Identification of key genes of papillary thyroid cancer using integrated bioinformatics analysis
Objective To identify novel clinically relevant genes in papillary thyroid carcinoma from public databases. Methods Four original microarray datasets, GSE3678, GSE3467, GSE33630 and GSE58545, were downloaded. Differentially expressed genes (DEGs) were filtered from integrated data. Gene ontology (GO...
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| Veröffentlicht in: | Journal of endocrinological investigation 2018-10, Vol.41 (10), p.1237-1245 |
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| creator | Liang, W. Sun, F. |
| description | Objective
To identify novel clinically relevant genes in papillary thyroid carcinoma from public databases.
Methods
Four original microarray datasets, GSE3678, GSE3467, GSE33630 and GSE58545, were downloaded. Differentially expressed genes (DEGs) were filtered from integrated data. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, followed by protein–protein interaction (PPI) network construction. The CentiScape pug-in was performed to scale degree. The genes at the top of the degree distribution (≥ 95% percentile) in the significantly perturbed networks were defined as central genes. UALCAN and The Cancer Genome Atlas Clinical Explorer were used to verify clinically relevant genes and perform survival analysis.
Result
225 commonly changed DEGs (111 up-regulated and 114 down-regulated) were identified. The DEGs were classified into three groups by GO terms. KEGG pathway enrichment analysis showed DEGs mainly enriched in the PI3K–Akt signaling pathway, pathways in cancer, focal adhesion and proteoglycans in cancer. DEGs’ protein–protein interaction (PPI) network complex was developed; six central genes (
BCL2
,
CCND1
,
FN1
,
IRS1
,
COL1A1
,
CXCL12
) were identified. Among them,
BCL2
,
CCND1
and
COL1A1
were identified as clinically relevant genes.
Conclusion
BCL2
,
CCND1
and
COL1A1
may be key genes for papillary thyroid carcinoma. Further molecular biological experiments are required to confirm the function of the identified genes. |
| doi_str_mv | 10.1007/s40618-018-0859-3 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2012913081</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2112243867</sourcerecordid><originalsourceid>FETCH-LOGICAL-c438t-eff6b4838669e38db8f2723f46ea3f5ea4f50ef200c6db5c7bee6788756a375e3</originalsourceid><addsrcrecordid>eNp1kElPwzAQhS0EomX5AVyQJS5cAl4S2z2iiqVSJS5wDo4zLi6tXezk0H-Po7IJicNoxvI3b54eQmeUXFFC5HUqiaCqIEOpalLwPTSmkpFCcSX2f80jdJTSkhAuuZKHaMQmFSNClWP0MmvBd846ozsXPA4Wv8EWL8BDGh4bvXGrlY5b3L1uY3AtNtobiLhPzi-w8x0sou6gxY0LztsQ11nIJKy9Xm2TSyfowOpVgtPPfoye726fpg_F_PF-Nr2ZF6bkqivAWtGUg1cxAa7aRlkmGbelAM1tBbq0FQHLCDGibSojGwAhlZKV0FxWwI_R5U53E8N7D6mr1y4ZyN49hD7VjFA2oZwomtGLP-gy9DH7zRSljGVDQmaK7igTQ0oRbL2Jbp2TqCmph_jrXfw1GSrHX_O8c_6p3DdraL83vvLOANsBKX_5BcSf0_-rfgALkpEi</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2112243867</pqid></control><display><type>article</type><title>Identification of key genes of papillary thyroid cancer using integrated bioinformatics analysis</title><source>MEDLINE</source><source>SpringerNature Journals</source><creator>Liang, W. ; Sun, F.</creator><creatorcontrib>Liang, W. ; Sun, F.</creatorcontrib><description>Objective
To identify novel clinically relevant genes in papillary thyroid carcinoma from public databases.
Methods
Four original microarray datasets, GSE3678, GSE3467, GSE33630 and GSE58545, were downloaded. Differentially expressed genes (DEGs) were filtered from integrated data. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, followed by protein–protein interaction (PPI) network construction. The CentiScape pug-in was performed to scale degree. The genes at the top of the degree distribution (≥ 95% percentile) in the significantly perturbed networks were defined as central genes. UALCAN and The Cancer Genome Atlas Clinical Explorer were used to verify clinically relevant genes and perform survival analysis.
Result
225 commonly changed DEGs (111 up-regulated and 114 down-regulated) were identified. The DEGs were classified into three groups by GO terms. KEGG pathway enrichment analysis showed DEGs mainly enriched in the PI3K–Akt signaling pathway, pathways in cancer, focal adhesion and proteoglycans in cancer. DEGs’ protein–protein interaction (PPI) network complex was developed; six central genes (
BCL2
,
CCND1
,
FN1
,
IRS1
,
COL1A1
,
CXCL12
) were identified. Among them,
BCL2
,
CCND1
and
COL1A1
were identified as clinically relevant genes.
Conclusion
BCL2
,
CCND1
and
COL1A1
may be key genes for papillary thyroid carcinoma. Further molecular biological experiments are required to confirm the function of the identified genes.</description><identifier>ISSN: 1720-8386</identifier><identifier>ISSN: 0391-4097</identifier><identifier>EISSN: 1720-8386</identifier><identifier>DOI: 10.1007/s40618-018-0859-3</identifier><identifier>PMID: 29520684</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>1-Phosphatidylinositol 3-kinase ; AKT protein ; Bioinformatics ; Collagen (type I) ; Computational Biology - methods ; Computational Biology - trends ; CXCL12 protein ; Databases, Genetic - trends ; DNA microarrays ; Endocrinology ; Gene Expression Profiling - methods ; Gene Expression Profiling - trends ; Gene Ontology - trends ; Gene Regulatory Networks - genetics ; Genomes ; Humans ; Medicine ; Medicine & Public Health ; Metabolic Diseases ; Original Article ; Papillary thyroid cancer ; Papillary thyroid carcinoma ; Proteins ; Proteoglycans ; Signal transduction ; Survival analysis ; Thyroid cancer ; Thyroid Cancer, Papillary - diagnosis ; Thyroid Cancer, Papillary - genetics ; Thyroid Neoplasms - diagnosis ; Thyroid Neoplasms - genetics</subject><ispartof>Journal of endocrinological investigation, 2018-10, Vol.41 (10), p.1237-1245</ispartof><rights>Italian Society of Endocrinology (SIE) 2018</rights><rights>Copyright Springer Science & Business Media 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c438t-eff6b4838669e38db8f2723f46ea3f5ea4f50ef200c6db5c7bee6788756a375e3</citedby><cites>FETCH-LOGICAL-c438t-eff6b4838669e38db8f2723f46ea3f5ea4f50ef200c6db5c7bee6788756a375e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s40618-018-0859-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s40618-018-0859-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,782,786,27931,27932,41495,42564,51326</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29520684$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liang, W.</creatorcontrib><creatorcontrib>Sun, F.</creatorcontrib><title>Identification of key genes of papillary thyroid cancer using integrated bioinformatics analysis</title><title>Journal of endocrinological investigation</title><addtitle>J Endocrinol Invest</addtitle><addtitle>J Endocrinol Invest</addtitle><description>Objective
To identify novel clinically relevant genes in papillary thyroid carcinoma from public databases.
Methods
Four original microarray datasets, GSE3678, GSE3467, GSE33630 and GSE58545, were downloaded. Differentially expressed genes (DEGs) were filtered from integrated data. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, followed by protein–protein interaction (PPI) network construction. The CentiScape pug-in was performed to scale degree. The genes at the top of the degree distribution (≥ 95% percentile) in the significantly perturbed networks were defined as central genes. UALCAN and The Cancer Genome Atlas Clinical Explorer were used to verify clinically relevant genes and perform survival analysis.
Result
225 commonly changed DEGs (111 up-regulated and 114 down-regulated) were identified. The DEGs were classified into three groups by GO terms. KEGG pathway enrichment analysis showed DEGs mainly enriched in the PI3K–Akt signaling pathway, pathways in cancer, focal adhesion and proteoglycans in cancer. DEGs’ protein–protein interaction (PPI) network complex was developed; six central genes (
BCL2
,
CCND1
,
FN1
,
IRS1
,
COL1A1
,
CXCL12
) were identified. Among them,
BCL2
,
CCND1
and
COL1A1
were identified as clinically relevant genes.
Conclusion
BCL2
,
CCND1
and
COL1A1
may be key genes for papillary thyroid carcinoma. Further molecular biological experiments are required to confirm the function of the identified genes.</description><subject>1-Phosphatidylinositol 3-kinase</subject><subject>AKT protein</subject><subject>Bioinformatics</subject><subject>Collagen (type I)</subject><subject>Computational Biology - methods</subject><subject>Computational Biology - trends</subject><subject>CXCL12 protein</subject><subject>Databases, Genetic - trends</subject><subject>DNA microarrays</subject><subject>Endocrinology</subject><subject>Gene Expression Profiling - methods</subject><subject>Gene Expression Profiling - trends</subject><subject>Gene Ontology - trends</subject><subject>Gene Regulatory Networks - genetics</subject><subject>Genomes</subject><subject>Humans</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Metabolic Diseases</subject><subject>Original Article</subject><subject>Papillary thyroid cancer</subject><subject>Papillary thyroid carcinoma</subject><subject>Proteins</subject><subject>Proteoglycans</subject><subject>Signal transduction</subject><subject>Survival analysis</subject><subject>Thyroid cancer</subject><subject>Thyroid Cancer, Papillary - diagnosis</subject><subject>Thyroid Cancer, Papillary - genetics</subject><subject>Thyroid Neoplasms - diagnosis</subject><subject>Thyroid Neoplasms - genetics</subject><issn>1720-8386</issn><issn>0391-4097</issn><issn>1720-8386</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kElPwzAQhS0EomX5AVyQJS5cAl4S2z2iiqVSJS5wDo4zLi6tXezk0H-Po7IJicNoxvI3b54eQmeUXFFC5HUqiaCqIEOpalLwPTSmkpFCcSX2f80jdJTSkhAuuZKHaMQmFSNClWP0MmvBd846ozsXPA4Wv8EWL8BDGh4bvXGrlY5b3L1uY3AtNtobiLhPzi-w8x0sou6gxY0LztsQ11nIJKy9Xm2TSyfowOpVgtPPfoye726fpg_F_PF-Nr2ZF6bkqivAWtGUg1cxAa7aRlkmGbelAM1tBbq0FQHLCDGibSojGwAhlZKV0FxWwI_R5U53E8N7D6mr1y4ZyN49hD7VjFA2oZwomtGLP-gy9DH7zRSljGVDQmaK7igTQ0oRbL2Jbp2TqCmph_jrXfw1GSrHX_O8c_6p3DdraL83vvLOANsBKX_5BcSf0_-rfgALkpEi</recordid><startdate>20181001</startdate><enddate>20181001</enddate><creator>Liang, W.</creator><creator>Sun, F.</creator><general>Springer International Publishing</general><general>Springer Nature B.V</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></search><sort><creationdate>20181001</creationdate><title>Identification of key genes of papillary thyroid cancer using integrated bioinformatics analysis</title><author>Liang, W. ; Sun, F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c438t-eff6b4838669e38db8f2723f46ea3f5ea4f50ef200c6db5c7bee6788756a375e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>1-Phosphatidylinositol 3-kinase</topic><topic>AKT protein</topic><topic>Bioinformatics</topic><topic>Collagen (type I)</topic><topic>Computational Biology - methods</topic><topic>Computational Biology - trends</topic><topic>CXCL12 protein</topic><topic>Databases, Genetic - trends</topic><topic>DNA microarrays</topic><topic>Endocrinology</topic><topic>Gene Expression Profiling - methods</topic><topic>Gene Expression Profiling - trends</topic><topic>Gene Ontology - trends</topic><topic>Gene Regulatory Networks - genetics</topic><topic>Genomes</topic><topic>Humans</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Metabolic Diseases</topic><topic>Original Article</topic><topic>Papillary thyroid cancer</topic><topic>Papillary thyroid carcinoma</topic><topic>Proteins</topic><topic>Proteoglycans</topic><topic>Signal transduction</topic><topic>Survival analysis</topic><topic>Thyroid cancer</topic><topic>Thyroid Cancer, Papillary - diagnosis</topic><topic>Thyroid Cancer, Papillary - genetics</topic><topic>Thyroid Neoplasms - diagnosis</topic><topic>Thyroid Neoplasms - genetics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liang, W.</creatorcontrib><creatorcontrib>Sun, F.</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><jtitle>Journal of endocrinological investigation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liang, W.</au><au>Sun, F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of key genes of papillary thyroid cancer using integrated bioinformatics analysis</atitle><jtitle>Journal of endocrinological investigation</jtitle><stitle>J Endocrinol Invest</stitle><addtitle>J Endocrinol Invest</addtitle><date>2018-10-01</date><risdate>2018</risdate><volume>41</volume><issue>10</issue><spage>1237</spage><epage>1245</epage><pages>1237-1245</pages><issn>1720-8386</issn><issn>0391-4097</issn><eissn>1720-8386</eissn><abstract>Objective
To identify novel clinically relevant genes in papillary thyroid carcinoma from public databases.
Methods
Four original microarray datasets, GSE3678, GSE3467, GSE33630 and GSE58545, were downloaded. Differentially expressed genes (DEGs) were filtered from integrated data. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, followed by protein–protein interaction (PPI) network construction. The CentiScape pug-in was performed to scale degree. The genes at the top of the degree distribution (≥ 95% percentile) in the significantly perturbed networks were defined as central genes. UALCAN and The Cancer Genome Atlas Clinical Explorer were used to verify clinically relevant genes and perform survival analysis.
Result
225 commonly changed DEGs (111 up-regulated and 114 down-regulated) were identified. The DEGs were classified into three groups by GO terms. KEGG pathway enrichment analysis showed DEGs mainly enriched in the PI3K–Akt signaling pathway, pathways in cancer, focal adhesion and proteoglycans in cancer. DEGs’ protein–protein interaction (PPI) network complex was developed; six central genes (
BCL2
,
CCND1
,
FN1
,
IRS1
,
COL1A1
,
CXCL12
) were identified. Among them,
BCL2
,
CCND1
and
COL1A1
were identified as clinically relevant genes.
Conclusion
BCL2
,
CCND1
and
COL1A1
may be key genes for papillary thyroid carcinoma. Further molecular biological experiments are required to confirm the function of the identified genes.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>29520684</pmid><doi>10.1007/s40618-018-0859-3</doi><tpages>9</tpages></addata></record> |
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| language | eng |
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| source | MEDLINE; SpringerNature Journals |
| subjects | 1-Phosphatidylinositol 3-kinase AKT protein Bioinformatics Collagen (type I) Computational Biology - methods Computational Biology - trends CXCL12 protein Databases, Genetic - trends DNA microarrays Endocrinology Gene Expression Profiling - methods Gene Expression Profiling - trends Gene Ontology - trends Gene Regulatory Networks - genetics Genomes Humans Medicine Medicine & Public Health Metabolic Diseases Original Article Papillary thyroid cancer Papillary thyroid carcinoma Proteins Proteoglycans Signal transduction Survival analysis Thyroid cancer Thyroid Cancer, Papillary - diagnosis Thyroid Cancer, Papillary - genetics Thyroid Neoplasms - diagnosis Thyroid Neoplasms - genetics |
| title | Identification of key genes of papillary thyroid cancer using integrated bioinformatics analysis |
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