as the abundance and subcellular location of ceRNA components, miRNA/ceRNA affinity, RNA editing and RBPs (7). This study only investigated the putative interaction of lncRNAs, miRNAs and genes, which require to be validated further.