Deep Profiling and Spatial Characterization of Tumor Microenvironment (TME) Using Hyperplex Immunofluorescence Assays

Novel immunotherapy has revolutionized the landscape of cancer therapy in multiple tumor types since Ipilimumab, the first ICB agent, was approved for the treatment of metastatic melanoma is 2011. Growing evidence has revealed the importance of TME and how it may impact the response to cancer immunotherapy. The dynamic and spatially heterogeneous TME is made up of malignant and nonmalignant cells such as endothelial cells, cancer-associated fibroblasts, immune cells in addition to vascular and lymphatic networks and the extracellular matrix. It is well established that a comprehensive characterization of the TME is needed to identify prognostic and predictive immune biomarkers. To this end, it has been demonstrated that the deep profiling and spatial characterization information provide by multiplex immunofluorescence (mIF) platform is a powerful tool. 

MultiOmyx is a proprietary mIF platform for the visualization and characterization of up to 60 protein biomarkers in a single FFPE section. Herein we reported to use different MultiOmyximmunoncology (IO) panels to characterize the TME in variety of tumor indications. Using these IO panels in combination with proprietary deep-learning based image analysis, we successfully studied the expression and spatial distribution of different subtypes of immune tumor infiltrates and immune modulators within the TME. In addition, the MultiOmyx panel also enables the detection of spatial morphological structures such as Tertiary lymphoid structures (TLS). Using MultiOmyx assay, we quantified TLS’s in 40 CRC samples and classified them by maturation stage based on biomarker expression and spatial organization of the immune markers.

The MultiOmyx assay provides a powerful tool to characterize the cellular composition and spatial organization of the TME. The rich datasets generated by the MultiOmyx assay can provide greater understanding of the immune contexture within the TME and deeper insights into the correlations between biomarkers. These findings may have broad application and help identify biomarker signatures with improved predictive performance to the efficacy of immunotherapeutics.

Learning Objectives:

1. Explain what a multiplex immunofluorescence (mIF) assay is and its advantages.

2. Describe spatial characterization of tumor microenvironment (TME) using mIF in combination with AI-based imaging analysis.

3. Explain using mIF and IA to support Immuno-oncology drug discovery.