Cargando…

Time course analysis based on gene expression profile and identification of target molecules for colorectal cancer

BACKGROUND: The study aimed to investigate the expression changes of genes in colorectal cancer (CRC) and screen the potential molecular targets. METHODS: The GSE37178 of mRNA expression profile including the CRC samples extracted by surgical resection and the paired normal samples was downloaded fr...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Guoting, Han, Ning, Li, Guofeng, Li, Xin, Li, Guang, Li, Zengchun, Li, Qinchuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4806509/
https://www.ncbi.nlm.nih.gov/pubmed/27013928
http://dx.doi.org/10.1186/s12935-016-0296-3
_version_ 1782423252710195200
author Chen, Guoting
Han, Ning
Li, Guofeng
Li, Xin
Li, Guang
Li, Zengchun
Li, Qinchuan
author_facet Chen, Guoting
Han, Ning
Li, Guofeng
Li, Xin
Li, Guang
Li, Zengchun
Li, Qinchuan
author_sort Chen, Guoting
collection PubMed
description BACKGROUND: The study aimed to investigate the expression changes of genes in colorectal cancer (CRC) and screen the potential molecular targets. METHODS: The GSE37178 of mRNA expression profile including the CRC samples extracted by surgical resection and the paired normal samples was downloaded from Gene Expression Omnibus database. The genes whose expressions were changed at four different time points were screened and clustered using Mfuzz package. Then DAVID was used to perform the functional and pathway enrichment analysis for genes in different clusters. The protein–protein interaction (PPI) networks were constructed for genes in the clusters according to the STRING database. Furthermore, the related-transcription factors (TFs) and microRNAs (miRNAs) were obtained based on the resources in databases and then were combined with the PPI networks in each cluster to construct the integrated network containing genes, TFs and miRNAs. RESULTS: As a result, 314 genes were clustered into four groups. Genes in cluster 1 and cluster 2 showed a decreasing trend, while genes in cluster 3 and cluster 4 presented an increasing trend. Then 18 TFs (e.g., TCF4, MEF2C and FOS) and 18 miRNAs (e.g., miR-382, miR-217, miR-1184, miR-326 and miR-330-5p) were identified and three integrated networks for cluster 1, 3, and 4 were constructed. CONCLUSIONS: The results implied that expression of PITX2, VSNL1, TCF4, MEF2C and FOS are time-related and associated with CRC development, accompanied by several miRNAs including miR-382, miR-217, miR-21, miR-1184, miR-326 and miR-330-5p. All of them might be used as potential diagnostic or therapeutic target molecules for CRC.
format Online
Article
Text
id pubmed-4806509
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-48065092016-03-25 Time course analysis based on gene expression profile and identification of target molecules for colorectal cancer Chen, Guoting Han, Ning Li, Guofeng Li, Xin Li, Guang Li, Zengchun Li, Qinchuan Cancer Cell Int Primary Research BACKGROUND: The study aimed to investigate the expression changes of genes in colorectal cancer (CRC) and screen the potential molecular targets. METHODS: The GSE37178 of mRNA expression profile including the CRC samples extracted by surgical resection and the paired normal samples was downloaded from Gene Expression Omnibus database. The genes whose expressions were changed at four different time points were screened and clustered using Mfuzz package. Then DAVID was used to perform the functional and pathway enrichment analysis for genes in different clusters. The protein–protein interaction (PPI) networks were constructed for genes in the clusters according to the STRING database. Furthermore, the related-transcription factors (TFs) and microRNAs (miRNAs) were obtained based on the resources in databases and then were combined with the PPI networks in each cluster to construct the integrated network containing genes, TFs and miRNAs. RESULTS: As a result, 314 genes were clustered into four groups. Genes in cluster 1 and cluster 2 showed a decreasing trend, while genes in cluster 3 and cluster 4 presented an increasing trend. Then 18 TFs (e.g., TCF4, MEF2C and FOS) and 18 miRNAs (e.g., miR-382, miR-217, miR-1184, miR-326 and miR-330-5p) were identified and three integrated networks for cluster 1, 3, and 4 were constructed. CONCLUSIONS: The results implied that expression of PITX2, VSNL1, TCF4, MEF2C and FOS are time-related and associated with CRC development, accompanied by several miRNAs including miR-382, miR-217, miR-21, miR-1184, miR-326 and miR-330-5p. All of them might be used as potential diagnostic or therapeutic target molecules for CRC. BioMed Central 2016-03-24 /pmc/articles/PMC4806509/ /pubmed/27013928 http://dx.doi.org/10.1186/s12935-016-0296-3 Text en © Chen et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Primary Research
Chen, Guoting
Han, Ning
Li, Guofeng
Li, Xin
Li, Guang
Li, Zengchun
Li, Qinchuan
Time course analysis based on gene expression profile and identification of target molecules for colorectal cancer
title Time course analysis based on gene expression profile and identification of target molecules for colorectal cancer
title_full Time course analysis based on gene expression profile and identification of target molecules for colorectal cancer
title_fullStr Time course analysis based on gene expression profile and identification of target molecules for colorectal cancer
title_full_unstemmed Time course analysis based on gene expression profile and identification of target molecules for colorectal cancer
title_short Time course analysis based on gene expression profile and identification of target molecules for colorectal cancer
title_sort time course analysis based on gene expression profile and identification of target molecules for colorectal cancer
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4806509/
https://www.ncbi.nlm.nih.gov/pubmed/27013928
http://dx.doi.org/10.1186/s12935-016-0296-3
work_keys_str_mv AT chenguoting timecourseanalysisbasedongeneexpressionprofileandidentificationoftargetmoleculesforcolorectalcancer
AT hanning timecourseanalysisbasedongeneexpressionprofileandidentificationoftargetmoleculesforcolorectalcancer
AT liguofeng timecourseanalysisbasedongeneexpressionprofileandidentificationoftargetmoleculesforcolorectalcancer
AT lixin timecourseanalysisbasedongeneexpressionprofileandidentificationoftargetmoleculesforcolorectalcancer
AT liguang timecourseanalysisbasedongeneexpressionprofileandidentificationoftargetmoleculesforcolorectalcancer
AT lizengchun timecourseanalysisbasedongeneexpressionprofileandidentificationoftargetmoleculesforcolorectalcancer
AT liqinchuan timecourseanalysisbasedongeneexpressionprofileandidentificationoftargetmoleculesforcolorectalcancer