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Translational Proteomic Approach for Cholangiocarcinoma Biomarker Discovery, Validation, and Multiplex Assay Development: A Pilot Study

Cholangiocarcinoma (CCA) is a highly lethal disease because most patients are asymptomatic until they progress to advanced stages. Current CCA diagnosis relies on clinical imaging tests and tissue biopsy, while specific CCA biomarkers are still lacking. This study employed a translational proteomic...

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Autores principales: Watcharatanyatip, Kamolwan, Chutipongtanate, Somchai, Chokchaichamnankit, Daranee, Weeraphan, Churat, Mingkwan, Kanokwan, Luevisadpibul, Virat, Newburg, David S., Morrow, Ardythe L., Svasti, Jisnuson, Srisomsap, Chantragan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9501115/
https://www.ncbi.nlm.nih.gov/pubmed/36144640
http://dx.doi.org/10.3390/molecules27185904
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author Watcharatanyatip, Kamolwan
Chutipongtanate, Somchai
Chokchaichamnankit, Daranee
Weeraphan, Churat
Mingkwan, Kanokwan
Luevisadpibul, Virat
Newburg, David S.
Morrow, Ardythe L.
Svasti, Jisnuson
Srisomsap, Chantragan
author_facet Watcharatanyatip, Kamolwan
Chutipongtanate, Somchai
Chokchaichamnankit, Daranee
Weeraphan, Churat
Mingkwan, Kanokwan
Luevisadpibul, Virat
Newburg, David S.
Morrow, Ardythe L.
Svasti, Jisnuson
Srisomsap, Chantragan
author_sort Watcharatanyatip, Kamolwan
collection PubMed
description Cholangiocarcinoma (CCA) is a highly lethal disease because most patients are asymptomatic until they progress to advanced stages. Current CCA diagnosis relies on clinical imaging tests and tissue biopsy, while specific CCA biomarkers are still lacking. This study employed a translational proteomic approach for the discovery, validation, and development of a multiplex CCA biomarker assay. In the discovery phase, label-free proteomic quantitation was performed on nine pooled plasma specimens derived from nine CCA patients, nine disease controls (DC), and nine normal individuals. Seven proteins (S100A9, AACT, AFM, and TAOK3 from proteomic analysis, and NGAL, PSMA3, and AMBP from previous literature) were selected as the biomarker candidates. In the validation phase, enzyme-linked immunosorbent assays (ELISAs) were applied to measure the plasma levels of the seven candidate proteins from 63 participants: 26 CCA patients, 17 DC, and 20 normal individuals. Four proteins, S100A9, AACT, NGAL, and PSMA3, were significantly increased in the CCA group. To generate the multiplex biomarker assays, nine machine learning models were trained on the plasma dynamics of all seven candidates (All-7 panel) or the four significant markers (Sig-4 panel) from 45 of the 63 participants (70%). The best-performing models were tested on the unseen values from the remaining 18 (30%) of the 63 participants. Very strong predictive performances for CCA diagnosis were obtained from the All-7 panel using a support vector machine with linear classification (AUC = 0.96; 95% CI 0.88–1.00) and the Sig-4 panel using partial least square analysis (AUC = 0.94; 95% CI 0.82–1.00). This study supports the use of the composite plasma biomarkers measured by clinically compatible ELISAs coupled with machine learning models to identify individuals at risk of CCA. The All-7 and Sig-4 assays for CCA diagnosis should be further validated in an independent prospective blinded clinical study.
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spelling pubmed-95011152022-09-24 Translational Proteomic Approach for Cholangiocarcinoma Biomarker Discovery, Validation, and Multiplex Assay Development: A Pilot Study Watcharatanyatip, Kamolwan Chutipongtanate, Somchai Chokchaichamnankit, Daranee Weeraphan, Churat Mingkwan, Kanokwan Luevisadpibul, Virat Newburg, David S. Morrow, Ardythe L. Svasti, Jisnuson Srisomsap, Chantragan Molecules Article Cholangiocarcinoma (CCA) is a highly lethal disease because most patients are asymptomatic until they progress to advanced stages. Current CCA diagnosis relies on clinical imaging tests and tissue biopsy, while specific CCA biomarkers are still lacking. This study employed a translational proteomic approach for the discovery, validation, and development of a multiplex CCA biomarker assay. In the discovery phase, label-free proteomic quantitation was performed on nine pooled plasma specimens derived from nine CCA patients, nine disease controls (DC), and nine normal individuals. Seven proteins (S100A9, AACT, AFM, and TAOK3 from proteomic analysis, and NGAL, PSMA3, and AMBP from previous literature) were selected as the biomarker candidates. In the validation phase, enzyme-linked immunosorbent assays (ELISAs) were applied to measure the plasma levels of the seven candidate proteins from 63 participants: 26 CCA patients, 17 DC, and 20 normal individuals. Four proteins, S100A9, AACT, NGAL, and PSMA3, were significantly increased in the CCA group. To generate the multiplex biomarker assays, nine machine learning models were trained on the plasma dynamics of all seven candidates (All-7 panel) or the four significant markers (Sig-4 panel) from 45 of the 63 participants (70%). The best-performing models were tested on the unseen values from the remaining 18 (30%) of the 63 participants. Very strong predictive performances for CCA diagnosis were obtained from the All-7 panel using a support vector machine with linear classification (AUC = 0.96; 95% CI 0.88–1.00) and the Sig-4 panel using partial least square analysis (AUC = 0.94; 95% CI 0.82–1.00). This study supports the use of the composite plasma biomarkers measured by clinically compatible ELISAs coupled with machine learning models to identify individuals at risk of CCA. The All-7 and Sig-4 assays for CCA diagnosis should be further validated in an independent prospective blinded clinical study. MDPI 2022-09-11 /pmc/articles/PMC9501115/ /pubmed/36144640 http://dx.doi.org/10.3390/molecules27185904 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Watcharatanyatip, Kamolwan
Chutipongtanate, Somchai
Chokchaichamnankit, Daranee
Weeraphan, Churat
Mingkwan, Kanokwan
Luevisadpibul, Virat
Newburg, David S.
Morrow, Ardythe L.
Svasti, Jisnuson
Srisomsap, Chantragan
Translational Proteomic Approach for Cholangiocarcinoma Biomarker Discovery, Validation, and Multiplex Assay Development: A Pilot Study
title Translational Proteomic Approach for Cholangiocarcinoma Biomarker Discovery, Validation, and Multiplex Assay Development: A Pilot Study
title_full Translational Proteomic Approach for Cholangiocarcinoma Biomarker Discovery, Validation, and Multiplex Assay Development: A Pilot Study
title_fullStr Translational Proteomic Approach for Cholangiocarcinoma Biomarker Discovery, Validation, and Multiplex Assay Development: A Pilot Study
title_full_unstemmed Translational Proteomic Approach for Cholangiocarcinoma Biomarker Discovery, Validation, and Multiplex Assay Development: A Pilot Study
title_short Translational Proteomic Approach for Cholangiocarcinoma Biomarker Discovery, Validation, and Multiplex Assay Development: A Pilot Study
title_sort translational proteomic approach for cholangiocarcinoma biomarker discovery, validation, and multiplex assay development: a pilot study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9501115/
https://www.ncbi.nlm.nih.gov/pubmed/36144640
http://dx.doi.org/10.3390/molecules27185904
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