Abstract
Long non-coding RNAs (lncRNAs) have been indicated as the candidate factors to predict cancer prognosis. However, it is still unknown whether lncRNA combinations may be utilized for predicting overall survival (OS) of prostate cancer (PCa). The present work focused on selecting the potent OS-related lncRNA signature for PCa and studying its molecular mechanism to enhance the prognosis prediction accuracy. Differentially expressed lncRNAs (DElncRNAs) or differentially expressed genes (DEGs) were obtained based on TCGA database by R software “edgeR” package. lncRNAs or mRNAs significantly related to PCa were screened through univariate as well as multivariate Cox regression, for the construction of the risk model for prognosis prediction. Moreover, this constructed risk model was validated through ROC analysis, univariate regression, and Kaplan–Meier (KM) analysis. Additionally, we built a lncRNA–miRNA–mRNA ceRNA network through bioinformatics analysis. Colony formation, CCK-8, flow cytometry, scratch, and Transwell assays were performed based on PCa cells subjected to small interfering RNA (siRNA) targeting LINC01679/SLC17A9 and vector expressing LINC01679/SLC17A9 transfection. Thereafter, the ceRNA mechanism was clarified via qRT-PCR, Western blotting (WB), RNA pull-down, and luciferase reporter assays. Nude mouse tumor xenograft was established to examine LINC01679’s oncogenicity within PCa cells. According to our results, LINC01679 depletion promoted cell proliferation, metastasis, tumor growth, and inhibited cell apoptosis in vivo and in vitro, which was also associated with poor survival. LINC01679 regulated miR-3150a-3p level by sponging it. Importantly, miR-3150a-3p overexpression was related to the increased proliferation and decreased apoptosis of PCa cells. Rescue assays suggested that miR-3150a-3p mimics rescued the repression on PCa progression mediated by LINC01679 upregulation, but SLC17A9 downregulation reversed the miR-3150a-3p inhibitor-mediated repression on PC progression. Importantly, SLC17A9 downregulation rescued the repression on PCa progression mediated by LINC01679 upregulation. LINC01679 and SLC17A9 are tightly associated with certain clinicopathological characteristics of PCa and its prognostic outcome. In addition, LINC01679 is the ceRNA that suppresses PCa development through modulating the miR-3150a-3p/SLC17A9 axis.
Highlights
Prostate cancer (PCa) is the most common reproductive cancer in men
The results of this study showed that SLC17A9 protein and mRNA expression saw a synchronous rise by transfection with LINC01679-OE, but this effect disappeared in cells co-transfected with LINC01679-OE and miR-3150a-3p mimics (Figure 10E)
A Competitive endogenous RNAs (ceRNAs) network of PCa was established by Long non-coding RNAs (lncRNAs) signature, mRNA signature, and their common miRNAs
Summary
Prostate cancer (PCa) is the most common reproductive cancer in men. PCa ranks the second and fifth in terms of its morbidity and death-related cause among men worldwide (Wang G. et al, 2018). In view of different development links, it is of important theoretical and clinical significance to use big data, cloud computing technology, and translational biomedical informatics methods to achieve accurate intervention, slow down, or even reverse the process of prostate cancerization through systematic analysis, integration, and identification of key elements. Analyzing network structure and function is of crucial significance to understand complex biological problems It has always been an important issue in network science and systems biology to find the key sites or key role relationships in the network system, so as to measure or evaluate the stability of biological systems. This study built a ceRNA network to find key sites affecting the stability of the network and system and their relationship, so as to provide theoretical reference for diagnosing and treating PCa and other cancers
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