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Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis
Gastric cancer (GC) is known as a top malignant type of tumors worldwide. Despite the recent decrease in mortality rates, the prognosis remains poor. Therefore, it is necessary to find novel biomarkers with early diagnostic value for GC. In this study, we present a large-scale proteomic analysis of...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8377014/ https://www.ncbi.nlm.nih.gov/pubmed/33607292 http://dx.doi.org/10.1016/j.gpb.2020.06.012 |
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author | Song, Yongxi Wang, Jun Sun, Jingxu Chen, Xiaowan Shi, Jinxin Wu, Zhonghua Yu, Dehao Zhang, Fei Wang, Zhenning |
author_facet | Song, Yongxi Wang, Jun Sun, Jingxu Chen, Xiaowan Shi, Jinxin Wu, Zhonghua Yu, Dehao Zhang, Fei Wang, Zhenning |
author_sort | Song, Yongxi |
collection | PubMed |
description | Gastric cancer (GC) is known as a top malignant type of tumors worldwide. Despite the recent decrease in mortality rates, the prognosis remains poor. Therefore, it is necessary to find novel biomarkers with early diagnostic value for GC. In this study, we present a large-scale proteomic analysis of 30 GC tissues and 30 matched healthy tissues using label-free global proteome profiling. Our results identified 537 differentially expressed proteins, including 280 upregulated and 257 downregulated proteins. The ingenuity pathway analysis (IPA) results indicated that the sirtuin signaling pathway was the most activated pathway in GC tissues whereas oxidative phosphorylation was the most inhibited. Moreover, the most activated molecular function was cellular movement, including tissue invasion by tumor cell lines. Based on IPA results, 15 hub proteins were screened. Using the receiver operating characteristic curve, most of hub proteins showed a high diagnostic power in distinguishing between tumors and healthy controls. A four-protein (ATP5B-ATP5O-NDUFB4-NDUFB8) diagnostic signature was built using a random forest model. The area under the curve (AUC) values of this model were 0.996 and 0.886 for the training and testing sets, respectively, suggesting that the four-protein signature has a high diagnostic power. This signature was further tested with independent datasets using plasma enzyme-linked immune sorbent assays, resulting in an AUC value of 0.778 for distinguishing GC tissues from healthy controls, and using immunohistochemical tissue microarray analysis, resulting in an AUC value of 0.805. In conclusion, this study identifies potential biomarkers and improves our understanding of the pathogenesis, providing novel therapeutic targets for GC. |
format | Online Article Text |
id | pubmed-8377014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-83770142021-08-24 Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis Song, Yongxi Wang, Jun Sun, Jingxu Chen, Xiaowan Shi, Jinxin Wu, Zhonghua Yu, Dehao Zhang, Fei Wang, Zhenning Genomics Proteomics Bioinformatics Original Research Gastric cancer (GC) is known as a top malignant type of tumors worldwide. Despite the recent decrease in mortality rates, the prognosis remains poor. Therefore, it is necessary to find novel biomarkers with early diagnostic value for GC. In this study, we present a large-scale proteomic analysis of 30 GC tissues and 30 matched healthy tissues using label-free global proteome profiling. Our results identified 537 differentially expressed proteins, including 280 upregulated and 257 downregulated proteins. The ingenuity pathway analysis (IPA) results indicated that the sirtuin signaling pathway was the most activated pathway in GC tissues whereas oxidative phosphorylation was the most inhibited. Moreover, the most activated molecular function was cellular movement, including tissue invasion by tumor cell lines. Based on IPA results, 15 hub proteins were screened. Using the receiver operating characteristic curve, most of hub proteins showed a high diagnostic power in distinguishing between tumors and healthy controls. A four-protein (ATP5B-ATP5O-NDUFB4-NDUFB8) diagnostic signature was built using a random forest model. The area under the curve (AUC) values of this model were 0.996 and 0.886 for the training and testing sets, respectively, suggesting that the four-protein signature has a high diagnostic power. This signature was further tested with independent datasets using plasma enzyme-linked immune sorbent assays, resulting in an AUC value of 0.778 for distinguishing GC tissues from healthy controls, and using immunohistochemical tissue microarray analysis, resulting in an AUC value of 0.805. In conclusion, this study identifies potential biomarkers and improves our understanding of the pathogenesis, providing novel therapeutic targets for GC. Elsevier 2020-12 2021-02-17 /pmc/articles/PMC8377014/ /pubmed/33607292 http://dx.doi.org/10.1016/j.gpb.2020.06.012 Text en © 2021 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China 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 | Original Research Song, Yongxi Wang, Jun Sun, Jingxu Chen, Xiaowan Shi, Jinxin Wu, Zhonghua Yu, Dehao Zhang, Fei Wang, Zhenning Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis |
title | Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis |
title_full | Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis |
title_fullStr | Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis |
title_full_unstemmed | Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis |
title_short | Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis |
title_sort | screening of potential biomarkers for gastric cancer with diagnostic value using label-free global proteome analysis |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8377014/ https://www.ncbi.nlm.nih.gov/pubmed/33607292 http://dx.doi.org/10.1016/j.gpb.2020.06.012 |
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