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Brorsen LF, McKenzie JS, Tullin MF, Bendtsen KMS, Pinto FE, Jensen HE, Haedersdal M, Takats Z, Janfelt C, Lerche CM. Cutaneous squamous cell carcinoma characterized by MALDI mass spectrometry imaging in combination with machine learning. Sci Rep 2024; 14:11091. [PMID: 38750270 PMCID: PMC11096391 DOI: 10.1038/s41598-024-62023-0] [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: 03/12/2024] [Accepted: 05/13/2024] [Indexed: 05/18/2024] Open
Abstract
Cutaneous squamous cell carcinoma (SCC) is an increasingly prevalent global health concern. Current diagnostic and surgical methods are reliable, but they require considerable resources and do not provide metabolomic insight. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) enables detailed, spatially resolved metabolomic analysis of tissue samples. Integrated with machine learning, MALDI-MSI could yield detailed information pertaining to the metabolic alterations characteristic for SCC. These insights have the potential to enhance SCC diagnosis and therapy, improving patient outcomes while tackling the growing disease burden. This study employs MALDI-MSI data, labelled according to histology, to train a supervised machine learning model (logistic regression) for the recognition and delineation of SCC. The model, based on data acquired from discrete tumor sections (n = 25) from a mouse model of SCC, achieved a predictive accuracy of 92.3% during cross-validation on the labelled data. A pathologist unacquainted with the dataset and tasked with evaluating the predictive power of the model in the unlabelled regions, agreed with the model prediction for over 99% of the tissue areas. These findings highlight the potential value of integrating MALDI-MSI with machine learning to characterize and delineate SCC, suggesting a promising direction for the advancement of mass spectrometry techniques in the clinical diagnosis of SCC and related keratinocyte carcinomas.
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Affiliation(s)
- Lauritz F Brorsen
- Department of Dermatology, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Nielsine Nielsens Vej 9, 2400, Copenhagen, Denmark.
- Department of Pharmacy, University of Copenhagen, Copenhagen, Denmark.
| | - James S McKenzie
- Department of Digestion, Metabolism and Reproduction, Imperial College London, London, UK
| | - Mette F Tullin
- Department of Pharmacy, University of Copenhagen, Copenhagen, Denmark
| | - Katja M S Bendtsen
- Department of Veterinary and Animal Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Fernanda E Pinto
- Department of Dermatology, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Nielsine Nielsens Vej 9, 2400, Copenhagen, Denmark
| | - Henrik E Jensen
- Department of Veterinary and Animal Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Merete Haedersdal
- Department of Dermatology, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Nielsine Nielsens Vej 9, 2400, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Zoltan Takats
- Department of Digestion, Metabolism and Reproduction, Imperial College London, London, UK
| | - Christian Janfelt
- Department of Pharmacy, University of Copenhagen, Copenhagen, Denmark
| | - Catharina M Lerche
- Department of Dermatology, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Nielsine Nielsens Vej 9, 2400, Copenhagen, Denmark
- Department of Pharmacy, University of Copenhagen, Copenhagen, Denmark
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Hristova J, Svinarov D. Enhancing precision medicine through clinical mass spectrometry platform. BIOTECHNOL BIOTEC EQ 2022. [DOI: 10.1080/13102818.2022.2053342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
Affiliation(s)
- Julieta Hristova
- Alexander University Hospital, Faculty of Medicine, Medical University of Sofia, Sofia, Bulgaria
| | - Dobrin Svinarov
- Alexander University Hospital, Faculty of Medicine, Medical University of Sofia, Sofia, Bulgaria
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Mass spectrometry imaging in gynecological cancers: the best is yet to come. Cancer Cell Int 2022; 22:414. [PMID: 36536419 PMCID: PMC9764543 DOI: 10.1186/s12935-022-02832-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 12/11/2022] [Indexed: 12/23/2022] Open
Abstract
Mass spectrometry imaging (MSI) enables obtaining multidimensional results simultaneously in a single run, including regiospecificity and m/z values corresponding with specific proteins, peptides, lipids, etc. The knowledge obtained in this way allows for a multifaceted analysis of the studied issue, e.g., the specificity of the neoplastic process and the search for new therapeutic targets. Despite the enormous possibilities, this relatively new technique in many aspects still requires the development or standardization of analytical protocols (from collecting biological material, through sample preparation, analysis, and data collection, to data processing). The introduction of standardized protocols for MSI studies, with its current potential to extend diagnostic and prognostic capabilities, can revolutionize clinical pathology. As far as identifying ovarian cancer subtypes can be challenging, especially in poorly differentiated tumors, developing MSI-based algorithms may enhance determining prognosis and tumor staging without the need for extensive surgery and optimize the choice of subsequent therapy. MSI might bring new solutions in predicting response to treatment in patients with endometrial cancer. Therefore, MSI may help to revolutionize the future of gynecological oncology in terms of diagnostics, treatment, and predicting the response to therapy. This review will encompass several aspects, e.g., contemporary discoveries in gynecological cancer research utilizing MSI, indicates current challenges, and future perspectives on MSI.
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Nascentes Melo LM, Lesner NP, Sabatier M, Ubellacker JM, Tasdogan A. Emerging metabolomic tools to study cancer metastasis. Trends Cancer 2022; 8:988-1001. [PMID: 35909026 DOI: 10.1016/j.trecan.2022.07.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 06/24/2022] [Accepted: 07/06/2022] [Indexed: 12/24/2022]
Abstract
Metastasis is responsible for 90% of deaths in patients with cancer. Understanding the role of metabolism during metastasis has been limited by the development of robust and sensitive technologies that capture metabolic processes in metastasizing cancer cells. We discuss the current technologies available to study (i) metabolism in primary and metastatic cancer cells and (ii) metabolic interactions between cancer cells and the tumor microenvironment (TME) at different stages of the metastatic cascade. We identify advantages and disadvantages of each method and discuss how these tools and technologies will further improve our understanding of metastasis. Studies investigating the complex metabolic rewiring of different cells using state-of-the-art metabolomic technologies have the potential to reveal novel biological processes and therapeutic interventions for human cancers.
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Affiliation(s)
| | - Nicholas P Lesner
- Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Marie Sabatier
- Department of Molecular Metabolism, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jessalyn M Ubellacker
- Department of Molecular Metabolism, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Alpaslan Tasdogan
- Department of Dermatology, University Hospital Essen and German Cancer Consortium, Partner Site, Essen, Germany.
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Matsushita S, Hasegawa T, Hiraoka M, Hayashi A, Suzuki Y. TLC-based MS Imaging Analysis of Glycosphingolipids and Glycerin Fatty Acid Esters after 1,2-Dichloroethane Washing. ANAL SCI 2021; 37:1491-1495. [PMID: 34690230 DOI: 10.2116/analsci.21c009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Matrix-assisted laser desorption/ionization-based mass spectrometry imaging (MSI) of separated lipids on thin-layer chromatography (TLC) plates or followed by blotted hydrophilic polyvinylidene fluoride (PVDF) membranes has become a powerful tool in lipidomic analyses. However, background peaks in MS spectra often cover lipid peaks in a low amount/ionization effect; consequently, only low intensities/resolutions MSI are obtained. To address the aforementioned problem, we attempted 1,2-dichloroethane pre-washing of TLC plates before development and found that backgrounds could successfully be removed from the TLC plate or PVDF membrane.
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Affiliation(s)
- Shoko Matsushita
- Department of Materials and Applied Chemistry, College of Science and Technology, Nihon University
| | - Takuma Hasegawa
- Department of Materials and Applied Chemistry, College of Science and Technology, Nihon University
| | - Marina Hiraoka
- Department of Materials and Applied Chemistry, College of Science and Technology, Nihon University
| | - Aki Hayashi
- Department of Materials and Applied Chemistry, College of Science and Technology, Nihon University
| | - Yusuke Suzuki
- Department of Materials and Applied Chemistry, College of Science and Technology, Nihon University
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Basu SS, Agar NYR. Bringing Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging to the Clinics. Clin Lab Med 2021; 41:309-324. [PMID: 34020766 DOI: 10.1016/j.cll.2021.03.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is an emerging analytical technique that promises to change tissue-based diagnostics. This article provides a brief introduction to MALDI MSI as well as clinical diagnostic workflows and opportunities to apply this powerful approach. It describes various MALDI MSI applications, from more clinically mature applications such as cancer to emerging applications such as infectious diseases and drug distribution. In addition, it discusses the analytical considerations that need to be considered when bringing these approaches to different diagnostic problems and settings.
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Affiliation(s)
- Sankha S Basu
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Nathalie Y R Agar
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Cancer Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA.
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Horala A, Plewa S, Derezinski P, Klupczynska A, Matysiak J, Nowak-Markwitz E, Kokot ZJ. Serum Free Amino Acid Profiling in Differential Diagnosis of Ovarian Tumors-A Comparative Study with Review of the Literature. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18042167. [PMID: 33672144 PMCID: PMC7926859 DOI: 10.3390/ijerph18042167] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 02/11/2021] [Accepted: 02/16/2021] [Indexed: 12/21/2022]
Abstract
Proper preoperative ovarian cancer (OC) diagnosis remains challenging. Serum free amino acid (SFAA) profiles were investigated to identify potential novel biomarkers of OC and assess their performance in ovarian tumor differential diagnosis. Serum samples were divided based on the histopathological result: epithelial OC (n = 38), borderline ovarian tumors (n = 6), and benign ovarian tumors (BOTs) (n = 62). SFAA profiles were evaluated using aTRAQ methodology based on high-performance liquid chromatography electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). Levels of eleven amino acids significantly differed between OC+borderline and BOTs. The highest area under the receiver operating characteristic curve (AUC of ROC) (0.787) was obtained for histidine. Cystine and histidine were identified as best single markers for early stage OC/BOT and type I OC. For advanced stage OC, seven amino acids differed significantly between the groups and citrulline obtained the best AUC of 0.807. Between type II OC and BOTs, eight amino acids differed significantly and the highest AUC of 0.798 was achieved by histidine and citrulline (AUC of 0.778). Histidine was identified as a potential new biomarker in differential diagnosis of ovarian tumors. Adding histidine to a multimarker panel together with CA125 and HE4 improved the differential diagnosis between OC and BOTs.
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Affiliation(s)
- Agnieszka Horala
- Gynecologic Oncology Department, Poznan University of Medical Sciences, Polna 33 Street, 60-535 Poznan, Poland;
- Correspondence:
| | - Szymon Plewa
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland; (S.P.); (P.D.); (A.K.); (J.M.)
| | - Pawel Derezinski
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland; (S.P.); (P.D.); (A.K.); (J.M.)
| | - Agnieszka Klupczynska
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland; (S.P.); (P.D.); (A.K.); (J.M.)
| | - Jan Matysiak
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland; (S.P.); (P.D.); (A.K.); (J.M.)
| | - Ewa Nowak-Markwitz
- Gynecologic Oncology Department, Poznan University of Medical Sciences, Polna 33 Street, 60-535 Poznan, Poland;
| | - Zenon J. Kokot
- Faculty of Health Sciences, Calisia University, 13 Kaszubska Street, 62-800 Kalisz, Poland;
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