Hidden treasures in ancient microarrays: Gene expression portrays biology and potential resistance pathways of major lung cancer subtypes and normal tissue
Objective: Novel statistical methods and increasingly more accurate gene annotations can transform old biological data into a renewed source of knowledge with potential clinical relevance. Here we provide an in-silico proof-of-concept by extracting novel information from a high quality mRNA expressi...
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Frontiers Media S.A.
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doaj-badd4131982144ef971a29e600b0577a2020-11-24T21:02:06ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2014-09-01410.3389/fonc.2014.00251109280Hidden treasures in ancient microarrays: Gene expression portrays biology and potential resistance pathways of major lung cancer subtypes and normal tissueKonstantinos eKerkentzes0Konstantinos eKerkentzes1Vincenzo eLagani2Ioannis eTsamardinos3Ioannis eTsamardinos4Mogens eVyberg5Oluf Dimitri Røe6Oluf Dimitri Røe7Oluf Dimitri Røe8University of CreteFoundation of Research and Technology – HellasFoundation of Research and Technology – HellasUniversity of CreteFoundation of Research and Technology – HellasAalborg University HospitalNorwegian University of Science and TechnologyAalborg University HospitalLevanger Hospital, Nord-Trøndelag Health TrustObjective: Novel statistical methods and increasingly more accurate gene annotations can transform old biological data into a renewed source of knowledge with potential clinical relevance. Here we provide an in-silico proof-of-concept by extracting novel information from a high quality mRNA expression dataset, originally published in 2001, using state-of-the-art bioinformatics approaches. Methods: The dataset consists of histologically defined cases of lung adenocarcinoma, squamous cell carcinoma, small-cell lung cancer, carcinoid, metastasis (breast and colon adenocarcinoma) and normal lung specimens (203 samples in total). A battery of statistical tests was used for identifying differential gene expressions, diagnostic and prognostic genes, enriched gene ontologies and signaling pathways. Results: Our results showed that gene expressions faithfully recapitulate immunohistochemical subtype markers, as chromogranin A in carcinoids, cytokeratin 5, p63 in squamous and TTF1 in non-squamous types. Moreover, biological information with putative clinical relevance was revealed as potentially novel diagnostic genes for each subtype with specificity 93-100% (AUC=0.93-1.00). Cancer subtypes where characterized by (a) differential expression of treatment target genes as TYMS, HER2 and HER3 and (b) overrepresentation of treatment-related pathways like cell cycle, DNA repair and ERBB pathways. The vascular smooth muscle contraction, leukocyte transendothelial migration and actin cytoskeleton pathways were overexpressed in normal tissue. Conclusion: Reanalysis of this public dataset displayed the known biological features of lung cancer subtypes and revealed novel pathways of potentially clinical importance. The findings also support our hypothesis that even old omics data of high quality can be a source of significant biological information when appropriate bioinformatics methods are used.http://journal.frontiersin.org/Journal/10.3389/fonc.2014.00251/fullMesotheliomabioinformaticsMicroarraycarcinoidLung AdenocarcinomaSquamous |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Konstantinos eKerkentzes Konstantinos eKerkentzes Vincenzo eLagani Ioannis eTsamardinos Ioannis eTsamardinos Mogens eVyberg Oluf Dimitri Røe Oluf Dimitri Røe Oluf Dimitri Røe |
spellingShingle |
Konstantinos eKerkentzes Konstantinos eKerkentzes Vincenzo eLagani Ioannis eTsamardinos Ioannis eTsamardinos Mogens eVyberg Oluf Dimitri Røe Oluf Dimitri Røe Oluf Dimitri Røe Hidden treasures in ancient microarrays: Gene expression portrays biology and potential resistance pathways of major lung cancer subtypes and normal tissue Frontiers in Oncology Mesothelioma bioinformatics Microarray carcinoid Lung Adenocarcinoma Squamous |
author_facet |
Konstantinos eKerkentzes Konstantinos eKerkentzes Vincenzo eLagani Ioannis eTsamardinos Ioannis eTsamardinos Mogens eVyberg Oluf Dimitri Røe Oluf Dimitri Røe Oluf Dimitri Røe |
author_sort |
Konstantinos eKerkentzes |
title |
Hidden treasures in ancient microarrays: Gene expression portrays biology and potential resistance pathways of major lung cancer subtypes and normal tissue |
title_short |
Hidden treasures in ancient microarrays: Gene expression portrays biology and potential resistance pathways of major lung cancer subtypes and normal tissue |
title_full |
Hidden treasures in ancient microarrays: Gene expression portrays biology and potential resistance pathways of major lung cancer subtypes and normal tissue |
title_fullStr |
Hidden treasures in ancient microarrays: Gene expression portrays biology and potential resistance pathways of major lung cancer subtypes and normal tissue |
title_full_unstemmed |
Hidden treasures in ancient microarrays: Gene expression portrays biology and potential resistance pathways of major lung cancer subtypes and normal tissue |
title_sort |
hidden treasures in ancient microarrays: gene expression portrays biology and potential resistance pathways of major lung cancer subtypes and normal tissue |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Oncology |
issn |
2234-943X |
publishDate |
2014-09-01 |
description |
Objective: Novel statistical methods and increasingly more accurate gene annotations can transform old biological data into a renewed source of knowledge with potential clinical relevance. Here we provide an in-silico proof-of-concept by extracting novel information from a high quality mRNA expression dataset, originally published in 2001, using state-of-the-art bioinformatics approaches. Methods: The dataset consists of histologically defined cases of lung adenocarcinoma, squamous cell carcinoma, small-cell lung cancer, carcinoid, metastasis (breast and colon adenocarcinoma) and normal lung specimens (203 samples in total). A battery of statistical tests was used for identifying differential gene expressions, diagnostic and prognostic genes, enriched gene ontologies and signaling pathways. Results: Our results showed that gene expressions faithfully recapitulate immunohistochemical subtype markers, as chromogranin A in carcinoids, cytokeratin 5, p63 in squamous and TTF1 in non-squamous types. Moreover, biological information with putative clinical relevance was revealed as potentially novel diagnostic genes for each subtype with specificity 93-100% (AUC=0.93-1.00). Cancer subtypes where characterized by (a) differential expression of treatment target genes as TYMS, HER2 and HER3 and (b) overrepresentation of treatment-related pathways like cell cycle, DNA repair and ERBB pathways. The vascular smooth muscle contraction, leukocyte transendothelial migration and actin cytoskeleton pathways were overexpressed in normal tissue. Conclusion: Reanalysis of this public dataset displayed the known biological features of lung cancer subtypes and revealed novel pathways of potentially clinical importance. The findings also support our hypothesis that even old omics data of high quality can be a source of significant biological information when appropriate bioinformatics methods are used. |
topic |
Mesothelioma bioinformatics Microarray carcinoid Lung Adenocarcinoma Squamous |
url |
http://journal.frontiersin.org/Journal/10.3389/fonc.2014.00251/full |
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