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Data from quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissues using high resolution mass spectrometry

Lung cancer is the leading cause of preventable death globally and is broadly classified into adenocarcinoma and squamous cell carcinoma. In this study, we carried out mass spectrometry based quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissue by employi...

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Autores principales: Khan, Aafaque Ahmad, Mangalaparthi, Kiran Kumar, Advani, Jayshree, Prasad, T.S. Keshava, Gowda, Harsha, Jain, Deepali, Chatterjee, Aditi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6141215/
https://www.ncbi.nlm.nih.gov/pubmed/30229035
http://dx.doi.org/10.1016/j.dib.2018.06.035
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author Khan, Aafaque Ahmad
Mangalaparthi, Kiran Kumar
Advani, Jayshree
Prasad, T.S. Keshava
Gowda, Harsha
Jain, Deepali
Chatterjee, Aditi
author_facet Khan, Aafaque Ahmad
Mangalaparthi, Kiran Kumar
Advani, Jayshree
Prasad, T.S. Keshava
Gowda, Harsha
Jain, Deepali
Chatterjee, Aditi
author_sort Khan, Aafaque Ahmad
collection PubMed
description Lung cancer is the leading cause of preventable death globally and is broadly classified into adenocarcinoma and squamous cell carcinoma. In this study, we carried out mass spectrometry based quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissue by employing the isobaric tags for relative and absolute quantitation (iTRAQ) approach. Proteomic data analyzed using SEQUEST algorithm resulted in identification of 25,998 peptides corresponding to 4342 proteins of which 610 proteins were differentially expressed (≥ 2-fold) between adenocarcinoma and squamous cell carcinoma. These differentially expressed proteins were further classified by gene ontology for their localization and biological processes. Pathway analysis of differentially expressed proteins revealed distinct alterations in networks and pathways in both adenocarcinoma and squamous cell carcinoma. We identified a subset of proteins that show inverse expression pattern between lung adenocarcinoma and squamous cell carcinoma. Such proteins may serve as potential markers to distinguish between the two subtypes. Mass spectrometric data generated in this study was submitted to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the dataset identifier PXD008700.
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spelling pubmed-61412152018-09-18 Data from quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissues using high resolution mass spectrometry Khan, Aafaque Ahmad Mangalaparthi, Kiran Kumar Advani, Jayshree Prasad, T.S. Keshava Gowda, Harsha Jain, Deepali Chatterjee, Aditi Data Brief Proteomics and Biochemistry Lung cancer is the leading cause of preventable death globally and is broadly classified into adenocarcinoma and squamous cell carcinoma. In this study, we carried out mass spectrometry based quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissue by employing the isobaric tags for relative and absolute quantitation (iTRAQ) approach. Proteomic data analyzed using SEQUEST algorithm resulted in identification of 25,998 peptides corresponding to 4342 proteins of which 610 proteins were differentially expressed (≥ 2-fold) between adenocarcinoma and squamous cell carcinoma. These differentially expressed proteins were further classified by gene ontology for their localization and biological processes. Pathway analysis of differentially expressed proteins revealed distinct alterations in networks and pathways in both adenocarcinoma and squamous cell carcinoma. We identified a subset of proteins that show inverse expression pattern between lung adenocarcinoma and squamous cell carcinoma. Such proteins may serve as potential markers to distinguish between the two subtypes. Mass spectrometric data generated in this study was submitted to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the dataset identifier PXD008700. Elsevier 2018-06-22 /pmc/articles/PMC6141215/ /pubmed/30229035 http://dx.doi.org/10.1016/j.dib.2018.06.035 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Proteomics and Biochemistry
Khan, Aafaque Ahmad
Mangalaparthi, Kiran Kumar
Advani, Jayshree
Prasad, T.S. Keshava
Gowda, Harsha
Jain, Deepali
Chatterjee, Aditi
Data from quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissues using high resolution mass spectrometry
title Data from quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissues using high resolution mass spectrometry
title_full Data from quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissues using high resolution mass spectrometry
title_fullStr Data from quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissues using high resolution mass spectrometry
title_full_unstemmed Data from quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissues using high resolution mass spectrometry
title_short Data from quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissues using high resolution mass spectrometry
title_sort data from quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissues using high resolution mass spectrometry
topic Proteomics and Biochemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6141215/
https://www.ncbi.nlm.nih.gov/pubmed/30229035
http://dx.doi.org/10.1016/j.dib.2018.06.035
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