Bladder cancer is a common malignant tumour worldwide. Epithelial–mesenchymal transition (EMT)-related biomarkers can be used for early diagnosis and prognosis of cancer patients. To explore, accurate prediction models are essential to the diagnosis and treatment for bladder cancer. In the present study, an EMT-related long noncoding RNA (lncRNA) model was developed to predict the prognosis of patients with bladder cancer. Firstly, the EMT-related lncRNAs were identified by Pearson correlation analysis, and a prognostic EMT-related lncRNA signature was constructed through univariate and multivariate Cox regression analyses. Then, the diagnostic efficacy and the clinically predictive capacity of the signature were assessed. Finally, Gene set enrichment analysis (GSEA) and functional enrichment analysis were carried out with bioinformatics. An EMT-related lncRNA signature consisting of TTC28-AS1, LINC02446, AL662844.4, AC105942.1, AL049840.3, SNHG26, USP30-AS1, PSMB8-AS1, AL031775.1, AC073534.1, U62317.2, C5orf56, AJ271736.1, and AL139385.1 was constructed. The diagnostic efficacy of the signature was evaluated by the time-dependent receiver-operating characteristic (ROC) curves, in which all the values of the area under the ROC (AUC) were more than 0.73. A nomogram established by integrating clinical variables and the risk score confirmed that the signature had a good clinically predict capacity. GSEA analysis revealed that some cancer-related and EMT-related pathways were enriched in high-risk groups, while immune-related pathways were enriched in low-risk groups. Functional enrichment analysis showed that EMT was associated with abundant GO terms or signaling pathways. In short, our research showed that the 14 EMT-related lncRNA signature may predict the prognosis and progression of patients with bladder cancer.
Purpose: NUSAP1 has been reported to be involved in the progression of several types of cancer. However, its expression and exact role in bladder cancer (BLCA) remains elusive. The aim of this study was to determine the expression and role of NUSAP1 in BLCA. Methods: Tissue microarray, real-time PCR, Western blot and immunohistochemistry assays were carried out to determine NUSAP1 expression in BLCA tissues and cells. The biological roles of NUSAP1 were investigated using CCK-8, EdU labeling, flow cytometry, Transwell, and wound healing assays. Additionally, the effect of NUSAP1 on epithelialmesenchymal transition (EMT) was investigated by Western blotting and real-time PCR. Results: We found that NUSAP1 was upregulated in BLCA, and its expression was closely related to the poor prognosis of patients. Subsequently, we transfected 5637 and T24 cell lines with NUSAP1 siRNA and an NUSAP1 overexpression plasmid, respectively. NUSAP1 downregulation in 5637 cells inhibited cell proliferation, migration, and invasiveness and enhanced chemosensitivity to gemcitabine, while NUSAP1 overexpression in T24 cells resulted in the inverse effects. Moreover, NUSAP1 regulated EMT via the TGF-β signaling pathway, and when TGF-beta receptor 1 (TGFBR1) was inhibited with the inhibitor SB525334, the invasion and metastasis ability of BLCA cells was significantly suppressed, as well as p-Smad2/3 and vimentin expression. Conclusion: Our above data demonstrate that NUSAP1 contributes to BLCA progression via the TGF-β signaling pathway.
Bladder cancer is a highly heterogeneous and aggressive malignancy with a poor prognosis. EGF/EGFR activation causes the detachment of SHC-binding protein 1 (SHCBP1) from SHC adapter protein 1 (SHC1), which subsequently translocates into the nucleus and promotes cancer development via multiple signaling pathways. However, the role of the EGF-SHCBP1 axis in bladder cancer progression remains unexplored. Herein, we report that SHCBP1 is upregulated in bladder cancer tissues and cells, with cytoplasmic or nuclear localization. Released SHCBP1 responds to EGF stimulation by translocating into the nucleus following Ser273 phosphorylation. Depletion of SHCBP1 reduces EGF-induced cell migration and invasiveness of bladder cancer cells. Mechanistically, SHCBP1 binds to RACGAP1 via its N-terminal domain of amino acids 1 ~ 428, and this interaction is enhanced following EGF treatment. Furthermore, SHCBP1 facilitates cell migration by inhibiting RACGAP-mediated GTP-RAC1 inactivation, whose activity is indispensable for cell movement. Collectively, we demonstrate that the EGF-SHCBP1-RACGAP1-RAC1 axis acts as a novel regulatory mechanism of bladder cancer progression, which offers a new clinical therapeutic strategy to combat bladder cancer.
BackgroundThe prognosis of renal cell carcinoma (RCC) varies greatly among different risk groups, and the traditional indicators have limited effect in the identification of risk grade in patients with RCC. The purpose of our study is to explore a glycolysis-based long non-coding RNAs (lncRNAs) signature and verify its potential clinical significance in prognostic prediction of RCC patients.MethodsIn this study, RNA data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate cox regression displayed six significantly related lncRNAs (AC124854.1, AC078778.1, EMX2OS, DLGAP1-AS2, AC084876.1, and AC026401.3) which were utilized in construction of risk score by a formula. The accuracy of risk score was verified by a series of statistical methods such as receiver operating characteristic (ROC) curves, nomogram and Kaplan-Meier curves. Its potential clinical significance was excavated by gene enrichment analysis.ResultsKaplan-Meier curves and ROC curves showed reliability of the risk score to predict the prognosis of RCC patients. Stratification analysis indicated that the risk score was independent predictor compare to other traditional clinical parameters. The clinical nomogram showed highly rigorous with index of 0.73 and precisely predicted 1-, 3-, and 5-year survival time of RCC patients. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene set enrichment analysis (GSEA) depicted the top ten correlated pathways in both high-risk group and low-risk group. There are 6 lncRNAs and 25 related mRNAs including 36 lncRNA-mRNA links in lncRNA-mRNA co-expression network.ConclusionThis research demonstrated that glycolysis-based lncRNAs possessed an important value in survival prediction of RCC patients, which would be a potential target for future treatment.
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