European Association for Cancer Reasearch (EACR) Annual Meeting 2026

Understanding the complexity of the tumor microenvironment (TME) requires simultaneous insight into multiple biological domains. Studying the molecular interactions that govern intercellular and intracellular signaling in combination with the analysis of cell phenotypes and transcriptional states, can guarantee an improved comprehension of key pathways driving tumor growth or the response of anti-cancer therapies. Protein–protein interactions (PPIs), such as PD-1/PD-L1, are central to immune evasion and targets of important immunotherapies. Despite the success of PD-1/PD-L1 and other checkpoint inhibitors, patient stratification for these therapies has been challenging, and marker expression alone has shown to not fully capture functional engagement or predict an efficient drug response. Here, we present a fully automated workflow that combines three omics layers on the same tissue section: protein-protein proximity, RNA, and protein expression, enabling a more comprehensive view of cellular interplay in cancer and modeling of treatment outcomes. 

The multiomics assay runs on the COMET™ platform. It allows the co-detection of: (i) RNA profiling via RNAscope™ HiPlex Pro, (ii) Protein expression through sequential immunofluorescence (seqIF™, PMID: 37813886), (iii) Protein–protein proximity detection using oligonucleotide-conjugated secondary antibody pairs and RNAscope™ amplification chemistry. 

Proximity signals are interpreted as probabilistic indicators of molecular interactions and supported by multiple controls to ensure their specificity: from the colocalization of seqIF™ signals to negative controls run on the same section. 

In this study, we demonstrated that it is possible to combine the detection of proximity signals for the analysis of intercellular interactions controlling anti-tumoral immune responses, alongside protein markers for cell phenotyping and RNA targets for functional markers and cell activation status. In detail, across multiple human FFPE tumor samples, PD-1/PD-L1 interaction was detected in combination with multiple proteins, for immune and stromal phenotyping, and RNA transcripts responsible for the expression of key secreted molecules like cytokines and chemokines. Furthermore, we showed that multiple iterative cycles allow the detection of more than one PPI on the same FFPE section. 

Tumor progression, immune evasion, and therapy resistance are not driven by single molecules but by complex interaction networks among proteins, signaling pathways, and cellular types. This automated spatial multiomics workflow incorporating protein–protein proximity as a third dimension, can help reveal how these processes are regulated. By combining RNA, protein, and proximity data, the assay offers a powerful approach to support biomarker discovery and improved patient stratification. 

The use of multiplex immunofluorescence (mIF) to study the tumor microenvironment (TME) has significantly advanced our understanding of spatial dynamics within tumors. This technique has emerged as a valuable tool for identifying biomarkers and therapeutic targets. Despite its growing adoption, mIF protocols remain complex and technically demanding. Their manual execution and reliance on dedicated reagents make them time-consuming and expensive. Additionally, concerns persist regarding their reproducibility and transferability across different tissue types. Ready-to-use, validated antibody panels, such as the SPYRE™ Core Panels, help address these challenges. 

In this study, we demonstrate the development and validation of two new antibody panels covering relevant stromal and vessel biomarkers to enable spatial analysis of the TME on the COMET™ platform across various tissue types as well as two additional antibodies against SOX10 and S100B optimized for melanoma studies. The stroma panel enables simultaneous detection of Vimentin, E-Cadherin, Collagen I, and FAP, while the vessel panel contains CD31, CD34, Podoplanin, and LYVE-1. Formalin-fixed paraffin-embedded human tissue sections from a 24-cores multi-organ tissue microarray and whole-section melanoma samples were stained on COMET™ by fully automated sequential immunofluorescence (seqIF™, PMID: 37813886). Staining and detection are done via indirect immunofluorescence using unlabeled primary antibodies and fluorophore conjugated secondary antibodies. Both panels were developed and validated on several tumoral and non-tumoral tissues at the same time. The sections retrieved from COMET™ after seqIF™, were stained by a histology facility with standard immunohistochemistry (IHC) established for pathological diagnosis to compare seqIF™ and IHC staining patterns and verify antibody specificity. All markers demonstrate accurate detection with specific seqIF™ staining, comparable to gold-standard IHC counterparts, as well as robust performance across multiple tissues. Protocols were optimized to achieve high staining quality for all ten markers in terms of sensitivity and signal-to-background ratio. The repeatability and reproducibility of the automated stainings on the COMET™ platform was verified by day-to-day tests on one instrument and tests among multiple ones.  

Our validated SPYRE™ Stroma and Vessel Focus panels, along with melanoma-specific antibodies, deliver highly specific and reproducible results across diverse tissues. Ready-to-use on the COMET™ platform and designed as modular extensions of the SPYRE™ Core Panels, they enablequantitative marker detection, combination with custom antibodies, and empower researchers with robust and scalable workflows for advanced spatial biology studies.

Background
The tumor microenvironment (TME) plays a pivotal role in cancer progression, immune evasion, and therapeutic response. Understanding the spatial organization and functional states of cells within the TME is essential for advancing immuno-oncology and precision medicine [PMID: 40102282]. However, simultaneous visualization of secreted molecules and cellular phenotypes in situ remains a major challenge in the spatial biology field [PMID: 39930476].  

Here, we employed an automated hyperplex multiomics assay to simultaneously detect RNA and protein expressions to spatially map cell phenotypes and their functional states in the TME of multiple cancer types. 

Methods
We examined a formalin-fixed paraffin-embedded tissue microarray (TMA) comprising various human cancer types: prostate, lung, breast, colorectal, melanoma, and lymphoma. A TMA section was stained and imaged on the COMET™ platform, integrating RNAscope™ HiPlex Pro for transcript detection and sequential immunofluorescence (seqIF™) for proteomic analysis [PMID: 22166544; 37813886; 41065276]. Image was analyzed using HORIZON™ software to extract single-cell and spatial features. 

Results
The automated multiomics approach enabled the concomitant in situ detection of over 100 biomolecular targets, including 12 transcripts and more than 90 proteins on the same section. High-resolution spatial profiling of the TME allowed accurate mapping of cancer, stromal, vascular and diverse immune cell subsets. It further revealed key molecular features associated with tumor-suppressor or proto-oncogene activity, including markers of proliferation, apoptosis, and immune checkpoint regulation. Concurrent detection of cytokine and chemokine transcripts highlighted localized immune signaling and cell-cell communication within tumor and stromal compartments.  

Conclusions
This multiomics workflow offers a powerful tool for in-depth characterization of the TME across multiple cancer types, while significantly reducing sample consumption. Spatial profiling provides new opportunities to dissect the tissue architecture and immune dynamics to identify functional cell states and interactions to be exploited in immunotherapy and personalized medicine.