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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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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. |
format | Online Article Text |
id | pubmed-6141215 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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