Serum Metabolomic Profiles for Distinguishing Lung Cancer From Pulmonary Tuberculosis : Identification of Rapid and Noninvasive Biomarker
© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissionsoup.com..
BACKGROUND: Pulmonary tuberculosis (PTB) and lung cancer (LC) have similar clinical symptoms and atypical imaging findings, which are easily misdiagnosed. There is an urgent need for a noninvasive and accurate biomarker to distinguish LC from PTB.
METHODS: A total of 694 subjects were enrolled and divided into discovery set (n = 122), identification set (n = 214), and validation set (n = 358). Metabolites were identified by multivariate and univariate analyses. Receiver operating characteristic curve were used to evaluate the diagnostic efficacy of biomarkers.
RESULTS: Seven metabolites were identified and validated. Phenylalanylphenylalanine for distinguishing LC from PTB yielded an area under the curve of 0.89, sensitivity of 71%, and specificity of 92%. It also showed good diagnostic abilities in discovery set and identification set. Compared with that in healthy volunteers (median [interquartile range], 1.57 [1.01, 2.34] μg/mL), it was elevated in LC (4.76 [2.74, 7.08] μg/mL; ratio of median, [ROM] = 3.03, P < .01) and reduced in PTB (1.06 [0.51, 2.09] μg/mL; ROM = 0.68, P < .05).
CONCLUSIONS: The metabolomic profile of LC and PTB was described and a key biomarker identified. We produced a rapid and noninvasive method to supplement existing clinical diagnostic examinations for distinguishing LC from PTB.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:228 |
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| Enthalten in: |
The Journal of infectious diseases - 228(2023), 9 vom: 02. Nov., Seite 1154-1165 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Chen, Siyu [VerfasserIn] |
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| Links: |
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| Themen: |
Biomarker |
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| Anmerkungen: |
Date Completed 09.11.2023 Date Revised 14.11.2023 published: Print Citation Status MEDLINE |
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| doi: |
10.1093/infdis/jiad175 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM35748763X |
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| 245 | 1 | 0 | |a Serum Metabolomic Profiles for Distinguishing Lung Cancer From Pulmonary Tuberculosis |b Identification of Rapid and Noninvasive Biomarker |
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| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissionsoup.com. | ||
| 520 | |a BACKGROUND: Pulmonary tuberculosis (PTB) and lung cancer (LC) have similar clinical symptoms and atypical imaging findings, which are easily misdiagnosed. There is an urgent need for a noninvasive and accurate biomarker to distinguish LC from PTB | ||
| 520 | |a METHODS: A total of 694 subjects were enrolled and divided into discovery set (n = 122), identification set (n = 214), and validation set (n = 358). Metabolites were identified by multivariate and univariate analyses. Receiver operating characteristic curve were used to evaluate the diagnostic efficacy of biomarkers | ||
| 520 | |a RESULTS: Seven metabolites were identified and validated. Phenylalanylphenylalanine for distinguishing LC from PTB yielded an area under the curve of 0.89, sensitivity of 71%, and specificity of 92%. It also showed good diagnostic abilities in discovery set and identification set. Compared with that in healthy volunteers (median [interquartile range], 1.57 [1.01, 2.34] μg/mL), it was elevated in LC (4.76 [2.74, 7.08] μg/mL; ratio of median, [ROM] = 3.03, P < .01) and reduced in PTB (1.06 [0.51, 2.09] μg/mL; ROM = 0.68, P < .05) | ||
| 520 | |a CONCLUSIONS: The metabolomic profile of LC and PTB was described and a key biomarker identified. We produced a rapid and noninvasive method to supplement existing clinical diagnostic examinations for distinguishing LC from PTB | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a biomarker | |
| 650 | 4 | |a diagnosis | |
| 650 | 4 | |a lung cancer | |
| 650 | 4 | |a metabolomics | |
| 650 | 4 | |a pulmonary tuberculosis | |
| 650 | 7 | |a Biomarkers |2 NLM | |
| 700 | 1 | |a Li, Chunyan |e verfasserin |4 aut | |
| 700 | 1 | |a Qin, Zhonghua |e verfasserin |4 aut | |
| 700 | 1 | |a Song, Lili |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Shiyuan |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Chongxiang |e verfasserin |4 aut | |
| 700 | 1 | |a Zhuang, Pengwei |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Yuming |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Bin |e verfasserin |4 aut | |
| 700 | 1 | |a Ning, Li |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Yubo |e verfasserin |4 aut | |
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