Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models
No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering that little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights into how metabolic and signaling al...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-01-01
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| Series: | Frontiers in Chemistry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fchem.2023.1332816/full |
| _version_ | 1797362530439397376 |
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| author | Xin Ma Andro Botros Sylvia R. Yun Eun Young Park Olga Kim Soojin Park Thu-Huyen Pham Ruihong Chen Murugesan Palaniappan Murugesan Palaniappan Martin M. Matzuk Martin M. Matzuk Jaeyeon Kim Facundo M. Fernández Facundo M. Fernández |
| author_facet | Xin Ma Andro Botros Sylvia R. Yun Eun Young Park Olga Kim Soojin Park Thu-Huyen Pham Ruihong Chen Murugesan Palaniappan Murugesan Palaniappan Martin M. Matzuk Martin M. Matzuk Jaeyeon Kim Facundo M. Fernández Facundo M. Fernández |
| author_sort | Xin Ma |
| collection | DOAJ |
| description | No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering that little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights into how metabolic and signaling alterations accompany its development. Herein, we present a comprehensive study using ultra-high-resolution Fourier transform ion cyclotron resonance matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to investigate the spatial distribution and alterations of lipids in ovarian tissues collected from double knockout (n = 4) and triple mutant mouse models (n = 4) of high-grade serous ovarian cancer (HGSOC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes were compared to those in healthy mouse reproductive tissue (n = 4), mapping onto major lipid pathways involved in OC progression. From intermediate-stage OC to advanced HGSC, we provide direct visualization of lipid distributions and their biological links to inflammatory response, cellular stress, cell proliferation, and other processes. We also show the ability to distinguish tumors at different stages from healthy tissues via a number of highly specific lipid biomarkers, providing targets for future panels that could be useful in diagnosis. |
| first_indexed | 2024-03-08T16:08:14Z |
| format | Article |
| id | doaj.art-4136372308ec4b55ab4eeaf71e2b8aa3 |
| institution | Directory Open Access Journal |
| issn | 2296-2646 |
| language | English |
| last_indexed | 2024-03-08T16:08:14Z |
| publishDate | 2024-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Chemistry |
| spelling | doaj.art-4136372308ec4b55ab4eeaf71e2b8aa32024-01-08T04:24:56ZengFrontiers Media S.A.Frontiers in Chemistry2296-26462024-01-011110.3389/fchem.2023.13328161332816Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse modelsXin Ma0Andro Botros1Sylvia R. Yun2Eun Young Park3Olga Kim4Soojin Park5Thu-Huyen Pham6Ruihong Chen7Murugesan Palaniappan8Murugesan Palaniappan9Martin M. Matzuk10Martin M. Matzuk11Jaeyeon Kim12Facundo M. Fernández13Facundo M. Fernández14School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, United StatesDepartments of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, United StatesDepartments of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, United StatesDepartments of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, United StatesDepartments of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, United StatesDepartments of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, United StatesDepartments of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, United StatesDepartment of Pathology and Immunology, Baylor College of Medicine, Houston, TX, United StatesDepartment of Pathology and Immunology, Baylor College of Medicine, Houston, TX, United StatesCenter for Drug Discovery, Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, United StatesDepartment of Pathology and Immunology, Baylor College of Medicine, Houston, TX, United StatesCenter for Drug Discovery, Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, United StatesDepartments of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, United StatesSchool of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, United StatesPetit Institute of Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, United StatesNo effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering that little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights into how metabolic and signaling alterations accompany its development. Herein, we present a comprehensive study using ultra-high-resolution Fourier transform ion cyclotron resonance matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to investigate the spatial distribution and alterations of lipids in ovarian tissues collected from double knockout (n = 4) and triple mutant mouse models (n = 4) of high-grade serous ovarian cancer (HGSOC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes were compared to those in healthy mouse reproductive tissue (n = 4), mapping onto major lipid pathways involved in OC progression. From intermediate-stage OC to advanced HGSC, we provide direct visualization of lipid distributions and their biological links to inflammatory response, cellular stress, cell proliferation, and other processes. We also show the ability to distinguish tumors at different stages from healthy tissues via a number of highly specific lipid biomarkers, providing targets for future panels that could be useful in diagnosis.https://www.frontiersin.org/articles/10.3389/fchem.2023.1332816/fullmass spectrometry imagingmatrix-assisted laser desorption/ionizationhigh-grade serous ovarian cancerlipidomicsbiomarkers mass spectrometry imagingbiomarkers |
| spellingShingle | Xin Ma Andro Botros Sylvia R. Yun Eun Young Park Olga Kim Soojin Park Thu-Huyen Pham Ruihong Chen Murugesan Palaniappan Murugesan Palaniappan Martin M. Matzuk Martin M. Matzuk Jaeyeon Kim Facundo M. Fernández Facundo M. Fernández Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models Frontiers in Chemistry mass spectrometry imaging matrix-assisted laser desorption/ionization high-grade serous ovarian cancer lipidomics biomarkers mass spectrometry imaging biomarkers |
| title | Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models |
| title_full | Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models |
| title_fullStr | Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models |
| title_full_unstemmed | Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models |
| title_short | Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models |
| title_sort | ultrahigh resolution lipid mass spectrometry imaging of high grade serous ovarian cancer mouse models |
| topic | mass spectrometry imaging matrix-assisted laser desorption/ionization high-grade serous ovarian cancer lipidomics biomarkers mass spectrometry imaging biomarkers |
| url | https://www.frontiersin.org/articles/10.3389/fchem.2023.1332816/full |
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