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.

Details

Title
High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry
Author
Morato, Nicolás M. 1 ; Brown, Hannah Marie 2 ; Garcia, Diogo 3 ; Middlebrooks, Erik H. 4 ; Jentoft, Mark 5 ; Chaichana, Kaisorn 3 ; Quiñones-Hinojosa, Alfredo 3 ; Cooks, R. Graham 1 

 Purdue University, Department of Chemistry, Purdue Center for Cancer Research, and Bindley Bioscience Center, West Lafayette, USA (GRID:grid.169077.e) (ISNI:0000 0004 1937 2197) 
 Purdue University, Department of Chemistry, Purdue Center for Cancer Research, and Bindley Bioscience Center, West Lafayette, USA (GRID:grid.169077.e) (ISNI:0000 0004 1937 2197); Washington University School of Medicine, Department of Pathology and Immunology, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002) 
 Mayo Clinic, Department of Neurosurgery, Jacksonville, USA (GRID:grid.417467.7) (ISNI:0000 0004 0443 9942) 
 Mayo Clinic, Department of Neurosurgery, Jacksonville, USA (GRID:grid.417467.7) (ISNI:0000 0004 0443 9942); Mayo Clinic, Department of Radiology, Jacksonville, USA (GRID:grid.417467.7) (ISNI:0000 0004 0443 9942) 
 Mayo Clinic, Department of Laboratory Medicine and Pathology, Jacksonville, USA (GRID:grid.417467.7) (ISNI:0000 0004 0443 9942) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2732927524
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.