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Differential Proteomic Analysis of Human Saliva using Tandem Mass Tags Quantification for Gastric Cancer Detection

Novel biomarkers and non-invasive diagnostic methods are urgently needed for the screening of gastric cancer to reduce its high mortality. We employed quantitative proteomics approach to develop discriminatory biomarker signatures from human saliva for the detection of gastric cancer. Salivary prote...

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Autores principales: Xiao, Hua, Zhang, Yan, Kim, Yong, Kim, Sung, Kim, Jae Joon, Kim, Kyoung Mee, Yoshizawa, Janice, Fan, Liu-Yin, Cao, Cheng-Xi, Wong, David T. W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4766442/
https://www.ncbi.nlm.nih.gov/pubmed/26911362
http://dx.doi.org/10.1038/srep22165
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author Xiao, Hua
Zhang, Yan
Kim, Yong
Kim, Sung
Kim, Jae Joon
Kim, Kyoung Mee
Yoshizawa, Janice
Fan, Liu-Yin
Cao, Cheng-Xi
Wong, David T. W.
author_facet Xiao, Hua
Zhang, Yan
Kim, Yong
Kim, Sung
Kim, Jae Joon
Kim, Kyoung Mee
Yoshizawa, Janice
Fan, Liu-Yin
Cao, Cheng-Xi
Wong, David T. W.
author_sort Xiao, Hua
collection PubMed
description Novel biomarkers and non-invasive diagnostic methods are urgently needed for the screening of gastric cancer to reduce its high mortality. We employed quantitative proteomics approach to develop discriminatory biomarker signatures from human saliva for the detection of gastric cancer. Salivary proteins were analyzed and compared between gastric cancer patients and matched control subjects by using tandem mass tags (TMT) technology. More than 500 proteins were identified with quantification, and 48 of them showed significant difference expression (p < 0.05) between normal controls and gastric cancer patients, including 7 up-regulated proteins and 41 down-regulated proteins. Five proteins were selected for initial verification by ELISA and three were successfully verified, namely cystatin B (CSTB), triosephosphate isomerase (TPI1), and deleted in malignant brain tumors 1 protein (DMBT1). All three proteins could differentiate gastric cancer patients from normal control subjects, dramatically (p < 0.05). The combination of these three biomarkers could reach 85% sensitivity and 80% specificity for the detection of gastric cancer with accuracy of 0.93. This study provides the proof of concept of salivary biomarkers for the non-invasive detection of gastric cancer. It is highly encouraging to turn these biomarkers into an applicable clinical test after large scale validation.
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spelling pubmed-47664422016-03-02 Differential Proteomic Analysis of Human Saliva using Tandem Mass Tags Quantification for Gastric Cancer Detection Xiao, Hua Zhang, Yan Kim, Yong Kim, Sung Kim, Jae Joon Kim, Kyoung Mee Yoshizawa, Janice Fan, Liu-Yin Cao, Cheng-Xi Wong, David T. W. Sci Rep Article Novel biomarkers and non-invasive diagnostic methods are urgently needed for the screening of gastric cancer to reduce its high mortality. We employed quantitative proteomics approach to develop discriminatory biomarker signatures from human saliva for the detection of gastric cancer. Salivary proteins were analyzed and compared between gastric cancer patients and matched control subjects by using tandem mass tags (TMT) technology. More than 500 proteins were identified with quantification, and 48 of them showed significant difference expression (p < 0.05) between normal controls and gastric cancer patients, including 7 up-regulated proteins and 41 down-regulated proteins. Five proteins were selected for initial verification by ELISA and three were successfully verified, namely cystatin B (CSTB), triosephosphate isomerase (TPI1), and deleted in malignant brain tumors 1 protein (DMBT1). All three proteins could differentiate gastric cancer patients from normal control subjects, dramatically (p < 0.05). The combination of these three biomarkers could reach 85% sensitivity and 80% specificity for the detection of gastric cancer with accuracy of 0.93. This study provides the proof of concept of salivary biomarkers for the non-invasive detection of gastric cancer. It is highly encouraging to turn these biomarkers into an applicable clinical test after large scale validation. Nature Publishing Group 2016-02-25 /pmc/articles/PMC4766442/ /pubmed/26911362 http://dx.doi.org/10.1038/srep22165 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Xiao, Hua
Zhang, Yan
Kim, Yong
Kim, Sung
Kim, Jae Joon
Kim, Kyoung Mee
Yoshizawa, Janice
Fan, Liu-Yin
Cao, Cheng-Xi
Wong, David T. W.
Differential Proteomic Analysis of Human Saliva using Tandem Mass Tags Quantification for Gastric Cancer Detection
title Differential Proteomic Analysis of Human Saliva using Tandem Mass Tags Quantification for Gastric Cancer Detection
title_full Differential Proteomic Analysis of Human Saliva using Tandem Mass Tags Quantification for Gastric Cancer Detection
title_fullStr Differential Proteomic Analysis of Human Saliva using Tandem Mass Tags Quantification for Gastric Cancer Detection
title_full_unstemmed Differential Proteomic Analysis of Human Saliva using Tandem Mass Tags Quantification for Gastric Cancer Detection
title_short Differential Proteomic Analysis of Human Saliva using Tandem Mass Tags Quantification for Gastric Cancer Detection
title_sort differential proteomic analysis of human saliva using tandem mass tags quantification for gastric cancer detection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4766442/
https://www.ncbi.nlm.nih.gov/pubmed/26911362
http://dx.doi.org/10.1038/srep22165
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