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Gene expression profiling analysis of ovarian cancer

As a gynecological oncology, ovarian cancer has high incidence and mortality. To study the mechanisms of ovarian cancer, the present study analyzed the GSE37582 microarray. GSE37582 was downloaded from Gene Expression Omnibus and included data from 74 ovarian cancer cases and 47 healthy controls. Th...

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Autores principales: YIN, JI-GANG, LIU, XIAN-YING, WANG, BIN, WANG, DAN-YANG, WEI, MAN, FANG, HUA, XIANG, MEI
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4906568/
https://www.ncbi.nlm.nih.gov/pubmed/27347159
http://dx.doi.org/10.3892/ol.2016.4663
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author YIN, JI-GANG
LIU, XIAN-YING
WANG, BIN
WANG, DAN-YANG
WEI, MAN
FANG, HUA
XIANG, MEI
author_facet YIN, JI-GANG
LIU, XIAN-YING
WANG, BIN
WANG, DAN-YANG
WEI, MAN
FANG, HUA
XIANG, MEI
author_sort YIN, JI-GANG
collection PubMed
description As a gynecological oncology, ovarian cancer has high incidence and mortality. To study the mechanisms of ovarian cancer, the present study analyzed the GSE37582 microarray. GSE37582 was downloaded from Gene Expression Omnibus and included data from 74 ovarian cancer cases and 47 healthy controls. The differentially-expressed genes (DEGs) were screened using linear models for microarray data package in R and were further screened for functional annotation. Next, Gene Ontology and pathway enrichment analysis of the DEGs was conducted. The interaction associations of the proteins encoded by the DEGs were searched using the Search Tool for the Retrieval of Interacting Genes, and the protein-protein interaction (PPI) network was visualized by Cytoscape. Moreover, module analysis of the PPI network was performed using the BioNet analysis tool in R. A total of 284 DEGs were screened, consisting of 145 upregulated genes and 139 downregulated genes. In particular, downregulated FBJ murine osteosarcoma viral oncogene homolog (FOS) was an oncogene, while downregulated cyclin-dependent kinase inhibitor 1A (CDKN1A) was a tumor suppressor gene and upregulated cluster of differentiation 44 (CD44) was classed as an ‘other’ gene. The enriched functions included collagen catabolic process, stress-activated mitogen-activated protein kinases cascade and insulin receptor signaling pathway. Meanwhile, FOS (degree, 15), CD44 (degree, 9), B-cell CLL/lymphoma 2 (BCL2; degree, 7), CDKN1A (degree, 7) and matrix metallopeptidase 3 (MMP3; degree, 6) had higher connectivity degrees in the PPI network for the DEGs. These genes may be involved in ovarian cancer by interacting with other genes in the module of the PPI network (e.g., BCL2-FOS, BCL2-CDKN1A, FOS-CDKN1A, FOS-CD44, MMP3-MMP7 and MMP7-CD44). Overall, BCL2, FOS, CDKN1A, CD44, MMP3 and MMP7 may be correlated with ovarian cancer.
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spelling pubmed-49065682016-06-24 Gene expression profiling analysis of ovarian cancer YIN, JI-GANG LIU, XIAN-YING WANG, BIN WANG, DAN-YANG WEI, MAN FANG, HUA XIANG, MEI Oncol Lett Articles As a gynecological oncology, ovarian cancer has high incidence and mortality. To study the mechanisms of ovarian cancer, the present study analyzed the GSE37582 microarray. GSE37582 was downloaded from Gene Expression Omnibus and included data from 74 ovarian cancer cases and 47 healthy controls. The differentially-expressed genes (DEGs) were screened using linear models for microarray data package in R and were further screened for functional annotation. Next, Gene Ontology and pathway enrichment analysis of the DEGs was conducted. The interaction associations of the proteins encoded by the DEGs were searched using the Search Tool for the Retrieval of Interacting Genes, and the protein-protein interaction (PPI) network was visualized by Cytoscape. Moreover, module analysis of the PPI network was performed using the BioNet analysis tool in R. A total of 284 DEGs were screened, consisting of 145 upregulated genes and 139 downregulated genes. In particular, downregulated FBJ murine osteosarcoma viral oncogene homolog (FOS) was an oncogene, while downregulated cyclin-dependent kinase inhibitor 1A (CDKN1A) was a tumor suppressor gene and upregulated cluster of differentiation 44 (CD44) was classed as an ‘other’ gene. The enriched functions included collagen catabolic process, stress-activated mitogen-activated protein kinases cascade and insulin receptor signaling pathway. Meanwhile, FOS (degree, 15), CD44 (degree, 9), B-cell CLL/lymphoma 2 (BCL2; degree, 7), CDKN1A (degree, 7) and matrix metallopeptidase 3 (MMP3; degree, 6) had higher connectivity degrees in the PPI network for the DEGs. These genes may be involved in ovarian cancer by interacting with other genes in the module of the PPI network (e.g., BCL2-FOS, BCL2-CDKN1A, FOS-CDKN1A, FOS-CD44, MMP3-MMP7 and MMP7-CD44). Overall, BCL2, FOS, CDKN1A, CD44, MMP3 and MMP7 may be correlated with ovarian cancer. D.A. Spandidos 2016-07 2016-06-01 /pmc/articles/PMC4906568/ /pubmed/27347159 http://dx.doi.org/10.3892/ol.2016.4663 Text en Copyright: © Yin 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
YIN, JI-GANG
LIU, XIAN-YING
WANG, BIN
WANG, DAN-YANG
WEI, MAN
FANG, HUA
XIANG, MEI
Gene expression profiling analysis of ovarian cancer
title Gene expression profiling analysis of ovarian cancer
title_full Gene expression profiling analysis of ovarian cancer
title_fullStr Gene expression profiling analysis of ovarian cancer
title_full_unstemmed Gene expression profiling analysis of ovarian cancer
title_short Gene expression profiling analysis of ovarian cancer
title_sort gene expression profiling analysis of ovarian cancer
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4906568/
https://www.ncbi.nlm.nih.gov/pubmed/27347159
http://dx.doi.org/10.3892/ol.2016.4663
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