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Serum Metabolic Disturbances in Lung Cancer Investigated through an Elaborative NMR-Based Serum Metabolomics Approach
[Image: see text] Detection of metabolic disturbances in lung cancer (LC) has the potential to aid early diagnosis/prognosis and hence improve disease management strategies through reliable grading, staging, and determination of neoadjuvant status in LC. However, a majority of previous metabolomics...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8851899/ https://www.ncbi.nlm.nih.gov/pubmed/35187366 http://dx.doi.org/10.1021/acsomega.1c06941 |
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author | Singh, Anjana Prakash, Ved Gupta, Nikhil Kumar, Ashish Kant, Ravi Kumar, Dinesh |
author_facet | Singh, Anjana Prakash, Ved Gupta, Nikhil Kumar, Ashish Kant, Ravi Kumar, Dinesh |
author_sort | Singh, Anjana |
collection | PubMed |
description | [Image: see text] Detection of metabolic disturbances in lung cancer (LC) has the potential to aid early diagnosis/prognosis and hence improve disease management strategies through reliable grading, staging, and determination of neoadjuvant status in LC. However, a majority of previous metabolomics studies compare the normalized spectral features which not only provide ambiguous information but further limit the clinical translation of this information. Various such issues can be resolved by performing the concentration profiling of various metabolites with respect to formate as an internal reference using commercial software Chenomx. Continuing our efforts in this direction, the serum metabolic profiles were measured on 39 LC patients and 42 normal controls (NCs, comparable in age/sex) using high-field 800 MHz NMR spectroscopy and compared using multivariate statistical analysis tools to identify metabolic disturbances and metabolites of diagnostic potential. Partial least-squares discriminant analysis (PLS-DA) model revealed a distinct separation between LC and NC groups and resulted in excellent discriminatory ability with the area under the receiver-operating characteristic (AUROC) = 0.97 [95% CI = 0.89–1.00]. The metabolic features contributing to the differentiation of LC from NC samples were identified first using variable importance in projection (VIP) score analysis and then checked for their statistical significance (with p-value < 0.05) and diagnostic potential using the ROC curve analysis. The analysis revealed relevant metabolic disturbances associated with LC. Among various circulatory metabolites, six metabolites, including histidine, glutamine, glycine, threonine, alanine, and valine, were found to be of apposite diagnostic potential for clinical implications. These metabolic alterations indicated altered glucose metabolism, aberrant fatty acid synthesis, and augmented utilization of various amino acids including active glutaminolysis in LC. |
format | Online Article Text |
id | pubmed-8851899 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-88518992022-02-18 Serum Metabolic Disturbances in Lung Cancer Investigated through an Elaborative NMR-Based Serum Metabolomics Approach Singh, Anjana Prakash, Ved Gupta, Nikhil Kumar, Ashish Kant, Ravi Kumar, Dinesh ACS Omega [Image: see text] Detection of metabolic disturbances in lung cancer (LC) has the potential to aid early diagnosis/prognosis and hence improve disease management strategies through reliable grading, staging, and determination of neoadjuvant status in LC. However, a majority of previous metabolomics studies compare the normalized spectral features which not only provide ambiguous information but further limit the clinical translation of this information. Various such issues can be resolved by performing the concentration profiling of various metabolites with respect to formate as an internal reference using commercial software Chenomx. Continuing our efforts in this direction, the serum metabolic profiles were measured on 39 LC patients and 42 normal controls (NCs, comparable in age/sex) using high-field 800 MHz NMR spectroscopy and compared using multivariate statistical analysis tools to identify metabolic disturbances and metabolites of diagnostic potential. Partial least-squares discriminant analysis (PLS-DA) model revealed a distinct separation between LC and NC groups and resulted in excellent discriminatory ability with the area under the receiver-operating characteristic (AUROC) = 0.97 [95% CI = 0.89–1.00]. The metabolic features contributing to the differentiation of LC from NC samples were identified first using variable importance in projection (VIP) score analysis and then checked for their statistical significance (with p-value < 0.05) and diagnostic potential using the ROC curve analysis. The analysis revealed relevant metabolic disturbances associated with LC. Among various circulatory metabolites, six metabolites, including histidine, glutamine, glycine, threonine, alanine, and valine, were found to be of apposite diagnostic potential for clinical implications. These metabolic alterations indicated altered glucose metabolism, aberrant fatty acid synthesis, and augmented utilization of various amino acids including active glutaminolysis in LC. American Chemical Society 2022-01-31 /pmc/articles/PMC8851899/ /pubmed/35187366 http://dx.doi.org/10.1021/acsomega.1c06941 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Singh, Anjana Prakash, Ved Gupta, Nikhil Kumar, Ashish Kant, Ravi Kumar, Dinesh Serum Metabolic Disturbances in Lung Cancer Investigated through an Elaborative NMR-Based Serum Metabolomics Approach |
title | Serum Metabolic Disturbances in Lung Cancer Investigated
through an Elaborative NMR-Based
Serum Metabolomics Approach |
title_full | Serum Metabolic Disturbances in Lung Cancer Investigated
through an Elaborative NMR-Based
Serum Metabolomics Approach |
title_fullStr | Serum Metabolic Disturbances in Lung Cancer Investigated
through an Elaborative NMR-Based
Serum Metabolomics Approach |
title_full_unstemmed | Serum Metabolic Disturbances in Lung Cancer Investigated
through an Elaborative NMR-Based
Serum Metabolomics Approach |
title_short | Serum Metabolic Disturbances in Lung Cancer Investigated
through an Elaborative NMR-Based
Serum Metabolomics Approach |
title_sort | serum metabolic disturbances in lung cancer investigated
through an elaborative nmr-based
serum metabolomics approach |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8851899/ https://www.ncbi.nlm.nih.gov/pubmed/35187366 http://dx.doi.org/10.1021/acsomega.1c06941 |
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