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Integrative approach for differentially overexpressed genes in gastric cancer by combining large-scale gene expression profiling and network analysis

Gene expression profiling is a valuable tool for identifying differentially expressed genes in studies of disease subtype and patient outcome for various cancers. However, it remains difficult to assign biological significance to the vast number of genes. There is an increasing awareness of gene exp...

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Autores principales: Takeno, A, Takemasa, I, Doki, Y, Yamasaki, M, Miyata, H, Takiguchi, S, Fujiwara, Y, Matsubara, K, Monden, M
Formato: Texto
Lenguaje:English
Publicado: Nature Publishing Group 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570518/
https://www.ncbi.nlm.nih.gov/pubmed/18827816
http://dx.doi.org/10.1038/sj.bjc.6604682
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author Takeno, A
Takemasa, I
Doki, Y
Yamasaki, M
Miyata, H
Takiguchi, S
Fujiwara, Y
Matsubara, K
Monden, M
author_facet Takeno, A
Takemasa, I
Doki, Y
Yamasaki, M
Miyata, H
Takiguchi, S
Fujiwara, Y
Matsubara, K
Monden, M
author_sort Takeno, A
collection PubMed
description Gene expression profiling is a valuable tool for identifying differentially expressed genes in studies of disease subtype and patient outcome for various cancers. However, it remains difficult to assign biological significance to the vast number of genes. There is an increasing awareness of gene expression profile as an important part of the contextual molecular network at play in complex biological processes such as cancer initiation and progression. This study analysed the transcriptional profiles commonly activated at different stages of gastric cancers using an integrated approach combining gene expression profiling of 222 human tissues and gene regulatory dynamic mapping. We focused on an inferred core network with CDKN1A (p21(WAF1/CIP1)) as the hub, and extracted seven candidates for gastric carcinogenesis (MMP7, SPARC, SOD2, INHBA, IGFBP7, NEK6, LUM). They were classified into two groups based on the correlation between expression level and stage. The seven genes were commonly activated and their expression levels tended to increase as disease progressed. NEK6 and INHBA are particularly promising candidate genes overexpressed at the protein level, as confirmed by immunohistochemistry and western blotting. This integrated approach could help to identify candidate players in gastric carcinogenesis and progression. These genes are potential markers of gastric cancer regardless of stage.
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spelling pubmed-25705182009-10-21 Integrative approach for differentially overexpressed genes in gastric cancer by combining large-scale gene expression profiling and network analysis Takeno, A Takemasa, I Doki, Y Yamasaki, M Miyata, H Takiguchi, S Fujiwara, Y Matsubara, K Monden, M Br J Cancer Genetics and Genomics Gene expression profiling is a valuable tool for identifying differentially expressed genes in studies of disease subtype and patient outcome for various cancers. However, it remains difficult to assign biological significance to the vast number of genes. There is an increasing awareness of gene expression profile as an important part of the contextual molecular network at play in complex biological processes such as cancer initiation and progression. This study analysed the transcriptional profiles commonly activated at different stages of gastric cancers using an integrated approach combining gene expression profiling of 222 human tissues and gene regulatory dynamic mapping. We focused on an inferred core network with CDKN1A (p21(WAF1/CIP1)) as the hub, and extracted seven candidates for gastric carcinogenesis (MMP7, SPARC, SOD2, INHBA, IGFBP7, NEK6, LUM). They were classified into two groups based on the correlation between expression level and stage. The seven genes were commonly activated and their expression levels tended to increase as disease progressed. NEK6 and INHBA are particularly promising candidate genes overexpressed at the protein level, as confirmed by immunohistochemistry and western blotting. This integrated approach could help to identify candidate players in gastric carcinogenesis and progression. These genes are potential markers of gastric cancer regardless of stage. Nature Publishing Group 2008-10-21 2008-09-30 /pmc/articles/PMC2570518/ /pubmed/18827816 http://dx.doi.org/10.1038/sj.bjc.6604682 Text en Copyright © 2008 Cancer Research UK https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material.If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/.
spellingShingle Genetics and Genomics
Takeno, A
Takemasa, I
Doki, Y
Yamasaki, M
Miyata, H
Takiguchi, S
Fujiwara, Y
Matsubara, K
Monden, M
Integrative approach for differentially overexpressed genes in gastric cancer by combining large-scale gene expression profiling and network analysis
title Integrative approach for differentially overexpressed genes in gastric cancer by combining large-scale gene expression profiling and network analysis
title_full Integrative approach for differentially overexpressed genes in gastric cancer by combining large-scale gene expression profiling and network analysis
title_fullStr Integrative approach for differentially overexpressed genes in gastric cancer by combining large-scale gene expression profiling and network analysis
title_full_unstemmed Integrative approach for differentially overexpressed genes in gastric cancer by combining large-scale gene expression profiling and network analysis
title_short Integrative approach for differentially overexpressed genes in gastric cancer by combining large-scale gene expression profiling and network analysis
title_sort integrative approach for differentially overexpressed genes in gastric cancer by combining large-scale gene expression profiling and network analysis
topic Genetics and Genomics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570518/
https://www.ncbi.nlm.nih.gov/pubmed/18827816
http://dx.doi.org/10.1038/sj.bjc.6604682
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