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Identification of key genes and pathways in adrenocortical carcinoma: evidence from bioinformatic analysis
Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with poor prognosis. The disease originates from the cortex of adrenal gland and lacks effective treatment. Efforts have been made to elucidate the pathogenesis of ACC, but the molecular mechanisms remain elusive. To identify key genes an...
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Published in: | Frontiers in endocrinology (Lausanne) 2023-11, Vol.14, p.1250033-1250033 |
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description | Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with poor prognosis. The disease originates from the cortex of adrenal gland and lacks effective treatment. Efforts have been made to elucidate the pathogenesis of ACC, but the molecular mechanisms remain elusive. To identify key genes and pathways in ACC, the expression profiles of GSE12368, GSE90713 and GSE143383 were downloaded from the Gene Expression Omnibus (GEO) database. After screening differentially expressed genes (DEGs) in each microarray dataset on the basis of cut-off, we identified 206 DEGs, consisting of 72 up-regulated and 134 down-regulated genes in three datasets. Function enrichment analyses of DEGs were performed by DAVID online database and the results revealed that the DEGs were mainly enriched in cell cycle, cell cycle process, mitotic cell cycle, response to oxygen-containing compound, progesterone-mediated oocyte maturation, p53 signaling pathway. The STRING database was used to construct the protein-protein interaction (PPI) network, and modules analysis was performed using Cytoscape. Finally, we filtered out eight hub genes, including CDK1, CCNA2, CCNB1, TOP2A, MAD2L1, BIRC5, BUB1 and AURKA. Biological process analysis showed that these hub genes were significantly enriched in nuclear division, mitosis, M phase of mitotic cell cycle and cell cycle process. Violin plot, Kaplan-Meier curve and stage plot of these hub genes confirmed the reliability of the results. In conclusion, the results in this study provided reliable key genes and pathways for ACC, which will be useful for ACC mechanisms, diagnosis and candidate targeted treatment. |
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The disease originates from the cortex of adrenal gland and lacks effective treatment. Efforts have been made to elucidate the pathogenesis of ACC, but the molecular mechanisms remain elusive. To identify key genes and pathways in ACC, the expression profiles of GSE12368, GSE90713 and GSE143383 were downloaded from the Gene Expression Omnibus (GEO) database. After screening differentially expressed genes (DEGs) in each microarray dataset on the basis of cut-off, we identified 206 DEGs, consisting of 72 up-regulated and 134 down-regulated genes in three datasets. Function enrichment analyses of DEGs were performed by DAVID online database and the results revealed that the DEGs were mainly enriched in cell cycle, cell cycle process, mitotic cell cycle, response to oxygen-containing compound, progesterone-mediated oocyte maturation, p53 signaling pathway. The STRING database was used to construct the protein-protein interaction (PPI) network, and modules analysis was performed using Cytoscape. Finally, we filtered out eight hub genes, including CDK1, CCNA2, CCNB1, TOP2A, MAD2L1, BIRC5, BUB1 and AURKA. Biological process analysis showed that these hub genes were significantly enriched in nuclear division, mitosis, M phase of mitotic cell cycle and cell cycle process. Violin plot, Kaplan-Meier curve and stage plot of these hub genes confirmed the reliability of the results. In conclusion, the results in this study provided reliable key genes and pathways for ACC, which will be useful for ACC mechanisms, diagnosis and candidate targeted treatment.</description><identifier>ISSN: 1664-2392</identifier><identifier>EISSN: 1664-2392</identifier><identifier>DOI: 10.3389/fendo.2023.1250033</identifier><identifier>PMID: 38053725</identifier><language>eng</language><publisher>Switzerland: Frontiers Media S.A</publisher><subject>Adrenal Cortex Neoplasms - genetics ; adrenocortical carcinoma ; Adrenocortical Carcinoma - genetics ; Computational Biology - methods ; differentially expressed genes ; Endocrinology ; gene expression omnibus ; Gene Expression Profiling - methods ; Gene Regulatory Networks ; Humans ; Kaplan-Meier curve ; protein-protein interaction ; Reproducibility of Results</subject><ispartof>Frontiers in endocrinology (Lausanne), 2023-11, Vol.14, p.1250033-1250033</ispartof><rights>Copyright © 2023 Yin, Wang, Ren, Han, Li, Liang, Wang and Gang.</rights><rights>Copyright © 2023 Yin, Wang, Ren, Han, Li, Liang, Wang and Gang 2023 Yin, Wang, Ren, Han, Li, Liang, Wang and Gang</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c420t-864a57ba60b7f10099e0e0d44e51e4269b7bda9bd6bac284f695828bf7c1dfef3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694291/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694291/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27923,27924,53790,53792</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38053725$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yin, Mengsha</creatorcontrib><creatorcontrib>Wang, Yao</creatorcontrib><creatorcontrib>Ren, Xinhua</creatorcontrib><creatorcontrib>Han, Mingyue</creatorcontrib><creatorcontrib>Li, Shanshan</creatorcontrib><creatorcontrib>Liang, Ruishuang</creatorcontrib><creatorcontrib>Wang, Guixia</creatorcontrib><creatorcontrib>Gang, Xiaokun</creatorcontrib><title>Identification of key genes and pathways in adrenocortical carcinoma: evidence from bioinformatic analysis</title><title>Frontiers in endocrinology (Lausanne)</title><addtitle>Front Endocrinol (Lausanne)</addtitle><description>Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with poor prognosis. The disease originates from the cortex of adrenal gland and lacks effective treatment. Efforts have been made to elucidate the pathogenesis of ACC, but the molecular mechanisms remain elusive. To identify key genes and pathways in ACC, the expression profiles of GSE12368, GSE90713 and GSE143383 were downloaded from the Gene Expression Omnibus (GEO) database. After screening differentially expressed genes (DEGs) in each microarray dataset on the basis of cut-off, we identified 206 DEGs, consisting of 72 up-regulated and 134 down-regulated genes in three datasets. Function enrichment analyses of DEGs were performed by DAVID online database and the results revealed that the DEGs were mainly enriched in cell cycle, cell cycle process, mitotic cell cycle, response to oxygen-containing compound, progesterone-mediated oocyte maturation, p53 signaling pathway. The STRING database was used to construct the protein-protein interaction (PPI) network, and modules analysis was performed using Cytoscape. Finally, we filtered out eight hub genes, including CDK1, CCNA2, CCNB1, TOP2A, MAD2L1, BIRC5, BUB1 and AURKA. Biological process analysis showed that these hub genes were significantly enriched in nuclear division, mitosis, M phase of mitotic cell cycle and cell cycle process. Violin plot, Kaplan-Meier curve and stage plot of these hub genes confirmed the reliability of the results. In conclusion, the results in this study provided reliable key genes and pathways for ACC, which will be useful for ACC mechanisms, diagnosis and candidate targeted treatment.</description><subject>Adrenal Cortex Neoplasms - genetics</subject><subject>adrenocortical carcinoma</subject><subject>Adrenocortical Carcinoma - genetics</subject><subject>Computational Biology - methods</subject><subject>differentially expressed genes</subject><subject>Endocrinology</subject><subject>gene expression omnibus</subject><subject>Gene Expression Profiling - methods</subject><subject>Gene Regulatory Networks</subject><subject>Humans</subject><subject>Kaplan-Meier curve</subject><subject>protein-protein interaction</subject><subject>Reproducibility of Results</subject><issn>1664-2392</issn><issn>1664-2392</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVkUtvGyEURkdVqyZK8we6qFh2Y5fXYOimqqI-LEXqpl2jC3NxcGfAhXEq__vi2I0SNiD47rnA6bq3jC6F0OZDwDTkJadcLBnvKRXiRXfJlJILLgx_-WR90V3XuqVtSMqM0a-7C6FpL1a8v-y26wHTHEP0MMecSA7kNx7IBhNWAmkgO5jv_sKhkpgIDAVT9rnMLT4SD8XHlCf4SPA-No5HEkqeiIs5ppDL1Ji-UWA81FjfdK8CjBWvz_NV9-vrl5833xe3P76tbz7fLrzkdF5oJaFfOVDUrQKj1BikSAcpsWcouTJu5QYwblAOPNcyKNNrrl1YeTYEDOKqW5-4Q4at3ZU4QTnYDNE-bOSysXB8wYg2UKGl5yid8VLpXtPWUoKhTEqhXN9Yn06s3d5NOPj2VwXGZ9DnJyne2U2-t4wqI7lhjfD-TCj5zx7rbKdYPY4jJMz7ark22vSKCd2i_BT1JddaMDz2YdQepdsH6fYo3Z6lt6J3T2_4WPJfsfgH5p-rPw</recordid><startdate>20231120</startdate><enddate>20231120</enddate><creator>Yin, Mengsha</creator><creator>Wang, Yao</creator><creator>Ren, Xinhua</creator><creator>Han, Mingyue</creator><creator>Li, Shanshan</creator><creator>Liang, Ruishuang</creator><creator>Wang, Guixia</creator><creator>Gang, Xiaokun</creator><general>Frontiers Media S.A</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20231120</creationdate><title>Identification of key genes and pathways in adrenocortical carcinoma: evidence from bioinformatic analysis</title><author>Yin, Mengsha ; Wang, Yao ; Ren, Xinhua ; Han, Mingyue ; Li, Shanshan ; Liang, Ruishuang ; Wang, Guixia ; Gang, Xiaokun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c420t-864a57ba60b7f10099e0e0d44e51e4269b7bda9bd6bac284f695828bf7c1dfef3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Adrenal Cortex Neoplasms - genetics</topic><topic>adrenocortical carcinoma</topic><topic>Adrenocortical Carcinoma - genetics</topic><topic>Computational Biology - methods</topic><topic>differentially expressed genes</topic><topic>Endocrinology</topic><topic>gene expression omnibus</topic><topic>Gene Expression Profiling - methods</topic><topic>Gene Regulatory Networks</topic><topic>Humans</topic><topic>Kaplan-Meier curve</topic><topic>protein-protein interaction</topic><topic>Reproducibility of Results</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yin, Mengsha</creatorcontrib><creatorcontrib>Wang, Yao</creatorcontrib><creatorcontrib>Ren, Xinhua</creatorcontrib><creatorcontrib>Han, Mingyue</creatorcontrib><creatorcontrib>Li, Shanshan</creatorcontrib><creatorcontrib>Liang, Ruishuang</creatorcontrib><creatorcontrib>Wang, Guixia</creatorcontrib><creatorcontrib>Gang, Xiaokun</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Frontiers in endocrinology (Lausanne)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yin, Mengsha</au><au>Wang, Yao</au><au>Ren, Xinhua</au><au>Han, Mingyue</au><au>Li, Shanshan</au><au>Liang, Ruishuang</au><au>Wang, Guixia</au><au>Gang, Xiaokun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of key genes and pathways in adrenocortical carcinoma: evidence from bioinformatic analysis</atitle><jtitle>Frontiers in endocrinology (Lausanne)</jtitle><addtitle>Front Endocrinol (Lausanne)</addtitle><date>2023-11-20</date><risdate>2023</risdate><volume>14</volume><spage>1250033</spage><epage>1250033</epage><pages>1250033-1250033</pages><issn>1664-2392</issn><eissn>1664-2392</eissn><abstract>Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with poor prognosis. The disease originates from the cortex of adrenal gland and lacks effective treatment. Efforts have been made to elucidate the pathogenesis of ACC, but the molecular mechanisms remain elusive. To identify key genes and pathways in ACC, the expression profiles of GSE12368, GSE90713 and GSE143383 were downloaded from the Gene Expression Omnibus (GEO) database. After screening differentially expressed genes (DEGs) in each microarray dataset on the basis of cut-off, we identified 206 DEGs, consisting of 72 up-regulated and 134 down-regulated genes in three datasets. Function enrichment analyses of DEGs were performed by DAVID online database and the results revealed that the DEGs were mainly enriched in cell cycle, cell cycle process, mitotic cell cycle, response to oxygen-containing compound, progesterone-mediated oocyte maturation, p53 signaling pathway. The STRING database was used to construct the protein-protein interaction (PPI) network, and modules analysis was performed using Cytoscape. Finally, we filtered out eight hub genes, including CDK1, CCNA2, CCNB1, TOP2A, MAD2L1, BIRC5, BUB1 and AURKA. Biological process analysis showed that these hub genes were significantly enriched in nuclear division, mitosis, M phase of mitotic cell cycle and cell cycle process. Violin plot, Kaplan-Meier curve and stage plot of these hub genes confirmed the reliability of the results. In conclusion, the results in this study provided reliable key genes and pathways for ACC, which will be useful for ACC mechanisms, diagnosis and candidate targeted treatment.</abstract><cop>Switzerland</cop><pub>Frontiers Media S.A</pub><pmid>38053725</pmid><doi>10.3389/fendo.2023.1250033</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adrenal Cortex Neoplasms - genetics adrenocortical carcinoma Adrenocortical Carcinoma - genetics Computational Biology - methods differentially expressed genes Endocrinology gene expression omnibus Gene Expression Profiling - methods Gene Regulatory Networks Humans Kaplan-Meier curve protein-protein interaction Reproducibility of Results |
title | Identification of key genes and pathways in adrenocortical carcinoma: evidence from bioinformatic analysis |
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