Work

1120 Hyperplex spatial profiling of transcriptomic, proteomic, and protein–protein proximity layers for an in-depth characterization of the tumor microenvironment

Year: 2026

Type: conference-abstract

Abstract: Background The tumor microenvironment (TME) is a highly organized and dynamic ecosystem that governs tumor evolution, immune escape, and response to therapy. Capturing not only the spatial distribution and phenotypic identity of cells, but also their functional states and physical interactions, is critical for a deeper understanding of tumor biology. Despite recent progress in spatial omics, it remains challenging to simultaneously interrogate these complementary dimensions in situ. Approaches that integrate cell phenotyping, transcriptional activity, and direct evidence of cell–cell or protein–protein interactions are still emerging.1 To address this gap, we developed a hyperplex spatial multiomics workflow that combines RNA detection, protein profiling and protein–protein proximity (PPP) staining to study intercellular interactions alongside phenotypic and functional markers.Methods A formalin-fixed paraffin-embedded tissue microarray (TMA) including various cancer types (prostate, lung, breast, colorectal, melanoma, and lymphoma) was stained and imaged using the COMET™ platform. The workflow integrates RNAscope™ HiPlex Pro for high-plex transcript detection, 2 sequential immunofluorescence (seqIF™) for high-plex protein profiling,3 and a PPP assay to visualize proximity-based interaction events at subcellular resolution. The resulting image was analyzed with HORIZON™ software to extract single-cell and spatial features.Results This automated multiomics approach enabled the simultaneous detection of over 130 biomolecular targets, including RNA, protein, and protein–protein proximity signals within the same tissue section. High-resolution spatial profiling of the TME allowed accurate mapping of malignant, stromal, vascular, and immune populations, and defined their phenotypic heterogeneity. The addition of PPP information provided direct evidence of molecular interactions and cell–cell communication within spatially confined niches, complementing transcriptomic and proteomic readouts. Integration of these 3-omics layers in a hyperplex assay allowed us to generate a multidimensional view of the TME and analyze spatial features within tumor and stromal compartments.Conclusions The simultaneous assessment of cellular identity, functional state, and interaction context within a single intact tissue provides a comprehensive framework to study the TME. This hyperplex strategy has strong potential to refine our understanding of tumor–immune relationships and to support the identification of spatially defined biomarkers and therapeutic targets in immuno-oncology.References Nguyen H, et al. Spatial omics for profiling the dynamic tumor microenvironment. Clin Transl Immunology. 2026 Apr 13;15(4):e70084. doi: 10.1002/cti2.70084.Wang F, et al. RNAscope: a novel in situ RNA analysis platform for formalin-fixed, paraffin-embedded tissues. J Mol Diagn. 2012 Jan;14(1):22–9. doi: 10.1016/j.jmoldx.2011.08.002. Rivest F, et al. Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics. Sci Rep. 2023;13(1):16994. doi: 10.1038/s41598-023-43435-w.

Source: Journal for ImmunoTherapy of Cancer

DOI: 10.1136/jitc-2026-sitc2026.1120