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Integrated analysis highlights multiple long non-coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a prevalent aggressive malignant tumor with poor prognosis. Investigations into the molecular changes that occur as a result of the disease, as well as identification of novel biomarkers for its diagnosis and prognosis, are urgently required. Long non-cod...

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Autores principales: Li, Cheng-Yun, Zhang, Wen-Wen, Xiang, Ji-Lian, Wang, Xing-Hua, Wang, Jun-Ling, Li, Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6859451/
https://www.ncbi.nlm.nih.gov/pubmed/31638253
http://dx.doi.org/10.3892/or.2019.7377
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author Li, Cheng-Yun
Zhang, Wen-Wen
Xiang, Ji-Lian
Wang, Xing-Hua
Wang, Jun-Ling
Li, Jin
author_facet Li, Cheng-Yun
Zhang, Wen-Wen
Xiang, Ji-Lian
Wang, Xing-Hua
Wang, Jun-Ling
Li, Jin
author_sort Li, Cheng-Yun
collection PubMed
description Esophageal squamous cell carcinoma (ESCC) is a prevalent aggressive malignant tumor with poor prognosis. Investigations into the molecular changes that occur as a result of the disease, as well as identification of novel biomarkers for its diagnosis and prognosis, are urgently required. Long non-coding RNAs (lncRNAs) have been reported to play a critical role in tumor progression. The present study performed data mining analyses for ESCC via an integrated study of accumulated datasets and identification of the differentially expressed lncRNAs from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The identified intersection of differentially expressed genes (lncRNAs, miRNAs and mRNAs) in ESCC tissues between the GEO and TCGA datasets was investigated. Based on these intersected lncRNAs, the present study constructed a competitive endogenous RNA (ceRNA) network of lncRNAs in ESCC. A total of 81 intersection lncRNAs were identified; 67 of these were included in the ceRNA network. Functional analyses revealed that these 67 key lncRNAs primarily dominated cellular biological processes. The present study then analyzed the associations between the expression levels of these 67 key lncRNAs and the clinicopathological characteristics of the ESCC patients, as well as their survival time using TCGA. The results revealed that 31 of these lncRNAs were associated with tumor grade, tumor-node-metastasis (TNM) stage and lymphatic metastasis status (P<0.05). In addition, 15 key lncRNAs were demonstrated to be associated with survival time (P<0.05). Finally, 5 key lncRNAs were selected for validation of their expression levels in 30 patients newly diagnosed with ESCC via reverse transcription-quantitative PCR (RT-qPCR). The results suggested that the fold changes in the trends of up- and downregulation between GEO, TCGA and RT-qPCR were consistent. In addition, it was also demonstrated that a select few of these 5 key lncRNAs were significantly associated with TNM stage and lymph node metastasis (P<0.05). The results of the clinically relevant analysis and the aforementioned bioinformatics were similar, hence proving that the bioinformatics analysis used in the present study is credible. Overall, the results from the present study may provide further insight into the functional characteristics of lncRNAs in ESCC through bioinformatics integrative analysis of the GEO and TCGA datasets, and reveal potential diagnostic and prognostic biomarkers for ESCC.
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spelling pubmed-68594512019-11-26 Integrated analysis highlights multiple long non-coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma Li, Cheng-Yun Zhang, Wen-Wen Xiang, Ji-Lian Wang, Xing-Hua Wang, Jun-Ling Li, Jin Oncol Rep Articles Esophageal squamous cell carcinoma (ESCC) is a prevalent aggressive malignant tumor with poor prognosis. Investigations into the molecular changes that occur as a result of the disease, as well as identification of novel biomarkers for its diagnosis and prognosis, are urgently required. Long non-coding RNAs (lncRNAs) have been reported to play a critical role in tumor progression. The present study performed data mining analyses for ESCC via an integrated study of accumulated datasets and identification of the differentially expressed lncRNAs from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The identified intersection of differentially expressed genes (lncRNAs, miRNAs and mRNAs) in ESCC tissues between the GEO and TCGA datasets was investigated. Based on these intersected lncRNAs, the present study constructed a competitive endogenous RNA (ceRNA) network of lncRNAs in ESCC. A total of 81 intersection lncRNAs were identified; 67 of these were included in the ceRNA network. Functional analyses revealed that these 67 key lncRNAs primarily dominated cellular biological processes. The present study then analyzed the associations between the expression levels of these 67 key lncRNAs and the clinicopathological characteristics of the ESCC patients, as well as their survival time using TCGA. The results revealed that 31 of these lncRNAs were associated with tumor grade, tumor-node-metastasis (TNM) stage and lymphatic metastasis status (P<0.05). In addition, 15 key lncRNAs were demonstrated to be associated with survival time (P<0.05). Finally, 5 key lncRNAs were selected for validation of their expression levels in 30 patients newly diagnosed with ESCC via reverse transcription-quantitative PCR (RT-qPCR). The results suggested that the fold changes in the trends of up- and downregulation between GEO, TCGA and RT-qPCR were consistent. In addition, it was also demonstrated that a select few of these 5 key lncRNAs were significantly associated with TNM stage and lymph node metastasis (P<0.05). The results of the clinically relevant analysis and the aforementioned bioinformatics were similar, hence proving that the bioinformatics analysis used in the present study is credible. Overall, the results from the present study may provide further insight into the functional characteristics of lncRNAs in ESCC through bioinformatics integrative analysis of the GEO and TCGA datasets, and reveal potential diagnostic and prognostic biomarkers for ESCC. D.A. Spandidos 2019-12 2019-10-17 /pmc/articles/PMC6859451/ /pubmed/31638253 http://dx.doi.org/10.3892/or.2019.7377 Text en Copyright: © Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Li, Cheng-Yun
Zhang, Wen-Wen
Xiang, Ji-Lian
Wang, Xing-Hua
Wang, Jun-Ling
Li, Jin
Integrated analysis highlights multiple long non-coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma
title Integrated analysis highlights multiple long non-coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma
title_full Integrated analysis highlights multiple long non-coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma
title_fullStr Integrated analysis highlights multiple long non-coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma
title_full_unstemmed Integrated analysis highlights multiple long non-coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma
title_short Integrated analysis highlights multiple long non-coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma
title_sort integrated analysis highlights multiple long non-coding rnas and their potential roles in the progression of human esophageal squamous cell carcinoma
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6859451/
https://www.ncbi.nlm.nih.gov/pubmed/31638253
http://dx.doi.org/10.3892/or.2019.7377
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