Abstract 2074: MALDI-ICC: a new tool for high-plex, multiomic profiling of single cells for cancer research and cancer therapy

Abstract Introduction: High-plex, multiomic profiling of single cells in cancer research and therapy is essential for understanding basic cancer mechanisms, discovery of new biomarkers and monitoring disease progression. Current profiling methods rely mainly on immunocytochemistry (ICC), multiparameter flow cytometry (MFC) and single cell RNA seq. However, these methods are limited by the number and/or classes of biomarkers that can be detected and/or inability to profile small molecular species such as lipids and metabolites. In contrast, a new method for high-plex, multiomic spatial imaging of single cells known as MALDI Immunocytochemistry (MALDI-ICC), based on novel photocleavable mass-tagged (PCMT) affinity probes in conjunction with single cell MALDI mass spectrometric imaging (MSI), facilitates the rapid profiling of individual cells at the proteomic, metabolomic, post-translational, and transcriptomic level in one integrated workflow on the same instrument. Methods: A variety of cell types such as peripheral blood mononuclear cell (PBMC) suspensions spiked with HeLa and MCF7 cancer cells, and chimeric antigen receptor (CAR) expressing cells were profiled using MALDI-ICC. Cells were processed by randomly depositing and desiccating them on glass or conductive IntelliSlides followed by a modified immunostaining protocol that combined PCMT-antibody and PCMT-oligo probes. Label-free, untargeted MSI of lipids/metabolites was first performed using a Bruker timsTOF fleX followed by a second MSI scan after binding a high-plex panel of PCMT-probes. A dual-labeled fluorophore/PCMT histone-targeted antibody was also included for high resolution microscopy. Results: High-plex PCMT-oligo and PCMT-antibody probe panels were utilized to target a variety of plasma membrane, cytoplasmic, and nuclear biomarkers at the mRNA and protein level, for several individual cell types, using the MALDI-ICC workflow. For example, MCF7 cells exhibited the epithelial marker E-cadherin, whereas HeLa did not but were detected with the mesenchymal marker vimentin, in full agreement with the Human Protein Atlas cell line database. Conversely, the lineage markers CD20 characteristic of B-cells and CD3 characteristic of T-cells were detected at the expected ratios for the cellular composition of the spiked PBMC. This method was further enhanced to detect >100 lipids/metabolites by performing an initial label-free, untargeted MSI scan before next implementing the MALDI-ICC protocol. AI clustering algorithms of all ‘omic’ layers revealed several distinct cell types. Conclusions: These results demonstrate that MALDI-ICC can provide a new method for rapid, high-plex and multiomic profiling of the same cell population on the same instrument. Potential uses include profiling of cancer cells in the field of hematology/oncology and of CAR T-cells both during manufacture and after infusion into patients. Citation Format: Mark J. Lim, Gargey Yagnik, Leonardo G. Dettori, Ziying Liu, Jonathan Bell, Kenneth J. Rothschild. MALDI-ICC: a new tool for high-plex, multiomic profiling of single cells for cancer research and cancer therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2074.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-2074
Primary Topic
Advanced Biosensing Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 2074: MALDI-ICC: a new tool for high-plex, multiomic profiling of single cells for cancer research and cancer therapy

Mark J. Lim, Kenneth J. Rothschild, Ziying Liu, Jonathan L. Bell et al.
Cancer Research
Advanced Biosensing Techniques and Applications
article

Abstract 2074: MALDI-ICC: a new tool for high-plex, multiomic profiling of single cells for cancer research and cancer therapy

Mark J. Lim, Kenneth J. Rothschild, Ziying Liu, Jonathan L. Bell, Gargey Yagnik, Leonardo G. Dettori
article en

Abstract

Abstract Introduction: High-plex, multiomic profiling of single cells in cancer research and therapy is essential for understanding basic cancer mechanisms, discovery of new biomarkers and monitoring disease progression. Current profiling methods rely mainly on immunocytochemistry (ICC), multiparameter flow cytometry (MFC) and single cell RNA seq. However, these methods are limited by the number and/or classes of biomarkers that can be detected and/or inability to profile small molecular species such as lipids and metabolites. In contrast, a new method for high-plex, multiomic spatial imaging of single cells known as MALDI Immunocytochemistry (MALDI-ICC), based on novel photocleavable mass-tagged (PCMT) affinity probes in conjunction with single cell MALDI mass spectrometric imaging (MSI), facilitates the rapid profiling of individual cells at the proteomic, metabolomic, post-translational, and transcriptomic level in one integrated workflow on the same instrument. Methods: A variety of cell types such as peripheral blood mononuclear cell (PBMC) suspensions spiked with HeLa and MCF7 cancer cells, and chimeric antigen receptor (CAR) expressing cells were profiled using MALDI-ICC. Cells were processed by randomly depositing and desiccating them on glass or conductive IntelliSlides followed by a modified immunostaining protocol that combined PCMT-antibody and PCMT-oligo probes. Label-free, untargeted MSI of lipids/metabolites was first performed using a Bruker timsTOF fleX followed by a second MSI scan after binding a high-plex panel of PCMT-probes. A dual-labeled fluorophore/PCMT histone-targeted antibody was also included for high resolution microscopy. Results: High-plex PCMT-oligo and PCMT-antibody probe panels were utilized to target a variety of plasma membrane, cytoplasmic, and nuclear biomarkers at the mRNA and protein level, for several individual cell types, using the MALDI-ICC workflow. For example, MCF7 cells exhibited the epithelial marker E-cadherin, whereas HeLa did not but were detected with the mesenchymal marker vimentin, in full agreement with the Human Protein Atlas cell line database. Conversely, the lineage markers CD20 characteristic of B-cells and CD3 characteristic of T-cells were detected at the expected ratios for the cellular composition of the spiked PBMC. This method was further enhanced to detect >100 lipids/metabolites by performing an initial label-free, untargeted MSI scan before next implementing the MALDI-ICC protocol. AI clustering algorithms of all ‘omic’ layers revealed several distinct cell types. Conclusions: These results demonstrate that MALDI-ICC can provide a new method for rapid, high-plex and multiomic profiling of the same cell population on the same instrument. Potential uses include profiling of cancer cells in the field of hematology/oncology and of CAR T-cells both during manufacture and after infusion into patients. Citation Format: Mark J. Lim, Gargey Yagnik, Leonardo G. Dettori, Ziying Liu, Jonathan Bell, Kenneth J. Rothschild. MALDI-ICC: a new tool for high-plex, multiomic profiling of single cells for cancer research and cancer therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2074.

Cancer ResearchVol. 85(8_Supplement_1)
AST Products (United States) (US)
Openalex Percentile: Top 92%
Advanced Biosensing Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.