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Integrative bioinformatics analysis identifies LINC01614 as a potential prognostic signature in esophageal cancer

BACKGROUND: Esophageal cancer (EC) is one of the most common gastrointestinal cancers and the incidence is on the increase in recent years. The aim of the present study was to assess novel long non-coding RNA (lncRNA) biomarkers for the prognosis of EC through the analysis of gene expression microar...

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Autores principales: Yan, Shuo, Xu, Jichong, Liu, Bingyan, Ma, Lin, Tan, Huaqiao, Fang, Chun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798299/
https://www.ncbi.nlm.nih.gov/pubmed/35116503
http://dx.doi.org/10.21037/tcr-20-2529
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author Yan, Shuo
Xu, Jichong
Liu, Bingyan
Ma, Lin
Tan, Huaqiao
Fang, Chun
author_facet Yan, Shuo
Xu, Jichong
Liu, Bingyan
Ma, Lin
Tan, Huaqiao
Fang, Chun
author_sort Yan, Shuo
collection PubMed
description BACKGROUND: Esophageal cancer (EC) is one of the most common gastrointestinal cancers and the incidence is on the increase in recent years. The aim of the present study was to assess novel long non-coding RNA (lncRNA) biomarkers for the prognosis of EC through the analysis of gene expression microarrays. METHODS: Three datasets (GSE53622, GSE53624, and GSE53625) were downloaded from the Gene Expression Omnibus (GEO) database and EC patients’ clinical information were from The Cancer Genome Atlas (TCGA) databases. Differentially expressed genes (DEGs) were screened by comparing tumor tissues with normal tissues using limma R package. The Gene Expression Profiling Interactive Analysis 2 (GEPIA2) database was used to obtain the novel lncRNAs and their co-expression genes in EC and these were visualized with the Cytoscape software. The Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology Based Annotation System (KOBAS) database was used to analyze the functions enrichment of selected DEGs. Cell Counting Kit-8 (CCK8) and Transwell assays were used to further confirm the function of target lncRNAs. RESULTS: We identified 24 differentially expressed (DE) lncRNAs and 659 DE mRNAs from the intersection of GEO and TCGA databases. And we found that only LINC01614 was concerned with a candidate prognostic signature in EC. “Extracellular matrix (ECM)-receptor interaction” and “PI3K-Akt signaling pathway” were observed, and we constructed a lncRNA-mRNA co-expression network for EC that includes LINC01614 and 64 mRNAs. The results of CCK8 and Transwell assays showed that suppression of LINC01614 inhibited EC cell proliferation and migration. CONCLUSIONS: Our study might provide LINC01614 as a novel lncRNA biomarker for diagnosis and prognosis in EC.
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spelling pubmed-87982992022-02-02 Integrative bioinformatics analysis identifies LINC01614 as a potential prognostic signature in esophageal cancer Yan, Shuo Xu, Jichong Liu, Bingyan Ma, Lin Tan, Huaqiao Fang, Chun Transl Cancer Res Original Article BACKGROUND: Esophageal cancer (EC) is one of the most common gastrointestinal cancers and the incidence is on the increase in recent years. The aim of the present study was to assess novel long non-coding RNA (lncRNA) biomarkers for the prognosis of EC through the analysis of gene expression microarrays. METHODS: Three datasets (GSE53622, GSE53624, and GSE53625) were downloaded from the Gene Expression Omnibus (GEO) database and EC patients’ clinical information were from The Cancer Genome Atlas (TCGA) databases. Differentially expressed genes (DEGs) were screened by comparing tumor tissues with normal tissues using limma R package. The Gene Expression Profiling Interactive Analysis 2 (GEPIA2) database was used to obtain the novel lncRNAs and their co-expression genes in EC and these were visualized with the Cytoscape software. The Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology Based Annotation System (KOBAS) database was used to analyze the functions enrichment of selected DEGs. Cell Counting Kit-8 (CCK8) and Transwell assays were used to further confirm the function of target lncRNAs. RESULTS: We identified 24 differentially expressed (DE) lncRNAs and 659 DE mRNAs from the intersection of GEO and TCGA databases. And we found that only LINC01614 was concerned with a candidate prognostic signature in EC. “Extracellular matrix (ECM)-receptor interaction” and “PI3K-Akt signaling pathway” were observed, and we constructed a lncRNA-mRNA co-expression network for EC that includes LINC01614 and 64 mRNAs. The results of CCK8 and Transwell assays showed that suppression of LINC01614 inhibited EC cell proliferation and migration. CONCLUSIONS: Our study might provide LINC01614 as a novel lncRNA biomarker for diagnosis and prognosis in EC. AME Publishing Company 2021-04 /pmc/articles/PMC8798299/ /pubmed/35116503 http://dx.doi.org/10.21037/tcr-20-2529 Text en 2021 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Original Article
Yan, Shuo
Xu, Jichong
Liu, Bingyan
Ma, Lin
Tan, Huaqiao
Fang, Chun
Integrative bioinformatics analysis identifies LINC01614 as a potential prognostic signature in esophageal cancer
title Integrative bioinformatics analysis identifies LINC01614 as a potential prognostic signature in esophageal cancer
title_full Integrative bioinformatics analysis identifies LINC01614 as a potential prognostic signature in esophageal cancer
title_fullStr Integrative bioinformatics analysis identifies LINC01614 as a potential prognostic signature in esophageal cancer
title_full_unstemmed Integrative bioinformatics analysis identifies LINC01614 as a potential prognostic signature in esophageal cancer
title_short Integrative bioinformatics analysis identifies LINC01614 as a potential prognostic signature in esophageal cancer
title_sort integrative bioinformatics analysis identifies linc01614 as a potential prognostic signature in esophageal cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798299/
https://www.ncbi.nlm.nih.gov/pubmed/35116503
http://dx.doi.org/10.21037/tcr-20-2529
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