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Molnár A, Horkovics-Kováts GS, Kucsma N, Szegő Z, Tauber B, Egri A, Szkupien Z, Deák BA, McKenzie JS, Thuróczy J, Schäffer R, Schlosser G, Szakács G, Balog J. Characterisation of Canine and Feline Breast Tumours, Their Metastases, and Corresponding Primary Cell Lines Using LA-REIMS and DESI-MS Imaging. Int J Mol Sci 2024; 25:7752. [PMID: 39062995 PMCID: PMC11277125 DOI: 10.3390/ijms25147752] [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: 03/16/2024] [Revised: 06/30/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
Breast cancer, a complex disease with a significant prevalence to form metastases, necessitates novel therapeutic strategies to improve treatment outcomes. Here, we present the results of a comparative molecular study of primary breast tumours, their metastases, and the corresponding primary cell lines using Desorption Electrospray Ionisation (DESI) and Laser-Assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS) imaging. Our results show that ambient ionisation mass spectrometry technology is suitable for rapid characterisation of samples, providing a lipid- and metabolite-rich spectrum within seconds. Our study demonstrates that the lipidomic fingerprint of the primary tumour is not significantly distinguishable from that of its metastasis, in parallel with the similarity observed between their respective primary cell lines. While significant differences were observed between tumours and the corresponding cell lines, distinct lipidomic signatures and several phospholipids such as PA(36:2), PE(36:1), and PE(P-38:4)/PE(O-38:5) for LA-REIMS imaging and PE(P-38:4)/PE(O-38:5), PS(36:1), and PI(38:4) for DESI-MSI were identified in both tumours and cells. We show that the tumours' characteristics can be found in the corresponding primary cell lines, offering a promising avenue for assessing tumour responsiveness to therapeutic interventions. A comparative analysis by DESI-MSI and LA-REIMS imaging revealed complementary information, demonstrating the utility of LA-REIMS in the molecular imaging of cancer.
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Affiliation(s)
- Adrienn Molnár
- Hevesy György PhD School of Chemistry, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary; (A.M.); (G.S.H.-K.)
- Waters Research Center, H-1031 Budapest, Hungary; (Z.S.); (A.E.); (R.S.)
- MTA-ELTE Lendület (Momentum) Ion Mobility Mass Spectrometry Research Group, Faculty of Science, Institute of Chemistry, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary;
| | - Gabriel Stefan Horkovics-Kováts
- Hevesy György PhD School of Chemistry, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary; (A.M.); (G.S.H.-K.)
- Waters Research Center, H-1031 Budapest, Hungary; (Z.S.); (A.E.); (R.S.)
| | - Nóra Kucsma
- Institute of Molecular Life Sciences, HUN-REN Research Centre for Natural Sciences, H-1117 Budapest, Hungary; (N.K.); (G.S.)
| | - Zsuzsanna Szegő
- Waters Research Center, H-1031 Budapest, Hungary; (Z.S.); (A.E.); (R.S.)
| | | | - Attila Egri
- Waters Research Center, H-1031 Budapest, Hungary; (Z.S.); (A.E.); (R.S.)
| | | | - Bálint András Deák
- Department of Pathology, Forensic and Insurance Medicine, Semmelweis University, H-1085 Budapest, Hungary;
| | - James S. McKenzie
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London W12 0NN, UK;
| | | | - Richard Schäffer
- Waters Research Center, H-1031 Budapest, Hungary; (Z.S.); (A.E.); (R.S.)
| | - Gitta Schlosser
- MTA-ELTE Lendület (Momentum) Ion Mobility Mass Spectrometry Research Group, Faculty of Science, Institute of Chemistry, ELTE Eötvös Loránd University, H-1117 Budapest, Hungary;
| | - Gergely Szakács
- Institute of Molecular Life Sciences, HUN-REN Research Centre for Natural Sciences, H-1117 Budapest, Hungary; (N.K.); (G.S.)
- Center for Cancer Research, Medical University of Vienna, 1090 Vienna, Austria
| | - Júlia Balog
- Waters Research Center, H-1031 Budapest, Hungary; (Z.S.); (A.E.); (R.S.)
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2
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Tata A, Zacometti C, Massaro A, Bragolusi M, Ceroni S, Falappa S, Prataviera D, Merenda M, Piro R, Catania S. Empowering veterinary clinical diagnosis in industrial poultry production by ambient mass spectrometry and chemiometrics: a new approach for precise poultry farming. Poult Sci 2024; 103:103709. [PMID: 38598914 PMCID: PMC11017065 DOI: 10.1016/j.psj.2024.103709] [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] [Received: 02/06/2024] [Revised: 03/22/2024] [Accepted: 03/28/2024] [Indexed: 04/12/2024] Open
Abstract
Untargeted metabolomic profiling, by ambient mass spectrometry and chemometric tools, has made a dramatic impact on human disease detection. In a similar vein, this study attempted the translation of this clinical human disease experience to farmed poultry for precise veterinary diagnosis. As a proof of principle, in this diagnostic/prognostic study, direct analysis in real-time high resolution mass spectrometry (DART-HRMS) was used in an untargeted manner to analyze fresh tissues (abdominal fat, leg skin, liver, and leg muscle) of pigmented and non-pigmented broilers to investigate the causes of lack of pigmentation in an industrial poultry farm. Afterwards, statistical analysis was applied to the DART-HRMS data to retrieve the molecular features that codified for 2 broiler groups, that is, properly pigmented and non-pigmented broilers. Higher abundance of oxidized lipids, high abundance of oxidized bile derivatives, and lower levels of tocopherol isomers (Vitamin E) and retinol (Vitamin A) were captured in nonpigmented than in pigmented broilers. In addition, conventional rapid analyses were used: 1) color parameters of the tissues of pigmented and non-pigmented broilers were measured to rationalize the color differences in abdominal fat, leg skin and leg muscle, and 2) macronutrients were determined in broiler leg muscle, to capture a detailed picture of the pathology and exclude other possible causes. In this study, the DART-HRMS system performed well in retrieving valuable chemical information from broilers that explained the differences between the 2 groups of broilers in absorption of xanthophylls and the subsequent lack of proper broiler pigmentation in affected broilers. The results suggest this technology could be useful in providing near real-time feedback to aid in veterinary decision-making in poultry farming.
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Affiliation(s)
- Alessandra Tata
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy.
| | - Carmela Zacometti
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Andrea Massaro
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Marco Bragolusi
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Simona Ceroni
- Fileni Alimentare SPA, Località Cerrete Collicelli N° 8, Cingoli, Macerata 62011, Italy
| | - Sonia Falappa
- Fileni Alimentare SPA, Località Cerrete Collicelli N° 8, Cingoli, Macerata 62011, Italy
| | - Davide Prataviera
- Avian Medicine Laboratory, Istituto Zooprofilattico Sperimentale delle Venezie, Buttapietra, Verona 37060, Italy
| | - Marianna Merenda
- Avian Medicine Laboratory, Istituto Zooprofilattico Sperimentale delle Venezie, Buttapietra, Verona 37060, Italy
| | - Roberto Piro
- Istituto Zooprofilattico Sperimentale delle Venezie, Laboratorio di Chimica Sperimentale, Vicenza, Italy
| | - Salvatore Catania
- Avian Medicine Laboratory, Istituto Zooprofilattico Sperimentale delle Venezie, Buttapietra, Verona 37060, Italy
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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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Pekov SI, Bormotov DS, Bocharova SI, Sorokin AA, Derkach MM, Popov IA. Mass spectrometry for neurosurgery: Intraoperative support in decision-making. MASS SPECTROMETRY REVIEWS 2024. [PMID: 38571445 DOI: 10.1002/mas.21883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 02/29/2024] [Accepted: 03/23/2024] [Indexed: 04/05/2024]
Abstract
Ambient ionization mass spectrometry was proved to be a powerful tool for oncological surgery. Still, it remains a translational technique on the way from laboratory to clinic. Brain surgery is the most sensitive to resection accuracy field since the balance between completeness of resection and minimization of nerve fiber damage determines patient outcome and quality of life. In this review, we summarize efforts made to develop various intraoperative support techniques for oncological neurosurgery and discuss difficulties arising on the way to clinical implementation of mass spectrometry-guided brain surgery.
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Affiliation(s)
- Stanislav I Pekov
- Skolkovo Institute of Science and Technology, Moscow, Russian Federation
- Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
- Siberian State Medical University, Tomsk, Russian Federation
| | - Denis S Bormotov
- Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
| | | | - Anatoly A Sorokin
- Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
| | - Maria M Derkach
- Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
| | - Igor A Popov
- Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
- Siberian State Medical University, Tomsk, Russian Federation
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5
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Garza KY, King ME, Nagi C, DeHoog RJ, Zhang J, Sans M, Krieger A, Feider CL, Bensussan AV, Keating MF, Lin JQ, Sun MW, Tibshirani R, Pirko C, Brahmbhatt KA, Al-Fartosi AR, Thompson AM, Bonefas E, Suliburk J, Carter SA, Eberlin LS. Intraoperative Evaluation of Breast Tissues During Breast Cancer Operations Using the MasSpec Pen. JAMA Netw Open 2024; 7:e242684. [PMID: 38517441 PMCID: PMC10960202 DOI: 10.1001/jamanetworkopen.2024.2684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 12/30/2023] [Indexed: 03/23/2024] Open
Abstract
Importance Surgery with complete tumor resection remains the main treatment option for patients with breast cancer. Yet, current technologies are limited in providing accurate assessment of breast tissue in vivo, warranting development of new technologies for surgical guidance. Objective To evaluate the performance of the MasSpec Pen for accurate intraoperative assessment of breast tissues and surgical margins based on metabolic and lipid information. Design, Setting, and Participants In this diagnostic study conducted between February 23, 2017, and August 19, 2021, the mass spectrometry-based device was used to analyze healthy breast and invasive ductal carcinoma (IDC) banked tissue samples from adult patients undergoing breast surgery for ductal carcinomas or nonmalignant conditions. Fresh-frozen tissue samples and touch imprints were analyzed in a laboratory. Intraoperative in vivo and ex vivo breast tissue analyses were performed by surgical staff in operating rooms (ORs) within 2 different hospitals at the Texas Medical Center. Molecular data were used to build statistical classifiers. Main Outcomes and Measures Prediction results of tissue analyses from classification models were compared with gross assessment, frozen section analysis, and/or final postoperative pathology to assess accuracy. Results All data acquired from the 143 banked tissue samples, including 79 healthy breast and 64 IDC tissues, were included in the statistical analysis. Data presented rich molecular profiles of healthy and IDC banked tissue samples, with significant changes in relative abundances observed for several metabolic species. Statistical classifiers yielded accuracies of 95.6%, 95.5%, and 90.6% for training, validation, and independent test sets, respectively. A total of 25 participants enrolled in the clinical, intraoperative study; all were female, and the median age was 58 years (IQR, 44-66 years). Intraoperative testing of the technology was successfully performed by surgical staff during 25 breast operations. Of 273 intraoperative analyses performed during 25 surgical cases, 147 analyses from 22 cases were subjected to statistical classification. Testing of the classifiers on 147 intraoperative mass spectra yielded 95.9% agreement with postoperative pathology results. Conclusions and Relevance The findings of this diagnostic study suggest that the mass spectrometry-based system could be clinically valuable to surgeons and patients by enabling fast molecular-based intraoperative assessment of in vivo and ex vivo breast tissue samples and surgical margins.
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Affiliation(s)
- Kyana Y. Garza
- Department of Chemistry, The University of Texas at Austin
| | - Mary E. King
- Department of Chemistry, The University of Texas at Austin
- Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Chandandeep Nagi
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, Texas
| | - Rachel J. DeHoog
- Department of Chemistry, The University of Texas at Austin
- Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Jialing Zhang
- Department of Chemistry, The University of Texas at Austin
| | - Marta Sans
- Department of Chemistry, The University of Texas at Austin
| | - Anna Krieger
- Department of Chemistry, The University of Texas at Austin
| | | | | | - Michael F. Keating
- Department of Chemistry, The University of Texas at Austin
- Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - John Q. Lin
- Department of Chemistry, The University of Texas at Austin
| | - Min Woo Sun
- Department of Biomedical Data Science, Stanford University, Stanford, California
| | - Robert Tibshirani
- Department of Biomedical Data Science, Stanford University, Stanford, California
| | - Christopher Pirko
- Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Kirtan A. Brahmbhatt
- Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Ahmed R. Al-Fartosi
- Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Alastair M. Thompson
- Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Elizabeth Bonefas
- Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - James Suliburk
- Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Stacey A. Carter
- Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Livia S. Eberlin
- Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas
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Guergan S, Boeer B, Fugunt R, Helms G, Roehm C, Solomianik A, Neugebauer A, Nuessle D, Schuermann M, Brunecker K, Jurjut O, Boehme KA, Dammeier S, Enderle MD, Bettio S, Gonzalez-Menendez I, Staebler A, Brucker SY, Kraemer B, Wallwiener D, Fend F, Hahn M. Optical Emission Spectroscopy for the Real-Time Identification of Malignant Breast Tissue. Diagnostics (Basel) 2024; 14:338. [PMID: 38337854 PMCID: PMC10855719 DOI: 10.3390/diagnostics14030338] [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: 11/03/2023] [Revised: 01/29/2024] [Accepted: 01/31/2024] [Indexed: 02/12/2024] Open
Abstract
Breast conserving resection with free margins is the gold standard treatment for early breast cancer recommended by guidelines worldwide. Therefore, reliable discrimination between normal and malignant tissue at the resection margins is essential. In this study, normal and abnormal tissue samples from breast cancer patients were characterized ex vivo by optical emission spectroscopy (OES) based on ionized atoms and molecules generated during electrosurgical treatment. The aim of the study was to determine spectroscopic features which are typical for healthy and neoplastic breast tissue allowing for future real-time tissue differentiation and margin assessment during breast cancer surgery. A total of 972 spectra generated by electrosurgical sparking on normal and abnormal tissue were used for support vector classifier (SVC) training. Specific spectroscopic features were selected for the classification of tissues in the included breast cancer patients. The average classification accuracy for all patients was 96.9%. Normal and abnormal breast tissue could be differentiated with a mean sensitivity of 94.8%, a specificity of 99.0%, a positive predictive value (PPV) of 99.1% and a negative predictive value (NPV) of 96.1%. For 66.6% patients all classifications reached 100%. Based on this convincing data, a future clinical application of OES-based tissue differentiation in breast cancer surgery seems to be feasible.
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Affiliation(s)
- Selin Guergan
- Department of Women’s Health, Tuebingen University Hospital, 72076 Tübingen, Germany; (B.B.); (R.F.); (G.H.); (C.R.); (A.S.); (S.Y.B.); (B.K.); (D.W.); (M.H.)
| | - Bettina Boeer
- Department of Women’s Health, Tuebingen University Hospital, 72076 Tübingen, Germany; (B.B.); (R.F.); (G.H.); (C.R.); (A.S.); (S.Y.B.); (B.K.); (D.W.); (M.H.)
| | - Regina Fugunt
- Department of Women’s Health, Tuebingen University Hospital, 72076 Tübingen, Germany; (B.B.); (R.F.); (G.H.); (C.R.); (A.S.); (S.Y.B.); (B.K.); (D.W.); (M.H.)
| | - Gisela Helms
- Department of Women’s Health, Tuebingen University Hospital, 72076 Tübingen, Germany; (B.B.); (R.F.); (G.H.); (C.R.); (A.S.); (S.Y.B.); (B.K.); (D.W.); (M.H.)
| | - Carmen Roehm
- Department of Women’s Health, Tuebingen University Hospital, 72076 Tübingen, Germany; (B.B.); (R.F.); (G.H.); (C.R.); (A.S.); (S.Y.B.); (B.K.); (D.W.); (M.H.)
| | - Anna Solomianik
- Department of Women’s Health, Tuebingen University Hospital, 72076 Tübingen, Germany; (B.B.); (R.F.); (G.H.); (C.R.); (A.S.); (S.Y.B.); (B.K.); (D.W.); (M.H.)
| | - Alexander Neugebauer
- Erbe Elektromedizin GmbH, Waldhoernlestr. 17, 72072 Tübingen, Germany; (A.N.); (D.N.); (M.S.); (O.J.); (K.A.B.); (S.D.); (M.D.E.)
| | - Daniela Nuessle
- Erbe Elektromedizin GmbH, Waldhoernlestr. 17, 72072 Tübingen, Germany; (A.N.); (D.N.); (M.S.); (O.J.); (K.A.B.); (S.D.); (M.D.E.)
| | - Mirjam Schuermann
- Erbe Elektromedizin GmbH, Waldhoernlestr. 17, 72072 Tübingen, Germany; (A.N.); (D.N.); (M.S.); (O.J.); (K.A.B.); (S.D.); (M.D.E.)
| | - Kristin Brunecker
- Erbe Elektromedizin GmbH, Waldhoernlestr. 17, 72072 Tübingen, Germany; (A.N.); (D.N.); (M.S.); (O.J.); (K.A.B.); (S.D.); (M.D.E.)
| | - Ovidiu Jurjut
- Erbe Elektromedizin GmbH, Waldhoernlestr. 17, 72072 Tübingen, Germany; (A.N.); (D.N.); (M.S.); (O.J.); (K.A.B.); (S.D.); (M.D.E.)
| | - Karen A. Boehme
- Erbe Elektromedizin GmbH, Waldhoernlestr. 17, 72072 Tübingen, Germany; (A.N.); (D.N.); (M.S.); (O.J.); (K.A.B.); (S.D.); (M.D.E.)
| | - Sascha Dammeier
- Erbe Elektromedizin GmbH, Waldhoernlestr. 17, 72072 Tübingen, Germany; (A.N.); (D.N.); (M.S.); (O.J.); (K.A.B.); (S.D.); (M.D.E.)
| | - Markus D. Enderle
- Erbe Elektromedizin GmbH, Waldhoernlestr. 17, 72072 Tübingen, Germany; (A.N.); (D.N.); (M.S.); (O.J.); (K.A.B.); (S.D.); (M.D.E.)
| | - Sabrina Bettio
- Institute of Pathology and Neuropathology, Tuebingen University Hospital, 72076 Tübingen, Germany; (S.B.); (I.G.-M.); (A.S.); (F.F.)
| | - Irene Gonzalez-Menendez
- Institute of Pathology and Neuropathology, Tuebingen University Hospital, 72076 Tübingen, Germany; (S.B.); (I.G.-M.); (A.S.); (F.F.)
| | - Annette Staebler
- Institute of Pathology and Neuropathology, Tuebingen University Hospital, 72076 Tübingen, Germany; (S.B.); (I.G.-M.); (A.S.); (F.F.)
| | - Sara Y. Brucker
- Department of Women’s Health, Tuebingen University Hospital, 72076 Tübingen, Germany; (B.B.); (R.F.); (G.H.); (C.R.); (A.S.); (S.Y.B.); (B.K.); (D.W.); (M.H.)
| | - Bernhard Kraemer
- Department of Women’s Health, Tuebingen University Hospital, 72076 Tübingen, Germany; (B.B.); (R.F.); (G.H.); (C.R.); (A.S.); (S.Y.B.); (B.K.); (D.W.); (M.H.)
| | - Diethelm Wallwiener
- Department of Women’s Health, Tuebingen University Hospital, 72076 Tübingen, Germany; (B.B.); (R.F.); (G.H.); (C.R.); (A.S.); (S.Y.B.); (B.K.); (D.W.); (M.H.)
| | - Falko Fend
- Institute of Pathology and Neuropathology, Tuebingen University Hospital, 72076 Tübingen, Germany; (S.B.); (I.G.-M.); (A.S.); (F.F.)
| | - Markus Hahn
- Department of Women’s Health, Tuebingen University Hospital, 72076 Tübingen, Germany; (B.B.); (R.F.); (G.H.); (C.R.); (A.S.); (S.Y.B.); (B.K.); (D.W.); (M.H.)
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7
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Chung HH, Huang P, Chen CL, Lee C, Hsu CC. Next-generation pathology practices with mass spectrometry imaging. MASS SPECTROMETRY REVIEWS 2023; 42:2446-2465. [PMID: 35815718 DOI: 10.1002/mas.21795] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 04/13/2022] [Accepted: 04/22/2022] [Indexed: 06/15/2023]
Abstract
Mass spectrometry imaging (MSI) is a powerful technique that reveals the spatial distribution of various molecules in biological samples, and it is widely used in pathology-related research. In this review, we summarize common MSI techniques, including matrix-assisted laser desorption/ionization and desorption electrospray ionization MSI, and their applications in pathological research, including disease diagnosis, microbiology, and drug discovery. We also describe the improvements of MSI, focusing on the accumulation of imaging data sets, expansion of chemical coverage, and identification of biological significant molecules, that have prompted the evolution of MSI to meet the requirements of pathology practices. Overall, this review details the applications and improvements of MSI techniques, demonstrating the potential of integrating MSI techniques into next-generation pathology practices.
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Affiliation(s)
- Hsin-Hsiang Chung
- Department of Chemistry, National Taiwan University, Taipei City, Taiwan
| | - Penghsuan Huang
- Department of Chemistry, National Taiwan University, Taipei City, Taiwan
| | - Chih-Lin Chen
- Department of Chemistry, National Taiwan University, Taipei City, Taiwan
| | - Chuping Lee
- Department of Chemistry, Fu Jen Catholic University, New Taipei City, Taiwan
| | - Cheng-Chih Hsu
- Department of Chemistry, National Taiwan University, Taipei City, Taiwan
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8
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Moore JL, Patterson NH, Norris JL, Caprioli RM. Prospective on Imaging Mass Spectrometry in Clinical Diagnostics. Mol Cell Proteomics 2023; 22:100576. [PMID: 37209813 PMCID: PMC10545939 DOI: 10.1016/j.mcpro.2023.100576] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 05/10/2023] [Accepted: 05/12/2023] [Indexed: 05/22/2023] Open
Abstract
Imaging mass spectrometry (IMS) is a molecular technology utilized for spatially driven research, providing molecular maps from tissue sections. This article reviews matrix-assisted laser desorption ionization (MALDI) IMS and its progress as a primary tool in the clinical laboratory. MALDI mass spectrometry has been used to classify bacteria and perform other bulk analyses for plate-based assays for many years. However, the clinical application of spatial data within a tissue biopsy for diagnoses and prognoses is still an emerging opportunity in molecular diagnostics. This work considers spatially driven mass spectrometry approaches for clinical diagnostics and addresses aspects of new imaging-based assays that include analyte selection, quality control/assurance metrics, data reproducibility, data classification, and data scoring. It is necessary to implement these tasks for the rigorous translation of IMS to the clinical laboratory; however, this requires detailed standardized protocols for introducing IMS into the clinical laboratory to deliver reliable and reproducible results that inform and guide patient care.
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Affiliation(s)
| | - Nathan Heath Patterson
- Frontier Diagnostics, Nashville, Tennessee, USA; Vanderbilt University Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA
| | - Jeremy L Norris
- Frontier Diagnostics, Nashville, Tennessee, USA; Vanderbilt University Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA
| | - Richard M Caprioli
- Frontier Diagnostics, Nashville, Tennessee, USA; Vanderbilt University Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA; Departments of Biochemistry, Pharmacology, Chemistry, and Medicine, Vanderbilt University, Nashville, Tennessee, USA.
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9
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Chappel JR, King ME, Fleming J, Eberlin LS, Reif DM, Baker ES. Aggregated Molecular Phenotype Scores: Enhancing Assessment and Visualization of Mass Spectrometry Imaging Data for Tissue-Based Diagnostics. Anal Chem 2023; 95:12913-12922. [PMID: 37579019 PMCID: PMC10561690 DOI: 10.1021/acs.analchem.3c02389] [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] [Indexed: 08/16/2023]
Abstract
Mass spectrometry imaging (MSI) has gained increasing popularity for tissue-based diagnostics due to its ability to identify and visualize molecular characteristics unique to different phenotypes within heterogeneous samples. Data from MSI experiments are often assessed and visualized using various supervised and unsupervised statistical approaches. However, these approaches tend to fall short in identifying and concisely visualizing subtle, phenotype-relevant molecular changes. To address these shortcomings, we developed aggregated molecular phenotype (AMP) scores. AMP scores are generated using an ensemble machine learning approach to first select features differentiating phenotypes, weight the features using logistic regression, and combine the weights and feature abundances. AMP scores are then scaled between 0 and 1, with lower values generally corresponding to class 1 phenotypes (typically control) and higher scores relating to class 2 phenotypes. AMP scores, therefore, allow the evaluation of multiple features simultaneously and showcase the degree to which these features correlate with various phenotypes. Due to the ensembled approach, AMP scores are able to overcome limitations associated with individual models, leading to high diagnostic accuracy and interpretability. Here, AMP score performance was evaluated using metabolomic data collected from desorption electrospray ionization MSI. Initial comparisons of cancerous human tissues to their normal or benign counterparts illustrated that AMP scores distinguished phenotypes with high accuracy, sensitivity, and specificity. Furthermore, when combined with spatial coordinates, AMP scores allow visualization of tissue sections in one map with distinguished phenotypic borders, highlighting their diagnostic utility.
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Affiliation(s)
- Jessie R Chappel
- Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27606, United States
| | - Mary E King
- Department of Surgery, Baylor College of Medicine, Houston, Texas 77030, United States
| | - Jonathon Fleming
- Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27606, United States
| | - Livia S Eberlin
- Department of Surgery, Baylor College of Medicine, Houston, Texas 77030, United States
| | - David M Reif
- Predictive Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, North Carolina 27709, United States
| | - Erin S Baker
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514, United States
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10
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Zhou Y, Jiang X, Wang X, Huang J, Li T, Jin H, He J. Promise of spatially resolved omics for tumor research. J Pharm Anal 2023; 13:851-861. [PMID: 37719191 PMCID: PMC10499658 DOI: 10.1016/j.jpha.2023.07.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 07/01/2023] [Accepted: 07/06/2023] [Indexed: 09/19/2023] Open
Abstract
Tumors are spatially heterogeneous tissues that comprise numerous cell types with intricate structures. By interacting with the microenvironment, tumor cells undergo dynamic changes in gene expression and metabolism, resulting in spatiotemporal variations in their capacity for proliferation and metastasis. In recent years, the rapid development of histological techniques has enabled efficient and high-throughput biomolecule analysis. By preserving location information while obtaining a large number of gene and molecular data, spatially resolved metabolomics (SRM) and spatially resolved transcriptomics (SRT) approaches can offer new ideas and reliable tools for the in-depth study of tumors. This review provides a comprehensive introduction and summary of the fundamental principles and research methods used for SRM and SRT techniques, as well as a review of their applications in cancer-related fields.
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Affiliation(s)
- Yanhe Zhou
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Xinyi Jiang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Xiangyi Wang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Jianpeng Huang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Tong Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Hongtao Jin
- New Drug Safety Evaluation Center, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100050, China
- NMPA Key Laboratory for Safety Research and Evaluation of Innovative Drug, Beijing, 10050, China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
- NMPA Key Laboratory for Safety Research and Evaluation of Innovative Drug, Beijing, 10050, China
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11
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DeHoog RJ, Lin M, Roman G, Martin R, Suliburk J, Eberlin LS. Evaluating the Generalizability of Predictive Classifiers Built from DESI Imaging Lipid Data across Mass Spectrometry Platforms. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:1532-1537. [PMID: 37294704 PMCID: PMC10882941 DOI: 10.1021/jasms.3c00075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
In this study, we evaluate the generalizability of predictive classifiers built from DESI lipid data for thyroid fine needle aspiration (FNA) biopsy analysis and classification using two high-performance mass spectrometers (time-of-flight and orbitrap) suited with different DESI imaging sources operated by different users. The molecular profiles obtained from thyroid samples with the different platforms presented similar trends, although specific differences in ion abundances were observed. When using a previously published statistical model built to discriminate thyroid cancer from benign thyroid tissues to predict on a new independent data set obtained, agreement for 24 of the 30 samples across the imaging platforms was achieved. We also tested the classifier on six clinical FNAs and obtained agreement between the predictive results and clinical diagnosis for the different conditions. Altogether, our results provide evidence that statistical classifiers generated from DESI lipid data are applicable across different high-resolution mass spectrometry platforms for thyroid FNA classification.
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Affiliation(s)
- Rachel J DeHoog
- Department of Surgery, Baylor College of Medicine, Houston, Texas 77030, USA
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, USA
| | - Monica Lin
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, USA
| | - Gregory Roman
- Waters Corporation, Milford, Massachusetts 01757, USA
| | - Roy Martin
- Waters Corporation, Milford, Massachusetts 01757, USA
| | - James Suliburk
- Department of Surgery, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Livia S Eberlin
- Department of Surgery, Baylor College of Medicine, Houston, Texas 77030, USA
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12
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Chappel JR, King ME, Fleming J, Eberlin LS, Reif DM, Baker ES. Utilizing Aggregated Molecular Phenotype (AMP) Scores to Visualize Simultaneous Molecular Changes in Mass Spectrometry Imaging Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.01.543306. [PMID: 37333214 PMCID: PMC10274704 DOI: 10.1101/2023.06.01.543306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Mass spectrometry imaging (MSI) has gained increasing popularity for tissue-based diagnostics due to its ability to identify and visualize molecular characteristics unique to different phenotypes within heterogeneous samples. Data from MSI experiments are often visualized using single ion images and further analyzed using machine learning and multivariate statistics to identify m/z features of interest and create predictive models for phenotypic classification. However, often only a single molecule or m/z feature is visualized per ion image, and mainly categorical classifications are provided from the predictive models. As an alternative approach, we developed an aggregated molecular phenotype (AMP) scoring system. AMP scores are generated using an ensemble machine learning approach to first select features differentiating phenotypes, weight the features using logistic regression, and combine the weights and feature abundances. AMP scores are then scaled between 0 and 1, with lower values generally corresponding to class 1 phenotypes (typically control) and higher scores relating to class 2 phenotypes. AMP scores therefore allow the evaluation of multiple features simultaneously and showcase the degree to which these features correlate with various phenotypes, leading to high diagnostic accuracy and interpretability of predictive models. Here, AMP score performance was evaluated using metabolomic data collected from desorption electrospray ionization (DESI) MSI. Initial comparisons of cancerous human tissues to normal or benign counterparts illustrated that AMP scores distinguished phenotypes with high accuracy, sensitivity, and specificity. Furthermore, when combined with spatial coordinates, AMP scores allow visualization of tissue sections in one map with distinguished phenotypic borders, highlighting their diagnostic utility.
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Affiliation(s)
- Jessie R. Chappel
- Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - Mary E. King
- Department of Surgery, Baylor College of Medicine, Houston, TX, USA
| | - Jonathon Fleming
- Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - Livia S. Eberlin
- Department of Surgery, Baylor College of Medicine, Houston, TX, USA
| | - David M. Reif
- Predictive Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Erin S. Baker
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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13
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Mondal S, Sthanikam Y, Kumar A, Nandy A, Chattopadhyay S, Koner D, Rukmangadha N, Narendra H, Banerjee S. Mass Spectrometry Imaging of Lumpectomy Specimens Deciphers Diacylglycerols as Potent Biomarkers for the Diagnosis of Breast Cancer. Anal Chem 2023; 95:8054-8062. [PMID: 37167069 DOI: 10.1021/acs.analchem.3c01019] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Detecting breast tumor markers with a fast turnaround time from frozen sections should foster intraoperative histopathology in breast-conserving surgery, reducing the need for a second operation. Hence, rapid label-free discrimination of the spatially resolved molecular makeup between cancer and adjacent normal breast tissue is of growing importance. We performed desorption electrospray ionization mass spectrometry imaging (DESI-MSI) of fresh-frozen excision specimens, including cancer and paired adjacent normal sections, obtained from the lumpectomy of 73 breast cancer patients. The results demonstrate that breast cancer tissue posits sharp metabolic upregulation of diacylglycerol, a lipid second messenger that activates protein kinase C for promoting tumor growth. We identified four specific sn-1,2-diacylglycerols that outperformed all other lipids simultaneously mapped by the positive ion mode DESI-MSI for distinguishing cancers from adjacent normal specimens. This result contrasts with several previous DESI-MSI studies that probed metabolic dysregulation of glycerophospholipids, sphingolipids, and free fatty acids for cancer diagnoses. A random forest-based supervised machine learning considering all detected ion signals also deciphered the highest diagnostic potential of these four diacylglycerols with the top four importance scores. This led us to construct a classifier with 100% overall prediction accuracy of breast cancer by using the parsimonious set of four diacylglycerol biomarkers only. The metabolic pathway analysis suggested that increased catabolism of phosphatidylcholine in breast cancer contributes to diacylglycerol overexpression. These results open up opportunities for mapping diacylglycerol signaling in breast cancer in the context of novel therapeutic and diagnostic developments, including the intraoperative assessment of breast cancer margin status.
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Affiliation(s)
- Supratim Mondal
- Department of Chemistry, Indian Institute of Science Education and Research Tirupati, Tirupati 517507, India
| | - Yeswanth Sthanikam
- Department of Chemistry, Indian Institute of Science Education and Research Tirupati, Tirupati 517507, India
| | - Anubhav Kumar
- Department of Chemistry, Indian Institute of Science Education and Research Tirupati, Tirupati 517507, India
| | - Abhijit Nandy
- Department of Chemistry, Indian Institute of Science Education and Research Tirupati, Tirupati 517507, India
| | - Sutirtha Chattopadhyay
- Department of Chemistry, Indian Institute of Science Education and Research Tirupati, Tirupati 517507, India
| | - Debasish Koner
- Department of Chemistry, Indian Institute of Science Education and Research Tirupati, Tirupati 517507, India
| | - Nandyala Rukmangadha
- Department of Pathology, Sri Venkateswara Institute of Medical Sciences, Tirupati 517507, India
| | - Hulikal Narendra
- Department of Surgical Oncology, Sri Venkateswara Institute of Medical Sciences, Tirupati 517507, India
| | - Shibdas Banerjee
- Department of Chemistry, Indian Institute of Science Education and Research Tirupati, Tirupati 517507, India
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14
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Soudah T, Zoabi A, Margulis K. Desorption electrospray ionization mass spectrometry imaging in discovery and development of novel therapies. MASS SPECTROMETRY REVIEWS 2023; 42:751-778. [PMID: 34642958 DOI: 10.1002/mas.21736] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Revised: 09/16/2021] [Accepted: 09/21/2021] [Indexed: 06/13/2023]
Abstract
Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is one of the least specimen destructive ambient ionization mass spectrometry tissue imaging methods. It enables rapid simultaneous mapping, measurement, and identification of hundreds of molecules from an unmodified tissue sample. Over the years, since its first introduction as an imaging technique in 2005, DESI-MSI has been extensively developed as a tool for separating tissue regions of various histopathologic classes for diagnostic applications. Recently, DESI-MSI has also emerged as a versatile technique that enables drug discovery and can guide the efficient development of drug delivery systems. For example, it has been increasingly employed for uncovering unique patterns of in vivo drug distribution, the discovery of potentially treatable biochemical pathways, revealing novel druggable targets, predicting therapeutic sensitivity of diseased tissues, and identifying early tissue response to pharmacological treatment. These and other recent advances in implementing DESI-MSI as the tool for the development of novel therapies are highlighted in this review.
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Affiliation(s)
- Terese Soudah
- The Faculty of Medicine, The School of Pharmacy, The Institute for Drug Research, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Amani Zoabi
- The Faculty of Medicine, The School of Pharmacy, The Institute for Drug Research, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Katherine Margulis
- The Faculty of Medicine, The School of Pharmacy, The Institute for Drug Research, The Hebrew University of Jerusalem, Jerusalem, Israel
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15
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Hermann M, Metwally H, Yu J, Smith R, Tomm H, Kaufmann M, Ren KYM, Liu C, LeBlanc Y, Covey TR, Ross AC, Oleschuk RD. 3D printer platform and conductance feedback loop for automated imaging of uneven surfaces by liquid microjunction-surface sampling probe mass spectrometry. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2023:e9492. [PMID: 36756683 DOI: 10.1002/rcm.9492] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 02/06/2023] [Accepted: 02/07/2023] [Indexed: 06/18/2023]
Abstract
RATIONALE Molecular imaging of samples using mass spectrometric techniques, such as matrix-assisted laser desorption ionization or desorption electrospray ionization, requires the sample surface to be even/flat and sliced into thin sections (c. 10 μm). Furthermore, sample preparation steps can alter the analyte composition of the sample. The liquid microjunction-surface sampling probe (LMJ-SSP) is a robust sampling interface that enables surface profiling with minimal sample preparation. In conjunction with a conductance feedback system, the LMJ-SSP can be used to automatically sample uneven specimens. METHODS A sampling stage was built with a modified 3D printer where the LMJ-SSP is attached to the printing head. This setup can scan across flat and even surfaces in a predefined pattern ("static sampling mode"). Uneven samples are automatically probed in "conductance sampling mode" where an electric potential is applied and measured at the probe. When the probe contacts the electrically grounded sample, the potential at the probe drops, which is used as a feedback signal to determine the optimal position of the probe for sampling each location. RESULTS The applicability of the probe/sensing system was demonstrated by first examining the strawberry tissue using the "static sampling mode." Second, porcine tissue samples were profiled using the "conductance sampling mode." With minimal sample preparation, an area of 11 × 15 mm was profiled in less than 2 h. From the obtained results, adipose areas could be distinguished from non-adipose parts. The versatility of the approach was further demonstrated by directly sampling the bacteria colonies on agar and resected human kidney (intratumoral hemorrhage) specimens with thicknesses ranging from 1 to 4 mm. CONCLUSION The LMJ-SSP in conjunction with a conductive feedback system is a powerful tool that allows for fast, reproducible, and automated assessment of uneven surfaces with minimal sample preparation. This setup could be used for perioperative assessment of tissue samples, food screening, and natural product discovery, among others.
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Affiliation(s)
- Matthias Hermann
- Department of Chemistry, Queen's University, Kingston, Ontario, Canada
| | - Haidy Metwally
- Department of Chemistry, Queen's University, Kingston, Ontario, Canada
| | - Jian Yu
- Department of Chemistry, Queen's University, Kingston, Ontario, Canada
| | - Rachael Smith
- Department of Chemistry, Queen's University, Kingston, Ontario, Canada
| | - Hailey Tomm
- Department of Chemistry, Queen's University, Kingston, Ontario, Canada
| | - Martin Kaufmann
- Department of Surgery, Queen's University, Kingston, Ontario, Canada
| | - Kevin Y M Ren
- Department of Pathology, Queen's University, Kingston, Ontario, Canada
| | | | | | | | - Avena C Ross
- Department of Chemistry, Queen's University, Kingston, Ontario, Canada
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16
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Gonçalves JPL, Bollwein C, Noske A, Jacob A, Jank P, Loibl S, Nekljudova V, Fasching PA, Karn T, Marmé F, Müller V, Schem C, Sinn BV, Stickeler E, van Mackelenbergh M, Schmitt WD, Denkert C, Weichert W, Schwamborn K. Characterization of Hormone Receptor and HER2 Status in Breast Cancer Using Mass Spectrometry Imaging. Int J Mol Sci 2023; 24:ijms24032860. [PMID: 36769215 PMCID: PMC9918176 DOI: 10.3390/ijms24032860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 01/27/2023] [Accepted: 01/31/2023] [Indexed: 02/05/2023] Open
Abstract
Immunohistochemical evaluation of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2 status stratify the different subtypes of breast cancer and define the treatment course. Triple-negative breast cancer (TNBC), which does not register receptor overexpression, is often associated with worse patient prognosis. Mass spectrometry imaging transcribes the molecular content of tissue specimens without requiring additional tags or preliminary analysis of the samples, being therefore an excellent methodology for an unbiased determination of tissue constituents, in particular tumor markers. In this study, the proteomic content of 1191 human breast cancer samples was characterized by mass spectrometry imaging and the epithelial regions were employed to train and test machine-learning models to characterize the individual receptor status and to classify TNBC. The classification models presented yielded high accuracies for estrogen and progesterone receptors and over 95% accuracy for classification of TNBC. Analysis of the molecular features revealed that vimentin overexpression is associated with TNBC, supported by immunohistochemistry validation, revealing a new potential target for diagnosis and treatment.
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Affiliation(s)
- Juliana Pereira Lopes Gonçalves
- Institute of Pathology, School of Medicine, Technical University of Munich, Trogerstraße 18, 81675 Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, 80336 Munich, Germany
| | - Christine Bollwein
- Institute of Pathology, School of Medicine, Technical University of Munich, Trogerstraße 18, 81675 Munich, Germany
| | - Aurelia Noske
- Institute of Pathology, School of Medicine, Technical University of Munich, Trogerstraße 18, 81675 Munich, Germany
| | - Anne Jacob
- Institute of Pathology, School of Medicine, Technical University of Munich, Trogerstraße 18, 81675 Munich, Germany
| | - Paul Jank
- Institute of Pathology, Philipps-University Marburg and University Hospital Marburg (UKGM), 35043 Marburg, Germany
| | - Sibylle Loibl
- German Breast Group (GBG), 63263 Neu-Isenburg, Germany
| | | | - Peter A. Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), 91054 Erlangen, Germany
| | - Thomas Karn
- Department of Gynecology and Obstetrics, Goethe-University Frankfurt, 60590 Frankfurt, Germany
| | - Frederik Marmé
- Department of Obstetrics and Gynecology, University Hospital Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany
| | - Volkmar Müller
- Department of Gynecology, Universitätsklinikum Hamburg-Eppendorf, 20251 Hamburg, Germany
| | | | | | - Elmar Stickeler
- Department of Obstetrics and Gynecology, University Hospital Aachen, 52074 Aachen, Germany
| | - Marion van Mackelenbergh
- Klinik für Gynäkologie und Geburtshilfe, Universitätsklinikum Schleswig-Holstein, 24105 Kiel, Germany
| | | | - Carsten Denkert
- Institute of Pathology, Philipps-University Marburg and University Hospital Marburg (UKGM), 35043 Marburg, Germany
| | - Wilko Weichert
- Institute of Pathology, School of Medicine, Technical University of Munich, Trogerstraße 18, 81675 Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, 80336 Munich, Germany
| | - Kristina Schwamborn
- Institute of Pathology, School of Medicine, Technical University of Munich, Trogerstraße 18, 81675 Munich, Germany
- Correspondence:
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17
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Hu H, Laskin J. Emerging Computational Methods in Mass Spectrometry Imaging. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2203339. [PMID: 36253139 PMCID: PMC9731724 DOI: 10.1002/advs.202203339] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 09/17/2022] [Indexed: 05/10/2023]
Abstract
Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.
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Affiliation(s)
- Hang Hu
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN47907USA
| | - Julia Laskin
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN47907USA
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18
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Gao SQ, Zhao JH, Guan Y, Tang YS, Li Y, Liu LY. Mass Spectrometry Imaging technology in metabolomics: a systematic review. Biomed Chromatogr 2022:e5494. [PMID: 36044038 DOI: 10.1002/bmc.5494] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/24/2022] [Accepted: 08/28/2022] [Indexed: 11/11/2022]
Abstract
Mass spectrometry imaging (MSI) is a powerful label-free analysis technique that can provide simultaneous spatial distribution of multiple compounds in a single experiment. By combining the sensitive and rapid screening of high-throughput mass spectrometry with spatial chemical information, metabolite analysis and morphological characteristics are presented in a single image. MSI can be used for qualitative and quantitative analysis of metabolic profiles and it can provide visual analysis of spatial distribution information of complex biological and microbial systems. Matrix assisted laser desorption ionization, laser ablation electrospray ionization and desorption electrospray ionization are commonly used in MSI. Here, we summarize and compare these three technologies, as well as the applications and prospects of MSI in metabolomics.
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Affiliation(s)
- Si-Qi Gao
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China
| | - Jin-Hui Zhao
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China
| | - Yue Guan
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China
| | - Ying-Shu Tang
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China
| | - Ying Li
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China
| | - Li-Yan Liu
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China
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19
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Mass Spectrometry Imaging Spatial Tissue Analysis toward Personalized Medicine. LIFE (BASEL, SWITZERLAND) 2022; 12:life12071037. [PMID: 35888125 PMCID: PMC9318569 DOI: 10.3390/life12071037] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/04/2022] [Accepted: 07/10/2022] [Indexed: 12/19/2022]
Abstract
Novel profiling methodologies are redefining the diagnostic capabilities and therapeutic approaches towards more precise and personalized healthcare. Complementary information can be obtained from different omic approaches in combination with the traditional macro- and microscopic analysis of the tissue, providing a more complete assessment of the disease. Mass spectrometry imaging, as a tissue typing approach, provides information on the molecular level directly measured from the tissue. Lipids, metabolites, glycans, and proteins can be used for better understanding imbalances in the DNA to RNA to protein translation, which leads to aberrant cellular behavior. Several studies have explored the capabilities of this technology to be applied to tumor subtyping, patient prognosis, and tissue profiling for intraoperative tissue evaluation. In the future, intercenter studies may provide the needed confirmation on the reproducibility, robustness, and applicability of the developed classification models for tissue characterization to assist in disease management.
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20
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Isberg OG, Giunchiglia V, McKenzie JS, Takats Z, Jonasson JG, Bodvarsdottir SK, Thorsteinsdottir M, Xiang Y. Automated Cancer Diagnostics via Analysis of Optical and Chemical Images by Deep and Shallow Learning. Metabolites 2022; 12:455. [PMID: 35629959 PMCID: PMC9143055 DOI: 10.3390/metabo12050455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 05/10/2022] [Accepted: 05/13/2022] [Indexed: 02/04/2023] Open
Abstract
Optical microscopy has long been the gold standard to analyse tissue samples for the diagnostics of various diseases, such as cancer. The current diagnostic workflow is time-consuming and labour-intensive, and manual annotation by a qualified pathologist is needed. With the ever-increasing number of tissue blocks and the complexity of molecular diagnostics, new approaches have been developed as complimentary or alternative solutions for the current workflow, such as digital pathology and mass spectrometry imaging (MSI). This study compares the performance of a digital pathology workflow using deep learning for tissue recognition and an MSI approach utilising shallow learning to annotate formalin-fixed and paraffin-embedded (FFPE) breast cancer tissue microarrays (TMAs). Results show that both deep learning algorithms based on conventional optical images and MSI-based shallow learning can provide automated diagnostics with F1-scores higher than 90%, with the latter intrinsically built on biochemical information that can be used for further analysis.
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Affiliation(s)
- Olof Gerdur Isberg
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (O.G.I.); (V.G.); (J.S.M.); (Z.T.)
- Faculty of Pharmaceutical Sciences, University of Iceland, Hofsvallagata 53, 107 Reykjavik, Iceland
- Biomedical Center, School of Health Sciences, University of Iceland, 101 Reykjavik, Iceland;
| | - Valentina Giunchiglia
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (O.G.I.); (V.G.); (J.S.M.); (Z.T.)
| | - James S. McKenzie
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (O.G.I.); (V.G.); (J.S.M.); (Z.T.)
| | - Zoltan Takats
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (O.G.I.); (V.G.); (J.S.M.); (Z.T.)
| | - Jon Gunnlaugur Jonasson
- Department of Pathology, Landspitali the National University Hospital, Hringbraut, 101 Reykjavik, Iceland;
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland
| | | | - Margret Thorsteinsdottir
- Faculty of Pharmaceutical Sciences, University of Iceland, Hofsvallagata 53, 107 Reykjavik, Iceland
- Biomedical Center, School of Health Sciences, University of Iceland, 101 Reykjavik, Iceland;
| | - Yuchen Xiang
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (O.G.I.); (V.G.); (J.S.M.); (Z.T.)
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Huang L, Nie L, Dai Z, Dong J, Jia X, Yang X, Yao L, Ma SC. The application of mass spectrometry imaging in traditional Chinese medicine: a review. Chin Med 2022; 17:35. [PMID: 35248086 PMCID: PMC8898510 DOI: 10.1186/s13020-022-00586-8] [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: 12/16/2021] [Accepted: 02/22/2022] [Indexed: 08/26/2023] Open
Abstract
AbstractMass spectrometry imaging is a frontier technique which connects classical mass spectrometry with ion imaging. Various types of chemicals could be visualized in their native tissues using mass spectrometry imaging. Up to now, the most commonly applied mass spectrometry imaging techniques are matrix assisted laser desorption ionization mass spectrometry imaging, desorption electrospray ionization mass spectrometry imaging and secondary ion mass spectrometry imaging. This review gives an introduction to the principles, development and applications of commonly applied mass spectrometry imaging techniques, and then illustrates the application of mass spectrometry imaging in the investigation of traditional Chinese medicine. Recently, mass spectrometry imaging has been adopted to explore the spatial distribution of endogenous metabolites in traditional Chinese medicine. Data collected from mass spectrometry imaging can be further utilized to search for marker components of traditional Chinese medicine, discover new compounds from traditional herbs, and differentiate between medicinal plants that are similar in botanical features. Moreover, mass spectrometry imaging also plays a role in revealing the pharmacological and toxicological mechanisms of traditional Chinese medicine.
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Huang L, Mao X, Sun C, Li T, Song X, Li J, Gao S, Zhang R, Chen J, He J, Abliz Z. Molecular Pathological Diagnosis of Thyroid Tumors Using Spatially Resolved Metabolomics. Molecules 2022; 27:molecules27041390. [PMID: 35209182 PMCID: PMC8876246 DOI: 10.3390/molecules27041390] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 02/11/2022] [Accepted: 02/11/2022] [Indexed: 02/04/2023] Open
Abstract
The pathological diagnosis of benign and malignant follicular thyroid tumors remains a major challenge using the current histopathological technique. To improve diagnosis accuracy, spatially resolved metabolomics analysis based on air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) technique was used to establish a molecular diagnostic strategy for discriminating four pathological types of thyroid tumor. Without any specific labels, numerous metabolite features with their spatial distribution information can be acquired by AFADESI-MSI. The underlying metabolic heterogeneity can be visualized in line with the cellular heterogeneity in native tumor tissue. Through micro-regional feature extraction and in situ metabolomics analysis, three sets of metabolic biomarkers for the visual discrimination of benign follicular adenoma and differentiated thyroid carcinomas were discovered. Additionally, the automated prediction of tumor foci was supported by a diagnostic model based on the metabolic profile of 65 thyroid nodules. The model prediction accuracy was 83.3% when a test set of 12 independent samples was used. This diagnostic strategy presents a new way of performing in situ pathological examinations using small molecular biomarkers and provides a model diagnosis for clinically indeterminate thyroid tumor cases.
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Affiliation(s)
- Luojiao Huang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
| | - Xinxin Mao
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China;
| | - Chenglong Sun
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
| | - Tiegang Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
| | - Xiaowei Song
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
| | - Jiangshuo Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
| | - Shanshan Gao
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
- NMPA Key Laboratory for Safety Research and Evaluation of Innovative Drug, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Jie Chen
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China;
- Correspondence: (J.C.); (J.H.)
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
- NMPA Key Laboratory for Safety Research and Evaluation of Innovative Drug, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
- Correspondence: (J.C.); (J.H.)
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
- Center for Imaging and Systems Biology, School of Pharmacy, Minzu University of China, Beijing 100081, China
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Recent Advances of Ambient Mass Spectrometry Imaging and Its Applications in Lipid and Metabolite Analysis. Metabolites 2021; 11:metabo11110780. [PMID: 34822438 PMCID: PMC8625079 DOI: 10.3390/metabo11110780] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 11/08/2021] [Accepted: 11/11/2021] [Indexed: 01/02/2023] Open
Abstract
Ambient mass spectrometry imaging (AMSI) has attracted much attention in recent years. As a kind of unlabeled molecular imaging technique, AMSI can enable in situ visualization of a large number of compounds in biological tissue sections in ambient conditions. In this review, the developments of various AMSI techniques are discussed according to one-step and two-step ionization strategies. In addition, recent applications of AMSI for lipid and metabolite analysis (from 2016 to 2021) in disease diagnosis, animal model research, plant science, drug metabolism and toxicology research, etc., are summarized. Finally, further perspectives of AMSI in spatial resolution, sensitivity, quantitative ability, convenience and software development are proposed.
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Isberg OG, Xiang Y, Bodvarsdottir SK, Jonasson JG, Thorsteinsdottir M, Takats Z. The effect of sample age on the metabolic information extracted from formalin-fixed and paraffin embedded tissue samples using desorption electrospray ionization mass spectrometry imaging. J Mass Spectrom Adv Clin Lab 2021; 22:50-55. [PMID: 34939055 PMCID: PMC8662337 DOI: 10.1016/j.jmsacl.2021.10.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Background: Metabolites, especially lipids, have been shown to be promising therapeutic targets. In conjugation with genes and proteins they can be used to identify phenotypes of disease and support the development of targeted treatments. The majority of clinically collected tissue samples are stored in formalin-fixed and paraffin embedded (FFPE) blocks due to their tissue conservation ability and indefinite storage capacity. For metabolic analysis, however, fresh frozen (FF) samples are currently preferred over FFPE samples due to concerns of metabolic information being lost when preparing the samples. With little or no sample preparation, desorption electrospray ionisation mass spectrometry imaging (DESI-MSI) allows for the study of spatial as well as spectral information. Methods: DESI-MSI analysis was performed on FFPE breast cancer tissue microarray samples from 213 patients collected between the years 1935-2013. Logistic regression (LR) models were built to classify samples based on age and FF samples were used for feature validation. Results: LR models developed on the FFPE samples achieved an average classification accuracy of 96% when predicting their age with a 10-year grouping. Closer examination of the metabolic change over time revealed that the mean signal intensities for the lower mass range (100 - 500 m/z) linearly decrease over time, while the mean intensities for the higher mass range (500 - 900 m/z), remained relatively constant. Conclusions: In our samples, which span over 70 years, sample age has a weak yet quantifiable impact on metabolite content in FFPE samples, while the higher mass range is seemingly unaffected. FFPE samples thus provide an alternative avenue for metabolic analysis of lipids.
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Affiliation(s)
- Olof Gerdur Isberg
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
- Faculty of Pharmaceutical Sciences, University of Iceland, Hofsvallagata 53, 107 Reykjavik, Iceland
- Biomedical Center, University of Iceland, Reykjavik, Iceland
| | - Yuchen Xiang
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | | | - Jon Gunnlaugur Jonasson
- Pathology, Landspitali-National University Hospital, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Margret Thorsteinsdottir
- Faculty of Pharmaceutical Sciences, University of Iceland, Hofsvallagata 53, 107 Reykjavik, Iceland
- Biomedical Center, University of Iceland, Reykjavik, Iceland
| | - Zoltan Takats
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
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A Mass Spectrometry Imaging Based Approach for Prognosis Prediction in UICC Stage I/II Colon Cancer. Cancers (Basel) 2021; 13:cancers13215371. [PMID: 34771536 PMCID: PMC8582467 DOI: 10.3390/cancers13215371] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 10/15/2021] [Accepted: 10/21/2021] [Indexed: 12/24/2022] Open
Abstract
Simple Summary Tumor treatment is heavily dictated by the tumor progression status. However, in colon cancer, it is difficult to predict disease progression in the early stages. In this study, we have employed a proteomic analysis using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). MALDI-MSI is a technique that measures the molecular content of (tumor) tissue. We analyzed tumor samples of 276 patients. If the patients developed distant metastasis, they were considered to have a more aggressive tumor type than the patients that did not. In this comparative study, we have developed bioinformatics methods that can predict the tendency of tumor progression and advance a couple of molecules that could be used as prognostic markers of colon cancer. The prediction of tumor progression can help to choose a more adequate treatment for each individual patient. Abstract Currently, pathological evaluation of stage I/II colon cancer, following the Union Internationale Contre Le Cancer (UICC) guidelines, is insufficient to identify patients that would benefit from adjuvant treatment. In our study, we analyzed tissue samples from 276 patients with colon cancer utilizing mass spectrometry imaging. Two distinct approaches are herein presented for data processing and analysis. In one approach, four different machine learning algorithms were applied to predict the tendency to develop metastasis, which yielded accuracies over 90% for three of the models. In the other approach, 1007 m/z features were evaluated with regards to their prognostic capabilities, yielding two m/z features as promising prognostic markers. One feature was identified as a fragment from collagen (collagen 3A1), hinting that a higher collagen content within the tumor is associated with poorer outcomes. Identification of proteins that reflect changes in the tumor and its microenvironment could give a very much-needed prediction of a patient’s prognosis, and subsequently assist in the choice of a more adequate treatment.
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Cao G, Song Z, Yang Z, Chen Z, Hong Y, Cai Z. Database-assisted global metabolomics profiling of pleural effusion induced by tuberculosis and malignancy. CHINESE CHEM LETT 2021. [DOI: 10.1016/j.cclet.2021.03.052] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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Deng J, Yang Y, Zeng Z, Xiao X, Li J, Luan T. Discovery of Potential Lipid Biomarkers for Human Colorectal Cancer by In-Capillary Extraction Nanoelectrospray Ionization Mass Spectrometry. Anal Chem 2021; 93:13089-13098. [PMID: 34523336 DOI: 10.1021/acs.analchem.1c03249] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Discovering cancer biomarkers is of significance for clinical medicine and disease diagnosis. In this article, we develop an in-capillary extraction nanoelectrospray ionization mass spectrometry (ICE-nanoESI-MS) method to rapidly and in situ investigate human colorectal cancer for discovering lipid biomarkers. The ICE-nanoESI-MS method is performed using a tungsten microdissecting probe for in situ microsampling of surgical human colorectal cancer tumors and their paired distal noncancerous tissues during/after surgery. After sampling, the tungsten probe and the adhered tissues are inserted into a nanospray tip prefilled with some solvent for simultaneous in-capillary extraction and nanoESI-MS detection under ambient and open-air conditions. Online coupling of the Paternò-Büchi reaction and radical-direct fragmentation with ICE-nanoESI-MS is easily realized, which provides the opportunity to precisely determine carbon-carbon double bond (C═C) locations and stereospecific numbering (sn) positions of lipid biomarkers. Subsequently, a total of 12 pairs of colorectal cancer tumors and distal noncancerous tissues from different patients are investigated by our proposed ICE-nanoESI-MS method. A significant increase in lysophospholipids and fatty acids as well as a significant decrease in ceramides are discovered, and lysophospholipids are found as the potential biomarkers related to the formation and pathogenesis of human colorectal cancer.
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Affiliation(s)
- Jiewei Deng
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China
| | - Yunyun Yang
- Guangdong Provincial Engineering Research Center for Ambient Mass Spectrometry, Guangdong Provincial Key Laboratory of Emergency Test for Dangerous Chemicals, Institute of Analysis, Guangdong Academy of Sciences (China National Analytical Center, Guangzhou), Guangzhou 510070, China
| | - Zhaolei Zeng
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou 510070, China
| | - Xue Xiao
- Guangdong Provincial Engineering Research Center for Ambient Mass Spectrometry, Guangdong Provincial Key Laboratory of Emergency Test for Dangerous Chemicals, Institute of Analysis, Guangdong Academy of Sciences (China National Analytical Center, Guangzhou), Guangzhou 510070, China
| | - Jiajie Li
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China
| | - Tiangang Luan
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China.,Institute of Environmental and Ecological Engineering, Guangdong University of Technology, Guangzhou 510006, China.,School of Life Sciences, Sun Yat-Sen University, Guangzhou 510275, China
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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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Tu A, Said N, Muddiman DC. Spatially resolved metabolomic characterization of muscle invasive bladder cancer by mass spectrometry imaging. Metabolomics 2021; 17:70. [PMID: 34287708 PMCID: PMC8893274 DOI: 10.1007/s11306-021-01819-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Accepted: 07/09/2021] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Muscle invasive bladder cancer (MIBC) is an advanced stage of bladder cancer which poses a severe threat to life. Cancer development is usually accompanied by remarkable alterations in cell metabolism, and hence deep insights into MIBC at the metabolomic level can facilitate the understanding of the biochemical mechanisms involved in the cancer development and progression. METHODS In this proof-of-concept study, the optimal cutting temperature (OCT)-embedded MIBC samples were first washed with pure water to remove the polymer compounds which could cause severe signal suppression during mass spectrometry. Further, the tissue sections were analyzed by infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging (IR-MALDESI MSI), providing an overview on the spatially resolved metabolomic profiles. RESULTS The MSI data enabled the discrimination between not only the cancerous and normal tissues, but also the subregions within a tissue section associated with different disease states. Using t-Distributed Stochastic Neighbor Embedding (t-SNE), the hyperdimensional MSI data was mapped into a two-dimensional space to visualize the spectral similarity, providing evidence that metabolomic alterations might have occurred outside the histopathological tumor border. Least absolute shrinkage and selection operator (LASSO) was further employed to classify sample pathology in a pixel-wise manner, yielding excellent prediction sensitivity and specificity up to 96% based on the statistically characteristic spectral features. CONCLUSION The results demonstrate great promise of IR-MALDESI MSI to identify molecular changes derived from cancer and unveil tumor heterogeneity, which can potentially promote the discovery of clinically relevant biomarkers and allow for applications in precision medicine.
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Affiliation(s)
- Anqi Tu
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, NC, 27695, USA
| | - Neveen Said
- Departments of Cancer Biology, Pathology, and Urology, Wake Forest University School of Medicine, Wake Forest Baptist Comprehensive Cancer Center, Winston Salem, NC, 27157, USA
| | - David C Muddiman
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, NC, 27695, USA.
- Molecular Education, Technology and Research Innovation Center (METRIC), North Carolina State University, Raleigh, NC, 27695, USA.
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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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Bensussan AV, Lin J, Guo C, Katz R, Krishnamurthy S, Cressman E, Eberlin LS. Distinguishing Non-Small Cell Lung Cancer Subtypes in Fine Needle Aspiration Biopsies by Desorption Electrospray Ionization Mass Spectrometry Imaging. Clin Chem 2021; 66:1424-1433. [PMID: 33141910 DOI: 10.1093/clinchem/hvaa207] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 08/17/2020] [Indexed: 11/13/2022]
Abstract
BACKGROUND Distinguishing adenocarcinoma and squamous cell carcinoma subtypes of non-small cell lung cancers is critical to patient care. Preoperative minimally-invasive biopsy techniques, such as fine needle aspiration (FNA), are increasingly used for lung cancer diagnosis and subtyping. Yet, histologic distinction of lung cancer subtypes in FNA material can be challenging. Here, we evaluated the usefulness of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to diagnose and differentiate lung cancer subtypes in tissues and FNA samples. METHODS DESI-MSI was used to analyze 22 normal, 26 adenocarcinoma, and 25 squamous cell carcinoma lung tissues. Mass spectra obtained from the tissue sections were used to generate and validate statistical classifiers for lung cancer diagnosis and subtyping. Classifiers were then tested on DESI-MSI data collected from 16 clinical FNA samples prospectively collected from 8 patients undergoing interventional radiology guided FNA. RESULTS Various metabolites and lipid species were detected in the mass spectra obtained from lung tissues. The classifiers generated from tissue sections yielded 100% accuracy, 100% sensitivity, and 100% specificity for lung cancer diagnosis, and 73.5% accuracy for lung cancer subtyping for the training set of tissues, per-patient. On the validation set of tissues, 100% accuracy for lung cancer diagnosis and 94.1% accuracy for lung cancer subtyping were achieved. When tested on the FNA samples, 100% diagnostic accuracy and 87.5% accuracy on subtyping were achieved per-slide. CONCLUSIONS DESI-MSI can be useful as an ancillary technique to conventional cytopathology for diagnosis and subtyping of non-small cell lung cancers.
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Affiliation(s)
- Alena V Bensussan
- Department of Chemistry, The University of Texas at Austin, Austin, TX
| | - John Lin
- Department of Chemistry, The University of Texas at Austin, Austin, TX
| | - Chunxiao Guo
- Department of Interventional Radiology, Division of Diagnostic Imaging, MD Anderson Cancer Center, Houston, TX
| | - Ruth Katz
- Department of Pathology, Division of Pathology and Laboratory Medicine, MD Anderson Cancer Center, Houston, TX
| | - Savitri Krishnamurthy
- Department of Pathology, Division of Pathology and Laboratory Medicine, MD Anderson Cancer Center, Houston, TX
| | - Erik Cressman
- Department of Interventional Radiology, Division of Diagnostic Imaging, MD Anderson Cancer Center, Houston, TX
| | - Livia S Eberlin
- Department of Chemistry, The University of Texas at Austin, Austin, TX
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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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35
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Drake RR, Scott DA, Angel PM. Imaging Mass Spectrometry. Mol Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00017-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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36
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Lee D, Rubakhin SS, Kusmartseva I, Wasserfall C, Atkinson MA, Sweedler JV. Removing Formaldehyde‐Induced Peptidyl Crosslinks Enables Mass Spectrometry Imaging of Peptide Hormone Distributions from Formalin‐Fixed Paraffin‐Embedded Tissues. Angew Chem Int Ed Engl 2020. [DOI: 10.1002/ange.202008847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Dong‐Kyu Lee
- Department of Chemistry and Beckman institute for Advanced Science and Technology University of Illinois at Urbana-Champaign 405 S. Mathews Ave. Urbana IL 61801 USA
| | - Stanislav S. Rubakhin
- Department of Chemistry and Beckman institute for Advanced Science and Technology University of Illinois at Urbana-Champaign 405 S. Mathews Ave. Urbana IL 61801 USA
| | - Irina Kusmartseva
- Department of Pathology, Immunology and Laboratory Medicine College of Medicine University of Florida Gainesville FL 32610 USA
| | - Clive Wasserfall
- Department of Pathology, Immunology and Laboratory Medicine College of Medicine University of Florida Gainesville FL 32610 USA
| | - Mark A. Atkinson
- Department of Pathology, Immunology and Laboratory Medicine College of Medicine University of Florida Gainesville FL 32610 USA
| | - Jonathan V. Sweedler
- Department of Chemistry and Beckman institute for Advanced Science and Technology University of Illinois at Urbana-Champaign 405 S. Mathews Ave. Urbana IL 61801 USA
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37
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Lukowski JK, Pamreddy A, Velickovic D, Zhang G, Pasa-Tolic L, Alexandrov T, Sharma K, Anderton CR. Storage Conditions of Human Kidney Tissue Sections Affect Spatial Lipidomics Analysis Reproducibility. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2020; 31:2538-2546. [PMID: 32897710 PMCID: PMC8162764 DOI: 10.1021/jasms.0c00256] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Lipids often are labile, unstable, and tend to degrade overtime, so it is of the upmost importance to study these molecules in their most native state. We sought to understand the optimal storage conditions for spatial lipidomic analysis of human kidney tissue sections. Specifically, we evaluated human kidney tissue sections on several different days throughout the span of a week using our established protocol for elucidating lipids using high mass resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). We studied kidney tissue sections stored under five different conditions: open stored at -80 °C, vacuumed sealed and stored at -80 °C, with matrix preapplied before storage at -80 °C, under a nitrogen atmosphere and stored at -80 °C, and at room temperature in a desiccator. Results were compared to data obtained from kidney tissue sections that were prepared and analyzed immediately after cryosectioning. Data was processed using METASPACE. After a week of storage, the sections stored at room temperature showed the largest amount of lipid degradation, while sections stored under nitrogen and at -80 °C retained the greatest number of overlapping annotations in relation to freshly cut tissue. Overall, we found that molecular degradation of the tissue sections was unavoidable over time, regardless of storage conditions, but storing tissue sections in an inert gas at low temperatures can curtail molecular degradation within tissue sections.
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Affiliation(s)
- Jessica K Lukowski
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, Washington99352, United States
| | - Annapurna Pamreddy
- Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, The University of Texas Health, San Antonio, Texas 78284, United States
| | - Dusan Velickovic
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, Washington99352, United States
| | - Guanshi Zhang
- Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, The University of Texas Health, San Antonio, Texas 78284, United States
- Audie L. Murphy Memorial VA Hospital, South Texas Veterans Health Care System, San Antonio, Texas 78284, United States
| | - Ljiljana Pasa-Tolic
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, Washington99352, United States
| | - Theodore Alexandrov
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg 69117, Germany
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States
| | - Kumar Sharma
- Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, The University of Texas Health, San Antonio, Texas 78284, United States
- Audie L. Murphy Memorial VA Hospital, South Texas Veterans Health Care System, San Antonio, Texas 78284, United States
| | - Christopher R Anderton
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, Washington99352, United States
- Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, The University of Texas Health, San Antonio, Texas 78284, United States
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38
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Vaysse PM, Kooreman LFS, Engelen SME, Kremer B, Olde Damink SWM, Heeren RMA, Smidt ML, Porta Siegel T. Stromal vapors for real-time molecular guidance of breast-conserving surgery. Sci Rep 2020; 10:20109. [PMID: 33208813 PMCID: PMC7674429 DOI: 10.1038/s41598-020-77102-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 10/05/2020] [Indexed: 11/17/2022] Open
Abstract
Achieving radical tumor resection while preserving disease-free tissue during breast-conserving surgery (BCS) remains a challenge. Here, mass spectrometry technologies were used to discriminate stromal tissues reported to be altered surrounding breast tumors, and build tissue classifiers ex vivo. Additionally, we employed the approach for in vivo and real-time classification of breast pathology based on electrosurgical vapors. Breast-resected samples were obtained from patients undergoing surgery at MUMC+. The specimens were subsequently sampled ex vivo to generate electrosurgical vapors analyzed by rapid evaporative ionization mass spectrometry (REIMS). Tissues were processed for histopathology to assign tissue components to the mass spectral profiles. We collected a total of 689 ex vivo REIMS profiles from 72 patients which were analyzed using multivariate statistical analysis (principal component analysis-linear discriminant analysis). These profiles were classified as adipose, stromal and tumor tissues with 92.3% accuracy with a leave-one patient-out cross-validation. Tissue recognition using this ex vivo-built REIMS classification model was subsequently tested in vivo on electrosurgical vapors. Stromal and adipose tissues were classified during one BCS. Complementary ex vivo analyses were performed by REIMS and by desorption electrospray ionization mass spectrometry (DESI-MS) to study the potential of breast stroma to guide BCS. Tumor border stroma (TBS) and remote tumor stroma (RTS) were classified by REIMS and DESI-MS with 86.4% and 87.8% accuracy, respectively. We demonstrate the potential of stromal molecular alterations surrounding breast tumors to guide BCS in real-time using REIMS analysis of electrosurgical vapors.
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Affiliation(s)
- Pierre-Maxence Vaysse
- Division of Imaging Mass Spectrometry, Maastricht MultiModal Molecular Imaging Institute (M4I), University of Maastricht, Maastricht, The Netherlands.,Department of Surgery, Maastricht University Medical Center+, Maastricht, The Netherlands.,Department of Otorhinolaryngology, Head and Neck Surgery, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Loes F S Kooreman
- Department of Pathology, Maastricht University Medical Center+, Maastricht, The Netherlands.,GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Sanne M E Engelen
- Department of Surgery, Maastricht University Medical Center+, Maastricht, The Netherlands.,GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Bernd Kremer
- Department of Otorhinolaryngology, Head and Neck Surgery, Maastricht University Medical Center+, Maastricht, The Netherlands.,GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Steven W M Olde Damink
- Department of Surgery, Maastricht University Medical Center+, Maastricht, The Netherlands.,Department of General, Visceral and Transplantation Surgery, RWTH University Hospital Aachen, Aachen, Germany.,NUTRIM School of Nutrition and Translational Research in Metabolism Faculty of Health, University of Maastricht, Maastricht, The Netherlands
| | - Ron M A Heeren
- Division of Imaging Mass Spectrometry, Maastricht MultiModal Molecular Imaging Institute (M4I), University of Maastricht, Maastricht, The Netherlands
| | - Marjolein L Smidt
- Department of Surgery, Maastricht University Medical Center+, Maastricht, The Netherlands.,GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Tiffany Porta Siegel
- Division of Imaging Mass Spectrometry, Maastricht MultiModal Molecular Imaging Institute (M4I), University of Maastricht, Maastricht, The Netherlands.
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39
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Lee DK, Rubakhin SS, Kusmartseva I, Wasserfall C, Atkinson MA, Sweedler JV. Removing Formaldehyde-Induced Peptidyl Crosslinks Enables Mass Spectrometry Imaging of Peptide Hormone Distributions from Formalin-Fixed Paraffin-Embedded Tissues. Angew Chem Int Ed Engl 2020; 59:22584-22590. [PMID: 32762062 DOI: 10.1002/anie.202008847] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 08/05/2020] [Indexed: 12/14/2022]
Abstract
Linking molecular and chemical changes to human disease states depends on the availability of appropriate clinical samples, mostly preserved as formalin-fixed paraffin-embedded (FFPE) specimens stored in tissue banks. Mass spectrometry imaging (MSI) enables the visualization of the spatiotemporal distribution of molecules in biological samples. However, MSI is not effective for imaging FFPE tissues because of the chemical modifications of analytes, including complex crosslinking between nucleophilic moieties. Here we used an MS-compatible inorganic nucleophile, hydroxylamine hydrochloride, to chemically reverse inter- and intra-crosslinks from endogenous molecules. The analyte restoration appears specific for formaldehyde-reactive amino acids. This approach enabled the MSI-assisted localization of pancreatic peptides expressed in the alpha, beta, and gamma cells. Pancreatic islet-like distributions of islet hormones were observed in human FFPE tissues preserved for more than five years, demonstrating that samples from biobanks can effectively be investigated with MSI.
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Affiliation(s)
- Dong-Kyu Lee
- Department of Chemistry and Beckman institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405 S. Mathews Ave., Urbana, IL, 61801, USA
| | - Stanislav S Rubakhin
- Department of Chemistry and Beckman institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405 S. Mathews Ave., Urbana, IL, 61801, USA
| | - Irina Kusmartseva
- Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, 32610, USA
| | - Clive Wasserfall
- Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, 32610, USA
| | - Mark A Atkinson
- Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, 32610, USA
| | - Jonathan V Sweedler
- Department of Chemistry and Beckman institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405 S. Mathews Ave., Urbana, IL, 61801, USA
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40
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Waas M, Kislinger T. Addressing Cellular Heterogeneity in Cancer through Precision Proteomics. J Proteome Res 2020; 19:3607-3619. [PMID: 32697918 DOI: 10.1021/acs.jproteome.0c00338] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Cells exhibit a broad spectrum of functions driven by differences in molecular phenotype. Understanding the heterogeneity between and within cell types has led to advances in our ability to diagnose and manipulate biological systems. Heterogeneity within and between tumors still poses a challenge to the development and efficacy of therapeutics. In this Perspective we review the toolkit of protein-level experimental approaches for investigating cellular heterogeneity. We describe how innovative approaches and technical developments have supported the advent of bottom-up single-cell proteomic analysis and present opportunities and challenges within cancer research. Finally, we introduce the concept of "precision proteomics" and discuss how the advantages and limitations of various experimental approaches render them suitable for different biological systems and questions.
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41
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Ivanov DG, Pekov SI, Bocharov KV, Bormotov DS, Spasskiy AI, Zhvansky ES, Sorokin AA, Eliferov VA, Zavorotnyuk DS, Tkachenko SI, Khaliullin IG, Kuksin AY, Shurkhay VA, Kononikhin AS, Nikolaev EN, Popov IA. Novel Mass Spectrometric Utilities for Assisting in Oncological Surgery. RUSSIAN JOURNAL OF PHYSICAL CHEMISTRY B 2020. [DOI: 10.1134/s1990793120030173] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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42
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Butler LM, Perone Y, Dehairs J, Lupien LE, de Laat V, Talebi A, Loda M, Kinlaw WB, Swinnen JV. Lipids and cancer: Emerging roles in pathogenesis, diagnosis and therapeutic intervention. Adv Drug Deliv Rev 2020; 159:245-293. [PMID: 32711004 PMCID: PMC7736102 DOI: 10.1016/j.addr.2020.07.013] [Citation(s) in RCA: 303] [Impact Index Per Article: 75.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 07/02/2020] [Accepted: 07/16/2020] [Indexed: 02/06/2023]
Abstract
With the advent of effective tools to study lipids, including mass spectrometry-based lipidomics, lipids are emerging as central players in cancer biology. Lipids function as essential building blocks for membranes, serve as fuel to drive energy-demanding processes and play a key role as signaling molecules and as regulators of numerous cellular functions. Not unexpectedly, cancer cells, as well as other cell types in the tumor microenvironment, exploit various ways to acquire lipids and extensively rewire their metabolism as part of a plastic and context-dependent metabolic reprogramming that is driven by both oncogenic and environmental cues. The resulting changes in the fate and composition of lipids help cancer cells to thrive in a changing microenvironment by supporting key oncogenic functions and cancer hallmarks, including cellular energetics, promoting feedforward oncogenic signaling, resisting oxidative and other stresses, regulating intercellular communication and immune responses. Supported by the close connection between altered lipid metabolism and the pathogenic process, specific lipid profiles are emerging as unique disease biomarkers, with diagnostic, prognostic and predictive potential. Multiple preclinical studies illustrate the translational promise of exploiting lipid metabolism in cancer, and critically, have shown context dependent actionable vulnerabilities that can be rationally targeted, particularly in combinatorial approaches. Moreover, lipids themselves can be used as membrane disrupting agents or as key components of nanocarriers of various therapeutics. With a number of preclinical compounds and strategies that are approaching clinical trials, we are at the doorstep of exploiting a hitherto underappreciated hallmark of cancer and promising target in the oncologist's strategy to combat cancer.
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Affiliation(s)
- Lisa M Butler
- Adelaide Medical School and Freemasons Foundation Centre for Men's Health, University of Adelaide, Adelaide, SA 5005, Australia; South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia
| | - Ylenia Perone
- Department of Surgery and Cancer, Imperial College London, Imperial Centre for Translational and Experimental Medicine, London, UK
| | - Jonas Dehairs
- Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, 3000 Leuven, Belgium
| | - Leslie E Lupien
- Program in Experimental and Molecular Medicine, Geisel School of Medicine at Dartmouth, 1 Medical Center Drive, Lebanon, NH 037560, USA
| | - Vincent de Laat
- Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, 3000 Leuven, Belgium
| | - Ali Talebi
- Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, 3000 Leuven, Belgium
| | - Massimo Loda
- Pathology and Laboratory Medicine, Weill Cornell Medical College, Cornell University, New York, NY 10065, USA
| | - William B Kinlaw
- The Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, 1 Medical Center Drive, Lebanon, NH 03756, USA
| | - Johannes V Swinnen
- Laboratory of Lipid Metabolism and Cancer, KU Leuven Cancer Institute, 3000 Leuven, Belgium.
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43
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Guo L, Lai Z, Wang Y, Li Z. In situ probing changes in fatty-acyl chain length and desaturation of lipids in cancerous areas using mass spectrometry imaging. JOURNAL OF MASS SPECTROMETRY : JMS 2020; 56:e4621. [PMID: 32776652 DOI: 10.1002/jms.4621] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 07/07/2020] [Accepted: 07/08/2020] [Indexed: 06/11/2023]
Abstract
Aberrant changes in the expression levels and structure of lipids may shape tumor microenvironment. In this study, we have performed mass spectrometry imaging and profiling analysis of 63 tissues of five types of cancer, namely, breast, colorectal, esophageal, lung, and gastric cancer, using in situ liquid extraction electrosonic spray ionization mass spectrometry imaging. Alteration of fatty-acyl chain length of unsaturated phosphatidylcholines, phosphatidylinositols, and phosphatidylserines and of chain length of (un)saturated fatty acids are associated with different cancerous areas of five types of cancer. The ratios of the same fatty-acyl carbon atom lipids with one double bond difference and the ratios of the same chain-length fatty acids with one double bond difference exhibited significant differences among the cancerous areas of five types of cancer. Our data may reveal that there were different lipid metabolism networks among five types of cancer.
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Affiliation(s)
- Lei Guo
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhizhen Lai
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yanmin Wang
- Department of Clinical Laboratory, Heze Municipal Hospital, Heze, China
| | - Zhili Li
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Li N, Nie H, Jiang L, Ruan G, Du F, Liu H. Recent advances of ambient ionization mass spectrometry imaging in clinical research. J Sep Sci 2020; 43:3146-3163. [PMID: 32573988 DOI: 10.1002/jssc.202000273] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 05/03/2020] [Accepted: 05/06/2020] [Indexed: 02/06/2023]
Abstract
The structural information and spatial distribution of molecules in biological tissues are closely related to the potential molecular mechanisms of disease origin, transfer, and classification. Ambient ionization mass spectrometry imaging is an effective tool that provides molecular images while describing in situ information of biomolecules in complex samples, in which ionization occurs at atmospheric pressure with the samples being analyzed in the native state. Ambient ionization mass spectrometry imaging can directly analyze tissue samples at a fairly high resolution to obtain molecules in situ information on the tissue surface to identify pathological features associated with a disease, resulting in the wide applications in pharmacy, food science, botanical research, and especially clinical research. Herein, novel ambient ionization techniques, such as techniques based on spray and solid-liquid extraction, techniques based on plasma desorption, techniques based on laser desorption ablation, and techniques based on acoustic desorption were introduced, and the data processing of ambient ionization mass spectrometry imaging was briefly reviewed. Besides, we also highlight recent applications of this imaging technology in clinical researches and discuss the challenges in this imaging technology and the perspectives on the future of the clinical research.
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Affiliation(s)
- Na Li
- Guangxi Key Laboratory of Electrochemical and Magnetochemical Functional Materials, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, P. R. China
- College of Chemistry and Molecular Engineering, Peking University, Beijing, P. R. China
| | - Honggang Nie
- College of Chemistry and Molecular Engineering, Peking University, Beijing, P. R. China
| | - Liping Jiang
- Guangxi Key Laboratory of Electrochemical and Magnetochemical Functional Materials, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, P. R. China
| | - Guihua Ruan
- Guangxi Key Laboratory of Electrochemical and Magnetochemical Functional Materials, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, P. R. China
| | - Fuyou Du
- Guangxi Key Laboratory of Electrochemical and Magnetochemical Functional Materials, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, P. R. China
- College of Biological and Environmental Engineering, Changsha University, Changsha, P. R. China
| | - Huwei Liu
- College of Chemistry and Molecular Engineering, Peking University, Beijing, P. R. China
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Deng J, Yang Y, Luo L, Xiao Y, Luan T. Lipid analysis and lipidomics investigation by ambient mass spectrometry. Trends Analyt Chem 2020. [DOI: 10.1016/j.trac.2020.115924] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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46
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Feider CL, Macias LA, Brodbelt JS, Eberlin LS. Double Bond Characterization of Free Fatty Acids Directly from Biological Tissues by Ultraviolet Photodissociation. Anal Chem 2020; 92:8386-8395. [PMID: 32421308 PMCID: PMC7433749 DOI: 10.1021/acs.analchem.0c00970] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Free fatty acids (FA) are a vital component of cells and are critical to cellular structure and function, so much so that alterations in FA are often associated with cell malfunction and disease. Analysis of FA from biological samples can be achieved by mass spectrometry (MS), but these analyses are often not capable of distinguishing the fine structural alterations within FA isomers and often limited to global profiling of lipids without spatial resolution. Here, we present the use of ultraviolet photodissociation (UVPD) for the characterization of double bond positional isomers of charge inverted dication·FA complexes and the subsequent implementation of this method for online desorption electrospray ionization (DESI) MS imaging of FA isomers from human tissue sections. This method allows relative quantification of FA isomers from heterogeneous biological tissue sections, yielding spatially resolved information about alterations in double bond isomers within these samples. Applying this method to the analysis of the monounsaturated FA 18:1 within breast cancer subtypes uncovered a correlation between double bond positional isomer abundance and the hormone receptor status of the tissue sample, an important factor in the prognosis and treatment of breast cancer patients. This result further validates similar studies that suggest FA synthase activity and FA isomer abundances are significantly altered within breast cancer tissue.
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Affiliation(s)
- Clara L Feider
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Luis A Macias
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Jennifer S Brodbelt
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Livia S Eberlin
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
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47
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Recent advances of ambient mass spectrometry imaging for biological tissues: A review. Anal Chim Acta 2020; 1117:74-88. [DOI: 10.1016/j.aca.2020.01.052] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 01/21/2020] [Accepted: 01/22/2020] [Indexed: 12/30/2022]
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Silva AAR, Cardoso MR, Rezende LM, Lin JQ, Guimaraes F, Silva GRP, Murgu M, Priolli DG, Eberlin MN, Tata A, Eberlin LS, Derchain SFM, Porcari AM. Multiplatform Investigation of Plasma and Tissue Lipid Signatures of Breast Cancer Using Mass Spectrometry Tools. Int J Mol Sci 2020; 21:E3611. [PMID: 32443844 PMCID: PMC7279467 DOI: 10.3390/ijms21103611] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 05/02/2020] [Accepted: 05/08/2020] [Indexed: 02/06/2023] Open
Abstract
Plasma and tissue from breast cancer patients are valuable for diagnostic/prognostic purposes and are accessible by multiple mass spectrometry (MS) tools. Liquid chromatography-mass spectrometry (LC-MS) and ambient mass spectrometry imaging (MSI) were shown to be robust and reproducible technologies for breast cancer diagnosis. Here, we investigated whether there is a correspondence between lipid cancer features observed by desorption electrospray ionization (DESI)-MSI in tissue and those detected by LC-MS in plasma samples. The study included 28 tissues and 20 plasma samples from 24 women with ductal breast carcinomas of both special and no special type (NST) along with 22 plasma samples from healthy women. The comparison of plasma and tissue lipid signatures revealed that each one of the studied matrices (i.e., blood or tumor) has its own specific molecular signature and the full interposition of their discriminant ions is not possible. This comparison also revealed that the molecular indicators of tissue injury, characteristic of the breast cancer tissue profile obtained by DESI-MSI, do not persist as cancer discriminators in peripheral blood even though some of them could be found in plasma samples.
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Affiliation(s)
- Alex Ap. Rosini Silva
- Postgraduate Program of Health Sciences, São Francisco University, Bragança Paulista SP 12916-900, Brazil; (A.A.R.S.); (D.G.P.)
| | - Marcella R. Cardoso
- Department of Gynecological and Breast Oncology, Women’s Hospital (CAISM), Faculty of Medical Sciences, State University of Campinas (UNICAMP), Campinas SP 13083-881, Brazil; (M.R.C.); (L.M.R.); (F.G.); (S.F.M.D.)
| | - Luciana Montes Rezende
- Department of Gynecological and Breast Oncology, Women’s Hospital (CAISM), Faculty of Medical Sciences, State University of Campinas (UNICAMP), Campinas SP 13083-881, Brazil; (M.R.C.); (L.M.R.); (F.G.); (S.F.M.D.)
| | - John Q. Lin
- Department of Chemistry, The University of Texas at Austin, Austin, TX 78712, USA; (J.Q.L.); (L.S.E.)
| | - Fernando Guimaraes
- Department of Gynecological and Breast Oncology, Women’s Hospital (CAISM), Faculty of Medical Sciences, State University of Campinas (UNICAMP), Campinas SP 13083-881, Brazil; (M.R.C.); (L.M.R.); (F.G.); (S.F.M.D.)
| | - Geisilene R. Paiva Silva
- Laboratory of Molecular and Investigative Pathology—LAPE, Women’s Hospital (CAISM), Faculty of Medical Sciences, State University of Campinas (UNICAMP), Campinas SP 13083-881, Brazil;
| | - Michael Murgu
- Waters Corporation, São Paulo, SP 13083-970, Brazil;
| | - Denise Gonçalves Priolli
- Postgraduate Program of Health Sciences, São Francisco University, Bragança Paulista SP 12916-900, Brazil; (A.A.R.S.); (D.G.P.)
| | - Marcos N. Eberlin
- School of Engineering, Mackenzie Presbyterian University, São Paulo SP 01302-907, Brazil;
| | - Alessandra Tata
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico Sperimentale delle Venezie, Viale Fiume 78, 36100 Vicenza, Italy;
| | - Livia S. Eberlin
- Department of Chemistry, The University of Texas at Austin, Austin, TX 78712, USA; (J.Q.L.); (L.S.E.)
| | - Sophie F. M. Derchain
- Department of Gynecological and Breast Oncology, Women’s Hospital (CAISM), Faculty of Medical Sciences, State University of Campinas (UNICAMP), Campinas SP 13083-881, Brazil; (M.R.C.); (L.M.R.); (F.G.); (S.F.M.D.)
| | - Andreia M. Porcari
- Postgraduate Program of Health Sciences, São Francisco University, Bragança Paulista SP 12916-900, Brazil; (A.A.R.S.); (D.G.P.)
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Holmes DT, Romney MG, Angel P, DeMarco ML. Proteomic applications in pathology and laboratory medicine: Present state and future prospects. Clin Biochem 2020; 82:12-20. [PMID: 32442429 DOI: 10.1016/j.clinbiochem.2020.05.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 05/13/2020] [Accepted: 05/13/2020] [Indexed: 12/11/2022]
Abstract
Clinical mass spectrometry applications have traditionally focused on small molecules, particularly in the areas of therapeutic drug monitoring, toxicology, and measurement of endogenous and exogenous steroids. More recently, the use of matrix assisted laser desorption/ionization time of flight mass spectrometry for the identification of microbial pathogens has been widely implemented. Following this evolution, there has been an expanding role for the measurement of peptides and proteins in pathology and laboratory medicine. This review explores the current state of protein measurement by clinical mass spectrometry and the analytical strategies employed, as well as emerging applications in clinical chemistry, clinical microbiology and anatomical pathology.
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Affiliation(s)
- Daniel T Holmes
- Department of Pathology and Laboratory Medicine, St. Paul's Hospital, 1081 Burrard St, Vancouver, BC V6Z 1Y6, Canada; University of British Columbia Department of Pathology and Laboratory Medicine, Vancouver, BC V6T 2B5 Canada.
| | - Marc G Romney
- Department of Pathology and Laboratory Medicine, St. Paul's Hospital, 1081 Burrard St, Vancouver, BC V6Z 1Y6, Canada; University of British Columbia Department of Pathology and Laboratory Medicine, Vancouver, BC V6T 2B5 Canada.
| | - Peggi Angel
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charelston, SC 29425 Canada.
| | - Mari L DeMarco
- Department of Pathology and Laboratory Medicine, St. Paul's Hospital, 1081 Burrard St, Vancouver, BC V6Z 1Y6, Canada; University of British Columbia Department of Pathology and Laboratory Medicine, Vancouver, BC V6T 2B5 Canada.
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50
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Robison HM, Chini CE, Comi TJ, Ryu SW, Ognjanovski E, Perry RH. Identification of lipid biomarkers of metastatic potential and gene expression (HER2/p53) in human breast cancer cell cultures using ambient mass spectrometry. Anal Bioanal Chem 2020; 412:2949-2961. [PMID: 32322955 DOI: 10.1007/s00216-020-02537-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Revised: 02/05/2020] [Accepted: 02/19/2020] [Indexed: 12/19/2022]
Abstract
In breast cancer, overexpression of human epidermal growth factor receptor 2 (HER2) correlates with overactivation of lipogenesis, mutation of tumor suppressor p53, and increased metastatic potential. The mechanisms through which lipids mediate p53, HER2, and metastatic potential are largely unknown. We have developed a desorption electrospray ionization mass spectrometry (DESI-MS) method to identify lipid biomarkers of HER2/p53 expression, metastatic potential, and disease state (viz. cancer vs. non-cancerous) in monolayer and suspension breast cancer cell cultures (metastatic potential: MCF-7, T-47D, MDA-MB-231; HER2/p53: HCC2218 (HER2+++/p53+), HCC1599 (HER2-/p53-), HCC202 (HER2++/p53-), HCC1419 (HER2+++/p53-) HCC70 (HER2-/p53+++); non-cancerous: MCF-10A). Unsupervised principal component analysis (PCA) of DESI-MS spectra enabled identification of twelve lipid biomarkers of metastatic potential and disease state, as well as ten lipids that distinguish cell lines based on HER2/p53 expression levels (> 200 lipids were identified per cell line). In addition, we developed a DESI-MS imaging (DESI-MSI) method for mapping the spatial distribution of lipids in metastatic spheroids (MDA-MB-231). Of the twelve lipids that correlate with changes in the metastatic potential of monolayer cell cultures, three were localized to the necrotic core of spheroids, indicating a potential role in promoting cancer cell survival in nutrient-deficient environments. One lipid species, which was not detected in monolayer MDA-MB-231 cultures, was spatially localized to the periphery of the spheroid, suggesting a potential role in invasion and/or proliferation. These results demonstrate that combining DESI-MS/PCA of monolayer and suspension cell cultures with DESI-MSI of spheroids is a promising approach for identifying lipid biomarkers of specific genotypes and phenotypes, as well as elucidating the potential function of these biomarkers in breast cancer. Graphical Absract.
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Affiliation(s)
- Heather M Robison
- Department of Chemistry, University of Illinois, Urbana, IL, 61801, USA
| | - Corryn E Chini
- Department of Chemistry, University of Illinois, Urbana, IL, 61801, USA
| | - Troy J Comi
- Department of Chemistry, University of Illinois, Urbana, IL, 61801, USA
| | - Seung Woo Ryu
- Department of Chemistry, University of Illinois, Urbana, IL, 61801, USA
| | - Elaine Ognjanovski
- Department of Chemistry and Physics, Nova Southeastern University, Fort Lauderdale, FL, 33314, USA
| | - Richard H Perry
- Department of Chemistry, University of Illinois, Urbana, IL, 61801, USA. .,Department of Chemistry and Physics, Nova Southeastern University, Fort Lauderdale, FL, 33314, USA.
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