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Sorokin AA, Pekov SI, Zavorotnyuk DS, Shamraeva MM, Bormotov DS, Popov IA. Modern machine-learning applications in ambient ionization mass spectrometry. MASS SPECTROMETRY REVIEWS 2024. [PMID: 38671553 DOI: 10.1002/mas.21886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 03/29/2024] [Accepted: 04/05/2024] [Indexed: 04/28/2024]
Abstract
This article provides a comprehensive overview of the applications of methods of machine learning (ML) and artificial intelligence (AI) in ambient ionization mass spectrometry (AIMS). AIMS has emerged as a powerful analytical tool in recent years, allowing for rapid and sensitive analysis of various samples without the need for extensive sample preparation. The integration of ML/AI algorithms with AIMS has further expanded its capabilities, enabling enhanced data analysis. This review discusses ML/AI algorithms applicable to the AIMS data and highlights the key advancements and potential benefits of utilizing ML/AI in the field of mass spectrometry, with a focus on the AIMS community.
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Affiliation(s)
- Anatoly A Sorokin
- Laboratory of Molecular Medical Diagnostics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Stanislav I Pekov
- Mass Spectrometry Laboratory, Skolkovo Institute of Science and Technology, Moscow, Russia
- Translational Medicine Laboratory, Siberian State Medical University, Tomsk, Russia
- Department for Molecular and Biological Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Denis S Zavorotnyuk
- Laboratory of Molecular Medical Diagnostics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Mariya M Shamraeva
- Laboratory of Molecular Medical Diagnostics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Denis S Bormotov
- Laboratory of Molecular Medical Diagnostics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Igor A Popov
- Laboratory of Molecular Medical Diagnostics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- Translational Medicine Laboratory, Siberian State Medical University, Tomsk, Russia
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2
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Pekov SI, Bormotov DS, Bocharova SI, Sorokin AA, Derkach MM, Popov IA. Mass spectrometry for neurosurgery: Intraoperative support in decision-making. MASS SPECTROMETRY REVIEWS 2024. [PMID: 38571445 DOI: 10.1002/mas.21883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 02/29/2024] [Accepted: 03/23/2024] [Indexed: 04/05/2024]
Abstract
Ambient ionization mass spectrometry was proved to be a powerful tool for oncological surgery. Still, it remains a translational technique on the way from laboratory to clinic. Brain surgery is the most sensitive to resection accuracy field since the balance between completeness of resection and minimization of nerve fiber damage determines patient outcome and quality of life. In this review, we summarize efforts made to develop various intraoperative support techniques for oncological neurosurgery and discuss difficulties arising on the way to clinical implementation of mass spectrometry-guided brain surgery.
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Affiliation(s)
- Stanislav I Pekov
- Skolkovo Institute of Science and Technology, Moscow, Russian Federation
- Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
- Siberian State Medical University, Tomsk, Russian Federation
| | - Denis S Bormotov
- Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
| | | | - Anatoly A Sorokin
- Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
| | - Maria M Derkach
- Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
| | - Igor A Popov
- Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
- Siberian State Medical University, Tomsk, Russian Federation
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3
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Cheng YJ, Fan F, Zhang Z, Zhang HJ. Lipid metabolism in malignant tumor brain metastasis: reprogramming and therapeutic potential. Expert Opin Ther Targets 2023; 27:861-878. [PMID: 37668244 DOI: 10.1080/14728222.2023.2255377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 07/19/2023] [Accepted: 08/31/2023] [Indexed: 09/06/2023]
Abstract
INTRODUCTION Brain metastasis is a highly traumatic event in the progression of malignant tumors, often symbolizing higher mortality. Metabolic alterations are hallmarks of cancer, and the mask of lipid metabolic program rearrangement in cancer progression is gradually being unraveled. AREAS COVERED In this work, we reviewed clinical and fundamental studies related to lipid expression and activity changes in brain metastases originating from lung, breast, and cutaneous melanomas, respectively. Novel roles of lipid metabolic reprogramming in the development of brain metastasis from malignant tumors were identified and its potential as a therapeutic target was evaluated. Published literature and clinical studies in databases consisting of PubMed, Embase, Scopus and www.ClinicalTrials.gov from 1990 to 2022 were searched. EXPERT OPINION Lipid metabolic reprogramming in brain metastasis is involved in de novo lipid synthesis within low lipid availability environments, regulation of lipid uptake and storage, metabolic interactions between brain tumors and the brain microenvironment, and membrane lipid remodeling, in addition to being a second messenger for signal transduction. Although some lipid metabolism modulators work efficiently in preclinical models, there is still a long way to go from laboratory to clinic. This area of research holds assurance for the organ-targeted treatment of brain metastases through drug-regulated metabolic targets and dietary interventions.
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Affiliation(s)
- Yan-Jie Cheng
- Department of Oncology, Zhongda Hospital, Medical School of Southeast University, Nanjing, Jiangsu, People's Republic of China
- Department of Oncology, Shanghai Fengxian District Central Hospital, Shanghai, China
| | - Fan Fan
- Department of Oncology, Zhongda Hospital, Medical School of Southeast University, Nanjing, Jiangsu, People's Republic of China
| | - Zhong Zhang
- Department of Oncology, Zhongda Hospital, Medical School of Southeast University, Nanjing, Jiangsu, People's Republic of China
| | - Hai-Jun Zhang
- Department of Oncology, Zhongda Hospital, Medical School of Southeast University, Nanjing, Jiangsu, People's Republic of China
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Shapley Value as a Quality Control for Mass Spectra of Human Glioblastoma Tissues. DATA 2023. [DOI: 10.3390/data8010021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
The automatic processing of high-dimensional mass spectrometry data is required for the clinical implementation of ambient ionization molecular profiling methods. However, complex algorithms required for the analysis of peak-rich spectra are sensitive to the quality of the input data. Therefore, an objective and quantitative indicator, insensitive to the conditions of the experiment, is currently in high demand for the automated treatment of mass spectrometric data. In this work, we demonstrate the utility of the Shapley value as an indicator of the quality of the individual mass spectrum in the classification task for human brain tumor tissue discrimination. The Shapley values are calculated on the training set of glioblastoma and nontumor pathological tissues spectra and used as feedback to create a random forest regression model to estimate the contributions for all spectra of each specimen. As a result, it is shown that the implementation of Shapley values significantly accelerates the data analysis of negative mode mass spectrometry data alongside simultaneous improving the regression models’ accuracy.
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Bormotov DS, Eliferov VA, Peregudova OV, Zavorotnyuk DS, Bocharov KV, Pekov SI, Sorokin AA, Nikolaev EN, Popov IA. Incorporation of a Disposable ESI Emitter into Inline Cartridge Extraction Mass Spectrometry Improves Throughput and Spectra Stability. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:119-122. [PMID: 36535019 DOI: 10.1021/jasms.2c00207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Rapid and reliable methods for detecting tumor margins are crucial for neuro-oncology. Several mass spectrometry-based methods have been recently proposed to address this problem. Inline Cartridge Extraction (ICE) demonstrates the potential for clinical application, based on ex-vivo analysis of dissected tissues, but requires time-consuming steps to avoid cross-contamination. In this work, a method of incorporating a disposable electrospray emitter into the ICE cartridge by PEEK sleeves melting is developed. It reduces total analysis time and improves throughput. The proposed setup also improves the robustness of the ICE molecular profiling as demonstrated with human glial tumor samples in that stability and reproducibility of the spectra were increased.
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Affiliation(s)
- Denis S Bormotov
- Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russian Federation
| | - Vasily A Eliferov
- Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russian Federation
| | - Olga V Peregudova
- Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russian Federation
| | - Denis S Zavorotnyuk
- Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russian Federation
| | - Konstantin V Bocharov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russian Federation
| | - Stanislav I Pekov
- Skolkovo Institute of Science and Technology, Moscow 121205, Russian Federation
- Siberian State Medical University, Tomsk 634050, Russian Federation
| | - Anatoly A Sorokin
- Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russian Federation
| | - Eugene N Nikolaev
- Skolkovo Institute of Science and Technology, Moscow 121205, Russian Federation
| | - Igor A Popov
- Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russian Federation
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6
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Pekov SI, Zhvansky ES, Eliferov VA, Sorokin AA, Ivanov DG, Nikolaev EN, Popov IA. Determination of Brain Tissue Samples Storage Conditions for Reproducible Intraoperative Lipid Profiling. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27082587. [PMID: 35458785 PMCID: PMC9029908 DOI: 10.3390/molecules27082587] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 11/16/2022]
Abstract
Ex-vivo molecular profiling has recently emerged as a promising method for intraoperative tissue identification, especially in neurosurgery. The short-term storage of resected samples at room temperature is proposed to have negligible influence on the lipid molecular profiles. However, a detailed investigation of short-term molecular profile stability is required to implement molecular profiling in a clinic. This study evaluates the effect of storage media, temperature, and washing solution to determine conditions that provide stable and reproducible molecular profiles, with the help of ambient ionization mass spectrometry using rat cerebral cortex as model brain tissue samples. Utilizing normal saline for sample storage and washing media shows a positive effect on the reproducibility of the spectra; however, the refrigeration shows a negligible effect on the spectral similarity. Thus, it was demonstrated that up to hour-long storage in normal saline, even at room temperature, ensures the acquisition of representative molecular profiles using ambient ionization mass spectrometry.
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Affiliation(s)
- Stanislav I. Pekov
- Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (E.S.Z.); (V.A.E.); (A.A.S.); (D.G.I.)
- Siberian State Medical University, 634050 Tomsk, Russia
- Correspondence: (S.I.P.); (E.N.N); (I.A.P.)
| | - Evgeny S. Zhvansky
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (E.S.Z.); (V.A.E.); (A.A.S.); (D.G.I.)
| | - Vasily A. Eliferov
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (E.S.Z.); (V.A.E.); (A.A.S.); (D.G.I.)
| | - Anatoly A. Sorokin
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (E.S.Z.); (V.A.E.); (A.A.S.); (D.G.I.)
- Department of Biochemistry and Systems Biology, Faculty of Health and Life Sciences, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3BX, UK
| | - Daniil G. Ivanov
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (E.S.Z.); (V.A.E.); (A.A.S.); (D.G.I.)
| | - Eugene N. Nikolaev
- Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
- Correspondence: (S.I.P.); (E.N.N); (I.A.P.)
| | - Igor A. Popov
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (E.S.Z.); (V.A.E.); (A.A.S.); (D.G.I.)
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov, 117997 Moscow, Russia
- Correspondence: (S.I.P.); (E.N.N); (I.A.P.)
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Lipid Profiles of Human Brain Tumors Obtained by High-Resolution Negative Mode Ambient Mass Spectrometry. DATA 2021. [DOI: 10.3390/data6120132] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Alterations in cell metabolism, including changes in lipid composition occurring during malignancy, are well characterized for various tumor types. However, a significant part of studies that deal with brain tumors have been performed using cell cultures and animal models. Here, we present a dataset of 124 high-resolution negative ionization mode lipid profiles of human brain tumors resected during neurosurgery. The dataset is supplemented with 38 non-tumor pathological brain tissue samples resected during elective surgery. The change in lipid composition alterations of brain tumors enables the possibility of discriminating between malignant and healthy tissues with the implementation of ambient mass spectrometry. On the other hand, the collection of clinical samples allows the comparison of the metabolism alteration patterns in animal models or in vitro models with natural tumor samples ex vivo. The presented dataset is intended to be a data sample for bioinformaticians to test various data analysis techniques with ambient mass spectrometry profiles, or to be a source of clinically relevant data for lipidomic research in oncology.
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Pekov SI, Sorokin AA, Kuzin AA, Bocharov KV, Bormotov DS, Shivalin AS, Shurkhay VA, Potapov AA, Nikolaev EN, Popov IA. Analysis of Phosphatidylcholines Alterations in Human Glioblastomas Ex Vivo. BIOCHEMISTRY (MOSCOW), SUPPLEMENT SERIES B: BIOMEDICAL CHEMISTRY 2021. [DOI: 10.1134/s1990750821030070] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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9
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Eliferov VA, Zhvansky ES, Sorokin AA, Shurkhay VA, Bormotov DS, Pekov SI, Nikitin PV, Ryzhova MV, Kulikov EE, Potapov AA, Nikolaev EN, Popov IA. The Role of Lipids in the Classification of Astrocytoma and Glioblastoma Using Mass Spectrometry Tumor Profiling. BIOCHEMISTRY (MOSCOW), SUPPLEMENT SERIES B: BIOMEDICAL CHEMISTRY 2021. [DOI: 10.1134/s1990750821020025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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10
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Zhvansky ES, Eliferov VA, Sorokin AA, Shurkhay VA, Pekov SI, Bormotov DS, Ivanov DG, Zavorotnyuk DS, Bocharov KV, Khaliullin IG, Belenikin MS, Potapov AA, Nikolaev EN, Popov IA. Assessment of variation of inline cartridge extraction mass spectra. JOURNAL OF MASS SPECTROMETRY : JMS 2021; 56:e4640. [PMID: 32798239 DOI: 10.1002/jms.4640] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 07/20/2020] [Accepted: 07/31/2020] [Indexed: 06/11/2023]
Abstract
Recently, mass-spectrometry methods show its utility in tumor boundary location. The effect of differences between research and clinical protocols such as low- and high-resolution measurements and sample storage have to be understood and taken into account to transfer methods from bench to bedside. In this study, we demonstrate a simple way to compare mass spectra obtained by different experimental protocols, assess its quality, and check for the presence of outliers and batch effect in the dataset. We compare the mass spectra of both fresh and frozen-thawed astrocytic brain tumor samples obtained with the inline cartridge extraction prior to electrospray ionization. Our results reveal the importance of both positive and negative ion mode mass spectrometry for getting reliable information about sample diversity. We show that positive mode highlights the difference between protocols of mass spectra measurement, such as fresh and frozen-thawed samples, whereas negative mode better characterizes the histological difference between samples. We also show how the use of similarity spectrum matrix helps to identify the proper choice of the measurement parameters, so data collection would be kept reliable, and analysis would be correct and meaningful.
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Affiliation(s)
- Evgeny S Zhvansky
- Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
| | - Vasiliy A Eliferov
- Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
| | - Anatoly A Sorokin
- Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
| | - Vsevolod A Shurkhay
- Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
- Outpatient department, Federal State Autonomous Institution «N.N. Burdenko National Scientific and Practical Center for Neurosurgery» of the Ministry of Healthcare of the Russian Federation, Moscow, Russian Federation
| | - Stanislav I Pekov
- Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow, Russian Federation
| | - Denis S Bormotov
- Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
| | - Daniil G Ivanov
- Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
- Emanuel Institute for Biochemical Physics, Russian Academy of Sciences, Moscow, Russian Federation
| | - Denis S Zavorotnyuk
- Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
| | - Konstantin V Bocharov
- Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Iliyas G Khaliullin
- Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
| | - Maksim S Belenikin
- Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
| | - Aleksandr A Potapov
- Outpatient department, Federal State Autonomous Institution «N.N. Burdenko National Scientific and Practical Center for Neurosurgery» of the Ministry of Healthcare of the Russian Federation, Moscow, Russian Federation
| | - Evgeny N Nikolaev
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow, Russian Federation
| | - Igor A Popov
- Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
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11
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Pekov SI, Bormotov DS, Nikitin PV, Sorokin AA, Shurkhay VA, Eliferov VA, Zavorotnyuk DS, Potapov AA, Nikolaev EN, Popov IA. Rapid estimation of tumor cell percentage in brain tissue biopsy samples using inline cartridge extraction mass spectrometry. Anal Bioanal Chem 2021; 413:2913-2922. [PMID: 33751161 DOI: 10.1007/s00216-021-03220-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 01/28/2021] [Accepted: 02/03/2021] [Indexed: 10/21/2022]
Abstract
Tumor cell percentage (TCP) is an essential characteristic of biopsy samples that directly affects the sensitivity of molecular testing in clinical practice. Apart from clarifying diagnoses, rapid evaluation of TCP combined with various neuronavigation systems can be used to support decision making in neurosurgery. It is known that ambient mass spectrometry makes it possible to rapidly distinguish healthy from malignant tissues. In connection with this, here we demonstrate the possibility of using non-imaging ambient mass spectrometry to evaluate TCP in glial tumor tissues with a high degree of confidence. Molecular profiles of histologically annotated human glioblastoma tissue samples were obtained using the inline cartridge extraction ambient mass spectrometry approach. XGBoost regressors were trained to evaluate tumor cell percentage. Using cross-validation, it was estimated that the TCP was determined by the regressors with a precision of approximately 90% using only low-resolution data. This result demonstrates that ambient mass spectrometry provides an accurate method todetermine TCP in dissected tissues even without implementing mass spectrometry imaging. The application of such techniques offers the possibility to automate routine tissue screening and TCP evaluation to boost the throughput of pathology laboratories. Rapid estimation of tumor cell percentage during neurosurgery.
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Affiliation(s)
- Stanislav I Pekov
- Skolkovo Institute of Science and Technology, Skolkovo, Moscow region, 143026, Russian Federation.,Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russian Federation
| | - Denis S Bormotov
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russian Federation
| | - Pavel V Nikitin
- N.N. Burdenko National Scientific and Practical Center for Neurosurgery, Moscow, 125047, Russian Federation
| | - Anatoly A Sorokin
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russian Federation
| | - Vsevolod A Shurkhay
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russian Federation.,N.N. Burdenko National Scientific and Practical Center for Neurosurgery, Moscow, 125047, Russian Federation
| | - Vasiliy A Eliferov
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russian Federation
| | - Denis S Zavorotnyuk
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russian Federation
| | - Alexander A Potapov
- N.N. Burdenko National Scientific and Practical Center for Neurosurgery, Moscow, 125047, Russian Federation
| | - Eugene N Nikolaev
- Skolkovo Institute of Science and Technology, Skolkovo, Moscow region, 143026, Russian Federation
| | - Igor A Popov
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russian Federation.
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12
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Zhvansky E, Sorokin A, Shurkhay V, Zavorotnyuk D, Bormotov D, Pekov S, Potapov A, Nikolaev E, Popov I. Comparison of Dimensionality Reduction Methods in Mass Spectra of Astrocytoma and Glioblastoma Tissues. Mass Spectrom (Tokyo) 2021; 10:A0094. [PMID: 33747696 PMCID: PMC7953827 DOI: 10.5702/massspectrometry.a0094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 01/21/2021] [Indexed: 11/24/2022] Open
Abstract
Recently developed methods of ambient ionization allow the collection of mass spectrometric datasets for biological and medical applications at an unprecedented pace. One of the areas that could employ such analysis is neurosurgery. The fast in situ identification of dissected tissues could assist the neurosurgery procedure. In this paper tumor tissues of astrocytoma and glioblastoma are compared. The vast majority of the data representation methods are hard to use, as the number of features is high and the amount of samples is limited. Furthermore, the ratio of features and samples number restricts the use of many machine learning methods. The number of features could be reduced through feature selection algorithms or dimensionality reduction methods. Different algorithms of dimensionality reduction are considered along with the traditional noise thresholding for the mass spectra. From our analysis, the Isomap algorithm appears to be the most effective dimensionality reduction algorithm for negative mode, whereas the positive mode could be processed with a simple noise reduction by a threshold. Also, negative and positive mode correspond to different sample properties: negative mode is responsible for the inner variability and the details of the sample, whereas positive mode describes measurement in general.
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Affiliation(s)
- Evgeny Zhvansky
- Moscow Institute of Physics and Technology, Dolgoprudny,
Moscow Region, Russian Federation
| | - Anatoly Sorokin
- Moscow Institute of Physics and Technology, Dolgoprudny,
Moscow Region, Russian Federation
- Institute of Cell Biophysics RAS, Pushchino, Russian
Federation
- Institute of Systems, Molecular and Integrative Biology,
University of Liverpool, Liverpool, UK
| | - Vsevolod Shurkhay
- Moscow Institute of Physics and Technology, Dolgoprudny,
Moscow Region, Russian Federation
- Federal State Autonomous Institution «N.N. Burdenko
National Scientific and Practical Center for Neurosurgery» of the Ministry of
Healthcare of the Russian Federation, Moscow, Russian Federation
| | - Denis Zavorotnyuk
- Moscow Institute of Physics and Technology, Dolgoprudny,
Moscow Region, Russian Federation
| | - Denis Bormotov
- Moscow Institute of Physics and Technology, Dolgoprudny,
Moscow Region, Russian Federation
| | - Stanislav Pekov
- N.N. Semenov Federal Research Center of Chemical Physics
Russian Academy of Sciences, Moscow, Russian Federation
| | - Alexander Potapov
- Federal State Autonomous Institution «N.N. Burdenko
National Scientific and Practical Center for Neurosurgery» of the Ministry of
Healthcare of the Russian Federation, Moscow, Russian Federation
| | - Evgeny Nikolaev
- Skolkovo Institute of Science and Technology, Moscow,
Russian Federation
| | - Igor Popov
- Moscow Institute of Physics and Technology, Dolgoprudny,
Moscow Region, Russian Federation
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13
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Pekov SI, Sorokin AA, Kuzin AA, Bocharov KV, Bormotov DS, Shivalin AS, Shurkhay VA, Potapov AA, Nikolaev EN, Popov IA. [Analysis of phosphatidylcholines alterations in human glioblastoma multiform tissues ex vivo]. BIOMEDIT︠S︡INSKAI︠A︡ KHIMII︠A︡ 2021; 67:81-87. [PMID: 33645525 DOI: 10.18097/pbmc20216701081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Significant metabolism alteration is accompanying the cell malignization process. Energy metabolism disturbance leads to the activation of de novo synthesis and beta-oxidation processes of lipids and fatty acids in a cancer cell, which becomes an indicator of pathological processes inside the cell. The majority of studies dealing with lipid metabolism alterations in glial tumors are performed using the cell lines in vitro or animal models. However, such conditions do not entirely represent the physiological conditions of cell growth or possible cells natural variability. This work presents the results of the data obtained by applying ambient mass spectrometry to human glioblastoma multiform tissues. By analyzing a relatively large cohort of primary and secondary glioblastoma samples, we identify the alterations in cells lipid composition, which accompanied the development of grade IV brain tumors. We demonstrate that primary glioblastomas, as well as ones developed from astrocytomas, are enriched with mono- and diunsaturated phosphatidylcholines (PC 26:1, 30:2, 32:1, 32:2, 34:1, 34:2). Simultaneously, the saturated and polyunsaturated phosphatidylcholines and phosphatidylethanolamines decrease. These alterations are obviously linked to the availability of the polyunsaturated fatty acids and activation of the de novo lipid synthesis and beta-oxidation pathways under the anaerobic conditions in the tumor core.
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Affiliation(s)
- S I Pekov
- Skolkovo Institute of Science and Technology, Moscow, Russia; Moscow Institute of Physics and Technology (National Research University), Moscow, Russia
| | - A A Sorokin
- Moscow Institute of Physics and Technology (National Research University), Moscow, Russia
| | - A A Kuzin
- Moscow Institute of Physics and Technology (National Research University), Moscow, Russia
| | - K V Bocharov
- Semenov Federal Center of Chemical Physic of RAS, Moscow, Russia
| | - D S Bormotov
- Moscow Institute of Physics and Technology (National Research University), Moscow, Russia
| | - A S Shivalin
- Moscow Institute of Physics and Technology (National Research University), Moscow, Russia
| | - V A Shurkhay
- Moscow Institute of Physics and Technology (National Research University), Moscow, Russia; N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - A A Potapov
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - E N Nikolaev
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | - I A Popov
- Moscow Institute of Physics and Technology (National Research University), Moscow, Russia
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14
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Zhvansky ES, Sorokin AA, Bormotov DS, Bocharov KV, Zavorotnyuk DS, Ivanov DG, Nikolaev EN, Popov IA. The software for interactive evaluation of mass spectra stability and reproducibility. Bioinformatics 2020; 37:140-142. [PMID: 33367588 DOI: 10.1093/bioinformatics/btaa1072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 11/25/2020] [Accepted: 12/15/2020] [Indexed: 11/13/2022] Open
Abstract
SUMMARY Mass spectrometry methods are widely used for the analysis of biological and medical samples. Recently developed methods such as DESI, REIMS, NESI allow fast analyses without sample preparation at the cost of higher variability of spectra. In biology and medicine, MS profiles are often used with machine learning (classification, regression, etc.) algorithms and statistical analysis, which are sensitive to outliers and intraclass variability. Here we present SSM Display software, a tool for fast visual outlier detection and variance estimation in mass spectrometric profiles. The tool speeds up the process of manual spectra inspection, improves accuracy and explainability of outlier detection, and decreases the requirements to the operator experience. It was shown that the batch effect could be revealed through SSM analysis and that the SSM calculation can also be used for tuning novel ion sources concerning the quality of obtained mass spectra. AVAILABILITY Source code, example datasets, binaries, and other information are available at https://github.com/EvgenyZhvansky/R_matrix. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- E S Zhvansky
- Dolgoprudny, Moscow Institute of Physics and Technology, Russia
| | - A A Sorokin
- Dolgoprudny, Moscow Institute of Physics and Technology, Russia
| | - D S Bormotov
- Dolgoprudny, Moscow Institute of Physics and Technology, Russia
| | - K V Bocharov
- Dolgoprudny, Moscow Institute of Physics and Technology, Russia
| | - D S Zavorotnyuk
- Dolgoprudny, Moscow Institute of Physics and Technology, Russia
| | - D G Ivanov
- Dolgoprudny, Moscow Institute of Physics and Technology, Russia.,Emanuel Institute for Biochemical Physics of the Russian Academy of Sciences, Moscow, Russia
| | - E N Nikolaev
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | - I A Popov
- Dolgoprudny, Moscow Institute of Physics and Technology, Russia
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15
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Eliferov VA, Zhvansky ES, Sorokin AA, Shurkhay VA, Bormotov DS, Pekov SI, Nikitin PV, Ryzhova MV, Kulikov EE, Potapov AA, Nikolaev EN, Popov IA. [The role of lipids in the classification of astrocytoma and glioblastoma using MS tumor profiling]. BIOMEDIT︠S︡INSKAI︠A︡ KHIMII︠A︡ 2020; 66:317-325. [PMID: 32893821 DOI: 10.18097/pbmc20206604317] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Express MS identification of biological tissues has become a much more accessible research method due to the application of direct specimen ionization at atmospheric pressure. In contrast to traditional methods of analysis employing GC-MS methods for determining the molecular composition of the analyzed objects it eliminates the influence of mutual ion suppression. Despite significant progress in the field of direct MS of biological tissues, the question of mass spectrometric profile attribution to a certain type of tissue still remains open. The use of modern machine learning methods and protocols (e.g., "random forests") enables us to trace possible relationships between the components of the sample MS profile and the result of brain tumor tissue classification (astrocytoma or glioblastoma). It has been shown that the most pronounced differences in the mass spectrometric profiles of these tumors are due to their lipid composition. Detection of statistically significant differences in lipid profiles of astrocytoma and glioblastoma may be used to perform an express test during surgery and inform the neurosurgeon what type of malignant tissue he is working with. The ability to accurately determine the boundaries of the neoplastic growth significantly improves the quality of both surgical intervention and postoperative rehabilitation, as well as the duration and quality of life of patients.
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Affiliation(s)
- V A Eliferov
- Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, Russia
| | - E S Zhvansky
- Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, Russia
| | - A A Sorokin
- Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, Russia
| | - V A Shurkhay
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - D S Bormotov
- Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, Russia
| | - S I Pekov
- Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, Russia
| | - P V Nikitin
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - M V Ryzhova
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - E E Kulikov
- Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, Russia; Federal Research Center "Fundamentals of Biotechnology", RAS, Moscow, Russia
| | - A A Potapov
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - E N Nikolaev
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | - I A Popov
- Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, Russia
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16
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Ivanov DG, Pekov SI, Bocharov KV, Bormotov DS, Spasskiy AI, Zhvansky ES, Sorokin AA, Eliferov VA, Zavorotnyuk DS, Tkachenko SI, Khaliullin IG, Kuksin AY, Shurkhay VA, Kononikhin AS, Nikolaev EN, Popov IA. Novel Mass Spectrometric Utilities for Assisting in Oncological Surgery. RUSSIAN JOURNAL OF PHYSICAL CHEMISTRY B 2020. [DOI: 10.1134/s1990793120030173] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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17
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Pekov SI, Eliferov VA, Sorokin AA, Shurkhay VA, Zhvansky ES, Vorobyev AS, Potapov AA, Nikolaev EN, Popov IA. Inline cartridge extraction for rapid brain tumor tissue identification by molecular profiling. Sci Rep 2019; 9:18960. [PMID: 31831871 PMCID: PMC6908710 DOI: 10.1038/s41598-019-55597-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 11/05/2019] [Indexed: 12/16/2022] Open
Abstract
The development of perspective diagnostic techniques in medicine requires efficient high-throughput biological sample analysis methods. Here, we present an inline cartridge extraction that facilitates the screening rate of mass spectrometry shotgun lipidomic analysis of tissue samples. We illustrate the method by its application to tumor tissue identification in neurosurgery. In perspective, this high-performance method provides new possibilities for the investigation of cancer pathogenesis and metabolic disorders.
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Affiliation(s)
- Stanislav I Pekov
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
| | - Vasily A Eliferov
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
| | - Anatoly A Sorokin
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
| | - Vsevolod A Shurkhay
- Federal State Autonomous Institution «N.N. Burdenko National Scientific and Practical Center for Neurosurgery» of the Ministry of Healthcare of the Russian Federation, Moscow, Russian Federation
| | - Evgeny S Zhvansky
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
| | - Alexander S Vorobyev
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation
| | - Alexander A Potapov
- Federal State Autonomous Institution «N.N. Burdenko National Scientific and Practical Center for Neurosurgery» of the Ministry of Healthcare of the Russian Federation, Moscow, Russian Federation
| | - Eugene N Nikolaev
- Skolkovo Institute of Science and Technology, Skolkovo, Russian Federation.
| | - Igor A Popov
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation.
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18
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Thakur SS. Anti-Cancer Drug Discovery: Structure, Function and Novel Strategy - Part-II. Curr Top Med Chem 2019; 19:1490. [PMID: 31592751 DOI: 10.2174/156802661917190828111439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
- Suman S Thakur
- Proteomics and Cell Signaling, Lab W110 Centre for Cellular & Molecular Biology Habsiguda, Uppal Road Hyderabad - 500 007 Telangana, India
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