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Quantitative proteomics characterization of cancer biomarkers and treatment
Cancer accounted for 16% of all death worldwide in 2018. Significant progress has been made in understanding tumor occurrence, progression, diagnosis, treatment, and prognosis at the molecular level. However, genomics changes cannot truly reflect the state of protein activity in the body due to the...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Gene & Cell Therapy
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8142045/ https://www.ncbi.nlm.nih.gov/pubmed/34095463 http://dx.doi.org/10.1016/j.omto.2021.04.006 |
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author | Yang, Xiao-Li Shi, Yi Zhang, Dan-Dan Xin, Rui Deng, Jing Wu, Ting-Miao Wang, Hui-Min Wang, Pei-Yao Liu, Ji-Bin Li, Wen Ma, Yu-Shui Fu, Da |
author_facet | Yang, Xiao-Li Shi, Yi Zhang, Dan-Dan Xin, Rui Deng, Jing Wu, Ting-Miao Wang, Hui-Min Wang, Pei-Yao Liu, Ji-Bin Li, Wen Ma, Yu-Shui Fu, Da |
author_sort | Yang, Xiao-Li |
collection | PubMed |
description | Cancer accounted for 16% of all death worldwide in 2018. Significant progress has been made in understanding tumor occurrence, progression, diagnosis, treatment, and prognosis at the molecular level. However, genomics changes cannot truly reflect the state of protein activity in the body due to the poor correlation between genes and proteins. Quantitative proteomics, capable of quantifying the relatively different protein abundance in cancer patients, has been increasingly adopted in cancer research. Quantitative proteomics has great application potentials, including cancer diagnosis, personalized therapeutic drug selection, real-time therapeutic effects and toxicity evaluation, prognosis and drug resistance evaluation, and new therapeutic target discovery. In this review, the development, testing samples, and detection methods of quantitative proteomics are introduced. The biomarkers identified by quantitative proteomics for clinical diagnosis, prognosis, and drug resistance are reviewed. The challenges and prospects of quantitative proteomics for personalized medicine are also discussed. |
format | Online Article Text |
id | pubmed-8142045 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Society of Gene & Cell Therapy |
record_format | MEDLINE/PubMed |
spelling | pubmed-81420452021-06-03 Quantitative proteomics characterization of cancer biomarkers and treatment Yang, Xiao-Li Shi, Yi Zhang, Dan-Dan Xin, Rui Deng, Jing Wu, Ting-Miao Wang, Hui-Min Wang, Pei-Yao Liu, Ji-Bin Li, Wen Ma, Yu-Shui Fu, Da Mol Ther Oncolytics Review Cancer accounted for 16% of all death worldwide in 2018. Significant progress has been made in understanding tumor occurrence, progression, diagnosis, treatment, and prognosis at the molecular level. However, genomics changes cannot truly reflect the state of protein activity in the body due to the poor correlation between genes and proteins. Quantitative proteomics, capable of quantifying the relatively different protein abundance in cancer patients, has been increasingly adopted in cancer research. Quantitative proteomics has great application potentials, including cancer diagnosis, personalized therapeutic drug selection, real-time therapeutic effects and toxicity evaluation, prognosis and drug resistance evaluation, and new therapeutic target discovery. In this review, the development, testing samples, and detection methods of quantitative proteomics are introduced. The biomarkers identified by quantitative proteomics for clinical diagnosis, prognosis, and drug resistance are reviewed. The challenges and prospects of quantitative proteomics for personalized medicine are also discussed. American Society of Gene & Cell Therapy 2021-04-20 /pmc/articles/PMC8142045/ /pubmed/34095463 http://dx.doi.org/10.1016/j.omto.2021.04.006 Text en © 2021 The Author(s) https://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 | Review Yang, Xiao-Li Shi, Yi Zhang, Dan-Dan Xin, Rui Deng, Jing Wu, Ting-Miao Wang, Hui-Min Wang, Pei-Yao Liu, Ji-Bin Li, Wen Ma, Yu-Shui Fu, Da Quantitative proteomics characterization of cancer biomarkers and treatment |
title | Quantitative proteomics characterization of cancer biomarkers and treatment |
title_full | Quantitative proteomics characterization of cancer biomarkers and treatment |
title_fullStr | Quantitative proteomics characterization of cancer biomarkers and treatment |
title_full_unstemmed | Quantitative proteomics characterization of cancer biomarkers and treatment |
title_short | Quantitative proteomics characterization of cancer biomarkers and treatment |
title_sort | quantitative proteomics characterization of cancer biomarkers and treatment |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8142045/ https://www.ncbi.nlm.nih.gov/pubmed/34095463 http://dx.doi.org/10.1016/j.omto.2021.04.006 |
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