MSACL 2025 Abstract

Array-Based Multimodal Mass Spectrometry Imaging Enables Single-Cell Profiling of Circulating Immune Cells

Lyndsay E.A. Young (1,2), James W. Dressman (1), M. Furkan Bayram (1), Kaitlyn Bejar (3), Robin J. Leach (3), Anand S. Mehta (1,2), Richard R. Drake (1,2)
(1) Department of Pharmacology and Immunology, College of Medicine, Medical University of South Carolina, 68 President Street, Charleston, SC, 29425, USA, (2) Hollings Cancer Center, Medical University of South Carolina, 86 Jonathan Lucas Street, Charleston, SC, 29425, USA (3) University of Texas Health Science Center, San Antonio, Texas

Lyndsay Young, PhD (Presenter) Medical University of South Carolina

Presenter Bio: Dr. Lyndsay E.A. Young is a Postdoctoral Scholar in the lab of Dr. Richard Drake in the Department of Pharmacology and Immunology at the Medical University of South Carolina. Her current work involves the implementation of spatial mass spectrometry imaging for disease profiling and mechanistic investigations. The Drake Lab has pioneered the use of MALDI-MSI to assess N-glycosylation in the tissue microenvironment from both FFPE and frozen sections. These N-glycan tissue maps serve as guides for targeting tumor-localized glycoproteins for proteomic analysis and provide molecular determinants for histopathology applications. Currently, Dr. Young is defining the N-glycome and cellular environment across colorectal carcinoma progression in patient specimens and profiling peripheral blood mononuclear cells using the lab’s latest single-cell capture methodology. She plans to dedicate her career to applying and integrating spatial imaging technologies to advance the understanding of metabolism’s role in disease progression.

Relevant Financial Disclosures (within past 24 months, reported on Apr 28, 2025) No relevant financial relationship(s) to disclose.

INTRODUCTION:
Peripheral Blood Mononuclear Cells (PBMCs) - including lymphocytes (T cells, B cells, NK cells), monocytes, and dendritic cells are essential circulating cells in the immune system, contributing to both innate and adaptive immunity. These cells are readily accessible through blood collection and offer valuable insights into systemic metabolic disturbances associated with various diseases, such as cancer and autoimmune disorders. Their accessibility and immunological relevance make PBMCs a powerful tool for bridging the gap between basic research and clinical applications, including next-generation cell therapies. Clinically, PBMCs are widely used in immunomonitoring, vaccine development, and the evaluation of immune responses in infectious diseases and immunotherapies. Our group has recently developed a single cell array-based slide platform is an attractive methodology to isolate, visualize, and characterize the cellular heterogeneity of PBMCs using serial multi-analyte by MALDI-MSI.

METHODS:
To gain a better understanding of immune cell metabolic status and cellular composition, we employed a high-throughput single cell array-based slide assay to clinical human PBMC isolates. To create the patterned grid of cells, we utilize a (polydimethylsiloxane) PDMS stamp at 240um or 60um spacing. Further, in house software programs such as SoloCell were developed to identify regions containing a single captured cell and accurately record its location on the slide. We then employed Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) and MALDI-immunohistochemistry (IHC) for biomolecular profiling of lipids, N-glycans, glycogen, tryptic peptides and photocleavable tagged antibodies (AmberGen Inc). Single cells were then analyzed on a Bruker timsTOFflex and data was analyzed in SCILS software.

PRELIMINARY DATA:
Single-cell analysis has significantly advanced our understanding of cell function, intercellular interactions, and the heterogeneity within cell populations. By adapting the mass spectrometry imaging platform as an single-cell array-based platform, we developed a robust framework for profiling PBMC isolates. We applied this assay to a cohort of 30 PBMC specimens from healthy male donors, enabling deeper metabolic characterization across self-reported race and ethnicity, age, and body mass index. Initially, bulk cells are captured in 1ul spots (~3000cells) via antibodies to CD4, CD8, CD19, and CD14 to allow for precise cellular signature identification. On the same slide, single cells are captured via lectin ensuring unbiased selection that preserves the natural heterogeneity of PBMC isolates. The optimized cell spacing allows for rapid profiling of <3,000 of single-cell profiles in 15 minutes or less. This approach supports multiplexed analysis of metabolites including 250 +lipids, 40+ N-glycans, glycogen-derived glucose polymers, and 50+ tryptic peptides from a single cell. Notably, the pooled relative intensities from ~4,000 single cells closely match those from bulk 1µL spots across all macromolecule classes, reinforcing confidence in biomolecular identification. Tiered analyses—particularly those combining lipid and N-glycan profiles—enable differentiation of immune cell lineages, clearly distinguishing myeloid from lymphoid populations. This method also accurately separates CD4+ from CD8+ T cells, CD19+ B cells, and CD14+ macrophages. Additionally, metabolic interrogation of glycogen revealed distinct levels among cells, suggesting its role in survival-related metabolic adaptations. This multimodal interrogation deepens our understanding of the metabolic landscape of circulating PBMCs. The array slide format is inherently flexible, supporting cell capture via antibodies, lectins, or bait proteins, while also allowing enzymatic processing with glycosidases and proteases for comprehensive molecular profiling. Beyond its analytical capabilities, we are currently investigating the use of this platform in the context of chimeric antigen receptor (CAR) T-cell therapies. By profiling CAR-T cells derived from cancer patients, we aim to improve in vivo persistence of infused cells and identify potential toxicities, such as cytokine release syndrome, through immunometabolic characterization.