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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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Autores principales: Reddy, Ram Bhupal, Bhat, Anupama Rajan, James, Bonney Lee, Govindan, Sindhu Valiyaveedan, Mathew, Rohit, DR, Ravindra, Hedne, Naveen, Illiayaraja, Jeyaram, Kekatpure, Vikram, Khora, Samanta S., Hicks, Wesley, Tata, Pramila, Kuriakose, Moni A., Suresh, Amritha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4726811/
https://www.ncbi.nlm.nih.gov/pubmed/26808319
http://dx.doi.org/10.1371/journal.pone.0147409
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author Reddy, Ram Bhupal
Bhat, Anupama Rajan
James, Bonney Lee
Govindan, Sindhu Valiyaveedan
Mathew, Rohit
DR, Ravindra
Hedne, Naveen
Illiayaraja, Jeyaram
Kekatpure, Vikram
Khora, Samanta S.
Hicks, Wesley
Tata, Pramila
Kuriakose, Moni A.
Suresh, Amritha
author_facet Reddy, Ram Bhupal
Bhat, Anupama Rajan
James, Bonney Lee
Govindan, Sindhu Valiyaveedan
Mathew, Rohit
DR, Ravindra
Hedne, Naveen
Illiayaraja, Jeyaram
Kekatpure, Vikram
Khora, Samanta S.
Hicks, Wesley
Tata, Pramila
Kuriakose, Moni A.
Suresh, Amritha
author_sort Reddy, Ram Bhupal
collection PubMed
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.
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spelling pubmed-47268112016-02-03 Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer Reddy, Ram Bhupal Bhat, Anupama Rajan James, Bonney Lee Govindan, Sindhu Valiyaveedan Mathew, Rohit DR, Ravindra Hedne, Naveen Illiayaraja, Jeyaram Kekatpure, Vikram Khora, Samanta S. Hicks, Wesley Tata, Pramila Kuriakose, Moni A. Suresh, Amritha PLoS One Research Article 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. Public Library of Science 2016-01-25 /pmc/articles/PMC4726811/ /pubmed/26808319 http://dx.doi.org/10.1371/journal.pone.0147409 Text en © 2016 Reddy et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Reddy, Ram Bhupal
Bhat, Anupama Rajan
James, Bonney Lee
Govindan, Sindhu Valiyaveedan
Mathew, Rohit
DR, Ravindra
Hedne, Naveen
Illiayaraja, Jeyaram
Kekatpure, Vikram
Khora, Samanta S.
Hicks, Wesley
Tata, Pramila
Kuriakose, Moni A.
Suresh, Amritha
Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer
title Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer
title_full Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer
title_fullStr Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer
title_full_unstemmed Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer
title_short Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer
title_sort meta-analyses of microarray datasets identifies ano1 and fadd as prognostic markers of head and neck cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4726811/
https://www.ncbi.nlm.nih.gov/pubmed/26808319
http://dx.doi.org/10.1371/journal.pone.0147409
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