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April 5, 2026Cancer Research0 citations

Abstract 2012: Spatial proteomic profiling of metabolic and cell signaling heterogeneity in breast cancer tumor microenvironment using imaging mass cytometry.

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QRQanber RazaNZNick ZabinyakovLLLiang Lim

Key Points

  • To investigate the heterogeneity of metabolic and signaling pathways in the tumor microenvironment of breast cancer using advanced imaging technology.
  • Utilized Imaging Mass Cytometry (IMC) with integrated antibody panels.
  • Assessed energy production and cellular signaling in breast cancer tissues.
  • Analyzed tissue sections using high-resolution imaging modes to evaluate cell phenotypes and immune activation.
  • Employed unsupervised pixel-clustering and hierarchical analysis for detailed profiling.
  • Identified spatial heterogeneity in metabolic and signaling states within breast tumors.
  • Found immune cells were enriched in areas with fatty acid oxidation, while tumor areas showed varied glycolysis.
  • Elevated glycolysis and mTOR activation indicated tumor adaptation to hypoxic environments.
  • Differential signaling pathway activity was observed between tumor and immune cells.

Abstract

Abstract The tumor microenvironment (TME) is a complex ecosystem of tumor and immune cells with dysregulated metabolic and signaling pathways that drive tumor heterogeneity, progression and differential treatment response. Targeting these pathways has emerged as a promising strategy to enhance immunotherapy efficacy. Imaging Mass Cytometry™ (IMC™) systems, leveraging CyTOF™ technology, enable simultaneous detection of 40 markers, providing scalable, high-throughput spatial characterization of the TME with true dynamic range, free from spectral overlap and autofluorescence limitations inherent to fluorescence-based approaches. We applied IMC technology to interrogate metabolic and signaling programs in human breast cancer using integrated antibody panels: the Human Immuno-Oncology IMC Panel (PN 201509) combined with either the Human Cell Metabolism (PN 201521) or Human Cell Signaling (PN 201522) IMC Panels. This approach enabled simultaneous assessment of energy production, cellular homeostasis and mitogenic signaling. Whole tissue sections were initially imaged in Preview Mode, followed by high-resolution analysis of regions of interest using Cell Mode or Tissue Mode to phenotype tumor and immune cells and evaluate immune activation. IMC technology revealed spatial heterogeneity in metabolic and signaling states within breast tumors. Tumor regions demonstrated differential energy utilization: Immune cells predominantly infiltrated areas enriched for fatty acid oxidation, whereas tumor regions with anaerobic or aerobic glycolysis corresponded to immune-excluded zones. Signaling pathway activity also varied by cell type. Elevated glycolysis and mTOR activation indicated adaptation to hypoxic and anabolic demands. Wnt signaling and PTEN expression were enriched in tumor cells, whereas MAP kinase signaling was localized primarily to stromal compartments. Unsupervised pixel-clustering and hierarchical analysis using MCD™ SmartViewer further resolved region-specific metabolic and signaling heterogeneity. IMC systems enable comprehensive spatial profiling of metabolism and signaling in breast cancer, revealing tumor-immune interactions and intratumoral heterogeneity. This high-dimensional spatially resolved approach provides a powerful framework for identifying clinically relevant targets, informing prognostic assessments and guiding development of personalized therapeutic strategies. For Research Use Only. Not for use in diagnostic procedures. Citation Format: Qanber Raza, Nick Zabinyakov, Liang Lim, Christina Loh. Spatial proteomic profiling of metabolic and cell signaling heterogeneity in breast cancer tumor microenvironment using imaging mass cytometry abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2012.

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Cite This Study

Raza et al. (2026) studied this question.

synapsesocial.com/papers/69d1fe18a79560c99a0a498dhttps://doi.org/10.1158/1538-7445.am2026-2012
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