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Systematic analysis of mRNA expression profiles in NSCLC cell lines to screen metastasis-related genes

Lung cancer is the most prevalent cancer in humans and has the lowest survival outcomes due to its high metastatic potential. The aim of the present study was to screen for metastasis-related genes (MRGs) by investigating the differential expression genes (DEGs) identified by the mRNA expression pro...

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Autores principales: Liu, Ying, Liu, Lei, Yu, Tao, Lin, He-Chun, Chu, Dandan, Deng, Wei, Yan, Ming-Xia, Li, Jing, Yao, Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5355670/
https://www.ncbi.nlm.nih.gov/pubmed/27840927
http://dx.doi.org/10.3892/mmr.2016.5911
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author Liu, Ying
Liu, Lei
Yu, Tao
Lin, He-Chun
Chu, Dandan
Deng, Wei
Yan, Ming-Xia
Li, Jing
Yao, Ming
author_facet Liu, Ying
Liu, Lei
Yu, Tao
Lin, He-Chun
Chu, Dandan
Deng, Wei
Yan, Ming-Xia
Li, Jing
Yao, Ming
author_sort Liu, Ying
collection PubMed
description Lung cancer is the most prevalent cancer in humans and has the lowest survival outcomes due to its high metastatic potential. The aim of the present study was to screen for metastasis-related genes (MRGs) by investigating the differential expression genes (DEGs) identified by the mRNA expression profiles in SPC-A-1sci (highly metastatic) and SPC-A-1 (parental) cells. DEGs were screened using Genespring software. Gene Ontology and pathway enrichment analyses of these DEGs were performed. Interaction networks between the proteins encoded by the DEGs were identified using the database BioGRID and were visualized by Cytoscape. Modular analysis of the protein-protein interaction network was performed in CFinder. Among these DEGs, the expression levels of 18 genes were examined in SPC-A-1sci and SPC-A-1 cell lines with reverse transcription-quantitative polymerase chain reaction, and 10 of the 18 genes were assessed by western blotting to validate the results of the microarray. Furthermore, the role of metallothionein 1X (MT1X) in non-small cell lung cancer was explored in functional assays and 72 pairs of clinical samples in vitro. Finally, 4,838 DEGs were screened, including 798 upregulated and 4,040 downregulated genes. The significantly enriched functions included gene expression, cytosol and poly-(A) RNA binding, and the most enriched pathway was biosynthesis of antibiotics. Furthermore, MT1X was revealed to promote the migration and invasion ability in SPC-A-1sci and PC-9 lung cancer cell lines. Therefore, MT1X was identified as a candidate MRG through systematic analysis in the present microarray, which was demonstrated to offer potential reference value in screening MRGs.
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spelling pubmed-53556702017-03-31 Systematic analysis of mRNA expression profiles in NSCLC cell lines to screen metastasis-related genes Liu, Ying Liu, Lei Yu, Tao Lin, He-Chun Chu, Dandan Deng, Wei Yan, Ming-Xia Li, Jing Yao, Ming Mol Med Rep Articles Lung cancer is the most prevalent cancer in humans and has the lowest survival outcomes due to its high metastatic potential. The aim of the present study was to screen for metastasis-related genes (MRGs) by investigating the differential expression genes (DEGs) identified by the mRNA expression profiles in SPC-A-1sci (highly metastatic) and SPC-A-1 (parental) cells. DEGs were screened using Genespring software. Gene Ontology and pathway enrichment analyses of these DEGs were performed. Interaction networks between the proteins encoded by the DEGs were identified using the database BioGRID and were visualized by Cytoscape. Modular analysis of the protein-protein interaction network was performed in CFinder. Among these DEGs, the expression levels of 18 genes were examined in SPC-A-1sci and SPC-A-1 cell lines with reverse transcription-quantitative polymerase chain reaction, and 10 of the 18 genes were assessed by western blotting to validate the results of the microarray. Furthermore, the role of metallothionein 1X (MT1X) in non-small cell lung cancer was explored in functional assays and 72 pairs of clinical samples in vitro. Finally, 4,838 DEGs were screened, including 798 upregulated and 4,040 downregulated genes. The significantly enriched functions included gene expression, cytosol and poly-(A) RNA binding, and the most enriched pathway was biosynthesis of antibiotics. Furthermore, MT1X was revealed to promote the migration and invasion ability in SPC-A-1sci and PC-9 lung cancer cell lines. Therefore, MT1X was identified as a candidate MRG through systematic analysis in the present microarray, which was demonstrated to offer potential reference value in screening MRGs. D.A. Spandidos 2016-12 2016-11-01 /pmc/articles/PMC5355670/ /pubmed/27840927 http://dx.doi.org/10.3892/mmr.2016.5911 Text en Copyright: © Liu 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
Liu, Ying
Liu, Lei
Yu, Tao
Lin, He-Chun
Chu, Dandan
Deng, Wei
Yan, Ming-Xia
Li, Jing
Yao, Ming
Systematic analysis of mRNA expression profiles in NSCLC cell lines to screen metastasis-related genes
title Systematic analysis of mRNA expression profiles in NSCLC cell lines to screen metastasis-related genes
title_full Systematic analysis of mRNA expression profiles in NSCLC cell lines to screen metastasis-related genes
title_fullStr Systematic analysis of mRNA expression profiles in NSCLC cell lines to screen metastasis-related genes
title_full_unstemmed Systematic analysis of mRNA expression profiles in NSCLC cell lines to screen metastasis-related genes
title_short Systematic analysis of mRNA expression profiles in NSCLC cell lines to screen metastasis-related genes
title_sort systematic analysis of mrna expression profiles in nsclc cell lines to screen metastasis-related genes
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5355670/
https://www.ncbi.nlm.nih.gov/pubmed/27840927
http://dx.doi.org/10.3892/mmr.2016.5911
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