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Pan-Cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics
The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) provides unique opportunities for cancer target discovery using protein expression. Proteomics data from CPTAC tumor types have been primarily generated using a multiplex tandem mass tag (TMT) approach, which is des...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Biochemistry and Molecular Biology
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494184/ https://www.ncbi.nlm.nih.gov/pubmed/37517589 http://dx.doi.org/10.1016/j.mcpro.2023.100626 |
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author | Wang, Jixin Yu, Wen D’Anna, Rachel Przybyla, Anna Wilson, Matt Sung, Matthew Bullen, John Hurt, Elaine D’Angelo, Gina Sidders, Ben Lai, Zhongwu Zhong, Wenyan |
author_facet | Wang, Jixin Yu, Wen D’Anna, Rachel Przybyla, Anna Wilson, Matt Sung, Matthew Bullen, John Hurt, Elaine D’Angelo, Gina Sidders, Ben Lai, Zhongwu Zhong, Wenyan |
author_sort | Wang, Jixin |
collection | PubMed |
description | The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) provides unique opportunities for cancer target discovery using protein expression. Proteomics data from CPTAC tumor types have been primarily generated using a multiplex tandem mass tag (TMT) approach, which is designed to provide protein quantification relative to reference samples. However, relative protein expression data are suboptimal for prioritization of targets within a tissue type, which requires additional reprocessing of the original proteomics data to derive absolute quantitation estimation. We evaluated the feasibility of using differential protein analysis coupled with intensity-based absolute quantification (iBAQ) to identify tumor-enriched and highly expressed cell surface antigens, employing tandem mass tag (TMT) proteomics data from CPTAC. Absolute quantification derived from TMT proteomics data was highly correlated with that of label-free proteomics data from the CPTAC colon adenocarcinoma cohort, which contains proteomics data measured by both approaches. We validated the TMT-iBAQ approach by comparing the iBAQ value to the receptor density value of HER2 and TROP2 measured by flow cytometry in about 30 selected breast and lung cancer cell lines from the Cancer Cell Line Encyclopedia. Collections of these tumor-enriched and highly expressed cell surface antigens could serve as a valuable resource for the development of cancer therapeutics, including antibody–drug conjugates and immunotherapeutic agents. |
format | Online Article Text |
id | pubmed-10494184 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Society for Biochemistry and Molecular Biology |
record_format | MEDLINE/PubMed |
spelling | pubmed-104941842023-09-12 Pan-Cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics Wang, Jixin Yu, Wen D’Anna, Rachel Przybyla, Anna Wilson, Matt Sung, Matthew Bullen, John Hurt, Elaine D’Angelo, Gina Sidders, Ben Lai, Zhongwu Zhong, Wenyan Mol Cell Proteomics Technological Innovation and Resources The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) provides unique opportunities for cancer target discovery using protein expression. Proteomics data from CPTAC tumor types have been primarily generated using a multiplex tandem mass tag (TMT) approach, which is designed to provide protein quantification relative to reference samples. However, relative protein expression data are suboptimal for prioritization of targets within a tissue type, which requires additional reprocessing of the original proteomics data to derive absolute quantitation estimation. We evaluated the feasibility of using differential protein analysis coupled with intensity-based absolute quantification (iBAQ) to identify tumor-enriched and highly expressed cell surface antigens, employing tandem mass tag (TMT) proteomics data from CPTAC. Absolute quantification derived from TMT proteomics data was highly correlated with that of label-free proteomics data from the CPTAC colon adenocarcinoma cohort, which contains proteomics data measured by both approaches. We validated the TMT-iBAQ approach by comparing the iBAQ value to the receptor density value of HER2 and TROP2 measured by flow cytometry in about 30 selected breast and lung cancer cell lines from the Cancer Cell Line Encyclopedia. Collections of these tumor-enriched and highly expressed cell surface antigens could serve as a valuable resource for the development of cancer therapeutics, including antibody–drug conjugates and immunotherapeutic agents. American Society for Biochemistry and Molecular Biology 2023-07-28 /pmc/articles/PMC10494184/ /pubmed/37517589 http://dx.doi.org/10.1016/j.mcpro.2023.100626 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Technological Innovation and Resources Wang, Jixin Yu, Wen D’Anna, Rachel Przybyla, Anna Wilson, Matt Sung, Matthew Bullen, John Hurt, Elaine D’Angelo, Gina Sidders, Ben Lai, Zhongwu Zhong, Wenyan Pan-Cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics |
title | Pan-Cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics |
title_full | Pan-Cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics |
title_fullStr | Pan-Cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics |
title_full_unstemmed | Pan-Cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics |
title_short | Pan-Cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics |
title_sort | pan-cancer proteomics analysis to identify tumor-enriched and highly expressed cell surface antigens as potential targets for cancer therapeutics |
topic | Technological Innovation and Resources |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494184/ https://www.ncbi.nlm.nih.gov/pubmed/37517589 http://dx.doi.org/10.1016/j.mcpro.2023.100626 |
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