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Scientific Reports, volume 13, issue 1, publication number 11072

Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer

Shestakova Ksenia M. ¹

Moskaleva Natalia E ¹

Boldin Andrey A. ^{2, 3}

Rezvanov Pavel M. ^{2, 3}

Shestopalov Alexandr V. ⁴

Rumyantsev Sergey A. ⁴

Zlatnik Elena Yu ⁵

Novikova Inna A ⁵

Sagakyants Alexander B ⁵

Timofeeva Sofya V. ⁵

Simonov Yuriy ³

Baskhanova Sabina N. ¹

Tobolkina Elena ⁶

Rudaz Serge ⁶

Appolonova Svetlana A ^{2, 3}

Hide authors affiliations Show authors affiliations: 6 affiliations

World-Class Research Center Digital Biodesign and Personalized Healthcare, I.M. Sechenov First Moscow State Medical University, Moscow, Russia |

I.M. Sechenov First Moscow State Medical University, Moscow, Russia |

Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow Medical University, Moscow, Russia |

⁴

Pirogov Russian National Research Medical University, Moscow, Russia |

⁵

National Medical Research Centre for Oncology (Rostov-On-Don, Russia), Rostov-on-Don, Russia |

⁶

Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva 4, Switzerland |

Publication type: Journal Article

Publication date: 2023-07-08

Springer Nature

Journal: Scientific Reports

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Impact factor: 4.6

ISSN: 20452322

DOI: 10.1038/s41598-023-38140-7

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PubMed ID: 37422585

Multidisciplinary

Abstract

Lung cancer is referred to as the second most common cancer worldwide and is mainly associated with complex diagnostics and the absence of personalized therapy. Metabolomics may provide significant insights into the improvement of lung cancer diagnostics through identification of the specific biomarkers or biomarker panels that characterize the pathological state of the patient. We performed targeted metabolomic profiling of plasma samples from individuals with non-small cell lung cancer (NSLC, n = 100) and individuals without any cancer or chronic pathologies (n = 100) to identify the relationship between plasma endogenous metabolites and NSLC by means of modern comprehensive bioinformatics tools, including univariate analysis, multivariate analysis, partial correlation network analysis and machine learning. Through the comparison of metabolomic profiles of patients with NSCLC and noncancer individuals, we identified significant alterations in the concentration levels of metabolites mainly related to tryptophan metabolism, the TCA cycle, the urea cycle and lipid metabolism. Additionally, partial correlation network analysis revealed new ratios of the metabolites that significantly distinguished the considered groups of participants. Using the identified significantly altered metabolites and their ratios, we developed a machine learning classification model with an ROC AUC value equal to 0.96. The developed machine learning lung cancer model may serve as a prototype of the approach for the in-time diagnostics of lung cancer that in the future may be introduced in routine clinical use. Overall, we have demonstrated that the combination of metabolomics and up-to-date bioinformatics can be used as a potential tool for proper diagnostics of patients with NSCLC.

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	1
Scientific Reports	Scientific Reports, 1, 33.33% Scientific Reports 1 publication, 33.33%
Frontiers in Oncology	Frontiers in Oncology, 1, 33.33% Frontiers in Oncology 1 publication, 33.33%
Molecular Cancer Therapeutics	Molecular Cancer Therapeutics, 1, 33.33% Molecular Cancer Therapeutics 1 publication, 33.33%
	1

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	1
Springer Nature	Springer Nature, 1, 33.33% Springer Nature 1 publication, 33.33%
Frontiers Media S.A.	Frontiers Media S.A., 1, 33.33% Frontiers Media S.A. 1 publication, 33.33%
American Association for Cancer Research (AACR)	American Association for Cancer Research (AACR), 1, 33.33% American Association for Cancer Research (AACR) 1 publication, 33.33%
	1

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Shestakova K. M. et al. Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer // Scientific Reports. 2023. Vol. 13. No. 1. 11072

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Shestakova K. M., Moskaleva N. E., Boldin A. A., Rezvanov P. M., Shestopalov A. V., Rumyantsev S. A., Zlatnik E. Yu., Novikova I. A., Sagakyants A. B., Timofeeva S. V., Simonov Y., Baskhanova S. N., Tobolkina E., Rudaz S., Appolonova S. A. Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer // Scientific Reports. 2023. Vol. 13. No. 1. 11072

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TY - JOUR

DO - 10.1038/s41598-023-38140-7

UR - https://doi.org/10.1038%2Fs41598-023-38140-7

TI - Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer

T2 - Scientific Reports

AU - Shestakova, Ksenia M.

AU - Moskaleva, Natalia E

AU - Boldin, Andrey A.

AU - Rezvanov, Pavel M.

AU - Shestopalov, Alexandr V.

AU - Rumyantsev, Sergey A.

AU - Zlatnik, Elena Yu

AU - Novikova, Inna A

AU - Sagakyants, Alexander B

AU - Timofeeva, Sofya V.

AU - Simonov, Yuriy

AU - Baskhanova, Sabina N.

AU - Tobolkina, Elena

AU - Rudaz, Serge

AU - Appolonova, Svetlana A

PY - 2023

DA - 2023/07/08 00:00:00

PB - Springer Nature

IS - 1

VL - 13

PMID - 37422585

SN - 2045-2322

ER -

BibTex

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BibTex Copy

@article{2023_Shestakova,

author = {Ksenia M. Shestakova and Natalia E Moskaleva and Andrey A. Boldin and Pavel M. Rezvanov and Alexandr V. Shestopalov and Sergey A. Rumyantsev and Elena Yu Zlatnik and Inna A Novikova and Alexander B Sagakyants and Sofya V. Timofeeva and Yuriy Simonov and Sabina N. Baskhanova and Elena Tobolkina and Serge Rudaz and Svetlana A Appolonova},

title = {Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer},

journal = {Scientific Reports},

year = {2023},

volume = {13},

publisher = {Springer Nature},

month = {jul},

url = {https://doi.org/10.1038%2Fs41598-023-38140-7},

number = {1},

doi = {10.1038/s41598-023-38140-7}

}

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Publisher

Springer Nature

Journal

Scientific Reports

Quartile SCImago

Quartile WOS

Impact factor

4.6

ISSN

20452322 (Print)

Labs

Laboratory of Pharmacokinetics and Metabolomic Analysis

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