High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry
Abstract Tissue microarrays (TMAs) are commonly used for the rapid analysis of large numbers of tissue samples, often in morphological assessments but increasingly in spectroscopic analysis, where specific molecular markers are targeted via immunostaining. Here we report the use of an automated high...
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Nature Portfolio
2022-11-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-022-22924-4 |
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author | Nicolás M. Morato Hannah Marie Brown Diogo Garcia Erik H. Middlebrooks Mark Jentoft Kaisorn Chaichana Alfredo Quiñones-Hinojosa R. Graham Cooks |
author_facet | Nicolás M. Morato Hannah Marie Brown Diogo Garcia Erik H. Middlebrooks Mark Jentoft Kaisorn Chaichana Alfredo Quiñones-Hinojosa R. Graham Cooks |
author_sort | Nicolás M. Morato |
collection | DOAJ |
description | Abstract Tissue microarrays (TMAs) are commonly used for the rapid analysis of large numbers of tissue samples, often in morphological assessments but increasingly in spectroscopic analysis, where specific molecular markers are targeted via immunostaining. Here we report the use of an automated high-throughput system based on desorption electrospray ionization (DESI) mass spectrometry (MS) for the rapid generation and online analysis of high-density (6144 samples/array) TMAs, at rates better than 1 sample/second. Direct open-air analysis of tissue samples (hundreds of nanograms) not subjected to prior preparation, plus the ability to provide molecular characterization by tandem mass spectrometry (MS/MS), make this experiment versatile and applicable to both targeted and untargeted analysis in a label-free manner. These capabilities are demonstrated in a proof-of-concept study of frozen brain tissue biopsies where we showcase (i) a targeted MS/MS application aimed at identification of isocitrate dehydrogenase mutation in glioma samples and (ii) an untargeted MS tissue type classification using lipid profiles and correlation with tumor cell percentage estimates from histopathology. The small sample sizes and large sample numbers accessible with this methodology make for a powerful analytical system that facilitates the identification of molecular markers for later use in intraoperative applications to guide precision surgeries and ultimately improve patient outcomes. |
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institution | Directory Open Access Journal |
issn | 2045-2322 |
language | English |
last_indexed | 2024-04-11T16:21:54Z |
publishDate | 2022-11-01 |
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spelling | doaj.art-1c91ae7d7f7c42f7b0f74bbe76de46d42022-12-22T04:14:17ZengNature PortfolioScientific Reports2045-23222022-11-0112111010.1038/s41598-022-22924-4High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometryNicolás M. Morato0Hannah Marie Brown1Diogo Garcia2Erik H. Middlebrooks3Mark Jentoft4Kaisorn Chaichana5Alfredo Quiñones-Hinojosa6R. Graham Cooks7Department of Chemistry, Purdue Center for Cancer Research, and Bindley Bioscience Center, Purdue UniversityDepartment of Chemistry, Purdue Center for Cancer Research, and Bindley Bioscience Center, Purdue UniversityDepartment of Neurosurgery, Mayo ClinicDepartment of Neurosurgery, Mayo ClinicDepartment of Laboratory Medicine and Pathology, Mayo ClinicDepartment of Neurosurgery, Mayo ClinicDepartment of Neurosurgery, Mayo ClinicDepartment of Chemistry, Purdue Center for Cancer Research, and Bindley Bioscience Center, Purdue UniversityAbstract Tissue microarrays (TMAs) are commonly used for the rapid analysis of large numbers of tissue samples, often in morphological assessments but increasingly in spectroscopic analysis, where specific molecular markers are targeted via immunostaining. Here we report the use of an automated high-throughput system based on desorption electrospray ionization (DESI) mass spectrometry (MS) for the rapid generation and online analysis of high-density (6144 samples/array) TMAs, at rates better than 1 sample/second. Direct open-air analysis of tissue samples (hundreds of nanograms) not subjected to prior preparation, plus the ability to provide molecular characterization by tandem mass spectrometry (MS/MS), make this experiment versatile and applicable to both targeted and untargeted analysis in a label-free manner. These capabilities are demonstrated in a proof-of-concept study of frozen brain tissue biopsies where we showcase (i) a targeted MS/MS application aimed at identification of isocitrate dehydrogenase mutation in glioma samples and (ii) an untargeted MS tissue type classification using lipid profiles and correlation with tumor cell percentage estimates from histopathology. The small sample sizes and large sample numbers accessible with this methodology make for a powerful analytical system that facilitates the identification of molecular markers for later use in intraoperative applications to guide precision surgeries and ultimately improve patient outcomes.https://doi.org/10.1038/s41598-022-22924-4 |
spellingShingle | Nicolás M. Morato Hannah Marie Brown Diogo Garcia Erik H. Middlebrooks Mark Jentoft Kaisorn Chaichana Alfredo Quiñones-Hinojosa R. Graham Cooks High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry Scientific Reports |
title | High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry |
title_full | High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry |
title_fullStr | High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry |
title_full_unstemmed | High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry |
title_short | High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry |
title_sort | high throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry |
url | https://doi.org/10.1038/s41598-022-22924-4 |
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