= Emerging. More than 5 years before clinical availability. (16.60%, 2024)
= Expected to be clinically available in 1 to 4 years. (37.02%, 2024)
= Clinically available now. (46.38%, 2024)
MSACL 2024 : Regan

MSACL 2024 Abstract

Self-Classified Topic Area(s): Imaging > Imaging > none

Podium Presentation in De Anza 1 on Thursday at 13:30 (Chair: Erin Seeley / Jessica Moore)

Intraoperative Workflows, MALDI MSI of Tissue, and Data Visualization in MRI

Michael Regan (Presenter)
Brigham and Women's Hospital

Presenter Bio: Michael received his B.S. in Neuroscience from the University of Vermont, a master’s degree in Biomedical Science in 2021 from Northeastern University, and is currently completing a doctoral degree in Pharmaceutical Sciences at Northeastern University while performing his thesis work at Brigham and Women’s Hospital. His research focuses on assessing the effect of therapeutic interventions for glioblastoma using a combination of analytical technologies including MALDI mass spectrometry to quantitatively map the distribution and effect of therapeutics on the tumor microenvironment (TME).

Abstract

Introduction:
Translation of mass spectrometry into clinical chemistry and microbiology laboratories has been achieved through improvements in several key analytical parameters, including speed and accuracy. Similar improvements are needed for matrix assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) to move into the clinical arena for tissue-based diagnostics. Intraoperative tissue preservation as well as innovative cryosection approaches allow for combined multiomics analyses. Here we present methodological advancements in MALDI MSI workflows to address clinical needs.

Methods:
We have developed a method using tissue microarray (TMA) molds to create calibration curves for several endogenous metabolites and drugs to be simultaneously quantified from a MALDI MS image. Serial dilutions of metabolite standards and therapeutics were prepared in gelatin molds generated from TMA templates. Calibration curves, along with accompanying tissue sections were imaged using a 15T FT-ICR MS or timsTOF instruments (Bruker). In addition, we applied our recently described rapid MALDI method based on matrix pre-coating and a high laser frequency for the imaging of clinical brain cancer samples. MS imaging results were integrated with complementary multiomic analyses into MRI volumes for visualization to elucidate some of the molecular mechanisms governing the TME in glioblastoma.

Results:
Using tissue mimetics in TMA molds allowed for a much higher number of calibration curves and analytes to be accurately measured on a single slide. All analytes demonstrated a high degree of linearity across a wide dynamic range, allowing to quantify levels in clinical tissue specimens. The integration of MALDI MSI with tissue cyclic immunofluorescence (CyCIF) and spatial transcriptomics provide comprehensive maps of the tumor microenvironment in response to therapeutics.

Conclusions:
We present here parallel advancements in MALDI MSI methods to enhance clinical applicability for the quantitative mapping of drugs and metabolites from clinical tissues. Future directions will include the integration of multiplex calibration with the turnaround times of the rapid MALDI MSI method. These advancements will contribute to translation to the clinical laboratory and provide a needed approach to address the heterogeneity of the glioblastoma TME critically needed for clinical advancement toward the treatment of this devastating disease.


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