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e14574 Background: Understanding cellular interactions within the tumor microenvironment (TME) is essential for elucidating disease progression and advancing immunotherapy. The TME is a complex ecosystem composed of cells with dysregulated metabolism immune response and signaling pathways, which in turn influence tumor development and treatment response. Multiplexed assessment serves as an important tool for clinical oncology. The simultaneous readout of multiple processes can provide biological insights and elucidate disease mechanism. Imaging Mass Cytometry (IMC) is a spatial biology imaging technique that utilizes CyTOF technology and enables deep characterization of the diversity and complexity of the TME. IMC technology offers scalable, high-throughput acquisition while generating high-quality data with true dynamic range of signal without amplification or fluorescence-based limitations such as spectral overlap and autofluorescence. Methods: To study cellular processes and their roles in tumor progression, we utilized the Human Cell Metabolism and Human Cell Signaling Panels to investigate energy production, cellular homeostasis and mitogenic signaling pathways. We then mapped these processes to the types of cells in the TME by using the Human Immuno-Oncology IMC Panel and the Human T Cell Exhaustion IMC Panel or the Maxpar Neuro Phenotyping IMC Panel Kit to characterize immune cell and neurological phenotypes in detail. We first acquired data using Preview Mode to assess the whole tissue, followed by higher-resolution imaging of selected regions of interest using Cell Mode or of the whole tissue section using Tissue Mode. Results: Our data analysis revealed significant insights into the spatial organization and metabolic profile of cells across cancer tissues. Elevated glycolysis and mTOR pathway activation suggested adaptations to hypoxia and anabolic growth in tumor areas, while interactions between fibroblasts and immune cells highlighted crosstalk within the TME. Our Neuro Phenotyping Panel was used to reveal potential for immune response in glioblastoma. Unsupervised pixel clustering and hierarchical clustering using MCD SmartViewer highlighted metabolic activity and activation of signaling pathways within tumor regions. Conclusions: Comprehensive spatial biology profiling using the IMC approach highlights the interconnected roles these pathways play in promoting tumor survival and resistance to therapies. These findings, which illuminate the metabolic and signaling heterogeneity of the TME, are crucial for developing future prognostic assessments and have the potential to guide more effective, personalized cancer therapies. For Research Use Only. Not for use in diagnostic procedures.
e14628 Background: Detecting clinically relevant biomarkers in cancer tissues provides key insights into the unique tumor characteristics of patients, allowing for more personalized and effective therapies. Clinical biomarkers such as PD-1 and PD-L1 are associated with an immune-suppressive tumor microenvironment (TME), whereas HER2 is associated with metastasis and recurrence in multiple types of cancers. Immunohistochemistry (IHC) is the gold-standard technique for biomarker detection and is widely used by pathologists to grade tissue expression. Limitations related to plexity, quantitation and false signal detection are frequently observed using IHC, and day-to-day variability due to signal amplification and false positive signal can misinform pathologists about biomarker expression. Imaging Mass Cytometry (IMC) technology is a multiplexed spatial imaging technique that incorporates stoichiometric and quantitative assessment of 40-plus biomarkers simultaneously on a single slide and offers a large dynamic range of signal detection. We strove to determine whether IMC based spatial proteomics can be used for pathological evaluation of PD-1, PD-L1 and HER2 and provide key biological insights for clinical and translational studies. Methods: We stained serial sections of tissues using the same antibody clone and generated IHC and IMC data, which was assessed by a board-certified pathologist. For IMC technology, we detected single cells using the Human Immuno-Oncology IMC Panel, which highlights individual tumor, immune and stromal components of the TME. We conducted quantitative image analysis to detect expression of relevant biomarkers on cells and found enriched cellular neighborhoods associated with various pro- and antitumor processes. Results: Our analysis demonstrated that IMC technology and IHC similarly detected PD-1 and PD-L1. However, IMC accomplished it without signal amplification. For HER2, IMC technology and IHC provided comparable data. However, IMC detected the true dynamic range of signal intensities. Quantitative comparison of IMC technology combined with single-cell spatial proteomic analysis resolved the location of PD-1-, PD-L1- and HER2-expressing cells relative to other immune, stromal and tumor cell populations and offered additional biological insights into disease mechanisms. Conclusions: Clinical assessment of tissues using IMC technology offers an advantage over IHC by providing true biological context through multiplexing capabilities. High-dimensional spatially resolved data offered by IMC technology has the potential to expand our understanding of disease mechanisms of cancers and expedite development of personalized therapies for cancer patients in the clinic. For Research Use Only. Not for use in diagnostic procedures.
e14575 Background: Over the last decade, immunotherapy has revolutionized cancer treatment, offering transformative outcomes for many patients. However, its effectiveness in treating solid tumors remains limited due to challenges such as T cell exhaustion, immunosuppressive tumor microenvironment (TME), lack of tumor-specific antigens and a complex immune landscape. Solid tumors also induce systemic immune changes that evolve dynamically with tumor progression. To improve patient outcome, it is essential to understand the interplay between localized and systemic immune responses. Methods: To address these challenges, we employed an integrative approach leveraging CyTOF and Imaging Mass Cytometry (IMC) technologies. Matched samples, including peripheral blood mononuclear cells (PBMCs), tumor-derived cells (TDCs) and formalin-fixed, paraffin-embedded (FFPE) tumor tissues from cancer patients, were analyzed. A custom CyTOF panel with over 40 markers was designed to profile immune subsets, checkpoint molecules, cytokines and transcription factors. Samples were barcoded, stained and analyzed using a CyTOF XT system. For spatial immune profiling, FFPE tumor tissues were stained with a 40-plus-marker IMC panel to characterize immune, stromal and tumor cells and assess immune activation states. Data was acquired with the Hyperion XTi Imaging System, enabling high-resolution imaging of tumor microenvironments. Results: CyTOF analysis revealed heterogeneity in T cell exhaustion and activation profiles in PBMCs and TDCs, highlighting the functional diversity of immune responses. IMC technology provided spatial insights into immune cell interactions within the TME, identifying distinct patterns of immune infiltration and congregation around tumor cells and stromal elements. Comparative analysis of CyTOF and IMC data uncovered shared and divergent phenotypes between peripheral and tumor-resident immune compartments, identifying biomarkers that link systemic immune profiles with TME dynamics. Conclusions: These findings offer invaluable insights into the immunological mechanisms driving antitumor responses. By integrating functional and spatial immune profiling, our approach identifies predictive biomarkers and potential therapeutic targets, guiding the development of personalized immunotherapies. This work highlights the importance of understanding systemic and localized immune responses to improve cancer treatment outcomes and optimize treatment strategies. For Research Use Only. Not for use in diagnostic procedures.
