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Study on plasma amino acids and piperonamide as potential diagnostic biomarkers of non-small cell lung cancer

BACKGROUND: The value of plasma threonine, cysteine, and piperonamide as diagnostic biomarkers for non-small cell lung cancer (NSCLC) has been rarely explored. The lack of a validation set containing confounders is common to most previous metabolomics studies. The purpose of this study was to explor...

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Autores principales: Zhang, Caifa, Wang, Yuanyuan, Cao, Yunfeng, Shi, Linyang, Wang, Ruonan, Sheng, Ningning, Wang, Qingjun, Zhu, Zhitu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9189173/
https://www.ncbi.nlm.nih.gov/pubmed/35706818
http://dx.doi.org/10.21037/tcr-22-865
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author Zhang, Caifa
Wang, Yuanyuan
Cao, Yunfeng
Shi, Linyang
Wang, Ruonan
Sheng, Ningning
Wang, Qingjun
Zhu, Zhitu
author_facet Zhang, Caifa
Wang, Yuanyuan
Cao, Yunfeng
Shi, Linyang
Wang, Ruonan
Sheng, Ningning
Wang, Qingjun
Zhu, Zhitu
author_sort Zhang, Caifa
collection PubMed
description BACKGROUND: The value of plasma threonine, cysteine, and piperonamide as diagnostic biomarkers for non-small cell lung cancer (NSCLC) has been rarely explored. The lack of a validation set containing confounders is common to most previous metabolomics studies. The purpose of this study was to explore and validate the value of plasma amino acids and piperonamide as diagnostic biomarkers for NSCLC using liquid chromatography-tandem mass spectrometry (LC-MS/MS). METHODS: A total of 250 participants were included in this study, including 167 patients with pathologically confirmed NSCLC and 83 healthy controls (HCs). These participants were divided into training set, validation set 1, and validation set 2 in chronological order and in a certain proportion. The plasma levels of 22 amino acids and 1 piperonamide in these pre-treatment NSCLC patients and HCs were measured by LC-MS/MS. Metabolic biomarkers were identified after multivariate analysis, univariate analysis, receiver operating characteristic (ROC) analysis. Furthermore, these biomarkers and transcriptomic data were subjected to joint pathway analysis. RESULTS: The area under the ROC curve (AUC) values for threonine, piperonamide, arginine, alanine, cysteine, methionine, and histidine in the integrated data set were 0.911, 0.848, 0.909, 0.869, 0.786, 0.597 and 0.637, respectively. This panel composed of these 7 metabolites showed good diagnostic capability for NSCLC (the AUC of this diagnostic panel in each data set was greater than 0.9). The specificity of this diagnostic panel in validation set 2, which included confounders, was 0.970, similar to that of the other datasets. The presence of confounding factors had little effect on the diagnostic accuracy of this panel. The ROC analysis of this diagnostic panel between all stage I NSCLC patients and HCs showed AUC, sensitivity, and specificity of 1.000, 1.000, and 0.988, respectively. Moreover, PSAT1, SHMT2, AOC3, and MAOB were found to be involved in the metabolism of threonine and cysteine. CONCLUSIONS: Plasma amino acids and piperonamide have potential as diagnostic biomarkers in NSCLC. This metabolic biomarker panel appears useful for the diagnosis and screening of NSCLC. In addition, metabolomic and transcriptomic integration pathway analysis may help elucidate the mechanism of NSCLC occurrence and development and even reveal new treatment vulnerabilities.
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spelling pubmed-91891732022-06-14 Study on plasma amino acids and piperonamide as potential diagnostic biomarkers of non-small cell lung cancer Zhang, Caifa Wang, Yuanyuan Cao, Yunfeng Shi, Linyang Wang, Ruonan Sheng, Ningning Wang, Qingjun Zhu, Zhitu Transl Cancer Res Original Article BACKGROUND: The value of plasma threonine, cysteine, and piperonamide as diagnostic biomarkers for non-small cell lung cancer (NSCLC) has been rarely explored. The lack of a validation set containing confounders is common to most previous metabolomics studies. The purpose of this study was to explore and validate the value of plasma amino acids and piperonamide as diagnostic biomarkers for NSCLC using liquid chromatography-tandem mass spectrometry (LC-MS/MS). METHODS: A total of 250 participants were included in this study, including 167 patients with pathologically confirmed NSCLC and 83 healthy controls (HCs). These participants were divided into training set, validation set 1, and validation set 2 in chronological order and in a certain proportion. The plasma levels of 22 amino acids and 1 piperonamide in these pre-treatment NSCLC patients and HCs were measured by LC-MS/MS. Metabolic biomarkers were identified after multivariate analysis, univariate analysis, receiver operating characteristic (ROC) analysis. Furthermore, these biomarkers and transcriptomic data were subjected to joint pathway analysis. RESULTS: The area under the ROC curve (AUC) values for threonine, piperonamide, arginine, alanine, cysteine, methionine, and histidine in the integrated data set were 0.911, 0.848, 0.909, 0.869, 0.786, 0.597 and 0.637, respectively. This panel composed of these 7 metabolites showed good diagnostic capability for NSCLC (the AUC of this diagnostic panel in each data set was greater than 0.9). The specificity of this diagnostic panel in validation set 2, which included confounders, was 0.970, similar to that of the other datasets. The presence of confounding factors had little effect on the diagnostic accuracy of this panel. The ROC analysis of this diagnostic panel between all stage I NSCLC patients and HCs showed AUC, sensitivity, and specificity of 1.000, 1.000, and 0.988, respectively. Moreover, PSAT1, SHMT2, AOC3, and MAOB were found to be involved in the metabolism of threonine and cysteine. CONCLUSIONS: Plasma amino acids and piperonamide have potential as diagnostic biomarkers in NSCLC. This metabolic biomarker panel appears useful for the diagnosis and screening of NSCLC. In addition, metabolomic and transcriptomic integration pathway analysis may help elucidate the mechanism of NSCLC occurrence and development and even reveal new treatment vulnerabilities. AME Publishing Company 2022-05 /pmc/articles/PMC9189173/ /pubmed/35706818 http://dx.doi.org/10.21037/tcr-22-865 Text en 2022 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Original Article
Zhang, Caifa
Wang, Yuanyuan
Cao, Yunfeng
Shi, Linyang
Wang, Ruonan
Sheng, Ningning
Wang, Qingjun
Zhu, Zhitu
Study on plasma amino acids and piperonamide as potential diagnostic biomarkers of non-small cell lung cancer
title Study on plasma amino acids and piperonamide as potential diagnostic biomarkers of non-small cell lung cancer
title_full Study on plasma amino acids and piperonamide as potential diagnostic biomarkers of non-small cell lung cancer
title_fullStr Study on plasma amino acids and piperonamide as potential diagnostic biomarkers of non-small cell lung cancer
title_full_unstemmed Study on plasma amino acids and piperonamide as potential diagnostic biomarkers of non-small cell lung cancer
title_short Study on plasma amino acids and piperonamide as potential diagnostic biomarkers of non-small cell lung cancer
title_sort study on plasma amino acids and piperonamide as potential diagnostic biomarkers of non-small cell lung cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9189173/
https://www.ncbi.nlm.nih.gov/pubmed/35706818
http://dx.doi.org/10.21037/tcr-22-865
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