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TP53 mutation prevalence in normal airway epithelium as a biomarker for lung cancer risk

BACKGROUND: There is a need for biomarkers that improve accuracy compared with current demographic risk indices to detect individuals at the highest lung cancer risk. Improved risk determination will enable more effective lung cancer screening and better stratification of lung nodules into high or l...

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Autores principales: Craig, Daniel J., Crawford, Erin L., Chen, Heidi, Grogan, Eric L., Deppen, Steven A., Morrison, Thomas, Antic, Sanja L., Massion, Pierre P., Willey, James C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464352/
https://www.ncbi.nlm.nih.gov/pubmed/37612638
http://dx.doi.org/10.1186/s12885-023-11266-7
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author Craig, Daniel J.
Crawford, Erin L.
Chen, Heidi
Grogan, Eric L.
Deppen, Steven A.
Morrison, Thomas
Antic, Sanja L.
Massion, Pierre P.
Willey, James C.
author_facet Craig, Daniel J.
Crawford, Erin L.
Chen, Heidi
Grogan, Eric L.
Deppen, Steven A.
Morrison, Thomas
Antic, Sanja L.
Massion, Pierre P.
Willey, James C.
author_sort Craig, Daniel J.
collection PubMed
description BACKGROUND: There is a need for biomarkers that improve accuracy compared with current demographic risk indices to detect individuals at the highest lung cancer risk. Improved risk determination will enable more effective lung cancer screening and better stratification of lung nodules into high or low-risk category. We previously reported discovery of a biomarker for lung cancer risk characterized by increased prevalence of TP53 somatic mutations in airway epithelial cells (AEC). Here we present results from a validation study in an independent retrospective case–control cohort. METHODS: Targeted next generation sequencing was used to identify mutations within three TP53 exons spanning 193 base pairs in AEC genomic DNA. RESULTS: TP53 mutation prevalence was associated with cancer status (P < 0.001). The lung cancer detection receiver operator characteristic (ROC) area under the curve (AUC) for the TP53 biomarker was 0.845 (95% confidence limits 0.749–0.942). In contrast, TP53 mutation prevalence was not significantly associated with age or smoking pack-years. The combination of TP53 mutation prevalence with PLCO(M2012) risk score had an ROC AUC of 0.916 (0.846–0.986) and this was significantly higher than that for either factor alone (P < 0.03). CONCLUSIONS: These results support the validity of the TP53 mutation prevalence biomarker and justify taking additional steps to assess this biomarker in AEC specimens from a prospective cohort and in matched nasal brushing specimens as a potential non-invasive surrogate specimen. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11266-7.
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spelling pubmed-104643522023-08-30 TP53 mutation prevalence in normal airway epithelium as a biomarker for lung cancer risk Craig, Daniel J. Crawford, Erin L. Chen, Heidi Grogan, Eric L. Deppen, Steven A. Morrison, Thomas Antic, Sanja L. Massion, Pierre P. Willey, James C. BMC Cancer Research BACKGROUND: There is a need for biomarkers that improve accuracy compared with current demographic risk indices to detect individuals at the highest lung cancer risk. Improved risk determination will enable more effective lung cancer screening and better stratification of lung nodules into high or low-risk category. We previously reported discovery of a biomarker for lung cancer risk characterized by increased prevalence of TP53 somatic mutations in airway epithelial cells (AEC). Here we present results from a validation study in an independent retrospective case–control cohort. METHODS: Targeted next generation sequencing was used to identify mutations within three TP53 exons spanning 193 base pairs in AEC genomic DNA. RESULTS: TP53 mutation prevalence was associated with cancer status (P < 0.001). The lung cancer detection receiver operator characteristic (ROC) area under the curve (AUC) for the TP53 biomarker was 0.845 (95% confidence limits 0.749–0.942). In contrast, TP53 mutation prevalence was not significantly associated with age or smoking pack-years. The combination of TP53 mutation prevalence with PLCO(M2012) risk score had an ROC AUC of 0.916 (0.846–0.986) and this was significantly higher than that for either factor alone (P < 0.03). CONCLUSIONS: These results support the validity of the TP53 mutation prevalence biomarker and justify taking additional steps to assess this biomarker in AEC specimens from a prospective cohort and in matched nasal brushing specimens as a potential non-invasive surrogate specimen. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11266-7. BioMed Central 2023-08-23 /pmc/articles/PMC10464352/ /pubmed/37612638 http://dx.doi.org/10.1186/s12885-023-11266-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Craig, Daniel J.
Crawford, Erin L.
Chen, Heidi
Grogan, Eric L.
Deppen, Steven A.
Morrison, Thomas
Antic, Sanja L.
Massion, Pierre P.
Willey, James C.
TP53 mutation prevalence in normal airway epithelium as a biomarker for lung cancer risk
title TP53 mutation prevalence in normal airway epithelium as a biomarker for lung cancer risk
title_full TP53 mutation prevalence in normal airway epithelium as a biomarker for lung cancer risk
title_fullStr TP53 mutation prevalence in normal airway epithelium as a biomarker for lung cancer risk
title_full_unstemmed TP53 mutation prevalence in normal airway epithelium as a biomarker for lung cancer risk
title_short TP53 mutation prevalence in normal airway epithelium as a biomarker for lung cancer risk
title_sort tp53 mutation prevalence in normal airway epithelium as a biomarker for lung cancer risk
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464352/
https://www.ncbi.nlm.nih.gov/pubmed/37612638
http://dx.doi.org/10.1186/s12885-023-11266-7
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