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Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma

[Image: see text] Lipid imaging mass spectrometry (LIMS) has been tested in several pathological contexts, demonstrating its ability to segregate and isolate lipid signatures in complex tissues, thanks to the technique’s spatial resolution. However, it cannot yet compete with the superior identifica...

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Autores principales: Martín-Saiz, Lucía, Abad-García, Beatriz, Solano-Iturri, Jon D., Mosteiro, Lorena, Martín-Allende, Javier, Rueda, Yuri, Pérez-Fernández, Amparo, Unda, Miguel, Coterón-Ochoa, Pedro, Goya, Aintzane, Saiz, Alberto, Martínez, Jennifer, Ochoa, Begoña, Fresnedo, Olatz, Larrinaga, Gorka, Fernández, José A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893214/
https://www.ncbi.nlm.nih.gov/pubmed/36638042
http://dx.doi.org/10.1021/acs.analchem.2c03953
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author Martín-Saiz, Lucía
Abad-García, Beatriz
Solano-Iturri, Jon D.
Mosteiro, Lorena
Martín-Allende, Javier
Rueda, Yuri
Pérez-Fernández, Amparo
Unda, Miguel
Coterón-Ochoa, Pedro
Goya, Aintzane
Saiz, Alberto
Martínez, Jennifer
Ochoa, Begoña
Fresnedo, Olatz
Larrinaga, Gorka
Fernández, José A.
author_facet Martín-Saiz, Lucía
Abad-García, Beatriz
Solano-Iturri, Jon D.
Mosteiro, Lorena
Martín-Allende, Javier
Rueda, Yuri
Pérez-Fernández, Amparo
Unda, Miguel
Coterón-Ochoa, Pedro
Goya, Aintzane
Saiz, Alberto
Martínez, Jennifer
Ochoa, Begoña
Fresnedo, Olatz
Larrinaga, Gorka
Fernández, José A.
author_sort Martín-Saiz, Lucía
collection PubMed
description [Image: see text] Lipid imaging mass spectrometry (LIMS) has been tested in several pathological contexts, demonstrating its ability to segregate and isolate lipid signatures in complex tissues, thanks to the technique’s spatial resolution. However, it cannot yet compete with the superior identification power of high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS), and therefore, very often, the latter is used to refine the assignment of the species detected by LIMS. Also, it is not clear if the differences in sensitivity and spatial resolution between the two techniques lead to a similar panel of biomarkers for a given disease. Here, we explore the capabilities of LIMS and HPLC-MS to produce a panel of lipid biomarkers to screen nephrectomy samples from 40 clear cell renal cell carcinoma patients. The same set of samples was explored by both techniques, and despite the important differences between them in terms of the number of detected and identified species (148 by LIMS and 344 by HPLC-MS in negative-ion mode) and the presence/absence of image capabilities, similar conclusions were reached: using the lipid fingerprint, it is possible to set up classifiers that correctly identify the samples as either healthy or tumor samples. The spatial resolution of LIMS enables extraction of additional information, such as the existence of necrotic areas or the existence of different tumor cell populations, but such information does not seem determinant for the correct classification of the samples, or it may be somehow compensated by the higher analytical power of HPLC-MS. Similar conclusions were reached with two very different techniques, validating their use for the discovery of lipid biomarkers.
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spelling pubmed-98932142023-02-03 Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma Martín-Saiz, Lucía Abad-García, Beatriz Solano-Iturri, Jon D. Mosteiro, Lorena Martín-Allende, Javier Rueda, Yuri Pérez-Fernández, Amparo Unda, Miguel Coterón-Ochoa, Pedro Goya, Aintzane Saiz, Alberto Martínez, Jennifer Ochoa, Begoña Fresnedo, Olatz Larrinaga, Gorka Fernández, José A. Anal Chem [Image: see text] Lipid imaging mass spectrometry (LIMS) has been tested in several pathological contexts, demonstrating its ability to segregate and isolate lipid signatures in complex tissues, thanks to the technique’s spatial resolution. However, it cannot yet compete with the superior identification power of high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS), and therefore, very often, the latter is used to refine the assignment of the species detected by LIMS. Also, it is not clear if the differences in sensitivity and spatial resolution between the two techniques lead to a similar panel of biomarkers for a given disease. Here, we explore the capabilities of LIMS and HPLC-MS to produce a panel of lipid biomarkers to screen nephrectomy samples from 40 clear cell renal cell carcinoma patients. The same set of samples was explored by both techniques, and despite the important differences between them in terms of the number of detected and identified species (148 by LIMS and 344 by HPLC-MS in negative-ion mode) and the presence/absence of image capabilities, similar conclusions were reached: using the lipid fingerprint, it is possible to set up classifiers that correctly identify the samples as either healthy or tumor samples. The spatial resolution of LIMS enables extraction of additional information, such as the existence of necrotic areas or the existence of different tumor cell populations, but such information does not seem determinant for the correct classification of the samples, or it may be somehow compensated by the higher analytical power of HPLC-MS. Similar conclusions were reached with two very different techniques, validating their use for the discovery of lipid biomarkers. American Chemical Society 2023-01-13 /pmc/articles/PMC9893214/ /pubmed/36638042 http://dx.doi.org/10.1021/acs.analchem.2c03953 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Martín-Saiz, Lucía
Abad-García, Beatriz
Solano-Iturri, Jon D.
Mosteiro, Lorena
Martín-Allende, Javier
Rueda, Yuri
Pérez-Fernández, Amparo
Unda, Miguel
Coterón-Ochoa, Pedro
Goya, Aintzane
Saiz, Alberto
Martínez, Jennifer
Ochoa, Begoña
Fresnedo, Olatz
Larrinaga, Gorka
Fernández, José A.
Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma
title Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma
title_full Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma
title_fullStr Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma
title_full_unstemmed Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma
title_short Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma
title_sort using the synergy between hplc-ms and maldi-ms imaging to explore the lipidomics of clear cell renal cell carcinoma
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893214/
https://www.ncbi.nlm.nih.gov/pubmed/36638042
http://dx.doi.org/10.1021/acs.analchem.2c03953
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