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Ogrinc N, Barka EA, Clément C, Salzet M, Sanchez L, Fournier I. In Vivo and Real-Time Metabolic Profiling of Plant-Microbe Interactions in Leaves, Stems, and Roots of Bacterially Inoculated Chardonnay Plantlets using SpiderMass. Anal Chem 2024. [PMID: 39155838 DOI: 10.1021/acs.analchem.4c01470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/20/2024]
Abstract
There is growing interest in limiting the use of fungicides and implementing innovative, environmentally friendly strategies, such as the use of beneficial bacteria-triggered immunity, to protect grapevines from natural pathogens. Therefore, we need rapid and innovative ways to translate the knowledge of the molecular mechanisms underlying the activation of grapevine defenses against pathogens to induced resistance. Here, we have implemented an in vivo minimally invasive approach to study the interaction between plants and beneficial bacteria based on metabolic signatures. Paraburkholderia phytofirmans strain PsJN and PsJN-grapevine were used as bacterial and plant-bacterium interaction models, respectively. Using an innovative tool, SpiderMass, based on water-assisted laser desorption ionization with an IR microsampling probe, we simultaneously detect metabolic and lipidomic species. A metabolomic spectrum was thus generated, which was used to build a library and identify the most variable and discriminative peaks between the two conditions. We then showed that caftaric acid (m/z 311.04), caftaric acid dimer (m/z 623.09), derived caftaric acid (m/z 653.15), and quercetin-O-glucuronide tended to accumulate in grapevine leaves after root bacterization with PsJN. In addition, together with these phenolic messengers, we identified lipid biomarkers such as palmitic acid, linoleic acid, and α-linoleic acid as important messengers of enhanced defense mechanisms in Chardonnay plantlets. Taken together, SpiderMass is the next-generation methodology for studying plant-microorganism metabolic interactions with the prospect of in vivo real-time analysis in viticulture.
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Affiliation(s)
- Nina Ogrinc
- Inserm, CHU Lille, U1192-Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), Université de Lille, F-59000 Lille, France
| | - Essaïd Ait Barka
- Unité de Recherche RIBP (Résistance Induite et Bioprotec-tion des Plantes), USC INRAE 1488, Université de Reims Champagne-Ardenne Moulin de la Housse BP 1039, 51687 Reim Cedex 2, France
| | - Christophe Clément
- Unité de Recherche RIBP (Résistance Induite et Bioprotec-tion des Plantes), USC INRAE 1488, Université de Reims Champagne-Ardenne Moulin de la Housse BP 1039, 51687 Reim Cedex 2, France
| | - Michel Salzet
- Inserm, CHU Lille, U1192-Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), Université de Lille, F-59000 Lille, France
| | - Lisa Sanchez
- Unité de Recherche RIBP (Résistance Induite et Bioprotec-tion des Plantes), USC INRAE 1488, Université de Reims Champagne-Ardenne Moulin de la Housse BP 1039, 51687 Reim Cedex 2, France
- Institut Universitaire de France (IUF), Paris, France, https://www.iufrance.fr/
| | - Isabelle Fournier
- Inserm, CHU Lille, U1192-Protéomique Réponse Inflammatoire Spectrométrie de Masse (PRISM), Université de Lille, F-59000 Lille, France
- Institut Universitaire de France (IUF), Paris, France, https://www.iufrance.fr/
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2
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Smith BL, Hankinson T, Maher S. Portable Instrumentation for Ambient Ionization and Miniature Mass Spectrometers. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2024; 17:69-102. [PMID: 38640067 DOI: 10.1146/annurev-anchem-061522-040824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/21/2024]
Abstract
We critically evaluate the current status of portable mass spectrometry (pMS), particularly where this aligns with ambient ionization. Assessing the field of pMS can be quite subjective, especially in relation to the portable aspects of design, deployment, and operation. In this review, we discuss what it means to be portable and introduce a set of criteria by which pMS and ambient ionization sources can be assessed. Moreover, we consider the recent literature in terms of the most popular and significant advances in portable instrumentation for ambient ionization and miniature mass spectrometers. Finally, emerging trends and exciting future prospects are discussed and some recommendations are offered.
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Affiliation(s)
- Barry L Smith
- Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, United Kingdom;
| | - Thomas Hankinson
- Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, United Kingdom;
| | - Simon Maher
- Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, United Kingdom;
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3
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Stillger MN, Li MJ, Hönscheid P, von Neubeck C, Föll MC. Advancing rare cancer research by MALDI mass spectrometry imaging: Applications, challenges, and future perspectives in sarcoma. Proteomics 2024; 24:e2300001. [PMID: 38402423 DOI: 10.1002/pmic.202300001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 02/10/2024] [Accepted: 02/12/2024] [Indexed: 02/26/2024]
Abstract
MALDI mass spectrometry imaging (MALDI imaging) uniquely advances cancer research, by measuring spatial distribution of endogenous and exogenous molecules directly from tissue sections. These molecular maps provide valuable insights into basic and translational cancer research, including tumor biology, tumor microenvironment, biomarker identification, drug treatment, and patient stratification. Despite its advantages, MALDI imaging is underutilized in studying rare cancers. Sarcomas, a group of malignant mesenchymal tumors, pose unique challenges in medical research due to their complex heterogeneity and low incidence, resulting in understudied subtypes with suboptimal management and outcomes. In this review, we explore the applicability of MALDI imaging in sarcoma research, showcasing its value in understanding this highly heterogeneous and challenging rare cancer. We summarize all MALDI imaging studies in sarcoma to date, highlight their impact on key research fields, including molecular signatures, cancer heterogeneity, and drug studies. We address specific challenges encountered when employing MALDI imaging for sarcomas, and propose solutions, such as using formalin-fixed paraffin-embedded tissues, and multiplexed experiments, and considerations for multi-site studies and digital data sharing practices. Through this review, we aim to spark collaboration between MALDI imaging researchers and clinical colleagues, to deploy the unique capabilities of MALDI imaging in the context of sarcoma.
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Affiliation(s)
- Maren Nicole Stillger
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Center, Freiburg, Germany
- Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Freiburg, Germany
| | - Mujia Jenny Li
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Center, Freiburg, Germany
- Institute for Pharmaceutical Sciences, University of Freiburg, Freiburg, Germany
| | - Pia Hönscheid
- Institute of Pathology, Faculty of Medicine, University Hospital Carl Gustav Carus at the Technische Universität Dresden, Dresden, Germany
- National Center for Tumor Diseases, Partner Site Dresden, German Cancer Research Center Heidelberg, Dresden, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Cläre von Neubeck
- Department of Particle Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Melanie Christine Föll
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Center, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Khoury College of Computer Sciences, Northeastern University, Boston, USA
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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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Fan J, Ma W, Yu Y, Li Y, Nie Z. Recent advances in entirely hand-held ionization sources for mass spectrometry. Anal Bioanal Chem 2024; 416:2057-2063. [PMID: 37930374 DOI: 10.1007/s00216-023-05022-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 10/07/2023] [Accepted: 10/23/2023] [Indexed: 11/07/2023]
Abstract
Ambient ionization mass spectrometry (AIMS) has been developing explosively since its first debut. The ionization process was hence able to be achieved under atmospheric pressure, facilitating on-site field analysis in a variety of areas, such as clinical diagnosis, metabolic phenotyping, and surface analysis. As part of the ambitious goal of making MS a general device that can be used in everyday life, lots of efforts have been paid to miniaturize the ionization source. This review discusses avant-garde sources that could be entirely hand-held without any accessories. The structure and applications of the devices are described in detail as well. They could be expediently used in real-time and on-site analysis, presenting a great future potential for the routinizing of MS.
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Affiliation(s)
- Jinghan Fan
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Wenbo Ma
- State Key Laboratory of High-Efficiency Utilization of Coal and Green Chemical Engineering, College of Chemistry and Chemical Engineering, Ningxia University, Yinchuan, 750021, China
| | - Yile Yu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuze Li
- State Key Laboratory of High-Efficiency Utilization of Coal and Green Chemical Engineering, College of Chemistry and Chemical Engineering, Ningxia University, Yinchuan, 750021, China.
| | - Zongxiu Nie
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of High-Efficiency Utilization of Coal and Green Chemical Engineering, College of Chemistry and Chemical Engineering, Ningxia University, Yinchuan, 750021, China.
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Vahur S, Treshchalov A, Lohmus R, Teearu A, Niman K, Hiiop H, Kikas J, Leito I. Laser-based analytical techniques in cultural heritage science - Tutorial review. Anal Chim Acta 2024; 1292:342107. [PMID: 38309841 DOI: 10.1016/j.aca.2023.342107] [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: 08/05/2023] [Revised: 12/01/2023] [Accepted: 12/02/2023] [Indexed: 02/05/2024]
Abstract
This tutorial review combines the fundamentals of the design and operation of lasers with their usage in applications related to conservation and cultural heritage (CH) science - as components of analytical devices for the study of the chemical composition of materials. The development of laser instruments and their fundamental physical background, including a short explanation of their properties and parameters, are briefly summarised, and an overview of different laser-based analytical techniques is given. The analytical techniques covered in this tutorial are divided into three groups based on their technical aspects and properties: (1) vibrational spectroscopy, (2) elemental analysis, and (3) different molecular mass spectrometric techniques.
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Affiliation(s)
- Signe Vahur
- Institute of Chemistry, University of Tartu, Ravila 14A, 50411, Tartu, Estonia.
| | - Alexey Treshchalov
- Institute of Physics, University of Tartu, W. Ostwaldi 1, 50411, Tartu, Estonia
| | - Rynno Lohmus
- Institute of Physics, University of Tartu, W. Ostwaldi 1, 50411, Tartu, Estonia
| | - Anu Teearu
- Institute of Chemistry, University of Tartu, Ravila 14A, 50411, Tartu, Estonia
| | - Käthi Niman
- Department of Cultural Heritage and Conservation, Estonian Academy of Arts, Põhja pst 7, 10412, Tallinn, Estonia
| | - Hilkka Hiiop
- Institute of Chemistry, University of Tartu, Ravila 14A, 50411, Tartu, Estonia; Department of Cultural Heritage and Conservation, Estonian Academy of Arts, Põhja pst 7, 10412, Tallinn, Estonia
| | - Jaak Kikas
- Institute of Physics, University of Tartu, W. Ostwaldi 1, 50411, Tartu, Estonia
| | - Ivo Leito
- Institute of Chemistry, University of Tartu, Ravila 14A, 50411, Tartu, Estonia
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Manoli E, Higginson J, Tolley N, Darzi A, Kinross J, Temelkuran B, Takats Z. Human robotic surgery with intraoperative tissue identification using rapid evaporation ionisation mass spectrometry. Sci Rep 2024; 14:1027. [PMID: 38200062 PMCID: PMC10781715 DOI: 10.1038/s41598-023-50942-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 12/28/2023] [Indexed: 01/12/2024] Open
Abstract
Instantaneous, continuous, and reliable information on the molecular biology of surgical target tissue could significantly contribute to the precision, safety, and speed of the intervention. In this work, we introduced a methodology for chemical tissue identification in robotic surgery using rapid evaporative ionisation mass spectrometry. We developed a surgical aerosol evacuation system that is compatible with a robotic platform enabling consistent intraoperative sample collection and assessed the feasibility of this platform during head and neck surgical cases, using two different surgical energy devices. Our data showed specific, characteristic lipid profiles associated with the tissue type including various ceramides, glycerophospholipids, and glycerolipids, as well as different ion formation mechanisms based on the energy device used. This platform allows continuous and accurate intraoperative mass spectrometry-based identification of ablated/resected tissue and in combination with robotic registration of images, time, and anatomical positions can improve the current robot-assisted surgical platforms and guide surgical strategy.
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Affiliation(s)
- Eftychios Manoli
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - James Higginson
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Neil Tolley
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Ara Darzi
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - James Kinross
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Burak Temelkuran
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- The Hamlyn Centre for Robotic Surgery, Imperial College London, London, UK
| | - Zoltan Takats
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
- Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Univ. Lille, INSERM U1192, Lille, France.
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8
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Vlocskó M, Piffkó J, Janovszky Á. Intraoperative Assessment of Resection Margin in Oral Cancer: The Potential Role of Spectroscopy. Cancers (Basel) 2023; 16:121. [PMID: 38201548 PMCID: PMC10777979 DOI: 10.3390/cancers16010121] [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: 10/25/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 01/12/2024] Open
Abstract
In parallel with the increasing number of oncological cases, the need for faster and more efficient diagnostic tools has also appeared. Different diagnostic approaches are available, such as radiological imaging or histological staining methods, but these do not provide adequate information regarding the resection margin, intraoperatively, or are time consuming. The purpose of this review is to summarize the current knowledge on spectrometric diagnostic modalities suitable for intraoperative use, with an emphasis on their relevance in the management of oral cancer. The literature agrees on the sensitivity, specificity, and accuracy of spectrometric diagnostic modalities, but further long-term prospective, multicentric clinical studies are needed, which may standardize the intraoperative assessment of the resection margin and the use of real-time spectroscopic approaches.
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Affiliation(s)
| | | | - Ágnes Janovszky
- Department of Oral and Maxillofacial Surgery, Albert Szent-Györgyi Medical School, University of Szeged, Kálvária 57, H-6725 Szeged, Hungary; (M.V.); (J.P.)
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Kaynar G, Cakmakci D, Bund C, Todeschi J, Namer IJ, Cicek AE. PiDeeL: metabolic pathway-informed deep learning model for survival analysis and pathological classification of gliomas. Bioinformatics 2023; 39:btad684. [PMID: 37952175 PMCID: PMC10663986 DOI: 10.1093/bioinformatics/btad684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/19/2023] [Accepted: 11/10/2023] [Indexed: 11/14/2023] Open
Abstract
MOTIVATION Online assessment of tumor characteristics during surgery is important and has the potential to establish an intra-operative surgeon feedback mechanism. With the availability of such feedback, surgeons could decide to be more liberal or conservative regarding the resection of the tumor. While there are methods to perform metabolomics-based tumor pathology prediction, their model complexity predictive performance is limited by the small dataset sizes. Furthermore, the information conveyed by the feedback provided on the tumor tissue could be improved both in terms of content and accuracy. RESULTS In this study, we propose a metabolic pathway-informed deep learning model (PiDeeL) to perform survival analysis and pathology assessment based on metabolite concentrations. We show that incorporating pathway information into the model architecture substantially reduces parameter complexity and achieves better survival analysis and pathological classification performance. With these design decisions, we show that PiDeeL improves tumor pathology prediction performance of the state-of-the-art in terms of the Area Under the ROC Curve by 3.38% and the Area Under the Precision-Recall Curve by 4.06%. Similarly, with respect to the time-dependent concordance index (c-index), PiDeeL achieves better survival analysis performance (improvement of 4.3%) when compared to the state-of-the-art. Moreover, we show that importance analyses performed on input metabolite features as well as pathway-specific neurons of PiDeeL provide insights into tumor metabolism. We foresee that the use of this model in the surgery room will help surgeons adjust the surgery plan on the fly and will result in better prognosis estimates tailored to surgical procedures. AVAILABILITY AND IMPLEMENTATION The code is released at https://github.com/ciceklab/PiDeeL. The data used in this study are released at https://zenodo.org/record/7228791.
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Affiliation(s)
- Gun Kaynar
- Computer Engineering Department, Bilkent University, 06800 Ankara, Turkey
| | - Doruk Cakmakci
- School of Computer Science, McGill University, Montreal, QC, H3A 0E9, Canada
| | - Caroline Bund
- MNMS Platform, University Hospitals of Strasbourg, Strasbourg 67098, France
- ICube, University of Strasbourg, CNRS UMR, 7357, Strasbourg 67000, France
- Department of Nuclear Medicine and Molecular Imaging, ICANS, Strasbourg 67000, France
| | - Julien Todeschi
- Department of Neurosurgery, University Hospitals of Strasbourg, Strasbourg, 67091, France
| | - Izzie Jacques Namer
- MNMS Platform, University Hospitals of Strasbourg, Strasbourg 67098, France
- ICube, University of Strasbourg, CNRS UMR, 7357, Strasbourg 67000, France
- Department of Nuclear Medicine and Molecular Imaging, ICANS, Strasbourg 67000, France
| | - A Ercument Cicek
- Computer Engineering Department, Bilkent University, 06800 Ankara, Turkey
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, United States
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10
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Wang Z, Zhu H, Xiong W. Advances in mass spectrometry-based multi-scale metabolomic methodologies and their applications in biological and clinical investigations. Sci Bull (Beijing) 2023; 68:2268-2284. [PMID: 37666722 DOI: 10.1016/j.scib.2023.08.047] [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: 06/15/2023] [Revised: 07/25/2023] [Accepted: 08/22/2023] [Indexed: 09/06/2023]
Abstract
Metabolomics is a nascent field of inquiry that emerged in the late 20th century. It encompasses the comprehensive profiling of metabolites across a spectrum of organisms, ranging from bacteria and cells to tissues. The rapid evolution of analytical methods and data analysis has greatly accelerated progress in this dynamic discipline over recent decades. Sophisticated techniques such as liquid chromatograph mass spectrometry (MS), gas chromatograph MS, capillary electrophoresis MS, and nuclear magnetic resonance serve as the cornerstone of metabolomic analysis. Building upon these methods, a plethora of modifications and combinations have emerged to propel the advancement of metabolomics. Despite this progress, scrutinizing metabolism at the single-cell or single-organelle level remains an arduous task over the decades. Some of the most thrilling advancements, such as single-cell and single-organelle metabolic profiling techniques, offer profound insights into the intricate mechanisms within cells and organelles. This allows for a comprehensive study of metabolic heterogeneity and its pivotal role in multiple biological processes. The progress made in MS imaging has enabled high-resolution in situ metabolic profiling of tissue sections and even individual cells. Spatial reconstruction techniques enable the direct representation of metabolic distribution and alteration in three-dimensional space. The application of novel metabolomic techniques has led to significant breakthroughs in biological and clinical studies, including the discovery of novel metabolic pathways, determination of cell fate in differentiation, anti-aging intervention through modulating metabolism, metabolomics-based clinicopathologic analysis, and surgical decision-making based on on-site intraoperative metabolic analysis. This review presents a comprehensive overview of both conventional and innovative metabolomic techniques, highlighting their applications in groundbreaking biological and clinical studies.
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Affiliation(s)
- Ziyi Wang
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Hefei National Research Center for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China
| | - Hongying Zhu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Hefei National Research Center for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China; Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing, Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China; CAS Key Laboratory of Brain Function and Disease, Hefei 230026, China; Anhui Province Key Laboratory of Biomedical Aging Research, Hefei 230026, China.
| | - Wei Xiong
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Hefei National Research Center for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China; Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing, Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China; CAS Key Laboratory of Brain Function and Disease, Hefei 230026, China; Anhui Province Key Laboratory of Biomedical Aging Research, Hefei 230026, China.
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11
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Ledoux L, Zirem Y, Renaud F, Duponchel L, Salzet M, Ogrinc N, Fournier I. Comparing MS imaging of lipids by WALDI and MALDI: two technologies for evaluating a common ground truth in MS imaging. Analyst 2023; 148:4982-4986. [PMID: 37740342 DOI: 10.1039/d3an01096a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/24/2023]
Abstract
In this study, we conducted a direct comparison of water-assisted laser desorption ionization (WALDI) and matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging, with MALDI serving as the benchmark for label-free molecular tissue analysis in biomedical research. Specifically, we investigated the lipidomic profiles of several biological samples and calculated the similarity of detected peaks and Pearson's correlation of spectral profile intensities between the two techniques. We show that, overall, MALDI MS and WALDI MS present very close lipidomic analyses and that the highest similarity is obtained for the norharmane MALDI matrix. Indeed, for norharmane in negative ion mode, the lipidomic spectra revealed 100% similarity of detected peaks and over 0.90 intensity correlation between both technologies for five samples. The MALDI-MSI positive ion lipid spectra displayed more than 83% similarity of detected peaks compared to those of WALDI-MSI. However, we observed a lower percentage (77%) of detected peaks when comparing WALDI-MSI with MALDI-MSI due to the rich WALDI-MSI lipid spectra. Despite this difference, the global lipidomic spectra showed high consistency between the two technologies, indicating that they are governed by similar processes. Thanks to this similarity, we can increase datasets by including data from both modalities to either co-train classification models or obtain cross-interrogation.
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Affiliation(s)
- Léa Ledoux
- Univ. Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France.
| | - Yanis Zirem
- Univ. Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France.
| | - Florence Renaud
- Unité mixte SIRIC CURAMUS et 938, Inserm. Université Paris Sorbonne, France
| | | | - Michel Salzet
- Univ. Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France.
- Institut Universitaire de France (IUF), Paris, France
| | - Nina Ogrinc
- Univ. Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France.
| | - Isabelle Fournier
- Univ. Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France.
- Institut Universitaire de France (IUF), Paris, France
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12
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P Gomes PW, Zuffa S, Bauermeister A, Caraballo-Rodríguez AM, Zhao HN, Mannochio-Russo H, Dogo-Isonagie C, Patel O, Pimenta P, Gronlund J, Lavender S, Pilch S, Maloney V, North M, Dorrestein PC. Ex vivo study of molecular changes of stained teeth following hydrogen peroxide and peroxymonosulfate treatments. Sci Rep 2023; 13:16349. [PMID: 37770593 PMCID: PMC10539445 DOI: 10.1038/s41598-023-43201-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 09/21/2023] [Indexed: 09/30/2023] Open
Abstract
White teeth can give confidence and tend to be associated with a healthier lifestyle in modern society. Therefore, tooth-bleaching strategies have been developed, including the use of hydrogen peroxide. Recently, peroxymonosulfate has been introduced as an alternative bleaching method to hydrogen peroxide. Although both chemicals are oxidizing agents, their effects on the molecular composition of the stained teeth are yet unknown. In this study, the molecular profiles of teeth bleached with hydrogen peroxide and peroxymonosulfate were compared using Liquid Chromatography-Tandem Mass Spectrometry. Statistical analyses were used to assess the samples. In addition, reference spectral libraries and in silico tools were used to perform metabolite annotation. Overall, principal component analysis showed a strong separation between control and hydrogen peroxide and peroxymonosulfate samples (p < 0.001). The analysis of molecular changes revealed amino acids and dipeptides in stained teeth samples after hydrogen peroxide and peroxymonosulfate treatments. Noteworthy, the two bleaching methods led to distinct molecular profiles. For example, diterpenoids were more prevalent after peroxymonosulfate treatment, while a greater abundance of alkaloids was detected after hydrogen peroxide treatment. Whereas non-bleached samples (controls) showed mainly lipids. Therefore, this study shows how two different tooth-whitening peroxides could affect the molecular profiles of human teeth.
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Affiliation(s)
- Paulo Wender P Gomes
- Skaggs School of Pharmacy and Pharmaceutical Sciences, Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Simone Zuffa
- Skaggs School of Pharmacy and Pharmaceutical Sciences, Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Anelize Bauermeister
- Skaggs School of Pharmacy and Pharmaceutical Sciences, Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Andrés Mauricio Caraballo-Rodríguez
- Skaggs School of Pharmacy and Pharmaceutical Sciences, Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Haoqi Nina Zhao
- Skaggs School of Pharmacy and Pharmaceutical Sciences, Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Helena Mannochio-Russo
- Skaggs School of Pharmacy and Pharmaceutical Sciences, Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA
| | | | - Om Patel
- Colgate-Palmolive, Global Technology Center, Piscataway, NJ, USA
| | - Paloma Pimenta
- Colgate-Palmolive, Global Technology Center, Piscataway, NJ, USA
| | | | - Stacey Lavender
- Colgate-Palmolive, Global Technology Center, Piscataway, NJ, USA
| | - Shira Pilch
- Colgate-Palmolive, Global Technology Center, Piscataway, NJ, USA
| | - Venda Maloney
- Colgate-Palmolive, Global Technology Center, Piscataway, NJ, USA
| | - Michael North
- Colgate-Palmolive, Global Technology Center, Piscataway, NJ, USA
| | - Pieter C Dorrestein
- Skaggs School of Pharmacy and Pharmaceutical Sciences, Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA.
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA.
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13
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Sarkar S, Squire A, Diab H, Rahman MK, Perdomo A, Awosile B, Calle A, Thompson J. Effect of Tryptic Digestion on Sensitivity and Specificity in MALDI-TOF-Based Molecular Diagnostics through Machine Learning. SENSORS (BASEL, SWITZERLAND) 2023; 23:8042. [PMID: 37836873 PMCID: PMC10575185 DOI: 10.3390/s23198042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 09/15/2023] [Accepted: 09/21/2023] [Indexed: 10/15/2023]
Abstract
The digestion of protein into peptide fragments reduces the size and complexity of protein molecules. Peptide fragments can be analyzed with higher sensitivity (often > 102 fold) and resolution using MALDI-TOF mass spectrometers, leading to improved pattern recognition by common machine learning algorithms. In turn, enhanced sensitivity and specificity for bacterial sorting and/or disease diagnosis may be obtained. To test this hypothesis, four exemplar case studies have been pursued in which samples are sorted into dichotomous groups by machine learning (ML) software based on MALDI-TOF spectra. Samples were analyzed in 'intact' mode in which the proteins present in the sample were not digested with protease prior to MALDI-TOF analysis and separately after the standard overnight tryptic digestion of the same samples. For each case, sensitivity (sens), specificity (spc), and the Youdin index (J) were used to assess the ML model performance. The proteolytic digestion of samples prior to MALDI-TOF analysis substantially enhanced the sensitivity and specificity of dichotomous sorting. Two exceptions were when substantial differences in chemical composition between the samples were present and, in such cases, both 'intact' and 'digested' protocols performed similarly. The results suggest proteolytic digestion prior to analysis can improve sorting in MALDI/ML-based workflows and may enable improved biomarker discovery. However, when samples are easily distinguishable protein digestion is not necessary to obtain useful diagnostic results.
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Affiliation(s)
| | | | | | | | | | | | | | - Jonathan Thompson
- School of Veterinary Medicine, Texas Tech University, 7671 Evans Dr., Amarillo, TX 79106, USA; (S.S.); (A.S.); (M.K.R.)
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14
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Zhang F, Xu J, Yue Y, Wang Y, Sun J, Song D, Zhang C, Qu L, Zhu S, Zhang J, Yang B. Three-dimensional histological electrophoresis enables fast automatic distinguishment of cancer margins and lymph node metastases. SCIENCE ADVANCES 2023; 9:eadg2690. [PMID: 37390200 PMCID: PMC10313175 DOI: 10.1126/sciadv.adg2690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 05/25/2023] [Indexed: 07/02/2023]
Abstract
Tissue diagnosis is important during surgical excision of solid tumors for margin evaluation. Conventional histopathologic methods rely heavily on image-based visual diagnosis by specialized pathologists, which can be time-consuming and subjective. We report a three-dimensional (3D) histological electrophoresis system for rapid labeling and separation of the proteins within tissue sections, providing a more precise assessment of tumor-positive margin in surgically resected tissues. The 3D histological electrophoresis system uses a tumor-seeking dye labeling strategy to visualize the distribution of tumor-specific proteins within sections and a tumor finder that automatically predicts the tumor contour. We successfully demonstrated the system's capability to predict the tumor contours from five murine xenograft models and distinguish the tumor-invaded region of sentinel lymph nodes. Specifically, we used the system to accurately assess tumor-positive margins from 14 patients with cancer. Our 3D histological electrophoresis system serves as an intraoperative tissue assessment technology for more accurate and automatic pathologic diagnosis.
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Affiliation(s)
- Feiran Zhang
- State Key Laboratory of Supramolecular Structure and Materials, Center for Supramolecular Chemical Biology, College of Chemistry, Jilin University, Changchun 130012, P. R. China
- Joint Laboratory of Opto-Functional Theranostics in Medicine and Chemistry, The First Hospital of Jilin University, Changchun 130021, P. R. China
| | - Jiajun Xu
- State Key Laboratory of Supramolecular Structure and Materials, Center for Supramolecular Chemical Biology, College of Chemistry, Jilin University, Changchun 130012, P. R. China
- Joint Laboratory of Opto-Functional Theranostics in Medicine and Chemistry, The First Hospital of Jilin University, Changchun 130021, P. R. China
| | - Ying Yue
- State Key Laboratory of Supramolecular Structure and Materials, Center for Supramolecular Chemical Biology, College of Chemistry, Jilin University, Changchun 130012, P. R. China
| | - Yajun Wang
- State Key Laboratory of Supramolecular Structure and Materials, Center for Supramolecular Chemical Biology, College of Chemistry, Jilin University, Changchun 130012, P. R. China
- Joint Laboratory of Opto-Functional Theranostics in Medicine and Chemistry, The First Hospital of Jilin University, Changchun 130021, P. R. China
| | - Jianing Sun
- School of Mathematics and Statistics, Northeast Normal University, Changchun 130024, P. R. China
| | - Dong Song
- Department of Breast Surgery, The First Hospital of Jilin University, Changchun 130021, P. R. China
| | - Chengbin Zhang
- Department of Pathology, The First Hospital of Jilin University, Changchun 130021, P. R. China
| | - Limei Qu
- Department of Pathology, The First Hospital of Jilin University, Changchun 130021, P. R. China
| | - Shoujun Zhu
- State Key Laboratory of Supramolecular Structure and Materials, Center for Supramolecular Chemical Biology, College of Chemistry, Jilin University, Changchun 130012, P. R. China
- Joint Laboratory of Opto-Functional Theranostics in Medicine and Chemistry, The First Hospital of Jilin University, Changchun 130021, P. R. China
| | - Junhu Zhang
- State Key Laboratory of Supramolecular Structure and Materials, Center for Supramolecular Chemical Biology, College of Chemistry, Jilin University, Changchun 130012, P. R. China
- Joint Laboratory of Opto-Functional Theranostics in Medicine and Chemistry, The First Hospital of Jilin University, Changchun 130021, P. R. China
| | - Bai Yang
- State Key Laboratory of Supramolecular Structure and Materials, Center for Supramolecular Chemical Biology, College of Chemistry, Jilin University, Changchun 130012, P. R. China
- Joint Laboratory of Opto-Functional Theranostics in Medicine and Chemistry, The First Hospital of Jilin University, Changchun 130021, P. R. China
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15
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King ME, Lin M, Spradlin M, Eberlin LS. Advances and Emerging Medical Applications of Direct Mass Spectrometry Technologies for Tissue Analysis. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2023; 16:1-25. [PMID: 36944233 DOI: 10.1146/annurev-anchem-061020-015544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Offering superb speed, chemical specificity, and analytical sensitivity, direct mass spectrometry (MS) technologies are highly amenable for the molecular analysis of complex tissues to aid in disease characterization and help identify new diagnostic, prognostic, and predictive markers. By enabling detection of clinically actionable molecular profiles from tissues and cells, direct MS technologies have the potential to guide treatment decisions and transform sample analysis within clinical workflows. In this review, we highlight recent health-related developments and applications of direct MS technologies that exhibit tangible potential to accelerate clinical research and disease diagnosis, including oncological and neurodegenerative diseases and microbial infections. We focus primarily on applications that employ direct MS technologies for tissue analysis, including MS imaging technologies to map spatial distributions of molecules in situ as well as handheld devices for rapid in vivo and ex vivo tissue analysis.
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Affiliation(s)
- Mary E King
- Department of Chemistry, The University of Texas at Austin, Austin, Texas, USA;
- Department of Surgery, Baylor College of Medicine, Houston, Texas, USA;
| | - Monica Lin
- Department of Chemistry, The University of Texas at Austin, Austin, Texas, USA;
| | - Meredith Spradlin
- Department of Chemistry, The University of Texas at Austin, Austin, Texas, USA;
| | - Livia S Eberlin
- Department of Surgery, Baylor College of Medicine, Houston, Texas, USA;
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16
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De Spiegeleer M, Plekhova V, Geltmeyer J, Schoolaert E, Pomian B, Singh V, Wijnant K, De Windt K, Paukku V, De Loof A, Gies I, Michels N, De Henauw S, De Graeve M, De Clerck K, Vanhaecke L. Point-of-care applicable metabotyping using biofluid-specific electrospun MetaSAMPs directly amenable to ambient LA-REIMS. SCIENCE ADVANCES 2023; 9:eade9933. [PMID: 37294759 PMCID: PMC10256167 DOI: 10.1126/sciadv.ade9933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 05/05/2023] [Indexed: 06/11/2023]
Abstract
In recent years, ambient ionization mass spectrometry (AIMS) including laser ablation rapid evaporation IMS, has enabled direct biofluid metabolome analysis. AIMS procedures are, however, still hampered by both analytical, i.e., matrix effects, and practical, i.e., sample transport stability, drawbacks that impede metabolome coverage. In this study, we aimed at developing biofluid-specific metabolome sampling membranes (MetaSAMPs) that offer a directly applicable and stabilizing substrate for AIMS. Customized rectal, salivary, and urinary MetaSAMPs consisting of electrospun (nano)fibrous membranes of blended hydrophilic (polyvinylpyrrolidone and polyacrylonitrile) and lipophilic (polystyrene) polymers supported metabolite absorption, adsorption, and desorption. Moreover, MetaSAMP demonstrated superior metabolome coverage and transport stability compared to crude biofluid analysis and was successfully validated in two pediatric cohorts (MetaBEAse, n = 234 and OPERA, n = 101). By integrating anthropometric and (patho)physiological with MetaSAMP-AIMS metabolome data, we obtained substantial weight-driven predictions and clinical correlations. In conclusion, MetaSAMP holds great clinical application potential for on-the-spot metabolic health stratification.
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Affiliation(s)
- Margot De Spiegeleer
- Laboratory of Integrative Metabolomics, Department of Translational Physiology, Infectiology and Public Health, Ghent University, Ghent, Belgium
| | - Vera Plekhova
- Laboratory of Integrative Metabolomics, Department of Translational Physiology, Infectiology and Public Health, Ghent University, Ghent, Belgium
| | - Jozefien Geltmeyer
- Department of Materials, Textiles and Chemical Engineering, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
| | - Ella Schoolaert
- Department of Materials, Textiles and Chemical Engineering, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
| | - Beata Pomian
- Laboratory of Integrative Metabolomics, Department of Translational Physiology, Infectiology and Public Health, Ghent University, Ghent, Belgium
| | - Varoon Singh
- Laboratory of Integrative Metabolomics, Department of Translational Physiology, Infectiology and Public Health, Ghent University, Ghent, Belgium
| | - Kathleen Wijnant
- Laboratory of Integrative Metabolomics, Department of Translational Physiology, Infectiology and Public Health, Ghent University, Ghent, Belgium
| | - Kimberly De Windt
- Laboratory of Integrative Metabolomics, Department of Translational Physiology, Infectiology and Public Health, Ghent University, Ghent, Belgium
| | - Volter Paukku
- Laboratory of Integrative Metabolomics, Department of Translational Physiology, Infectiology and Public Health, Ghent University, Ghent, Belgium
| | - Alexander De Loof
- Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Inge Gies
- Department of Pediatrics, Free University of Brussels (VUB), University Hospital Brussels (UZ Brussel), Brussels, Belgium
| | - Nathalie Michels
- Department of Developmental, Personality and Social Psychology, Ghent University, Ghent, Belgium
| | - Stefaan De Henauw
- Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Marilyn De Graeve
- Laboratory of Integrative Metabolomics, Department of Translational Physiology, Infectiology and Public Health, Ghent University, Ghent, Belgium
| | - Karen De Clerck
- Department of Materials, Textiles and Chemical Engineering, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
| | - Lynn Vanhaecke
- Laboratory of Integrative Metabolomics, Department of Translational Physiology, Infectiology and Public Health, Ghent University, Ghent, Belgium
- Institute for Global Food Security, School of Biological Sciences, Queen’s University, Belfast, UK
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17
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Shankar V, Vijayalakshmi K, Nolley R, Sonn GA, Kao CS, Zhao H, Wen R, Eberlin LS, Tibshirani R, Zare RN, Brooks JD. Distinguishing Renal Cell Carcinoma From Normal Kidney Tissue Using Mass Spectrometry Imaging Combined With Machine Learning. JCO Precis Oncol 2023; 7:e2200668. [PMID: 37285559 PMCID: PMC10309512 DOI: 10.1200/po.22.00668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 02/26/2023] [Accepted: 04/10/2023] [Indexed: 06/09/2023] Open
Abstract
PURPOSE Accurately distinguishing renal cell carcinoma (RCC) from normal kidney tissue is critical for identifying positive surgical margins (PSMs) during partial and radical nephrectomy, which remains the primary intervention for localized RCC. Techniques that detect PSM with higher accuracy and faster turnaround time than intraoperative frozen section (IFS) analysis can help decrease reoperation rates, relieve patient anxiety and costs, and potentially improve patient outcomes. MATERIALS AND METHODS Here, we extended our combined desorption electrospray ionization mass spectrometry imaging (DESI-MSI) and machine learning methodology to identify metabolite and lipid species from tissue surfaces that can distinguish normal tissues from clear cell RCC (ccRCC), papillary RCC (pRCC), and chromophobe RCC (chRCC) tissues. RESULTS From 24 normal and 40 renal cancer (23 ccRCC, 13 pRCC, and 4 chRCC) tissues, we developed a multinomial lasso classifier that selects 281 total analytes from over 27,000 detected molecular species that distinguishes all histological subtypes of RCC from normal kidney tissues with 84.5% accuracy. On the basis of independent test data reflecting distinct patient populations, the classifier achieves 85.4% and 91.2% accuracy on a Stanford test set (20 normal and 28 RCC) and a Baylor-UT Austin test set (16 normal and 41 RCC), respectively. The majority of the model's selected features show consistent trends across data sets affirming its stable performance, where the suppression of arachidonic acid metabolism is identified as a shared molecular feature of ccRCC and pRCC. CONCLUSION Together, these results indicate that signatures derived from DESI-MSI combined with machine learning may be used to rapidly determine surgical margin status with accuracies that meet or exceed those reported for IFS.
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Affiliation(s)
- Vishnu Shankar
- Program in Immunology, Stanford University School of Medicine, Stanford, CA
| | | | - Rosalie Nolley
- Department of Urology, Stanford University School of Medicine, Stanford, CA
| | - Geoffrey A. Sonn
- Department of Urology, Stanford University School of Medicine, Stanford, CA
| | - Chia-Sui Kao
- Department of Pathology, Stanford University School of Medicine, Stanford, CA
| | - Hongjuan Zhao
- Department of Urology, Stanford University School of Medicine, Stanford, CA
| | - Ru Wen
- Department of Urology, Stanford University School of Medicine, Stanford, CA
| | | | - Robert Tibshirani
- Department of Biomedical Data Science, and Statistics, Stanford University, Stanford, CA
| | | | - James D. Brooks
- Department of Urology, Stanford University School of Medicine, Stanford, CA
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18
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Stadlhofer R, Moritz M, Fuh MM, Heeren J, Zech H, Clauditz TS, Schlüter H, Betz CS, Eggert D, Böttcher A, Hahn J. Lipidome Analysis of Oropharyngeal Tumor Tissues Using Nanosecond Infrared Laser (NIRL) Tissue Sampling and Subsequent Mass Spectrometry. Int J Mol Sci 2023; 24:ijms24097820. [PMID: 37175533 PMCID: PMC10178251 DOI: 10.3390/ijms24097820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 04/16/2023] [Accepted: 04/21/2023] [Indexed: 05/15/2023] Open
Abstract
Ultrashort pulse infrared lasers can simultaneously sample and homogenize biological tissue using desorption by impulsive vibrational excitation (DIVE). With growing attention on alterations in lipid metabolism in malignant disease, mass spectrometry (MS)-based lipidomic analysis has become an emerging topic in cancer research. In this pilot study, we investigated the feasibility of tissue sampling with a nanosecond infrared laser (NIRL) for the subsequent lipidomic analysis of oropharyngeal tissues, and its potential to discriminate oropharyngeal squamous cell carcinoma (OPSCC) from non-tumorous oropharyngeal tissue. Eleven fresh frozen oropharyngeal tissue samples were ablated. The produced aerosols were collected by a glass fiber filter, and the lipidomes were analyzed with mass spectrometry. Data was evaluated by principal component analysis and Welch's t-tests. Lipid profiles comprised 13 lipid classes and up to 755 lipid species. We found significant inter- and intrapatient alterations in lipid profiles for tumor and non-tumor samples (p-value < 0.05, two-fold difference). Thus, NIRL tissue sampling with consecutive MS lipidomic analysis is a feasible and promising approach for the differentiation of OPSCC and non-tumorous oropharyngeal tissue and may provide new insights into lipid composition alterations in OPSCC.
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Affiliation(s)
- Rupert Stadlhofer
- Department of Otorhinolaryngology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Manuela Moritz
- Section/Core Facility Mass Spectrometric Proteomics, Diagnostic Center, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Marceline M Fuh
- Department of Biochemistry and Molecular Cell Biology, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Jörg Heeren
- Department of Biochemistry and Molecular Cell Biology, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Henrike Zech
- Department of Otorhinolaryngology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
- Mildred Scheel Cancer Career Center HaTriCS4, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Till S Clauditz
- Department of Pathology, Diagnostic Center, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Hartmut Schlüter
- Section/Core Facility Mass Spectrometric Proteomics, Diagnostic Center, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Christian S Betz
- Department of Otorhinolaryngology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Dennis Eggert
- Department of Otorhinolaryngology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Arne Böttcher
- Department of Otorhinolaryngology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Jan Hahn
- Section/Core Facility Mass Spectrometric Proteomics, Diagnostic Center, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
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19
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Mason SE, Manoli E, Alexander JL, Poynter L, Ford L, Paizs P, Adebesin A, McKenzie JS, Rosini F, Goldin R, Darzi A, Takats Z, Kinross JM. Lipidomic Profiling of Colorectal Lesions for Real-Time Tissue Recognition and Risk-Stratification Using Rapid Evaporative Ionization Mass Spectrometry. Ann Surg 2023; 277:e569-e577. [PMID: 34387206 DOI: 10.1097/sla.0000000000005164] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Rapid evaporative ionization mass spectrometry (REIMS) is a metabolomic technique analyzing tissue metabolites, which can be applied intraoperatively in real-time. The objective of this study was to profile the lipid composition of colorectal tissues using REIMS, assessing its accuracy for real-time tissue recognition and risk-stratification. SUMMARY BACKGROUND DATA Metabolic dysregulation is a hallmark feature of carcinogenesis; however, it remains unknown if this can be leveraged for real-time clinical applications in colorectal disease. METHODS Patients undergoing colorectal resection were included, with carcinoma, adenoma and paired-normal mucosa sampled. Ex vivo analysis with REIMS was conducted using monopolar diathermy, with the aerosol aspirated into a Xevo G2S QToF mass spectrometer. Negatively charged ions over 600 to 1000 m/z were used for univariate and multivariate functions including linear discriminant analysis. RESULTS A total of 161 patients were included, generating 1013 spectra. Unique lipidomic profiles exist for each tissue type, with REIMS differentiating samples of carcinoma, adenoma, and normal mucosa with 93.1% accuracy and 96.1% negative predictive value for carcinoma. Neoplasia (carcinoma or adenoma) could be predicted with 96.0% accuracy and 91.8% negative predictive value. Adenomas can be risk-stratified by grade of dysplasia with 93.5% accuracy, but not histological subtype. The structure of 61 lipid metabolites was identified, revealing that during colorectal carcinogenesis there is progressive increase in relative abundance of phosphatidylglycerols, sphingomyelins, and mono-unsaturated fatty acid-containing phospholipids. CONCLUSIONS The colorectal lipidome can be sampled by REIMS and leveraged for accurate real-time tissue recognition, in addition to riskstratification of colorectal adenomas. Unique lipidomic features associated with carcinogenesis are described.
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Affiliation(s)
- Sam E Mason
- Department of Surgery and Cancer, Imperial College, London
| | | | - James L Alexander
- Department of Metabolism, Digestion and Reproduction, Imperial College, London; and
| | - Liam Poynter
- Department of Surgery and Cancer, Imperial College, London
| | - Lauren Ford
- Department of Surgery and Cancer, Imperial College, London
| | - Petra Paizs
- Department of Metabolism, Digestion and Reproduction, Imperial College, London; and
| | - Afeez Adebesin
- Department of Surgery and Cancer, Imperial College, London
| | - James S McKenzie
- Department of Metabolism, Digestion and Reproduction, Imperial College, London; and
| | | | - Rob Goldin
- Department of Metabolism, Digestion and Reproduction, Imperial College, London; and
| | - Ara Darzi
- Department of Surgery and Cancer, Imperial College, London
| | - Zoltan Takats
- Department of Metabolism, Digestion and Reproduction, Imperial College, London; and
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20
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Applications of Mass Spectrometry in Dentistry. Biomedicines 2023; 11:biomedicines11020286. [PMID: 36830822 PMCID: PMC9953492 DOI: 10.3390/biomedicines11020286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 01/16/2023] [Accepted: 01/18/2023] [Indexed: 01/21/2023] Open
Abstract
Mass Spectrometry (MS) is one of the fastest-developing methods in analytical instrumentation. As a highly sensitive, universal detector, it can identify known and unknown compounds, which can indeed be found in a minimal concentration. This review aims to highlight the significant milestones in MS applications in dentistry during recent decades. MS can be applied in three different fields of dentistry: (1) in research of dental materials and chemical agents, (2) in laboratory analysis of biospecimens, and (3) as a real-time diagnostic tool in service of oral surgery and pathology. MS applications on materials and agents may focus on numerous aspects, such as their clinical behavior, possible toxicity, or antimicrobial properties. MS is also a valuable, non-invasive tool for biomarkers' detection in saliva and has found great application in -omics technologies as it achieves efficient structure-finding in metabolites. As metabolites are located beyond the central dogma, this technique can provide a complete understanding of cellular functions. Thus, it is possible to determine the biological profile in normal and pathological conditions, detect various oral or systematic diseases and conditions, and predict their course. Lastly, some promising advances concerning the surgical approach to potentially oral malignant or malignant disorders exist. This breakthrough method provides a comprehensive approach to dental materials research and biomarker discovery in dental and craniofacial tissues. The current availability of various 'OMIC' approaches paves the way for individualized dentistry and provides suggestions for clinical applications in the point-of-care hubs.
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21
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Ogrinc N, Chaillou P, Kruszewski A, Duriez C, Salzet M, Fournier I. Ambient Mass Spectrometry Imaging by Water-Assisted Laser Desorption/Ionization for Ex Vivo and in Vivo Applications. Methods Mol Biol 2023; 2688:83-94. [PMID: 37410286 DOI: 10.1007/978-1-0716-3319-9_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
Abstract
Water-assisted laser desorption/ionization mass spectrometry (WALDI-MS), also known as SpiderMass, is an emerging ambient ionization technique for in vivo and real-time analysis. It employs a remote infrared (IR) laser tuned to excite the most intense vibrational band (O-H) of water. The water molecules act as an endogenous matrix leading to the desorption/ionization of a variety of biomolecules from tissues, particularly metabolites and lipids. WALDI-MS was recently advanced into an imaging modality for ex vivo 2D sections and 3D in vivo real-time imaging. Here, we describe the methodological aspects for performing 2D and 3D imaging experiments with WALDI-MSI and the parameters for optimizing the image acquisition.
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Affiliation(s)
- Nina Ogrinc
- Université de Lille, Inserm, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, Lille, France
| | - Paul Chaillou
- Université de Lille, Inserm, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, Lille, France
| | - Alexandre Kruszewski
- Université de Lille, Inserm, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, Lille, France
| | - Cristian Duriez
- Université de Lille, Inserm, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, Lille, France
| | - Michel Salzet
- Université de Lille, Inserm, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, Lille, France
| | - Isabelle Fournier
- Université de Lille, Inserm, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, Lille, France.
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22
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Katz L, Woolman M, Kiyota T, Pires L, Zaidi M, Hofer SO, Leong W, Wouters BG, Ghazarian D, Chan AW, Ginsberg HJ, Aman A, Wilson BC, Berman HK, Zarrine-Afsar A. Picosecond Infrared Laser Mass Spectrometry Identifies a Metabolite Array for 10 s Diagnosis of Select Skin Cancer Types: A Proof-of-Concept Feasibility Study. Anal Chem 2022; 94:16821-16830. [DOI: 10.1021/acs.analchem.2c03918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Affiliation(s)
- Lauren Katz
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
| | - Michael Woolman
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
| | - Taira Kiyota
- Ontario Institute for Cancer Research (OICR), 661 University Ave Suite 510, Toronto, Ontario M5G 0A3, Canada
| | - Layla Pires
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, Ontario M5G 2C1, Canada
| | - Mark Zaidi
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
| | - Stefan O.P. Hofer
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, Ontario M5T 1P5, Canada
- Division of Plastic and Reconstructive Surgery, Department of Surgery and Surgical Oncology, University Health Network, University of Toronto. Toronto General Hospital, 200 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada
| | - Wey Leong
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, Ontario M5G 2C1, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, Ontario M5T 1P5, Canada
- Department of Surgical Oncology, Princess Margaret Cancer Centre, University Health Network, Toronto Ontario M5G 2C1, Canada
| | - Brad G. Wouters
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, Ontario M5G 2C1, Canada
| | - Danny Ghazarian
- Department of Laboratory Medicine and Pathobiology, University of Toronto and University Health Network, 200 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada
| | - An-Wen Chan
- Division of Dermatology, Department of Medicine, University of Toronto, Canada and Women’s College Research Institute, Women’s College Hospital, 76 Grenville St, Toronto, Ontario M5S 1B2, Canada
| | - Howard J. Ginsberg
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, Ontario M5T 1P5, Canada
- Keenan Research Center for Biomedical Science & the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 30 Bond Street, Toronto, Ontario M5B 1W8, Canada
| | - Ahmed Aman
- Ontario Institute for Cancer Research (OICR), 661 University Ave Suite 510, Toronto, Ontario M5G 0A3, Canada
- Leslie Dan, Faculty of Pharmacy, University of Toronto, 144 College St, Toronto, Ontario M5S 3M2, Canada
| | - Brian C. Wilson
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, Ontario M5G 2C1, Canada
| | - Hal K. Berman
- Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, Ontario M5G 2C1, Canada
- Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada
| | - Arash Zarrine-Afsar
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, Ontario M5T 1P5, Canada
- Keenan Research Center for Biomedical Science & the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 30 Bond Street, Toronto, Ontario M5B 1W8, Canada
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23
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Spatial analysis of the glioblastoma proteome reveals specific molecular signatures and markers of survival. Nat Commun 2022; 13:6665. [PMID: 36333286 PMCID: PMC9636229 DOI: 10.1038/s41467-022-34208-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 10/18/2022] [Indexed: 11/06/2022] Open
Abstract
Molecular heterogeneity is a key feature of glioblastoma that impedes patient stratification and leads to large discrepancies in mean patient survival. Here, we analyze a cohort of 96 glioblastoma patients with survival ranging from a few months to over 4 years. 46 tumors are analyzed by mass spectrometry-based spatially-resolved proteomics guided by mass spectrometry imaging. Integration of protein expression and clinical information highlights three molecular groups associated with immune, neurogenesis, and tumorigenesis signatures with high intra-tumoral heterogeneity. Furthermore, a set of proteins originating from reference and alternative ORFs is found to be statistically significant based on patient survival times. Among these proteins, a 5-protein signature is associated with survival. The expression of these 5 proteins is validated by immunofluorescence on an additional cohort of 50 patients. Overall, our work characterizes distinct molecular regions within glioblastoma tissues based on protein expression, which may help guide glioblastoma prognosis and improve current glioblastoma classification.
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24
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Challen B, Cramer R. Advances in ionisation techniques for mass spectrometry-based omics research. Proteomics 2022; 22:e2100394. [PMID: 35709387 DOI: 10.1002/pmic.202100394] [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: 04/20/2022] [Revised: 06/09/2022] [Accepted: 06/10/2022] [Indexed: 11/10/2022]
Abstract
Omics analysis by mass spectrometry (MS) is a vast field, with proteomics, metabolomics and lipidomics dominating recent research by exploiting biological MS ionisation techniques. Traditional MS ionisation techniques such as electrospray ionisation have limitations in analyte-specific sensitivity, modes of sampling and throughput, leading to many researchers investigating new ionisation methods for omics research. In this review, we examine the current landscape of these new ionisation techniques, divided into the three groups of (electro)spray-based, laser-based and other miscellaneous ionisation techniques. Due to the wide range of new developments, this review can only provide a starting point for further reading on each ionisation technique, as each have unique benefits, often for specialised applications, which promise beneficial results for different areas in the omics world.
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Affiliation(s)
- Bob Challen
- Department of Chemistry, University of Reading, Whiteknights, Reading, UK
| | - Rainer Cramer
- Department of Chemistry, University of Reading, Whiteknights, Reading, UK
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25
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Cakmakci D, Kaynar G, Bund C, Piotto M, Proust F, Namer IJ, Cicek AE. Targeted metabolomics analyses for brain tumor margin assessment during surgery. BIOINFORMATICS (OXFORD, ENGLAND) 2022; 38:3238-3244. [PMID: 35512389 DOI: 10.1093/bioinformatics/btac309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 04/13/2022] [Accepted: 05/02/2022] [Indexed: 01/17/2023]
Abstract
MOTIVATION Identification and removal of micro-scale residual tumor tissue during brain tumor surgery are key for survival in glioma patients. For this goal, High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) spectroscopy-based assessment of tumor margins during surgery has been an effective method. However, the time required for metabolite quantification and the need for human experts such as a pathologist to be present during surgery are major bottlenecks of this technique. While machine learning techniques that analyze the NMR spectrum in an untargeted manner (i.e. using the full raw signal) have been shown to effectively automate this feedback mechanism, high dimensional and noisy structure of the NMR signal limits the attained performance. RESULTS In this study, we show that identifying informative regions in the HRMAS NMR spectrum and using them for tumor margin assessment improves the prediction power. We use the spectra normalized with the ERETIC (electronic reference to access in vivo concentrations) method which uses an external reference signal to calibrate the HRMAS NMR spectrum. We train models to predict quantities of metabolites from annotated regions of this spectrum. Using these predictions for tumor margin assessment provides performance improvements up to 4.6% the Area Under the ROC Curve (AUC-ROC) and 2.8% the Area Under the Precision-Recall Curve (AUC-PR). We validate the importance of various tumor biomarkers and identify a novel region between 7.97 ppm and 8.09 ppm as a new candidate for a glioma biomarker. AVAILABILITY AND IMPLEMENTATION The code is released at https://github.com/ciceklab/targeted_brain_tumor_margin_assessment. The data underlying this article are available in Zenodo, at https://doi.org/10.5281/zenodo.5781769. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Doruk Cakmakci
- School of Computer Science, McGill University, Montreal, QC H3A 0E9, Canada
| | - Gun Kaynar
- School of Computer Science, McGill University, Montreal, QC H3A 0E9, Canada
| | - Caroline Bund
- MNMS Platform, University Hospitals of Strasbourg, Strasbourg 67098, France.,ICube, University of Strasbourg/CNRS UMR 7357, Strasbourg 67000, France.,Department of Nuclear Medicine and Molecular Imaging, ICANS, Strasbourg 67000, France
| | | | - Francois Proust
- Department of Neurosurgery, University Hospitals of Strasbourg, Strasbourg 67091, France
| | - Izzie Jacques Namer
- MNMS Platform, University Hospitals of Strasbourg, Strasbourg 67098, France.,ICube, University of Strasbourg/CNRS UMR 7357, Strasbourg 67000, France.,Department of Nuclear Medicine and Molecular Imaging, ICANS, Strasbourg 67000, France
| | - A Ercument Cicek
- Computer Engineering Department, Bilkent University, Ankara 06800, Turkey.,Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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26
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Ogrinc N, Schneider S, Bourmaud A, Gengler N, Salzet M, Fournier I. Direct In Vivo Analysis of CBD- and THC-Acid Cannabinoids and Classification of Cannabis Cultivars Using SpiderMass. Metabolites 2022; 12:metabo12060480. [PMID: 35736414 PMCID: PMC9227750 DOI: 10.3390/metabo12060480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 05/21/2022] [Accepted: 05/23/2022] [Indexed: 02/01/2023] Open
Abstract
In recent years, cannabis and hemp-based products have become increasingly popular for recreational use, edibles, beverages, health care products, and medicines. The rapid detection and differentiation of phytocannabinoids is, therefore, essential to assess the potency and the therapeutic and nutritional values of cannabis cultivars. Here, we implemented SpiderMass technology for in vivo detection of cannabidiolic acid (CBDA) and ∆9-tetrahydrocannabinolicacid (∆9-THCA), and other endogenous organic plant compounds, to access distribution gradients within the plants and differentiate between cultivars. The SpiderMass system is composed of an IR-laser handheld microsampling probe connected to a mass spectrometer through a transfer tube. The analysis was performed on different plant organs from freshly cultivated cannabis plants in only a few seconds. SpiderMass analysis easily discriminated the two acid phytocannabinoid isomers via MS/MS, and the built statistical models differentiated between four cannabis cultivars. Different abundancies of the two acid phytocannabinoids were found along the plant as well as between different cultivars. Overall, these results introduce direct analysis by SpiderMass as a compelling analytical alternative for rapid hemp analysis.
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Affiliation(s)
- Nina Ogrinc
- Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Inserm U1192, Université de Lille, F-59000 Lille, France; (N.O.); (M.S.)
| | - Serge Schneider
- Service de Toxicologie Analytique–Chimie Pharmaceutique, Laboratoire National de Santé (LNS), Dudelange, L-3555 Luxembourg, Luxembourg; (S.S.); (A.B.); (N.G.)
| | - Adèle Bourmaud
- Service de Toxicologie Analytique–Chimie Pharmaceutique, Laboratoire National de Santé (LNS), Dudelange, L-3555 Luxembourg, Luxembourg; (S.S.); (A.B.); (N.G.)
| | - Nicolas Gengler
- Service de Toxicologie Analytique–Chimie Pharmaceutique, Laboratoire National de Santé (LNS), Dudelange, L-3555 Luxembourg, Luxembourg; (S.S.); (A.B.); (N.G.)
| | - Michel Salzet
- Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Inserm U1192, Université de Lille, F-59000 Lille, France; (N.O.); (M.S.)
- Institut Universitaire de France (IUF), F-75000 Paris, France
| | - Isabelle Fournier
- Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Inserm U1192, Université de Lille, F-59000 Lille, France; (N.O.); (M.S.)
- Institut Universitaire de France (IUF), F-75000 Paris, France
- Correspondence:
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27
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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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28
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Van Hese L, De Vleeschouwer S, Theys T, Larivière E, Solie L, Sciot R, Siegel TP, Rex S, Heeren RM, Cuypers E. Towards real-time intraoperative tissue interrogation for REIMS-guided glioma surgery. J Mass Spectrom Adv Clin Lab 2022; 24:80-89. [PMID: 35572786 PMCID: PMC9095887 DOI: 10.1016/j.jmsacl.2022.04.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 04/27/2022] [Accepted: 04/27/2022] [Indexed: 11/17/2022] Open
Abstract
REIMS can differentiate glioblastoma from normal brain with 99.2% sensitivity. Starting from 5% glioblastoma, REIMS showed a 100% correct classification rate. Low-grade gliomas can be identified with a 97.5% sensitivity.
Introduction Objectives Methods Results Conclusion
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Affiliation(s)
- Laura Van Hese
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
- Department of Anaesthesiology, UZ Leuven; Department of Cardiovascular Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Steven De Vleeschouwer
- Department of Neurosurgery, Laboratory for Experimental Neurosurgery and Neuroanatomy, UZ Leuven, KU Leuven, 3000 Leuven, Belgium
| | - Tom Theys
- Department of Neurosurgery, Laboratory for Experimental Neurosurgery and Neuroanatomy, UZ Leuven, KU Leuven, 3000 Leuven, Belgium
| | - Emma Larivière
- Department of Neurosurgery, Laboratory for Experimental Neurosurgery and Neuroanatomy, UZ Leuven, KU Leuven, 3000 Leuven, Belgium
| | - Lien Solie
- Department of Neurosurgery, Laboratory for Experimental Neurosurgery and Neuroanatomy, UZ Leuven, KU Leuven, 3000 Leuven, Belgium
| | - Raf Sciot
- Department of Pathology, University Hospitals Leuven, KU Leuven, 3000 Leuven, Belgium
| | - Tiffany Porta Siegel
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
| | - Steffen Rex
- Department of Anaesthesiology, UZ Leuven; Department of Cardiovascular Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Ron M.A. Heeren
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
| | - Eva Cuypers
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
- Corresponding author at: M4I Institute, Division of Imaging Mass Spectrometry, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands.
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29
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Head T, Cady NC. Monitoring and modulation of the tumor microenvironment for enhanced cancer modeling. Exp Biol Med (Maywood) 2022; 247:598-613. [PMID: 35088603 PMCID: PMC9014523 DOI: 10.1177/15353702221074293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Cancer treatments utilizing biologic or cytotoxic drugs compose the frontline of therapy, and though gains in treatment efficacy have been persistent in recent decades, much work remains in understanding cancer progression and treatment. Compounding this situation is the low rate of success when translating preclinical drug candidates to the clinic, which raises costs and development timelines. This underperformance is due in part to the poor recapitulation of the tumor microenvironment, a critical component of cancer biology, in cancer model systems. New technologies capable of both accurately observing and manipulating the tumor microenvironment are needed to effectively model cancer response to treatment. In this review, conventional cancer models are summarized, and a primer on emerging techniques for monitoring and modulating the tumor microenvironment is presented and discussed.
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Affiliation(s)
- Tristen Head
- College of Nanoscale Science & Engineering,
State University of New York Polytechnic Institute, Albany, NY 12203, USA
| | - Nathaniel C Cady
- College of Nanoscale Science & Engineering,
State University of New York Polytechnic Institute, Albany, NY 12203, USA
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30
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Ogrinc N, Attencourt C, Colin E, Boudahi A, Tebbakha R, Salzet M, Testelin S, Dakpé S, Fournier I. Mass Spectrometry-Based Differentiation of Oral Tongue Squamous Cell Carcinoma and Nontumor Regions With the SpiderMass Technology. FRONTIERS IN ORAL HEALTH 2022; 3:827360. [PMID: 35309279 PMCID: PMC8929397 DOI: 10.3389/froh.2022.827360] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 01/26/2022] [Indexed: 12/14/2022] Open
Abstract
Oral cavity cancers are the 15th most common cancer with more than 350,000 new cases and ~178,000 deaths each year. Among them, squamous cell carcinoma (SCC) accounts for more than 90% of tumors located in the oral cavity and on oropharynx. For the oral cavity SCC, the surgical resection remains the primary course of treatment. Generally, surgical margins are defined intraoperatively using visual and tactile elements. However, in 15-30% of cases, positive margins are found after histopathological examination several days postsurgery. Technologies based on mass spectrometry (MS) were recently developed to help guide surgical resection. The SpiderMass technology is designed for in-vivo real-time analysis under minimally invasive conditions. This instrument achieves tissue microsampling and real-time molecular analysis with the combination of a laser microprobe and a mass spectrometer. It ultimately acts as a tool to support histopathological decision-making and diagnosis. This pilot study included 14 patients treated for tongue SCC (T1 to T4) with the surgical resection as the first line of treatment. Samples were first analyzed by a pathologist to macroscopically delineate the tumor, dysplasia, and peritumoral areas. The retrospective and prospective samples were sectioned into three consecutive sections and thaw-mounted on slides for H&E staining (7 μm), SpiderMass analysis (20 μm), and matrix-assisted laser desorption ionization (MALDI) MS imaging (12 μm). The SpiderMass microprobe collected lipidometabolic profiles of the dysplasia, tumor, and peritumoral regions annotated by the pathologist. The MS spectra were then subjected to the multivariate statistical analysis. The preliminary data demonstrate that the lipidometabolic molecular profiles collected with the SpiderMass are significantly different between the tumor and peritumoral regions enabling molecular classification to be established by linear discriminant analysis (LDA). MALDI images of the different samples were submitted to segmentation for cross instrument validation and revealed additional molecular discrimination within the tumor and nontumor regions. These very promising preliminary results show the applicability of the SpiderMass to SCC of the tongue and demonstrate its interest in the surgical treatment of head and neck cancers.
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Affiliation(s)
- Nina Ogrinc
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse – PRISM, Lille, France
| | - Christophe Attencourt
- Department of Pathology, CHU Amiens-Picardie, Amiens, France
- UR7516 CHIMERE, Université de Picardie Jules Verne, Amiens, France
| | - Emilien Colin
- UR7516 CHIMERE, Université de Picardie Jules Verne, Amiens, France
- Department of Maxillofacial Surgery, CHU Amiens-Picardie, Amiens, France
- Institut Faire Faces, Amiens, France
| | - Ahmed Boudahi
- Department of Pathology, CHU Amiens-Picardie, Amiens, France
| | - Riad Tebbakha
- Tumorothèque de Picardie, CHU Amiens-Picardie, Amiens, France
| | - Michel Salzet
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse – PRISM, Lille, France
- Institut Universitaire de France (IUF), Paris, France
| | - Sylvie Testelin
- UR7516 CHIMERE, Université de Picardie Jules Verne, Amiens, France
- Department of Maxillofacial Surgery, CHU Amiens-Picardie, Amiens, France
- Institut Faire Faces, Amiens, France
| | - Stéphanie Dakpé
- UR7516 CHIMERE, Université de Picardie Jules Verne, Amiens, France
- Department of Maxillofacial Surgery, CHU Amiens-Picardie, Amiens, France
- Institut Faire Faces, Amiens, France
| | - Isabelle Fournier
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse – PRISM, Lille, France
- Institut Universitaire de France (IUF), Paris, France
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Metabolomic Phenotyping of Gliomas: What Can We Get with Simplified Protocol for Intact Tissue Analysis? Cancers (Basel) 2022; 14:cancers14020312. [PMID: 35053475 PMCID: PMC8773998 DOI: 10.3390/cancers14020312] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/02/2022] [Accepted: 01/05/2022] [Indexed: 12/17/2022] Open
Abstract
Glioblastoma multiforme is one of the most malignant neoplasms among humans in their third and fourth decades of life, which is evidenced by short patient survival times and rapid tumor-cell proliferation after radiation and chemotherapy. At present, the diagnosis of gliomas and decisions related to therapeutic strategies are based on genetic testing and histological analysis of the tumor, with molecular biomarkers still being sought to complement the diagnostic panel. This work aims to enable the metabolomic characterization of cancer tissue and the discovery of potential biomarkers via high-resolution mass spectrometry coupled to liquid chromatography and a solvent-free sampling protocol that uses a microprobe to extract metabolites directly from intact tumors. The metabolomic analyses were performed independently from genetic and histological testing and at a later time. Despite the small cohort analyzed in this study, the results indicated that the proposed method is able to identify metabolites associated with different malignancy grades of glioma, as well as IDH and 1p19q codeletion mutations. A comparison of the constellation of identified metabolites and the results of standard tests indicated the validity of using the characterization of one comprehensive tumor phenotype as a reflection of all diagnostically meaningful information. Due to its simplicity, the proposed analytical approach was verified as being compatible with a surgical environment and applicable for large-scale studies.
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Santilli AML, Ren K, Oleschuk R, Kaufmann M, Rudan J, Fichtinger G, Mousavi P. Application of Intraoperative Mass Spectrometry and Data Analytics for Oncological Margin Detection, A Review. IEEE Trans Biomed Eng 2022; 69:2220-2232. [PMID: 34982670 DOI: 10.1109/tbme.2021.3139992] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
OBJECTIVE A common phase of early-stage oncological treatment is the surgical resection of cancerous tissue. The presence of cancer cells on the resection margin, referred to as positive margin, is correlated with the recurrence of cancer and may require re-operation, negatively impacting many facets of patient outcomes. There exists a significant gap in the surgeons ability to intraoperatively delineate between tissues. Mass spectrometry methods have shown considerable promise as intraoperative tissue profiling tools that can assist with the complete resection of cancer. To do so, the vastness of the information collected through these modalities must be digested, relying on robust and efficient extraction of insights through data analysis pipelines. METHODS We review clinical mass spectrometry literature and prioritize intraoperatively applied modalities. We also survey the data analysis methods employed in these studies. RESULTS Our review outlines the advantages and shortcomings of mass spectrometry imaging and point-based tissue probing methods. For each modality, we identify statistical, linear transformation and machine learning techniques that demonstrate high performance in classifying cancerous tissues across several organ systems. A limited number of studies presented results captured intraoperatively. CONCLUSION Through continued research of data centric techniques, like mass spectrometry, and the development of robust analysis approaches, intraoperative margin assessment is becoming feasible. SIGNIFICANCE By establishing the relatively short history of mass spectrometry techniques applied to surgical studies, we hope to inform future applications and aid in the selection of suitable data analysis frameworks for the development of intraoperative margin detection technologies.
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Yaari Z, Horoszko CP, Antman-Passig M, Kim M, Nguyen FT, Heller DA. Emerging technologies in cancer detection. Cancer Biomark 2022. [DOI: 10.1016/b978-0-12-824302-2.00011-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Ogrinc N, Kruszewski A, Chaillou P, Saudemont P, Lagadec C, Salzet M, Duriez C, Fournier I. Robot-Assisted SpiderMass for In Vivo Real-Time Topography Mass Spectrometry Imaging. Anal Chem 2021; 93:14383-14391. [PMID: 34670081 DOI: 10.1021/acs.analchem.1c01692] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Mass spectrometry imaging (MSI) has shown to bring invaluable information for biological and clinical applications. However, conventional MSI is generally performed ex vivo from tissue sections. Here, we developed a novel MS-based method for in vivo mass spectrometry imaging. By coupling the SpiderMass technology, that provides in vivo minimally invasive analysis-to a robotic arm of high accuracy, we demonstrate that images can be acquired from any surface by moving the laser probe above the surface. By equipping the robotic arm with a sensor, we are also able to both get the topography image of the sample surface and the molecular distribution, and then and plot back the molecular data, directly to the 3D topographical image without the need for image fusion. This is shown for the first time with the 3D topographic MS-based whole-body imaging of a mouse. Enabling fast in vivo MSI bridged to topography paves the way for surgical applications to excision margins.
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Affiliation(s)
- Nina Ogrinc
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France
| | - Alexandre Kruszewski
- UMR 9189 - CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille, University of Lille, INRIA, CNRS, F-59000 Lille, France
| | - Paul Chaillou
- UMR 9189 - CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille, University of Lille, INRIA, CNRS, F-59000 Lille, France
| | - Philippe Saudemont
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France
| | - Chann Lagadec
- University of Lille, CNRS, Inserm, CHU Lille, Centre Oscar Lambret, UMR9020 - UMR-S 1277 - Canther - Cancer Heterogeneity, Plasticity and Resistance to Therapies, F-59000 Lille, France
| | - Michel Salzet
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France.,Institut Universitaire de France (IUF), Paris 75231, France
| | - Christian Duriez
- UMR 9189 - CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille, University of Lille, INRIA, CNRS, F-59000 Lille, France
| | - Isabelle Fournier
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France.,Institut Universitaire de France (IUF), Paris 75231, France
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Ogrinc N, Caux PD, Robin YM, Bouchaert E, Fatou B, Ziskind M, Focsa C, Bertin D, Tierny D, Takats Z, Salzet M, Fournier I. Direct Water-Assisted Laser Desorption/Ionization Mass Spectrometry Lipidomic Analysis and Classification of Formalin-Fixed Paraffin-Embedded Sarcoma Tissues without Dewaxing. Clin Chem 2021; 67:1513-1523. [PMID: 34586394 DOI: 10.1093/clinchem/hvab160] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 07/26/2021] [Indexed: 11/13/2022]
Abstract
BACKGROUND Formalin-fixed paraffin-embedded (FFPE) tissue has been the gold standard for routine pathology for general and cancer postoperative diagnostics. Despite robust histopathology, immunohistochemistry, and molecular methods, accurate diagnosis remains difficult for certain cases. Overall, the entire process can be time consuming, labor intensive, and does not reach over 90% diagnostic sensitivity and specificity. There is a growing need in onco-pathology for adjunct novel rapid, accurate, reliable, diagnostically sensitive, and specific methods for high-throughput biomolecular identification. Lipids have long been considered only as building blocks of cell membranes or signaling molecules, but have recently been introduced as central players in cancer. Due to sample processing, which limits their detection, lipid analysis directly from unprocessed FFPE tissues has never been reported. METHODS We present a proof-of-concept with direct analysis of tissue-lipidomic signatures from FFPE tissues without dewaxing and minimal sample preparation using water-assisted laser desorption ionization mass spectrometry and deep-learning. RESULTS On a cohort of difficult canine and human sarcoma cases, classification for canine sarcoma subtyping was possible with 99.1% accuracy using "5-fold" and 98.5% using "leave-one-patient out," and 91.2% accuracy for human sarcoma using 5-fold and 73.8% using leave-one-patient out. The developed classification model enabled stratification of blind samples in <5 min and showed >95% probability for discriminating 2 human sarcoma blind samples. CONCLUSION It is possible to create a rapid diagnostic platform to screen clinical FFPE tissues with minimal sample preparation for molecular pathology.
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Affiliation(s)
- Nina Ogrinc
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse-PRISM, Lille, France
| | - Pierre-Damien Caux
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse-PRISM, Lille, France
| | - Yves-Marie Robin
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse-PRISM, Lille, France.,Unité de Pathologie Morphologique et Moléculaire, Centre Oscar Lambret, Lille, France
| | - Emmanuel Bouchaert
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse-PRISM, Lille, France.,OCR (Oncovet Clinical Research), Parc Eurasante Lille Metropole, Loos, France
| | - Benoit Fatou
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse-PRISM, Lille, France
| | - Michael Ziskind
- University of Lille, CNRS, UMR 8523, PhLAM-Physique des Lasers, Atomes et Molécules, Lille, France
| | - Cristian Focsa
- University of Lille, CNRS, UMR 8523, PhLAM-Physique des Lasers, Atomes et Molécules, Lille, France
| | - Delphine Bertin
- Unité de Pathologie Morphologique et Moléculaire, Centre Oscar Lambret, Lille, France
| | - Dominique Tierny
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse-PRISM, Lille, France.,OCR (Oncovet Clinical Research), Parc Eurasante Lille Metropole, Loos, France
| | - Zoltan Takats
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse-PRISM, Lille, France
| | - Michel Salzet
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse-PRISM, Lille, France.,Institut Universitaire de France (IUF), Paris, France
| | - Isabelle Fournier
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse-PRISM, Lille, France.,Institut Universitaire de France (IUF), Paris, France
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Hahn J, Moritz M, Voß H, Pelczar P, Huber S, Schlüter H. Tissue Sampling and Homogenization in the Sub-Microliter Scale with a Nanosecond Infrared Laser (NIRL) for Mass Spectrometric Proteomics. Int J Mol Sci 2021; 22:ijms221910833. [PMID: 34639174 PMCID: PMC8509473 DOI: 10.3390/ijms221910833] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 09/30/2021] [Accepted: 10/02/2021] [Indexed: 12/12/2022] Open
Abstract
It was recently shown that ultrashort pulse infrared (IR) lasers, operating at the wavelength of the OH vibration stretching band of water, are highly efficient for sampling and homogenizing biological tissue. In this study we utilized a tunable nanosecond infrared laser (NIRL) for tissue sampling and homogenization with subsequent liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis for mass spectrometric proteomics. For the first time, laser sampling was performed with murine spleen and colon tissue. An ablation volume of 1.1 × 1.1 × 0.4 mm³ (approximately 0.5 µL) was determined with optical coherence tomography (OCT). The results of bottom-up proteomics revealed proteins with significant abundance differences for both tissue types, which are in accordance with the corresponding data of the Human Protein Atlas. The results demonstrate that tissue sampling and homogenization of small tissue volumes less than 1 µL for subsequent mass spectrometric proteomics is feasible with a NIRL.
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Affiliation(s)
- Jan Hahn
- Section/Core Facility Mass Spectrometry and Proteomics, University Medical Center Hamburg-Eppendorf (UKE), Martinistr. 52, 20246 Hamburg, Germany; (M.M.); (H.V.); (H.S.)
- Correspondence: ; Tel.: +49-1522-2827-168
| | - Manuela Moritz
- Section/Core Facility Mass Spectrometry and Proteomics, University Medical Center Hamburg-Eppendorf (UKE), Martinistr. 52, 20246 Hamburg, Germany; (M.M.); (H.V.); (H.S.)
| | - Hannah Voß
- Section/Core Facility Mass Spectrometry and Proteomics, University Medical Center Hamburg-Eppendorf (UKE), Martinistr. 52, 20246 Hamburg, Germany; (M.M.); (H.V.); (H.S.)
| | - Penelope Pelczar
- Section of Molecular Immunology and Gastroenterology, I. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Martinistr. 52, 20246 Hamburg, Germany; (P.P.); (S.H.)
| | - Samuel Huber
- Section of Molecular Immunology and Gastroenterology, I. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Martinistr. 52, 20246 Hamburg, Germany; (P.P.); (S.H.)
| | - Hartmut Schlüter
- Section/Core Facility Mass Spectrometry and Proteomics, University Medical Center Hamburg-Eppendorf (UKE), Martinistr. 52, 20246 Hamburg, Germany; (M.M.); (H.V.); (H.S.)
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Katz L, Tata A, Woolman M, Zarrine-Afsar A. Lipid Profiling in Cancer Diagnosis with Hand-Held Ambient Mass Spectrometry Probes: Addressing the Late-Stage Performance Concerns. Metabolites 2021; 11:metabo11100660. [PMID: 34677375 PMCID: PMC8537725 DOI: 10.3390/metabo11100660] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 09/18/2021] [Accepted: 09/22/2021] [Indexed: 02/06/2023] Open
Abstract
Untargeted lipid fingerprinting with hand-held ambient mass spectrometry (MS) probes without chromatographic separation has shown promise in the rapid characterization of cancers. As human cancers present significant molecular heterogeneities, careful molecular modeling and data validation strategies are required to minimize late-stage performance variations of these models across a large population. This review utilizes parallels from the pitfalls of conventional protein biomarkers in reaching bedside utility and provides recommendations for robust modeling as well as validation strategies that could enable the next logical steps in large scale assessment of the utility of ambient MS profiling for cancer diagnosis. Six recommendations are provided that range from careful initial determination of clinical added value to moving beyond just statistical associations to validate lipid involvements in disease processes mechanistically. Further guidelines for careful selection of suitable samples to capture expected and unexpected intragroup variance are provided and discussed in the context of demographic heterogeneities in the lipidome, further influenced by lifestyle factors, diet, and potential intersect with cancer lipid pathways probed in ambient mass spectrometry profiling studies.
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Affiliation(s)
- Lauren Katz
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada; (L.K.); (M.W.)
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, ON M5G 1P5, Canada
| | - Alessandra Tata
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico delle Venezie, Viale Fiume 78, 36100 Vicenza, Italy;
| | - Michael Woolman
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada; (L.K.); (M.W.)
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, ON M5G 1P5, Canada
| | - Arash Zarrine-Afsar
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON M5G 1L7, Canada; (L.K.); (M.W.)
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, ON M5G 1P5, Canada
- Department of Surgery, University of Toronto, 149 College Street, Toronto, ON M5T 1P5, Canada
- Keenan Research Center for Biomedical Science & the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 30 Bond Street, Toronto, ON M5B 1W8, Canada
- Correspondence: ; Tel.: +1-416-581-8473
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Zhang J, Sans M, Garza KY, Eberlin LS. MASS SPECTROMETRY TECHNOLOGIES TO ADVANCE CARE FOR CANCER PATIENTS IN CLINICAL AND INTRAOPERATIVE USE. MASS SPECTROMETRY REVIEWS 2021; 40:692-720. [PMID: 33094861 DOI: 10.1002/mas.21664] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 09/09/2020] [Accepted: 09/09/2020] [Indexed: 06/11/2023]
Abstract
Developments in mass spectrometry technologies have driven a widespread interest and expanded their use in cancer-related research and clinical applications. In this review, we highlight the developments in mass spectrometry methods and instrumentation applied to direct tissue analysis that have been tailored at enhancing performance in clinical research as well as facilitating translation and implementation of mass spectrometry in clinical settings, with a focus on cancer-related studies. Notable studies demonstrating the capabilities of direct mass spectrometry analysis in biomarker discovery, cancer diagnosis and prognosis, tissue analysis during oncologic surgeries, and other clinically relevant problems that have the potential to substantially advance cancer patient care are discussed. Key challenges that need to be addressed before routine clinical implementation including regulatory efforts are also discussed. Overall, the studies highlighted in this review demonstrate the transformative potential of mass spectrometry technologies to advance clinical research and care for cancer patients. © 2020 Wiley Periodicals, Inc. Mass Spec Rev.
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Affiliation(s)
- Jialing Zhang
- Department of Chemistry, University of Texas at Austin, Austin, TX
| | - Marta Sans
- Department of Chemistry, University of Texas at Austin, Austin, TX
| | - Kyana Y Garza
- Department of Chemistry, University of Texas at Austin, Austin, TX
| | - Livia S Eberlin
- Department of Chemistry, University of Texas at Austin, Austin, TX
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Plekhova V, Van Meulebroek L, De Graeve M, Perdones-Montero A, De Spiegeleer M, De Paepe E, Van de Walle E, Takats Z, Cameron SJS, Vanhaecke L. Rapid ex vivo molecular fingerprinting of biofluids using laser-assisted rapid evaporative ionization mass spectrometry. Nat Protoc 2021; 16:4327-4354. [PMID: 34341579 DOI: 10.1038/s41596-021-00580-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 05/31/2021] [Indexed: 01/29/2023]
Abstract
Of the many metabolites involved in any clinical condition, only a narrow range of biomarkers is currently being used in the clinical setting. A key to personalized medicine would be to extend this range. Metabolic fingerprinting provides a more comprehensive insight, but many methods used for metabolomics analysis are too complex and time-consuming to be diagnostically useful. Here, a rapid evaporative ionization mass spectrometry (REIMS) system for direct ex vivo real-time analysis of biofluids with minor sample pretreatment is detailed. The REIMS can be linked to various laser wavelength systems (such as optical parametric oscillator or CO2 laser) and with automation for high-throughput analysis. Laser-induced sample evaporation occurs within seconds through radiative heating with the plume guided to the MS instrument. The presented procedure includes (i) laser setup with automation, (ii) analysis of biofluids (blood/urine/stool/saliva/sputum/breast milk) and (iii) data analysis. We provide the optimal settings for biofluid analysis and quality control, enabling sensitive, precise and robust analysis. Using the automated setup, 96 samples can be analyzed in ~35-40 min per ionization mode, with no intervention required. Metabolic fingerprints are made up of 2,000-4,000 features, for which relative quantification can be achieved at high repeatability when total ion current normalization is applied. With saliva and feces as example matrices, >70% of features had a coefficient of variance ≤30%. However, to achieve acceptable long-term reproducibility, additional normalizations by, e.g., LOESS are recommended, especially for positive ionization.
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Affiliation(s)
- Vera Plekhova
- Laboratory of Chemical Analysis, Ghent University, Merelbeke, Belgium
| | - Lieven Van Meulebroek
- Laboratory of Chemical Analysis, Ghent University, Merelbeke, Belgium.,ProDigest BV, Zwijnaarde, Belgium
| | - Marilyn De Graeve
- Laboratory of Chemical Analysis, Ghent University, Merelbeke, Belgium
| | | | | | - Ellen De Paepe
- Laboratory of Chemical Analysis, Ghent University, Merelbeke, Belgium
| | - Emma Van de Walle
- Laboratory of Chemical Analysis, Ghent University, Merelbeke, Belgium
| | - Zoltan Takats
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Simon J S Cameron
- School of Biological Sciences, Institute for Global Food Security, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Lynn Vanhaecke
- Laboratory of Chemical Analysis, Ghent University, Merelbeke, Belgium. .,School of Biological Sciences, Institute for Global Food Security, Queen's University Belfast, Belfast, Northern Ireland, UK.
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Fu X, Wang Y, Xia B, Shi P, Zhou Y. Ultrasonic Sputter Desorption Mass Spectrometry Technique for Minimally Invasive Tissue Analysis. Anal Chem 2021; 93:10502-10510. [PMID: 34284576 DOI: 10.1021/acs.analchem.1c01448] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Minimally invasive techniques for in vivo tissue analysis are desired by life science and medical research. Herein, a new ionization interface coupled with ultrasonic sputter desorption (USD) was developed for in vitro and in vivo tissue analysis. Sample molecules were effectively sputtered out when the high-frequency ultrasonic probe touched the tissue. Then, the sputtered molecules were collected and ionized by a custom-made heated quartz tube and finally analyzed by mass spectrometry (MS) online. The sample pretreatment of the USD-MS technique was quite simple and required no other steps except for wetting the tissue surface with ethanol to assist molecular extraction. Experimental results demonstrated that the proposed method was suitable for the analysis of different morphologies of tissues (such as liver, brain, kidney, and lung) and performed well in the analysis of liver tumors and paracancerous tissues. Moreover, as the proposed method caused little damage to the tissues during analysis, rats and mice with orthotopic tumors still survived after the experiments. Overall, the newly developed USD-MS technique was an effective tool for minimally invasive tissue analysis and could be used as a new candidate method for in situ and real-time analysis of biological tissues in vitro and in vivo.
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Affiliation(s)
- Xian Fu
- Chengdu Institute of Biology, Chinese Academy of Sciences, No. 93 South Keyuan Road, Gaoxin Distinct, Chengdu 610041, P. R. China.,Center for Novel Target & Therapeutic Intervention, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, P. R. China
| | - Yu Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, No. 93 South Keyuan Road, Gaoxin Distinct, Chengdu 610041, P. R. China.,University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Bing Xia
- Chengdu Institute of Biology, Chinese Academy of Sciences, No. 93 South Keyuan Road, Gaoxin Distinct, Chengdu 610041, P. R. China
| | - Peiyu Shi
- Chengdu Institute of Biology, Chinese Academy of Sciences, No. 93 South Keyuan Road, Gaoxin Distinct, Chengdu 610041, P. R. China.,University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Yan Zhou
- Chengdu Institute of Biology, Chinese Academy of Sciences, No. 93 South Keyuan Road, Gaoxin Distinct, Chengdu 610041, P. R. China
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Zhang J, Sans M, DeHoog RJ, Garza KY, King ME, Feider CL, Bensussan A, Keating MF, Lin JQ, Povilaitis SC, Katta N, Milner TE, Yu W, Nagi C, Dhingra S, Pirko C, Brahmbhatt KA, Van Buren G, Carter S, Thompson A, Grogan RH, Suliburk J, Eberlin LS. Clinical Translation and Evaluation of a Handheld and Biocompatible Mass Spectrometry Probe for Surgical Use. Clin Chem 2021; 67:1271-1280. [PMID: 34263289 DOI: 10.1093/clinchem/hvab098] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 05/05/2021] [Indexed: 11/13/2022]
Abstract
BACKGROUND Intraoperative tissue analysis and identification are critical to guide surgical procedures and improve patient outcomes. Here, we describe the clinical translation and evaluation of the MasSpec Pen technology for molecular analysis of in vivo and freshly excised tissues in the operating room (OR). METHODS An Orbitrap mass spectrometer equipped with a MasSpec Pen interface was installed in an OR. A "dual-path" MasSpec Pen interface was designed and programmed for the clinical studies with 2 parallel systems that facilitated the operation of the MasSpec Pen. The MasSpec Pen devices were autoclaved before each surgical procedure and were used by surgeons and surgical staff during 100 surgeries over a 12-month period. RESULTS Detection of mass spectral profiles from 715 in vivo and ex vivo analyses performed on thyroid, parathyroid, lymph node, breast, pancreatic, and bile duct tissues during parathyroidectomies, thyroidectomies, breast, and pancreatic neoplasia surgeries was achieved. The MasSpec Pen enabled gentle extraction and sensitive detection of various molecular species including small metabolites and lipids using a droplet of sterile water without causing apparent tissue damage. Notably, effective molecular analysis was achieved while no limitations to sequential histologic tissue analysis were identified and no device-related complications were reported for any of the patients. CONCLUSIONS This study shows that the MasSpec Pen system can be successfully incorporated into the OR, allowing direct detection of rich molecular profiles from tissues with a seconds-long turnaround time that could be used to inform surgical and clinical decisions without disrupting tissue analysis workflows.
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Affiliation(s)
- Jialing Zhang
- Department of Chemistry, The University of Texas at Austin, Austin, TX
| | - Marta Sans
- Department of Chemistry, The University of Texas at Austin, Austin, TX
| | - Rachel J DeHoog
- Department of Chemistry, The University of Texas at Austin, Austin, TX
| | - Kyana Y Garza
- Department of Chemistry, The University of Texas at Austin, Austin, TX
| | - Mary E King
- Department of Chemistry, The University of Texas at Austin, Austin, TX
| | - Clara L Feider
- Department of Chemistry, The University of Texas at Austin, Austin, TX
| | - Alena Bensussan
- Department of Chemistry, The University of Texas at Austin, Austin, TX
| | - Michael F Keating
- Department of Chemistry, The University of Texas at Austin, Austin, TX
| | - John Q Lin
- Department of Chemistry, The University of Texas at Austin, Austin, TX
| | | | - Nitesh Katta
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX
| | - Thomas E Milner
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX
| | - Wendong Yu
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX
| | - Chandandeep Nagi
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX
| | - Sadhna Dhingra
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX
| | | | | | | | - Stacey Carter
- Department of Surgery, Baylor College of Medicine, Houston, TX
| | | | - Raymon H Grogan
- Department of Surgery, Baylor College of Medicine, Houston, TX
| | - James Suliburk
- Department of Surgery, Baylor College of Medicine, Houston, TX
| | - Livia S Eberlin
- Department of Chemistry, The University of Texas at Austin, Austin, TX
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Brown HM, Alfaro CM, Pirro V, Dey M, Hattab EM, Cohen-Gadol AA, Cooks RG. Intraoperative Mass Spectrometry Platform for IDH Mutation Status Prediction, Glioma Diagnosis, and Estimation of Tumor Cell Infiltration. J Appl Lab Med 2021; 6:902-916. [PMID: 33523209 PMCID: PMC8266740 DOI: 10.1093/jalm/jfaa233] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 11/23/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND Surgical tumor resection is the primary treatment option for diffuse glioma, the most common malignant brain cancer. The intraoperative diagnosis of gliomas from tumor core samples can be improved by use of molecular diagnostics. Further, residual tumor at surgical margins is a primary cause of tumor recurrence and malignant progression. This study evaluates a desorption electrospray ionization mass spectrometry (DESI-MS) system for intraoperative isocitrate dehydrogenase (IDH) mutation assessment, estimation of tumor cell infiltration as tumor cell percentage (TCP), and disease status. This information could be used to enhance the extent of safe resection and so potentially improve patient outcomes. METHODS A mobile DESI-MS instrument was modified and used in neurosurgical operating rooms (ORs) on a cohort of 49 human subjects undergoing craniotomy with tumor resection for suspected diffuse glioma. Small tissue biopsies (ntotal = 203) from the tumor core and surgical margins were analyzed by DESI-MS in the OR and classified using univariate and multivariate statistical methods. RESULTS Assessment of IDH mutation status using DESI-MS/MS to measure 2-hydroxyglutarate (2-HG) ion intensities from tumor cores yielded a sensitivity, specificity, and overall diagnostic accuracy of 89, 100, and 94%, respectively (ncore = 71). Assessment of TCP (categorized as low or high) in tumor margin and core biopsies using N-acetyl-aspartic acid (NAA) intensity provided a sensitivity, specificity, and accuracy of 91, 76, and 83%, respectively (ntotal = 203). TCP assessment using lipid profile deconvolution provided sensitivity, specificity, and accuracy of 76, 85, and 81%, respectively (ntotal = 203). Combining the experimental data and using PCA-LDA predictions of disease status, the sensitivity, specificity, and accuracy in predicting disease status are 63%, 83%, and 74%, respectively (ntotal = 203). CONCLUSIONS The DESI-MS system allowed for identification of IDH mutation status, glioma diagnosis, and estimation of tumor cell infiltration intraoperatively in a large human glioma cohort. This methodology should be further refined for clinical diagnostic applications.
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Affiliation(s)
| | - Clint M. Alfaro
- Department of Chemistry, Purdue University, West Lafayette, IN, USA
| | - Valentina Pirro
- Department of Chemistry, Purdue University, West Lafayette, IN, USA
| | - Mahua Dey
- Department of Neurological Surgery, Indiana University School of Medicine, Goodman Campbell Brain and Spine, Indianapolis, IN, USA
| | - Eyas M. Hattab
- Department of Pathology and Laboratory Medicine, University of Louisville, KY, USA
| | - Aaron A. Cohen-Gadol
- Department of Neurological Surgery, Indiana University School of Medicine, Goodman Campbell Brain and Spine, Indianapolis, IN, USA
| | - R. Graham Cooks
- Department of Chemistry, Purdue University, West Lafayette, IN, USA
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44
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Rapid diagnosis and tumor margin assessment during pancreatic cancer surgery with the MasSpec Pen technology. Proc Natl Acad Sci U S A 2021; 118:2104411118. [PMID: 34260388 DOI: 10.1073/pnas.2104411118] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Intraoperative delineation of tumor margins is critical for effective pancreatic cancer surgery. Yet, intraoperative frozen section analysis of tumor margins is a time-consuming and often challenging procedure that can yield confounding results due to histologic heterogeneity and tissue-processing artifacts. We have previously described the development of the MasSpec Pen technology as a handheld mass spectrometry-based device for nondestructive tissue analysis. Here, we evaluated the usefulness of the MasSpec Pen for intraoperative diagnosis of pancreatic ductal adenocarcinoma based on alterations in the metabolite and lipid profiles in in vivo and ex vivo tissues. We used the MasSpec Pen to analyze 157 banked human tissues, including pancreatic ductal adenocarcinoma, pancreatic, and bile duct tissues. Classification models generated from the molecular data yielded an overall agreement with pathology of 91.5%, sensitivity of 95.5%, and specificity of 89.7% for discriminating normal pancreas from cancer. We built a second classifier to distinguish bile duct from pancreatic cancer, achieving an overall accuracy of 95%, sensitivity of 92%, and specificity of 100%. We then translated the MasSpec Pen to the operative room and predicted on in vivo and ex vivo data acquired during 18 pancreatic surgeries, achieving 93.8% overall agreement with final postoperative pathology reports. Notably, when integrating banked tissue data with intraoperative data, an improved agreement of 100% was achieved. The result obtained demonstrate that the MasSpec Pen provides high predictive performance for tissue diagnosis and compatibility for intraoperative use, suggesting that the technology may be useful to guide surgical decision-making during pancreatic cancer surgeries.
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Nauta SP, Poeze M, Heeren RMA, Porta Siegel T. Clinical use of mass spectrometry (imaging) for hard tissue analysis in abnormal fracture healing. Clin Chem Lab Med 2021; 58:897-913. [PMID: 32049645 DOI: 10.1515/cclm-2019-0857] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 12/16/2019] [Indexed: 12/23/2022]
Abstract
Common traumas to the skeletal system are bone fractures and injury-related articular cartilage damage. The healing process can be impaired resulting in non-unions in 5-10% of the bone fractures and in post-traumatic osteoarthritis (PTOA) in up to 75% of the cases of cartilage damage. Despite the amount of research performed in the areas of fracture healing and cartilage repair as well as non-unions and PTOA, still, the outcome of a bone fracture or articular cartilage damage cannot be predicted. Here, we discuss known risk factors and key molecules involved in the repair process, together with the main challenges associated with the prediction of outcome of these injuries. Furthermore, we review and discuss the opportunities for mass spectrometry (MS) - an analytical tool capable of detecting a wide variety of molecules in tissues - to contribute to extending molecular understanding of impaired healing and the discovery of predictive biomarkers. Therefore, the current knowledge and challenges concerning MS imaging of bone and cartilage tissue as well as in vivo MS are discussed. Finally, we explore the possibilities of in situ, real-time MS for the prediction of outcome during surgery of bone fractures and injury-related articular cartilage damage.
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Affiliation(s)
- Sylvia P Nauta
- The Maastricht MultiModal Molecular Imaging Institute (M4I), Division of Imaging Mass Spectrometry, Maastricht University, Maastricht, The Netherlands.,Department of Orthopedic Surgery and Traumasurgery, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Martijn Poeze
- Department of Surgery, Division of Traumasurgery, Maastricht University Medical Center, Maastricht, The Netherlands.,NUTRIM, School for Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Ron M A Heeren
- The Maastricht MultiModal Molecular Imaging Institute (M4I), Division of Imaging Mass Spectrometry, Maastricht University, Universiteitssingel 50, 6229ER Maastricht, The Netherlands
| | - Tiffany Porta Siegel
- The Maastricht MultiModal Molecular Imaging Institute (M4I), Division of Imaging Mass Spectrometry, Maastricht University, Maastricht, The Netherlands
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46
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Ogrinc N, Saudemont P, Takats Z, Salzet M, Fournier I. Cancer Surgery 2.0: Guidance by Real-Time Molecular Technologies. Trends Mol Med 2021; 27:602-615. [PMID: 33965341 DOI: 10.1016/j.molmed.2021.04.001] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 03/30/2021] [Accepted: 04/02/2021] [Indexed: 12/14/2022]
Abstract
In vivo cancer margin delineation during surgery remains a major challenge. Despite the availability of several image guidance techniques and intraoperative assessment, clear surgical margins and debulking efficiency remain scarce. For this reason, there is particular interest in developing rapid intraoperative tools with high sensitivity and specificity to help guide cancer surgery in vivo. Recently, several emerging technologies including intraoperative mass spectrometry have paved the way for molecular guidance in a clinical setting. We evaluate these techniques and assess their relevance for intraoperative surgical guidance and how they can transform the future of molecular cancer surgery, diagnostics, patient management and care.
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Affiliation(s)
- Nina Ogrinc
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France
| | - Philippe Saudemont
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France
| | - Zoltan Takats
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France
| | - Michel Salzet
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France; Institut Universitaire de France (IUF), Paris, France.
| | - Isabelle Fournier
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, F-59000 Lille, France; Institut Universitaire de France (IUF), Paris, France.
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47
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Woolman M, Katz L, Tata A, Basu SS, Zarrine-Afsar A. Breaking Through the Barrier: Regulatory Considerations Relevant to Ambient Mass Spectrometry at the Bedside. Clin Lab Med 2021; 41:221-246. [PMID: 34020761 DOI: 10.1016/j.cll.2021.03.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Rapid characterization of tissue disorder using ambient mass spectrometry (MS) techniques, requiring little to no preanalytical preparations of sampled tissues, has been shown using a variety of ion sources and with many disease classes. A brief overview of ambient MS in clinical applications, the state of the art in regulatory affairs, and recommendations to facilitate adoption for use at the bedside are presented. Unique challenges in the validation of untargeted MS methods and additional safety and compliance requirements for deployment within a clinical setting are further discussed. Development of a harmonized validation strategy for ambient MS methods is emphasized.
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Affiliation(s)
- Michael Woolman
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada; Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
| | - Lauren Katz
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada; Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada
| | - Alessandra Tata
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico delle Venezie, Viale Fiume 78, 36100 Vicenza, Italy
| | - Sankha S Basu
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Arash Zarrine-Afsar
- Techna Institute for the Advancement of Technology for Health, University Health Network, 100 College Street, Toronto, Ontario M5G 1P5, Canada; Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, Canada; Department of Surgery, University of Toronto, 149 College Street, Toronto, Ontario M5T 1P5, Canada; Keenan Research Center for Biomedical Science & the Li Ka Shing Knowledge Institute, St. Michael's Hospital, 30 Bond Street, Toronto, Ontario M5B 1W8, Canada.
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Manoli E, Mason S, Ford L, Adebesin A, Bodai Z, Darzi A, Kinross J, Takats Z. Validation of Ultrasonic Harmonic Scalpel for Real-Time Tissue Identification Using Rapid Evaporative Ionization Mass Spectrometry. Anal Chem 2021; 93:5906-5916. [PMID: 33787247 PMCID: PMC8153397 DOI: 10.1021/acs.analchem.1c00270] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
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In this study, we integrate rapid
evaporative ionization mass spectrometry
(REIMS) with the Harmonic scalpel, an advanced laparoscopic surgical
instrument that utilizes ultrasound energy to dissect and coagulate
tissues. It provides unparalleled manipulation capability to surgeons
and has superseded traditional electrosurgical tools particularly
in abdominal surgery, but is yet to be validated with REIMS. The REIMS
platform coupled with the Harmonic device was shown to produce tissue-specific
lipid profiles through the analysis of porcine tissues in both negative
and positive ionization modes. Comparison with other methods of electrosurgical
dissection, such as monopolar electrosurgery and CO2 laser,
showed spectral differences in the profile dependent on the energy
device used. The Harmonic device demonstrated major spectral differences
in the phospholipid region of m/z 600–1000 compared with the monopolar electrosurgical and
CO2 laser-generated spectra. Within the Harmonic REIMS
spectra, high intensities of diglycerides and triglycerides were observed.
In contrast, monopolar electrosurgical and laser spectra demonstrated
high abundances of glycerophospholipids. The Harmonic scalpel was
able to differentiate between the liver, muscle, colon, and small
intestine, demonstrating 100% diagnostic accuracy. The validation
of the Harmonic device–mass spectrometry combination will allow
the platform to be used safely and robustly for real-time in vivo surgical tissue identification in a variety of clinical
applications.
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Affiliation(s)
- Eftychios Manoli
- Department of Surgery and Cancer, Imperial College London, St Marys Hospital, London W2 1NY, United Kingdom
| | - Sam Mason
- Department of Surgery and Cancer, Imperial College London, St Marys Hospital, London W2 1NY, United Kingdom
| | - Lauren Ford
- Department of Surgery and Cancer, Imperial College London, St Marys Hospital, London W2 1NY, United Kingdom
| | - Afeez Adebesin
- Department of Surgery and Cancer, Imperial College London, St Marys Hospital, London W2 1NY, United Kingdom
| | - Zsolt Bodai
- Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Ara Darzi
- Department of Surgery and Cancer, Imperial College London, St Marys Hospital, London W2 1NY, United Kingdom
| | - James Kinross
- Department of Surgery and Cancer, Imperial College London, St Marys Hospital, London W2 1NY, United Kingdom
| | - Zoltan Takats
- Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
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Yan B, Murta T, Elia EA, Steven RT, Bunch J. Direct Tissue Mass Spectrometry Imaging by Atmospheric Pressure UV-Laser Desorption Plasma Postionization. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:429-435. [PMID: 33289553 DOI: 10.1021/jasms.0c00315] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Matrix-assisted laser desorption ionization (MALDI) operated at atmospheric pressure has been shown to be a promising technique for mass spectrometry imaging of biological tissues at high spatial resolution. Recent studies have shown several orders of magnitude improvement in sensitivity afforded by coupling with a low-temperature plasma (LTP) for postionization. In this work we report the first results from "matrix-free" imaging using our atmospheric pressure (AP) transmission mode (TM) (MA)LDI source with LTP postionization. Direct MSI analysis of murine testis with no sample preparation after tissue sectioning enabled imaging of a range of lipid classes at pixel sizes of 25 μm. We compared results from the matrix-free methods with MALDI experiments in which the matrix was applied on top, underneath, or layered as a sandwich. The sandwich preparation was found to lead to ion yields approximately 2- or 3-fold higher than the other methods, indicating that the addition of a light absorbing matrix remains beneficial. Nonetheless, LDI methods confer a range of advantages, and the sensitivity improvements provided by postionization strategies are a promising step toward high-efficiency laser sampling under ambient conditions.
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Affiliation(s)
- Bin Yan
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington TW11 0LW, United Kingdom
| | - Teresa Murta
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington TW11 0LW, United Kingdom
| | - Efstathios A Elia
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington TW11 0LW, United Kingdom
| | - Rory T Steven
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington TW11 0LW, United Kingdom
| | - Josephine Bunch
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington TW11 0LW, United Kingdom
- Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
- Rosalind Franklin Institute, Harwell Campus, Didcot OX11 0FA, United Kingdom
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50
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Cumulative learning enables convolutional neural network representations for small mass spectrometry data classification. Nat Commun 2020; 11:5595. [PMID: 33154370 PMCID: PMC7644674 DOI: 10.1038/s41467-020-19354-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 10/05/2020] [Indexed: 12/13/2022] Open
Abstract
Rapid and accurate clinical diagnosis remains challenging. A component of diagnosis tool development is the design of effective classification models with Mass spectrometry (MS) data. Some Machine Learning approaches have been investigated but these models require time-consuming preprocessing steps to remove artifacts, making them unsuitable for rapid analysis. Convolutional Neural Networks (CNNs) have been found to perform well under such circumstances since they can learn representations from raw data. However, their effectiveness decreases when the number of available training samples is small, which is a common situation in medicine. In this work, we investigate transfer learning on 1D-CNNs, then we develop a cumulative learning method when transfer learning is not powerful enough. We propose to train the same model through several classification tasks over various small datasets to accumulate knowledge in the resulting representation. By using rat brain as the initial training dataset, a cumulative learning approach can have a classification accuracy exceeding 98% for 1D clinical MS-data. We show the use of cumulative learning using datasets generated in different biological contexts, on different organisms, and acquired by different instruments. Here we show a promising strategy for improving MS data classification accuracy when only small numbers of samples are available. Convolutional Neural Networks are powerful tools for clinical diagnosis but their effectiveness decreases when the number of available samples is small. Here, the authors develop a cumulative learning method by training the same model through several classification tasks over various small Mass Spectrometry datasets.
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