A novel five gene signature derived from stem-like side population cells predicts overall and recurrence-free survival in NSCLC
Gene expression profiling has been used to characterize prognosis in various cancers. Earlier studies had shown that side population cells isolated from Non-Small Cell Lung Cancer (NSCLC) cell lines exhibit cancer stem cell properties. In this study we apply a systems biology approach to gene expres...
Gespeichert in:
| Veröffentlicht in: | PloS one 2012-08, Vol.7 (8), p.e43589-e43589 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | e43589 |
|---|---|
| container_issue | 8 |
| container_start_page | e43589 |
| container_title | PloS one |
| container_volume | 7 |
| creator | Perumal, Deepak Singh, Sandeep Yoder, Sean J Bloom, Gregory C Chellappan, Srikumar P |
| description | Gene expression profiling has been used to characterize prognosis in various cancers. Earlier studies had shown that side population cells isolated from Non-Small Cell Lung Cancer (NSCLC) cell lines exhibit cancer stem cell properties. In this study we apply a systems biology approach to gene expression profiling data from cancer stem like cells isolated from lung cancer cell lines to identify novel gene signatures that could predict prognosis. Microarray data from side population (SP) and main population (MP) cells isolated from 4 NSCLC lines (A549, H1650, H460, H1975) were used to examine gene expression profiles associated with stem like properties. Differentially expressed genes that were over or under-expressed at least two fold commonly in all 4 cell lines were identified. We found 354 were upregulated and 126 were downregulated in SP cells compared to MP cells; of these, 89 up and 62 downregulated genes (average 2 fold changes) were used for Principle Component Analysis (PCA) and MetaCore pathway analysis. The pathway analysis demonstrated representation of 4 up regulated genes (TOP2A, AURKB, BRRN1, CDK1) in chromosome condensation pathway and 1 down regulated gene FUS in chromosomal translocation. Microarray data was validated using qRT-PCR on the 5 selected genes and all showed robust correlation between microarray and qRT-PCR. Further, we analyzed two independent gene expression datasets that included 360 lung adenocarcinoma patients from NCI Director's Challenge Set for overall survival and 63 samples from Sungkyunkwan University (SKKU) for recurrence free survival. Kaplan-Meier and log-rank test analysis predicted poor survival of patients in both data sets. Our results suggest that genes involved in chromosome condensation are likely related with stem-like properties and might predict survival in lung adenocarcinoma. Our findings highlight a gene signature for effective identification of lung adenocarcinoma patients with poor prognosis and designing more aggressive therapies for such patients. |
| doi_str_mv | 10.1371/journal.pone.0043589 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_1326450578</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A498244365</galeid><doaj_id>oai_doaj_org_article_a09af6fa640b49238085e3d67f9bc31d</doaj_id><sourcerecordid>A498244365</sourcerecordid><originalsourceid>FETCH-LOGICAL-c692t-3833ea4ca162451a32fcef6f64540ba13c649bc7c7ff9cfc6a89724368a759f63</originalsourceid><addsrcrecordid>eNqNk82O0zAUhSMEYoaBN0BgCQnBosWxHcfZIFUVP5UqRmKAreU616kH1y52UsGKV8elmVGLZoGySHT9nXPtE9-ieFriaUnr8s11GKJXbroNHqYYM1qJ5l5xXjaUTDjB9P7R91nxKKVrjCsqOH9YnBHSVKQu2Xnxe4Z82IFDxu4AdeABJdt51Q8RUAsxV1tkYtig1MNm4uz3PdAC2obt4FRvg0canEtoG6G1uk8o20XlHFK-RRH0ECN4DRMTIUuHuLM75ZD16NPVfDl_XDwwyiV4Mr4viq_v332Zf5wsLz8s5rPlRPOG9BMqKAXFtCo5YVWpKDEaDDecVQyvVEk1Z81K17o2ptFGcyWamjDKhaqrxnB6UTw_-G5dSHLMLsmSkmyBq1pkYnEg2qCu5TbajYq_ZFBW_i2E2EkVe6sdSIUblZsrnnuzhlCBRQW05bXJe6Blm73ejt2G1QZaDb7PkZyYnq54u5Zd2EnKKK4xzgavRoMYfgyQermxaZ-z8hCGvG9MRdUIJkhGX_yD3n26kepUPoD1JuS-em8qZ6wRhOWsqkxN76Dy08LG6nzRjM31E8HrE0FmevjZd2pISS6uPv8_e_ntlH15xK5BuX6dghv29y2dguwA6hhSimBuQy6x3M_JTRpyPydynJMse3b8g25FN4NB_wCWBQ5r</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1326450578</pqid></control><display><type>article</type><title>A novel five gene signature derived from stem-like side population cells predicts overall and recurrence-free survival in NSCLC</title><source>PubMed Central Free</source><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Public Library of Science (PLoS) Journals Open Access</source><source>EZB-FREE-00999 freely available EZB journals</source><source>Free Full-Text Journals in Chemistry</source><creator>Perumal, Deepak ; Singh, Sandeep ; Yoder, Sean J ; Bloom, Gregory C ; Chellappan, Srikumar P</creator><contributor>Das, Gokul M.</contributor><creatorcontrib>Perumal, Deepak ; Singh, Sandeep ; Yoder, Sean J ; Bloom, Gregory C ; Chellappan, Srikumar P ; Das, Gokul M.</creatorcontrib><description>Gene expression profiling has been used to characterize prognosis in various cancers. Earlier studies had shown that side population cells isolated from Non-Small Cell Lung Cancer (NSCLC) cell lines exhibit cancer stem cell properties. In this study we apply a systems biology approach to gene expression profiling data from cancer stem like cells isolated from lung cancer cell lines to identify novel gene signatures that could predict prognosis. Microarray data from side population (SP) and main population (MP) cells isolated from 4 NSCLC lines (A549, H1650, H460, H1975) were used to examine gene expression profiles associated with stem like properties. Differentially expressed genes that were over or under-expressed at least two fold commonly in all 4 cell lines were identified. We found 354 were upregulated and 126 were downregulated in SP cells compared to MP cells; of these, 89 up and 62 downregulated genes (average 2 fold changes) were used for Principle Component Analysis (PCA) and MetaCore pathway analysis. The pathway analysis demonstrated representation of 4 up regulated genes (TOP2A, AURKB, BRRN1, CDK1) in chromosome condensation pathway and 1 down regulated gene FUS in chromosomal translocation. Microarray data was validated using qRT-PCR on the 5 selected genes and all showed robust correlation between microarray and qRT-PCR. Further, we analyzed two independent gene expression datasets that included 360 lung adenocarcinoma patients from NCI Director's Challenge Set for overall survival and 63 samples from Sungkyunkwan University (SKKU) for recurrence free survival. Kaplan-Meier and log-rank test analysis predicted poor survival of patients in both data sets. Our results suggest that genes involved in chromosome condensation are likely related with stem-like properties and might predict survival in lung adenocarcinoma. Our findings highlight a gene signature for effective identification of lung adenocarcinoma patients with poor prognosis and designing more aggressive therapies for such patients.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0043589</identifier><identifier>PMID: 22952714</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adenocarcinoma ; Biology ; Biotechnology ; Cancer ; Cancer recurrence ; Cancer therapies ; Carcinoma, Non-Small-Cell Lung - pathology ; Care and treatment ; Cell Line, Tumor ; Cell survival ; Chromosomes ; Disease-Free Survival ; DNA microarrays ; Gene amplification ; Gene expression ; Genes ; Genetic aspects ; Genomics ; Humans ; Kinases ; Lung cancer ; Lung diseases ; Lung Neoplasms - pathology ; Medical prognosis ; Medical research ; Medicine ; Neoplastic Stem Cells - metabolism ; Neoplastic Stem Cells - pathology ; Non-small cell lung cancer ; Non-small cell lung carcinoma ; Oligonucleotide Array Sequence Analysis ; Patients ; Population ; Principal Component Analysis ; Principal components analysis ; Prognosis ; Properties (attributes) ; Real-Time Polymerase Chain Reaction ; Risk factors ; Senescence ; Stem cells ; Studies ; Survival ; Transcriptome ; Translocation ; Tumor cell lines ; Tumors</subject><ispartof>PloS one, 2012-08, Vol.7 (8), p.e43589-e43589</ispartof><rights>COPYRIGHT 2012 Public Library of Science</rights><rights>Perumal 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>2012 Perumal et al 2012 Perumal et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-3833ea4ca162451a32fcef6f64540ba13c649bc7c7ff9cfc6a89724368a759f63</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3430700/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3430700/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22952714$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Das, Gokul M.</contributor><creatorcontrib>Perumal, Deepak</creatorcontrib><creatorcontrib>Singh, Sandeep</creatorcontrib><creatorcontrib>Yoder, Sean J</creatorcontrib><creatorcontrib>Bloom, Gregory C</creatorcontrib><creatorcontrib>Chellappan, Srikumar P</creatorcontrib><title>A novel five gene signature derived from stem-like side population cells predicts overall and recurrence-free survival in NSCLC</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Gene expression profiling has been used to characterize prognosis in various cancers. Earlier studies had shown that side population cells isolated from Non-Small Cell Lung Cancer (NSCLC) cell lines exhibit cancer stem cell properties. In this study we apply a systems biology approach to gene expression profiling data from cancer stem like cells isolated from lung cancer cell lines to identify novel gene signatures that could predict prognosis. Microarray data from side population (SP) and main population (MP) cells isolated from 4 NSCLC lines (A549, H1650, H460, H1975) were used to examine gene expression profiles associated with stem like properties. Differentially expressed genes that were over or under-expressed at least two fold commonly in all 4 cell lines were identified. We found 354 were upregulated and 126 were downregulated in SP cells compared to MP cells; of these, 89 up and 62 downregulated genes (average 2 fold changes) were used for Principle Component Analysis (PCA) and MetaCore pathway analysis. The pathway analysis demonstrated representation of 4 up regulated genes (TOP2A, AURKB, BRRN1, CDK1) in chromosome condensation pathway and 1 down regulated gene FUS in chromosomal translocation. Microarray data was validated using qRT-PCR on the 5 selected genes and all showed robust correlation between microarray and qRT-PCR. Further, we analyzed two independent gene expression datasets that included 360 lung adenocarcinoma patients from NCI Director's Challenge Set for overall survival and 63 samples from Sungkyunkwan University (SKKU) for recurrence free survival. Kaplan-Meier and log-rank test analysis predicted poor survival of patients in both data sets. Our results suggest that genes involved in chromosome condensation are likely related with stem-like properties and might predict survival in lung adenocarcinoma. Our findings highlight a gene signature for effective identification of lung adenocarcinoma patients with poor prognosis and designing more aggressive therapies for such patients.</description><subject>Adenocarcinoma</subject><subject>Biology</subject><subject>Biotechnology</subject><subject>Cancer</subject><subject>Cancer recurrence</subject><subject>Cancer therapies</subject><subject>Carcinoma, Non-Small-Cell Lung - pathology</subject><subject>Care and treatment</subject><subject>Cell Line, Tumor</subject><subject>Cell survival</subject><subject>Chromosomes</subject><subject>Disease-Free Survival</subject><subject>DNA microarrays</subject><subject>Gene amplification</subject><subject>Gene expression</subject><subject>Genes</subject><subject>Genetic aspects</subject><subject>Genomics</subject><subject>Humans</subject><subject>Kinases</subject><subject>Lung cancer</subject><subject>Lung diseases</subject><subject>Lung Neoplasms - pathology</subject><subject>Medical prognosis</subject><subject>Medical research</subject><subject>Medicine</subject><subject>Neoplastic Stem Cells - metabolism</subject><subject>Neoplastic Stem Cells - pathology</subject><subject>Non-small cell lung cancer</subject><subject>Non-small cell lung carcinoma</subject><subject>Oligonucleotide Array Sequence Analysis</subject><subject>Patients</subject><subject>Population</subject><subject>Principal Component Analysis</subject><subject>Principal components analysis</subject><subject>Prognosis</subject><subject>Properties (attributes)</subject><subject>Real-Time Polymerase Chain Reaction</subject><subject>Risk factors</subject><subject>Senescence</subject><subject>Stem cells</subject><subject>Studies</subject><subject>Survival</subject><subject>Transcriptome</subject><subject>Translocation</subject><subject>Tumor cell lines</subject><subject>Tumors</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk82O0zAUhSMEYoaBN0BgCQnBosWxHcfZIFUVP5UqRmKAreU616kH1y52UsGKV8elmVGLZoGySHT9nXPtE9-ieFriaUnr8s11GKJXbroNHqYYM1qJ5l5xXjaUTDjB9P7R91nxKKVrjCsqOH9YnBHSVKQu2Xnxe4Z82IFDxu4AdeABJdt51Q8RUAsxV1tkYtig1MNm4uz3PdAC2obt4FRvg0canEtoG6G1uk8o20XlHFK-RRH0ECN4DRMTIUuHuLM75ZD16NPVfDl_XDwwyiV4Mr4viq_v332Zf5wsLz8s5rPlRPOG9BMqKAXFtCo5YVWpKDEaDDecVQyvVEk1Z81K17o2ptFGcyWamjDKhaqrxnB6UTw_-G5dSHLMLsmSkmyBq1pkYnEg2qCu5TbajYq_ZFBW_i2E2EkVe6sdSIUblZsrnnuzhlCBRQW05bXJe6Blm73ejt2G1QZaDb7PkZyYnq54u5Zd2EnKKK4xzgavRoMYfgyQermxaZ-z8hCGvG9MRdUIJkhGX_yD3n26kepUPoD1JuS-em8qZ6wRhOWsqkxN76Dy08LG6nzRjM31E8HrE0FmevjZd2pISS6uPv8_e_ntlH15xK5BuX6dghv29y2dguwA6hhSimBuQy6x3M_JTRpyPydynJMse3b8g25FN4NB_wCWBQ5r</recordid><startdate>20120829</startdate><enddate>20120829</enddate><creator>Perumal, Deepak</creator><creator>Singh, Sandeep</creator><creator>Yoder, Sean J</creator><creator>Bloom, Gregory C</creator><creator>Chellappan, Srikumar P</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>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>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20120829</creationdate><title>A novel five gene signature derived from stem-like side population cells predicts overall and recurrence-free survival in NSCLC</title><author>Perumal, Deepak ; Singh, Sandeep ; Yoder, Sean J ; Bloom, Gregory C ; Chellappan, Srikumar P</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-3833ea4ca162451a32fcef6f64540ba13c649bc7c7ff9cfc6a89724368a759f63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Adenocarcinoma</topic><topic>Biology</topic><topic>Biotechnology</topic><topic>Cancer</topic><topic>Cancer recurrence</topic><topic>Cancer therapies</topic><topic>Carcinoma, Non-Small-Cell Lung - pathology</topic><topic>Care and treatment</topic><topic>Cell Line, Tumor</topic><topic>Cell survival</topic><topic>Chromosomes</topic><topic>Disease-Free Survival</topic><topic>DNA microarrays</topic><topic>Gene amplification</topic><topic>Gene expression</topic><topic>Genes</topic><topic>Genetic aspects</topic><topic>Genomics</topic><topic>Humans</topic><topic>Kinases</topic><topic>Lung cancer</topic><topic>Lung diseases</topic><topic>Lung Neoplasms - pathology</topic><topic>Medical prognosis</topic><topic>Medical research</topic><topic>Medicine</topic><topic>Neoplastic Stem Cells - metabolism</topic><topic>Neoplastic Stem Cells - pathology</topic><topic>Non-small cell lung cancer</topic><topic>Non-small cell lung carcinoma</topic><topic>Oligonucleotide Array Sequence Analysis</topic><topic>Patients</topic><topic>Population</topic><topic>Principal Component Analysis</topic><topic>Principal components analysis</topic><topic>Prognosis</topic><topic>Properties (attributes)</topic><topic>Real-Time Polymerase Chain Reaction</topic><topic>Risk factors</topic><topic>Senescence</topic><topic>Stem cells</topic><topic>Studies</topic><topic>Survival</topic><topic>Transcriptome</topic><topic>Translocation</topic><topic>Tumor cell lines</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Perumal, Deepak</creatorcontrib><creatorcontrib>Singh, Sandeep</creatorcontrib><creatorcontrib>Yoder, Sean J</creatorcontrib><creatorcontrib>Bloom, Gregory C</creatorcontrib><creatorcontrib>Chellappan, Srikumar P</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Perumal, Deepak</au><au>Singh, Sandeep</au><au>Yoder, Sean J</au><au>Bloom, Gregory C</au><au>Chellappan, Srikumar P</au><au>Das, Gokul M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A novel five gene signature derived from stem-like side population cells predicts overall and recurrence-free survival in NSCLC</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2012-08-29</date><risdate>2012</risdate><volume>7</volume><issue>8</issue><spage>e43589</spage><epage>e43589</epage><pages>e43589-e43589</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Gene expression profiling has been used to characterize prognosis in various cancers. Earlier studies had shown that side population cells isolated from Non-Small Cell Lung Cancer (NSCLC) cell lines exhibit cancer stem cell properties. In this study we apply a systems biology approach to gene expression profiling data from cancer stem like cells isolated from lung cancer cell lines to identify novel gene signatures that could predict prognosis. Microarray data from side population (SP) and main population (MP) cells isolated from 4 NSCLC lines (A549, H1650, H460, H1975) were used to examine gene expression profiles associated with stem like properties. Differentially expressed genes that were over or under-expressed at least two fold commonly in all 4 cell lines were identified. We found 354 were upregulated and 126 were downregulated in SP cells compared to MP cells; of these, 89 up and 62 downregulated genes (average 2 fold changes) were used for Principle Component Analysis (PCA) and MetaCore pathway analysis. The pathway analysis demonstrated representation of 4 up regulated genes (TOP2A, AURKB, BRRN1, CDK1) in chromosome condensation pathway and 1 down regulated gene FUS in chromosomal translocation. Microarray data was validated using qRT-PCR on the 5 selected genes and all showed robust correlation between microarray and qRT-PCR. Further, we analyzed two independent gene expression datasets that included 360 lung adenocarcinoma patients from NCI Director's Challenge Set for overall survival and 63 samples from Sungkyunkwan University (SKKU) for recurrence free survival. Kaplan-Meier and log-rank test analysis predicted poor survival of patients in both data sets. Our results suggest that genes involved in chromosome condensation are likely related with stem-like properties and might predict survival in lung adenocarcinoma. Our findings highlight a gene signature for effective identification of lung adenocarcinoma patients with poor prognosis and designing more aggressive therapies for such patients.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>22952714</pmid><doi>10.1371/journal.pone.0043589</doi><tpages>e43589</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2012-08, Vol.7 (8), p.e43589-e43589 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1326450578 |
| source | PubMed Central Free; MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; Free Full-Text Journals in Chemistry |
| subjects | Adenocarcinoma Biology Biotechnology Cancer Cancer recurrence Cancer therapies Carcinoma, Non-Small-Cell Lung - pathology Care and treatment Cell Line, Tumor Cell survival Chromosomes Disease-Free Survival DNA microarrays Gene amplification Gene expression Genes Genetic aspects Genomics Humans Kinases Lung cancer Lung diseases Lung Neoplasms - pathology Medical prognosis Medical research Medicine Neoplastic Stem Cells - metabolism Neoplastic Stem Cells - pathology Non-small cell lung cancer Non-small cell lung carcinoma Oligonucleotide Array Sequence Analysis Patients Population Principal Component Analysis Principal components analysis Prognosis Properties (attributes) Real-Time Polymerase Chain Reaction Risk factors Senescence Stem cells Studies Survival Transcriptome Translocation Tumor cell lines Tumors |
| title | A novel five gene signature derived from stem-like side population cells predicts overall and recurrence-free survival in NSCLC |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T00%3A30%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20novel%20five%20gene%20signature%20derived%20from%20stem-like%20side%20population%20cells%20predicts%20overall%20and%20recurrence-free%20survival%20in%20NSCLC&rft.jtitle=PloS%20one&rft.au=Perumal,%20Deepak&rft.date=2012-08-29&rft.volume=7&rft.issue=8&rft.spage=e43589&rft.epage=e43589&rft.pages=e43589-e43589&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0043589&rft_dat=%3Cgale_plos_%3EA498244365%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1326450578&rft_id=info:pmid/22952714&rft_galeid=A498244365&rft_doaj_id=oai_doaj_org_article_a09af6fa640b49238085e3d67f9bc31d&rfr_iscdi=true |