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Integrated quantitative proteomic and transcriptomic analysis of lung tumor and control tissue: a lung cancer showcase

Proteomics analysis of paired cancer and control tissue can be applied to investigate pathological processes in tumors. Advancements in data-independent acquisition mass spectrometry allow for highly reproducible quantitative analysis of complex proteomic patterns. Optimized sample preparation workf...

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Autores principales: Tenzer, Stefan, Leidinger, Petra, Backes, Christina, Huwer, Hanno, Hildebrandt, Andreas, Lenhof, Hans-Peter, Wesse, Tanja, Franke, Andre, Meese, Eckart, Keller, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4924757/
https://www.ncbi.nlm.nih.gov/pubmed/26930711
http://dx.doi.org/10.18632/oncotarget.7562
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author Tenzer, Stefan
Leidinger, Petra
Backes, Christina
Huwer, Hanno
Hildebrandt, Andreas
Lenhof, Hans-Peter
Wesse, Tanja
Franke, Andre
Meese, Eckart
Keller, Andreas
author_facet Tenzer, Stefan
Leidinger, Petra
Backes, Christina
Huwer, Hanno
Hildebrandt, Andreas
Lenhof, Hans-Peter
Wesse, Tanja
Franke, Andre
Meese, Eckart
Keller, Andreas
author_sort Tenzer, Stefan
collection PubMed
description Proteomics analysis of paired cancer and control tissue can be applied to investigate pathological processes in tumors. Advancements in data-independent acquisition mass spectrometry allow for highly reproducible quantitative analysis of complex proteomic patterns. Optimized sample preparation workflows enable integrative multi-omics studies from the same tissue specimens. We performed ion mobility enhanced, data-independent acquisition MS to characterize the proteome of 21 lung tumor tissues including adenocarcinoma and squamous cell carcinoma (SCC) as compared to control lung tissues of the same patient each. Transcriptomic data were generated for the same specimens. The quantitative proteomic patterns and mRNA abundances were subsequently analyzed using systems biology approaches. We report a significantly (p = 0.0001) larger repertoire of proteins in cancer tissues. 12 proteins were higher in all tumor tissues as compared to matching control tissues. Three proteins, CAV1, CAV2, and RAGE, were vice versa higher in all controls. We also identified characteristic SCC and adenocarcinoma protein patterns. Principal Component Analysis provided evidence that not only cancer from control tissue but also tissue from adenocarcinoma and SCC can be differentiated. Transcriptomic levels of key proteins measured from the same matched tissue samples correlated with the observed protein patterns. The applied study set-up with paired lung tissue specimens of which different omics are measured, is generally suited for an integrated multi-omics analysis.
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spelling pubmed-49247572016-07-13 Integrated quantitative proteomic and transcriptomic analysis of lung tumor and control tissue: a lung cancer showcase Tenzer, Stefan Leidinger, Petra Backes, Christina Huwer, Hanno Hildebrandt, Andreas Lenhof, Hans-Peter Wesse, Tanja Franke, Andre Meese, Eckart Keller, Andreas Oncotarget Research Paper Proteomics analysis of paired cancer and control tissue can be applied to investigate pathological processes in tumors. Advancements in data-independent acquisition mass spectrometry allow for highly reproducible quantitative analysis of complex proteomic patterns. Optimized sample preparation workflows enable integrative multi-omics studies from the same tissue specimens. We performed ion mobility enhanced, data-independent acquisition MS to characterize the proteome of 21 lung tumor tissues including adenocarcinoma and squamous cell carcinoma (SCC) as compared to control lung tissues of the same patient each. Transcriptomic data were generated for the same specimens. The quantitative proteomic patterns and mRNA abundances were subsequently analyzed using systems biology approaches. We report a significantly (p = 0.0001) larger repertoire of proteins in cancer tissues. 12 proteins were higher in all tumor tissues as compared to matching control tissues. Three proteins, CAV1, CAV2, and RAGE, were vice versa higher in all controls. We also identified characteristic SCC and adenocarcinoma protein patterns. Principal Component Analysis provided evidence that not only cancer from control tissue but also tissue from adenocarcinoma and SCC can be differentiated. Transcriptomic levels of key proteins measured from the same matched tissue samples correlated with the observed protein patterns. The applied study set-up with paired lung tissue specimens of which different omics are measured, is generally suited for an integrated multi-omics analysis. Impact Journals LLC 2016-02-22 /pmc/articles/PMC4924757/ /pubmed/26930711 http://dx.doi.org/10.18632/oncotarget.7562 Text en Copyright: © 2016 Tenzer et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Tenzer, Stefan
Leidinger, Petra
Backes, Christina
Huwer, Hanno
Hildebrandt, Andreas
Lenhof, Hans-Peter
Wesse, Tanja
Franke, Andre
Meese, Eckart
Keller, Andreas
Integrated quantitative proteomic and transcriptomic analysis of lung tumor and control tissue: a lung cancer showcase
title Integrated quantitative proteomic and transcriptomic analysis of lung tumor and control tissue: a lung cancer showcase
title_full Integrated quantitative proteomic and transcriptomic analysis of lung tumor and control tissue: a lung cancer showcase
title_fullStr Integrated quantitative proteomic and transcriptomic analysis of lung tumor and control tissue: a lung cancer showcase
title_full_unstemmed Integrated quantitative proteomic and transcriptomic analysis of lung tumor and control tissue: a lung cancer showcase
title_short Integrated quantitative proteomic and transcriptomic analysis of lung tumor and control tissue: a lung cancer showcase
title_sort integrated quantitative proteomic and transcriptomic analysis of lung tumor and control tissue: a lung cancer showcase
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4924757/
https://www.ncbi.nlm.nih.gov/pubmed/26930711
http://dx.doi.org/10.18632/oncotarget.7562
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