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Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations
BACKGROUND: The development of a more refined prognostic methodology for early non-small cell lung cancer (NSCLC) is an unmet clinical need. An accurate prognostic tool might help to select patients at early stages for adjuvant therapies. RESULTS: A new integrated bioinformatics searching strategy,...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4595201/ https://www.ncbi.nlm.nih.gov/pubmed/26444668 http://dx.doi.org/10.1186/s12864-015-1935-0 |
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author | Aramburu, Ander Zudaire, Isabel Pajares, María J. Agorreta, Jackeline Orta, Alberto Lozano, María D. Gúrpide, Alfonso Gómez-Román, Javier Martinez-Climent, Jose A. Jassem, Jacek Skrzypski, Marcin Suraokar, Milind Behrens, Carmen Wistuba, Ignacio I. Pio, Ruben Rubio, Angel Montuenga, Luis M. |
author_facet | Aramburu, Ander Zudaire, Isabel Pajares, María J. Agorreta, Jackeline Orta, Alberto Lozano, María D. Gúrpide, Alfonso Gómez-Román, Javier Martinez-Climent, Jose A. Jassem, Jacek Skrzypski, Marcin Suraokar, Milind Behrens, Carmen Wistuba, Ignacio I. Pio, Ruben Rubio, Angel Montuenga, Luis M. |
author_sort | Aramburu, Ander |
collection | PubMed |
description | BACKGROUND: The development of a more refined prognostic methodology for early non-small cell lung cancer (NSCLC) is an unmet clinical need. An accurate prognostic tool might help to select patients at early stages for adjuvant therapies. RESULTS: A new integrated bioinformatics searching strategy, that combines gene copy number alterations and expression, together with clinical parameters was applied to derive two prognostic genomic signatures. The proposed methodology combines data from patients with and without clinical data with a priori information on the ability of a gene to be a prognostic marker. Two initial candidate sets of 513 and 150 genes for lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively, were generated by identifying genes which have both: a) significant correlation between copy number and gene expression, and b) significant prognostic value at the gene expression level in external databases. From these candidates, two panels of 7 (ADC) and 5 (SCC) genes were further identified via semi-supervised learning. These panels, together with clinical data (stage, age and sex), were used to construct the ADC and SCC hazard scores combining clinical and genomic data. The signatures were validated in two independent datasets (n = 73 for ADC, n = 97 for SCC), confirming that the prognostic value of both clinical-genomic models is robust, statistically significant (P = 0.008 for ADC and P = 0.019 for SCC) and outperforms both the clinical models (P = 0.060 for ADC and P = 0.121 for SCC) and the genomic models applied separately (P = 0.350 for ADC and P = 0.269 for SCC). CONCLUSION: The present work provides a methodology to generate a robust signature using copy number data that can be potentially used to any cancer. Using it, we found new prognostic scores based on tumor DNA that, jointly with clinical information, are able to predict overall survival (OS) in patients with early-stage ADC and SCC. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1935-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4595201 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-45952012015-10-07 Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations Aramburu, Ander Zudaire, Isabel Pajares, María J. Agorreta, Jackeline Orta, Alberto Lozano, María D. Gúrpide, Alfonso Gómez-Román, Javier Martinez-Climent, Jose A. Jassem, Jacek Skrzypski, Marcin Suraokar, Milind Behrens, Carmen Wistuba, Ignacio I. Pio, Ruben Rubio, Angel Montuenga, Luis M. BMC Genomics Methodology BACKGROUND: The development of a more refined prognostic methodology for early non-small cell lung cancer (NSCLC) is an unmet clinical need. An accurate prognostic tool might help to select patients at early stages for adjuvant therapies. RESULTS: A new integrated bioinformatics searching strategy, that combines gene copy number alterations and expression, together with clinical parameters was applied to derive two prognostic genomic signatures. The proposed methodology combines data from patients with and without clinical data with a priori information on the ability of a gene to be a prognostic marker. Two initial candidate sets of 513 and 150 genes for lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively, were generated by identifying genes which have both: a) significant correlation between copy number and gene expression, and b) significant prognostic value at the gene expression level in external databases. From these candidates, two panels of 7 (ADC) and 5 (SCC) genes were further identified via semi-supervised learning. These panels, together with clinical data (stage, age and sex), were used to construct the ADC and SCC hazard scores combining clinical and genomic data. The signatures were validated in two independent datasets (n = 73 for ADC, n = 97 for SCC), confirming that the prognostic value of both clinical-genomic models is robust, statistically significant (P = 0.008 for ADC and P = 0.019 for SCC) and outperforms both the clinical models (P = 0.060 for ADC and P = 0.121 for SCC) and the genomic models applied separately (P = 0.350 for ADC and P = 0.269 for SCC). CONCLUSION: The present work provides a methodology to generate a robust signature using copy number data that can be potentially used to any cancer. Using it, we found new prognostic scores based on tumor DNA that, jointly with clinical information, are able to predict overall survival (OS) in patients with early-stage ADC and SCC. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1935-0) contains supplementary material, which is available to authorized users. BioMed Central 2015-10-06 /pmc/articles/PMC4595201/ /pubmed/26444668 http://dx.doi.org/10.1186/s12864-015-1935-0 Text en © Aramburu et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Aramburu, Ander Zudaire, Isabel Pajares, María J. Agorreta, Jackeline Orta, Alberto Lozano, María D. Gúrpide, Alfonso Gómez-Román, Javier Martinez-Climent, Jose A. Jassem, Jacek Skrzypski, Marcin Suraokar, Milind Behrens, Carmen Wistuba, Ignacio I. Pio, Ruben Rubio, Angel Montuenga, Luis M. Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations |
title | Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations |
title_full | Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations |
title_fullStr | Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations |
title_full_unstemmed | Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations |
title_short | Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations |
title_sort | combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4595201/ https://www.ncbi.nlm.nih.gov/pubmed/26444668 http://dx.doi.org/10.1186/s12864-015-1935-0 |
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