Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer
The head and neck squamous cell carcinoma (HNSCC) transcriptome has been profiled extensively, nevertheless, identifying biomarkers that are clinically relevant and thereby with translational benefit, has been a major challenge. The objective of this study was to use a meta-analysis based approach t...
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| creator | Reddy, Ram Bhupal Bhat, Anupama Rajan James, Bonney Lee Govindan, Sindhu Valiyaveedan Mathew, Rohit Ravindra, D R Hedne, Naveen Illiayaraja, Jeyaram Kekatpure, Vikram Khora, Samanta S Hicks, Wesley Tata, Pramila Kuriakose, Moni A Suresh, Amritha |
| description | The head and neck squamous cell carcinoma (HNSCC) transcriptome has been profiled extensively, nevertheless, identifying biomarkers that are clinically relevant and thereby with translational benefit, has been a major challenge. The objective of this study was to use a meta-analysis based approach to catalog candidate biomarkers with high potential for clinical application in HNSCC. Data from publically available microarray series (N = 20) profiled using Agilent (4X44K G4112F) and Affymetrix (HGU133A, U133A_2, U133Plus 2) platforms was downloaded and analyzed in a platform/chip-specific manner (GeneSpring software v12.5, Agilent, USA). Principal Component Analysis (PCA) and clustering analysis was carried out iteratively for segregating outliers; 140 normal and 277 tumor samples from 15 series were included in the final analysis. The analyses identified 181 differentially expressed, concordant and statistically significant genes; STRING analysis revealed interactions between 122 of them, with two major gene clusters connected by multiple nodes (MYC, FOS and HSPA4). Validation in the HNSCC-specific database (N = 528) in The Cancer Genome Atlas (TCGA) identified a panel (ECT2, ANO1, TP63, FADD, EXT1, NCBP2) that was altered in 30% of the samples. Validation in treatment naïve (Group I; N = 12) and post treatment (Group II; N = 12) patients identified 8 genes significantly associated with the disease (Area under curve>0.6). Correlation with recurrence/re-recurrence showed ANO1 had highest efficacy (sensitivity: 0.8, specificity: 0.6) to predict failure in Group I. UBE2V2, PLAC8, FADD and TTK showed high sensitivity (1.00) in Group I while UBE2V2 and CRYM were highly sensitive (>0.8) in predicting re-recurrence in Group II. Further, TCGA analysis showed that ANO1 and FADD, located at 11q13, were co-expressed at transcript level and significantly associated with overall and disease-free survival (p |
| doi_str_mv | 10.1371/journal.pone.0147409 |
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The objective of this study was to use a meta-analysis based approach to catalog candidate biomarkers with high potential for clinical application in HNSCC. Data from publically available microarray series (N = 20) profiled using Agilent (4X44K G4112F) and Affymetrix (HGU133A, U133A_2, U133Plus 2) platforms was downloaded and analyzed in a platform/chip-specific manner (GeneSpring software v12.5, Agilent, USA). Principal Component Analysis (PCA) and clustering analysis was carried out iteratively for segregating outliers; 140 normal and 277 tumor samples from 15 series were included in the final analysis. The analyses identified 181 differentially expressed, concordant and statistically significant genes; STRING analysis revealed interactions between 122 of them, with two major gene clusters connected by multiple nodes (MYC, FOS and HSPA4). Validation in the HNSCC-specific database (N = 528) in The Cancer Genome Atlas (TCGA) identified a panel (ECT2, ANO1, TP63, FADD, EXT1, NCBP2) that was altered in 30% of the samples. Validation in treatment naïve (Group I; N = 12) and post treatment (Group II; N = 12) patients identified 8 genes significantly associated with the disease (Area under curve>0.6). Correlation with recurrence/re-recurrence showed ANO1 had highest efficacy (sensitivity: 0.8, specificity: 0.6) to predict failure in Group I. UBE2V2, PLAC8, FADD and TTK showed high sensitivity (1.00) in Group I while UBE2V2 and CRYM were highly sensitive (>0.8) in predicting re-recurrence in Group II. Further, TCGA analysis showed that ANO1 and FADD, located at 11q13, were co-expressed at transcript level and significantly associated with overall and disease-free survival (p<0.05). The meta-analysis approach adopted in this study has identified candidate markers correlated with disease outcome in HNSCC; further validation in a larger cohort of patients will establish their clinical relevance.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0147409</identifier><identifier>PMID: 26808319</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Anoctamin-1 ; Apoptosis ; Archives & records ; Biology and Life Sciences ; Biomarkers ; Biomarkers, Tumor - metabolism ; Breast cancer ; Cancer ; Chloride Channels - genetics ; Cluster analysis ; Clustering ; Collaboration ; Correlation analysis ; Data analysis ; Data processing ; Datasets ; DNA microarrays ; FADD protein ; Fas-Associated Death Domain Protein - genetics ; Gene amplification ; Gene clusters ; Gene expression ; Genes ; Genomes ; Head ; Head & neck cancer ; Head and neck cancer ; Head and Neck Neoplasms - genetics ; Head and Neck Neoplasms - pathology ; Human papillomavirus ; Humans ; Life sciences ; Medical prognosis ; Medical research ; Medicine and Health Sciences ; Meta-analysis ; mu-Crystallins ; Myc protein ; Neoplasm Proteins - genetics ; Office parks ; Oncology ; Otolaryngology ; Outliers (statistics) ; Pathology ; Patients ; Physical Sciences ; Principal components analysis ; Prognosis ; Prostate ; Proteins ; Research and Analysis Methods ; Sensitivity ; Squamous cell carcinoma ; Statistical analysis ; Statistical methods ; Studies ; Surgery ; Transcription ; Tumors</subject><ispartof>PloS one, 2016-01, Vol.11 (1), p.e0147409-e0147409</ispartof><rights>2016 Reddy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://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>2016 Reddy et al 2016 Reddy et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c526t-ea9714022af433b729f202ee906b47d5d2fe2fbf9054d2e84b340dc44e3f16873</citedby><cites>FETCH-LOGICAL-c526t-ea9714022af433b729f202ee906b47d5d2fe2fbf9054d2e84b340dc44e3f16873</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/PMC4726811/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4726811/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79569,79570</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26808319$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Reddy, Ram Bhupal</creatorcontrib><creatorcontrib>Bhat, Anupama Rajan</creatorcontrib><creatorcontrib>James, Bonney Lee</creatorcontrib><creatorcontrib>Govindan, Sindhu Valiyaveedan</creatorcontrib><creatorcontrib>Mathew, Rohit</creatorcontrib><creatorcontrib>Ravindra, D R</creatorcontrib><creatorcontrib>Hedne, Naveen</creatorcontrib><creatorcontrib>Illiayaraja, Jeyaram</creatorcontrib><creatorcontrib>Kekatpure, Vikram</creatorcontrib><creatorcontrib>Khora, Samanta S</creatorcontrib><creatorcontrib>Hicks, Wesley</creatorcontrib><creatorcontrib>Tata, Pramila</creatorcontrib><creatorcontrib>Kuriakose, Moni A</creatorcontrib><creatorcontrib>Suresh, Amritha</creatorcontrib><title>Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>The head and neck squamous cell carcinoma (HNSCC) transcriptome has been profiled extensively, nevertheless, identifying biomarkers that are clinically relevant and thereby with translational benefit, has been a major challenge. The objective of this study was to use a meta-analysis based approach to catalog candidate biomarkers with high potential for clinical application in HNSCC. Data from publically available microarray series (N = 20) profiled using Agilent (4X44K G4112F) and Affymetrix (HGU133A, U133A_2, U133Plus 2) platforms was downloaded and analyzed in a platform/chip-specific manner (GeneSpring software v12.5, Agilent, USA). Principal Component Analysis (PCA) and clustering analysis was carried out iteratively for segregating outliers; 140 normal and 277 tumor samples from 15 series were included in the final analysis. The analyses identified 181 differentially expressed, concordant and statistically significant genes; STRING analysis revealed interactions between 122 of them, with two major gene clusters connected by multiple nodes (MYC, FOS and HSPA4). Validation in the HNSCC-specific database (N = 528) in The Cancer Genome Atlas (TCGA) identified a panel (ECT2, ANO1, TP63, FADD, EXT1, NCBP2) that was altered in 30% of the samples. Validation in treatment naïve (Group I; N = 12) and post treatment (Group II; N = 12) patients identified 8 genes significantly associated with the disease (Area under curve>0.6). Correlation with recurrence/re-recurrence showed ANO1 had highest efficacy (sensitivity: 0.8, specificity: 0.6) to predict failure in Group I. UBE2V2, PLAC8, FADD and TTK showed high sensitivity (1.00) in Group I while UBE2V2 and CRYM were highly sensitive (>0.8) in predicting re-recurrence in Group II. Further, TCGA analysis showed that ANO1 and FADD, located at 11q13, were co-expressed at transcript level and significantly associated with overall and disease-free survival (p<0.05). The meta-analysis approach adopted in this study has identified candidate markers correlated with disease outcome in HNSCC; further validation in a larger cohort of patients will establish their clinical relevance.</description><subject>Anoctamin-1</subject><subject>Apoptosis</subject><subject>Archives & records</subject><subject>Biology and Life Sciences</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor - metabolism</subject><subject>Breast cancer</subject><subject>Cancer</subject><subject>Chloride Channels - genetics</subject><subject>Cluster analysis</subject><subject>Clustering</subject><subject>Collaboration</subject><subject>Correlation analysis</subject><subject>Data analysis</subject><subject>Data processing</subject><subject>Datasets</subject><subject>DNA microarrays</subject><subject>FADD protein</subject><subject>Fas-Associated Death Domain Protein - genetics</subject><subject>Gene amplification</subject><subject>Gene clusters</subject><subject>Gene 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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>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest Health & Medical Research Collection</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Health & Nursing</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</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>Reddy, Ram Bhupal</au><au>Bhat, Anupama Rajan</au><au>James, Bonney Lee</au><au>Govindan, Sindhu Valiyaveedan</au><au>Mathew, Rohit</au><au>Ravindra, D R</au><au>Hedne, Naveen</au><au>Illiayaraja, Jeyaram</au><au>Kekatpure, Vikram</au><au>Khora, Samanta S</au><au>Hicks, Wesley</au><au>Tata, Pramila</au><au>Kuriakose, Moni A</au><au>Suresh, Amritha</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2016-01-01</date><risdate>2016</risdate><volume>11</volume><issue>1</issue><spage>e0147409</spage><epage>e0147409</epage><pages>e0147409-e0147409</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>The head and neck squamous cell carcinoma (HNSCC) transcriptome has been profiled extensively, nevertheless, identifying biomarkers that are clinically relevant and thereby with translational benefit, has been a major challenge. The objective of this study was to use a meta-analysis based approach to catalog candidate biomarkers with high potential for clinical application in HNSCC. Data from publically available microarray series (N = 20) profiled using Agilent (4X44K G4112F) and Affymetrix (HGU133A, U133A_2, U133Plus 2) platforms was downloaded and analyzed in a platform/chip-specific manner (GeneSpring software v12.5, Agilent, USA). Principal Component Analysis (PCA) and clustering analysis was carried out iteratively for segregating outliers; 140 normal and 277 tumor samples from 15 series were included in the final analysis. The analyses identified 181 differentially expressed, concordant and statistically significant genes; STRING analysis revealed interactions between 122 of them, with two major gene clusters connected by multiple nodes (MYC, FOS and HSPA4). Validation in the HNSCC-specific database (N = 528) in The Cancer Genome Atlas (TCGA) identified a panel (ECT2, ANO1, TP63, FADD, EXT1, NCBP2) that was altered in 30% of the samples. Validation in treatment naïve (Group I; N = 12) and post treatment (Group II; N = 12) patients identified 8 genes significantly associated with the disease (Area under curve>0.6). Correlation with recurrence/re-recurrence showed ANO1 had highest efficacy (sensitivity: 0.8, specificity: 0.6) to predict failure in Group I. UBE2V2, PLAC8, FADD and TTK showed high sensitivity (1.00) in Group I while UBE2V2 and CRYM were highly sensitive (>0.8) in predicting re-recurrence in Group II. Further, TCGA analysis showed that ANO1 and FADD, located at 11q13, were co-expressed at transcript level and significantly associated with overall and disease-free survival (p<0.05). The meta-analysis approach adopted in this study has identified candidate markers correlated with disease outcome in HNSCC; further validation in a larger cohort of patients will establish their clinical relevance.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>26808319</pmid><doi>10.1371/journal.pone.0147409</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2016-01, Vol.11 (1), p.e0147409-e0147409 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1760027130 |
| source | Public Library of Science (PLoS) Journals Open Access; MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Anoctamin-1 Apoptosis Archives & records Biology and Life Sciences Biomarkers Biomarkers, Tumor - metabolism Breast cancer Cancer Chloride Channels - genetics Cluster analysis Clustering Collaboration Correlation analysis Data analysis Data processing Datasets DNA microarrays FADD protein Fas-Associated Death Domain Protein - genetics Gene amplification Gene clusters Gene expression Genes Genomes Head Head & neck cancer Head and neck cancer Head and Neck Neoplasms - genetics Head and Neck Neoplasms - pathology Human papillomavirus Humans Life sciences Medical prognosis Medical research Medicine and Health Sciences Meta-analysis mu-Crystallins Myc protein Neoplasm Proteins - genetics Office parks Oncology Otolaryngology Outliers (statistics) Pathology Patients Physical Sciences Principal components analysis Prognosis Prostate Proteins Research and Analysis Methods Sensitivity Squamous cell carcinoma Statistical analysis Statistical methods Studies Surgery Transcription Tumors |
| title | Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer |
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