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Development and evaluation of matrix application techniques for high throughput mass spectrometry imaging of tissues in the clinic.


ABSTRACT: Matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI) is a sensitive label-free technique that can be used to study a wide variety of clinical phenotypes. In this context, MSI offers huge diagnostic potential by supporting decision making in the determination of personalized treatment strategies. However, improvements in throughput and robustness are still needed before it finds a place in routine application. While the field has seen tremendous improvements in the throughput of data acquisition, robust and high-throughput sample preparation methods compatible with these acquisition methods need to be developed. To address this challenge, we have developed several methods to reduce the matrix application time to less than 5 min, while maintaining sensitivity and reproducibility. Workflows incorporating these methods provide a pipeline analysis time for MSI sample preparation and acquisition of less than 30 min. The reduced time for these analyses will contribute towards the integration of MSI into routine molecular pathology for clinical diagnostics.

SUBMITTER: Huizing LRS 

PROVIDER: S-EPMC8620134 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Development and evaluation of matrix application techniques for high throughput mass spectrometry imaging of tissues in the clinic.

Huizing Lennart R S LRS   Ellis Shane R SR   Beulen Bart W A M M BWAMM   Barré Florian P Y FPY   Kwant Paul B PB   Vreeken Rob J RJ   Heeren Ron M A RMA  

Clinical mass spectrometry (Del Mar, Calif.) 20190128


Matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI) is a sensitive label-free technique that can be used to study a wide variety of clinical phenotypes. In this context, MSI offers huge diagnostic potential by supporting decision making in the determination of personalized treatment strategies. However, improvements in throughput and robustness are still needed before it finds a place in routine application. While the field has seen tremendous improvements in the  ...[more]

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