Dataset Information

An epithelial-mesenchymal transition-related long noncoding RNA signature correlates with the prognosis and progression in patients with bladder cancer.

ABSTRACT: 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.

SUBMITTER: Tong H

PROVIDER: S-EPMC7786330 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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An epithelial-mesenchymal transition-related long noncoding RNA signature correlates with the prognosis and progression in patients with bladder cancer.

Tong Hang H Li Tinghao T Gao Shun S Yin Hubin H Cao Honghao H He Weiyang W

Bioscience reports 20210101 1

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 a ...[more]

PMID: 33289830

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Project description:AbstractReliable biomarkers are of great significance for the treatment and diagnosis of hepatocellular carcinoma (HCC). This study identified potential prognostic epithelial-mesenchymal transition related lncRNAs (ERLs) by the cancer genome atlas (TCGA) database and bioinformatics.The differential expression of long noncoding RNA (lncRNA) was obtained by analyzing the lncRNA data of 370 HCC samples in TCGA. Then, Pearson correlation analysis was carried out with EMT related genes (ERGs) from molecular signatures database. Combined with the univariate Cox expression analysis of the total survival rate of hepatocellular carcinoma (HCC) patients, the prognostic ERLs were obtained. Then use "step" function to select the optimal combination of constructing multivariate Cox expression model. The expression levels of ERLs in HCC samples were verified by real-time quantitative polymerase chain reaction.Finally, we identified 5 prognostic ERLs (AC023157.3, AC099850.3, AL031985.3, AL365203.2, CYTOR). The model showed that these prognostic markers were reliable independent predictors of risk factors (P value <.0001, hazard ratio [HR] = 2.400, 95% confidence interval [CI] = 1.667-3.454 for OS). In the time-dependent receiver operating characteristic analysis, this prognostic marker is a good predictor of HCC survival (area under the curve of 1 year, 2 years, 3 years, and 5 years are 0.754, 0.720, 0.704, and 0.662 respectively). We analyzed the correlation of clinical characteristics of these prognostic markers, and the results show that this prognostic marker is an independent factor that can predict the prognosis of HCC more accurately. In addition, by matching with the Molecular Signatures Database, we obtained 18 ERLs, and then constructed the HCC prognosis model and clinical feature correlation analysis using 5 prognostic ERLs. The results show that these prognostic markers have reliable independent predictive value. Bioinformatics analysis showed that these prognostic markers were involved in the regulation of EMT and related functions of tumor occurrence and migration.Five prognostic types of ERLs identified in this study can be used as potential biomarkers to predict the prognosis of HCC.

Dataset Information

An epithelial-mesenchymal transition-related long noncoding RNA signature correlates with the prognosis and progression in patients with bladder cancer.

Publications

An epithelial-mesenchymal transition-related long noncoding RNA signature correlates with the prognosis and progression in patients with bladder cancer.

Similar Datasets

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