Integrated analyses of copy number variations and gene expression in lung adenocarcinoma
Numerous efforts have been made to elucidate the etiology and improve the treatment of lung cancer, but the overall five-year survival rate is still only 15%. Identification of prognostic biomarkers for lung cancer using gene expression microarrays poses a major challenge in that very few overlappin...
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| Veröffentlicht in: | PloS one 2011-09, Vol.6 (9), p.e24829-e24829 |
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| creator | Lu, Tzu-Pin Lai, Liang-Chuan Tsai, Mong-Hsun Chen, Pei-Chun Hsu, Chung-Ping Lee, Jang-Ming Hsiao, Chuhsing Kate Chuang, Eric Y |
| description | Numerous efforts have been made to elucidate the etiology and improve the treatment of lung cancer, but the overall five-year survival rate is still only 15%. Identification of prognostic biomarkers for lung cancer using gene expression microarrays poses a major challenge in that very few overlapping genes have been reported among different studies. To address this issue, we have performed concurrent genome-wide analyses of copy number variation and gene expression to identify genes reproducibly associated with tumorigenesis and survival in non-smoking female lung adenocarcinoma. The genomic landscape of frequent copy number variable regions (CNVRs) in at least 30% of samples was revealed, and their aberration patterns were highly similar to several studies reported previously. Further statistical analysis for genes located in the CNVRs identified 475 genes differentially expressed between tumor and normal tissues (p |
| doi_str_mv | 10.1371/journal.pone.0024829 |
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Identification of prognostic biomarkers for lung cancer using gene expression microarrays poses a major challenge in that very few overlapping genes have been reported among different studies. To address this issue, we have performed concurrent genome-wide analyses of copy number variation and gene expression to identify genes reproducibly associated with tumorigenesis and survival in non-smoking female lung adenocarcinoma. The genomic landscape of frequent copy number variable regions (CNVRs) in at least 30% of samples was revealed, and their aberration patterns were highly similar to several studies reported previously. Further statistical analysis for genes located in the CNVRs identified 475 genes differentially expressed between tumor and normal tissues (p<10(-5)). We demonstrated the reproducibility of these genes in another lung cancer study (p = 0.0034, Fisher's exact test), and showed the concordance between copy number variations and gene expression changes by elevated Pearson correlation coefficients. Pathway analysis revealed two major dysregulated functions in lung tumorigenesis: survival regulation via AKT signaling and cytoskeleton reorganization. Further validation of these enriched pathways using three independent cohorts demonstrated effective prediction of survival. In conclusion, by integrating gene expression profiles and copy number variations, we identified genes/pathways that may serve as prognostic biomarkers for lung tumorigenesis.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0024829</identifier><identifier>PMID: 21935476</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Aberration ; Acids ; Adenocarcinoma ; Adenocarcinoma - genetics ; Adenocarcinoma of Lung ; Aged ; AKT protein ; Analysis ; Arrays ; Bioinformatics ; Biology ; Biomarkers ; Breast cancer ; Cancer ; Cancer genetics ; Cancer treatment ; Care and treatment ; Cluster analysis ; Copy number ; Correlation analysis ; Correlation coefficient ; Correlation coefficients ; Cytoskeleton ; Development and progression ; DNA Copy Number Variations - genetics ; DNA microarrays ; Etiology ; Female ; Gene expression ; Gene Expression Regulation, Neoplastic - genetics ; Genes ; Genetic aspects ; Genetic research ; Genomes ; Genomics ; Humans ; Kinases ; Lung cancer ; Lung diseases ; Lung Neoplasms - genetics ; Medical prognosis ; Medicine ; Middle Aged ; Oligonucleotide Array Sequence Analysis ; Pathways ; Phase transitions ; Proteins ; Reproducibility ; Respiratory system agents ; Signaling ; Smoking ; Statistical analysis ; Statistical methods ; Studies ; Survival ; Thoracic surgery ; Tissues ; Tumorigenesis ; Variation</subject><ispartof>PloS one, 2011-09, Vol.6 (9), p.e24829-e24829</ispartof><rights>COPYRIGHT 2011 Public Library of Science</rights><rights>2011 Lu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Lu et al. 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c691t-dffad50d4e1ce4202287f0d91a08507ff2c75c3cde464320ce19e9ea53a41e9f3</citedby><cites>FETCH-LOGICAL-c691t-dffad50d4e1ce4202287f0d91a08507ff2c75c3cde464320ce19e9ea53a41e9f3</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/PMC3173487/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3173487/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21935476$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lu, Tzu-Pin</creatorcontrib><creatorcontrib>Lai, Liang-Chuan</creatorcontrib><creatorcontrib>Tsai, Mong-Hsun</creatorcontrib><creatorcontrib>Chen, Pei-Chun</creatorcontrib><creatorcontrib>Hsu, Chung-Ping</creatorcontrib><creatorcontrib>Lee, Jang-Ming</creatorcontrib><creatorcontrib>Hsiao, Chuhsing Kate</creatorcontrib><creatorcontrib>Chuang, Eric Y</creatorcontrib><title>Integrated analyses of copy number variations and gene expression in lung adenocarcinoma</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Numerous efforts have been made to elucidate the etiology and improve the treatment of lung cancer, but the overall five-year survival rate is still only 15%. Identification of prognostic biomarkers for lung cancer using gene expression microarrays poses a major challenge in that very few overlapping genes have been reported among different studies. To address this issue, we have performed concurrent genome-wide analyses of copy number variation and gene expression to identify genes reproducibly associated with tumorigenesis and survival in non-smoking female lung adenocarcinoma. The genomic landscape of frequent copy number variable regions (CNVRs) in at least 30% of samples was revealed, and their aberration patterns were highly similar to several studies reported previously. Further statistical analysis for genes located in the CNVRs identified 475 genes differentially expressed between tumor and normal tissues (p<10(-5)). We demonstrated the reproducibility of these genes in another lung cancer study (p = 0.0034, Fisher's exact test), and showed the concordance between copy number variations and gene expression changes by elevated Pearson correlation coefficients. Pathway analysis revealed two major dysregulated functions in lung tumorigenesis: survival regulation via AKT signaling and cytoskeleton reorganization. Further validation of these enriched pathways using three independent cohorts demonstrated effective prediction of survival. In conclusion, by integrating gene expression profiles and copy number variations, we identified genes/pathways that may serve as prognostic biomarkers for lung tumorigenesis.</description><subject>Aberration</subject><subject>Acids</subject><subject>Adenocarcinoma</subject><subject>Adenocarcinoma - genetics</subject><subject>Adenocarcinoma of Lung</subject><subject>Aged</subject><subject>AKT protein</subject><subject>Analysis</subject><subject>Arrays</subject><subject>Bioinformatics</subject><subject>Biology</subject><subject>Biomarkers</subject><subject>Breast cancer</subject><subject>Cancer</subject><subject>Cancer genetics</subject><subject>Cancer treatment</subject><subject>Care and treatment</subject><subject>Cluster analysis</subject><subject>Copy number</subject><subject>Correlation analysis</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Cytoskeleton</subject><subject>Development and progression</subject><subject>DNA Copy Number Variations - genetics</subject><subject>DNA microarrays</subject><subject>Etiology</subject><subject>Female</subject><subject>Gene expression</subject><subject>Gene Expression Regulation, Neoplastic - genetics</subject><subject>Genes</subject><subject>Genetic aspects</subject><subject>Genetic research</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Humans</subject><subject>Kinases</subject><subject>Lung cancer</subject><subject>Lung diseases</subject><subject>Lung Neoplasms - genetics</subject><subject>Medical prognosis</subject><subject>Medicine</subject><subject>Middle Aged</subject><subject>Oligonucleotide Array Sequence Analysis</subject><subject>Pathways</subject><subject>Phase transitions</subject><subject>Proteins</subject><subject>Reproducibility</subject><subject>Respiratory system agents</subject><subject>Signaling</subject><subject>Smoking</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Studies</subject><subject>Survival</subject><subject>Thoracic surgery</subject><subject>Tissues</subject><subject>Tumorigenesis</subject><subject>Variation</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNkttqGzEQhpfS0qRp36C0C4WWXtjVaQ-6KYTQgyEQ6IneibF2tJZZS660G-K3rxxvgrfkouhCYuabf6TRn2UvKZlTXtEPaz8EB9186x3OCWGiZvJRdkolZ7OSEf746HySPYtxTUjB67J8mp2wlClEVZ5mvxeuxzZAj00OSW4XMebe5Npvd7kbNksM-TUEC731LiakyVt0mOPNNmCMKZhbl3eDa3No0HkNQVvnN_A8e2Kgi_hi3M-yn58__bj4Oru8-rK4OL-c6VLSftYYA01BGoFUo2CEsboypJEUSF2Qyhimq0Jz3aAoBWdEI5UoEQoOgqI0_Cx7fdDddj6qcShRUU7qiklJSCIWB6LxsFbbYDcQdsqDVbcBH1oFobe6Q8WkQVFTbHQtBF1yqDhtjJZCLBE050nr49htWG4Shq4P0E1EpxlnV6r114rTiou6SgLvRoHg_wwYe7WxUWPXgUM_RFVLXjGa5pDIN_-QDz9upFpI97fO-NRW7zXVefrguk5Mmaj5A1RaDW6sTgYyNsUnBe8nBYnp8aZvYYhRLb5_-3_26teUfXvErhC6fhV9N9y6awqKA6iDjzGguZ8xJWrv_7tpqL3_1ej_VPbq-H_ui-4Mz_8CRsQBRw</recordid><startdate>20110914</startdate><enddate>20110914</enddate><creator>Lu, Tzu-Pin</creator><creator>Lai, Liang-Chuan</creator><creator>Tsai, Mong-Hsun</creator><creator>Chen, Pei-Chun</creator><creator>Hsu, Chung-Ping</creator><creator>Lee, Jang-Ming</creator><creator>Hsiao, Chuhsing Kate</creator><creator>Chuang, Eric Y</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20110914</creationdate><title>Integrated analyses of copy number variations and gene expression in lung adenocarcinoma</title><author>Lu, Tzu-Pin ; Lai, Liang-Chuan ; Tsai, Mong-Hsun ; Chen, Pei-Chun ; Hsu, Chung-Ping ; Lee, Jang-Ming ; Hsiao, Chuhsing Kate ; Chuang, Eric Y</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c691t-dffad50d4e1ce4202287f0d91a08507ff2c75c3cde464320ce19e9ea53a41e9f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Aberration</topic><topic>Acids</topic><topic>Adenocarcinoma</topic><topic>Adenocarcinoma - genetics</topic><topic>Adenocarcinoma of Lung</topic><topic>Aged</topic><topic>AKT protein</topic><topic>Analysis</topic><topic>Arrays</topic><topic>Bioinformatics</topic><topic>Biology</topic><topic>Biomarkers</topic><topic>Breast cancer</topic><topic>Cancer</topic><topic>Cancer genetics</topic><topic>Cancer treatment</topic><topic>Care and treatment</topic><topic>Cluster analysis</topic><topic>Copy number</topic><topic>Correlation analysis</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Cytoskeleton</topic><topic>Development and progression</topic><topic>DNA Copy Number Variations - genetics</topic><topic>DNA microarrays</topic><topic>Etiology</topic><topic>Female</topic><topic>Gene expression</topic><topic>Gene Expression Regulation, Neoplastic - genetics</topic><topic>Genes</topic><topic>Genetic aspects</topic><topic>Genetic research</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Humans</topic><topic>Kinases</topic><topic>Lung cancer</topic><topic>Lung diseases</topic><topic>Lung Neoplasms - 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Identification of prognostic biomarkers for lung cancer using gene expression microarrays poses a major challenge in that very few overlapping genes have been reported among different studies. To address this issue, we have performed concurrent genome-wide analyses of copy number variation and gene expression to identify genes reproducibly associated with tumorigenesis and survival in non-smoking female lung adenocarcinoma. The genomic landscape of frequent copy number variable regions (CNVRs) in at least 30% of samples was revealed, and their aberration patterns were highly similar to several studies reported previously. Further statistical analysis for genes located in the CNVRs identified 475 genes differentially expressed between tumor and normal tissues (p<10(-5)). We demonstrated the reproducibility of these genes in another lung cancer study (p = 0.0034, Fisher's exact test), and showed the concordance between copy number variations and gene expression changes by elevated Pearson correlation coefficients. Pathway analysis revealed two major dysregulated functions in lung tumorigenesis: survival regulation via AKT signaling and cytoskeleton reorganization. Further validation of these enriched pathways using three independent cohorts demonstrated effective prediction of survival. In conclusion, by integrating gene expression profiles and copy number variations, we identified genes/pathways that may serve as prognostic biomarkers for lung tumorigenesis.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>21935476</pmid><doi>10.1371/journal.pone.0024829</doi><tpages>e24829</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Aberration Acids Adenocarcinoma Adenocarcinoma - genetics Adenocarcinoma of Lung Aged AKT protein Analysis Arrays Bioinformatics Biology Biomarkers Breast cancer Cancer Cancer genetics Cancer treatment Care and treatment Cluster analysis Copy number Correlation analysis Correlation coefficient Correlation coefficients Cytoskeleton Development and progression DNA Copy Number Variations - genetics DNA microarrays Etiology Female Gene expression Gene Expression Regulation, Neoplastic - genetics Genes Genetic aspects Genetic research Genomes Genomics Humans Kinases Lung cancer Lung diseases Lung Neoplasms - genetics Medical prognosis Medicine Middle Aged Oligonucleotide Array Sequence Analysis Pathways Phase transitions Proteins Reproducibility Respiratory system agents Signaling Smoking Statistical analysis Statistical methods Studies Survival Thoracic surgery Tissues Tumorigenesis Variation |
| title | Integrated analyses of copy number variations and gene expression in lung adenocarcinoma |
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