Webinar

In this webinar, we’ll share how phenoptrReports provides powerful, easy-to-use tools to analyze spatial relationships between cellular phenotypes and visualize their relationships overlaid on the tissue, phenotype cells co-expressing markers, determine the quality of your unmixing library, and display results in shareable, easy-to-read data reports. Tips and tricks for getting the most out of your analysis will be reviewed as well.

Observing cell-cell interactions is critical to understanding causative factors of biological outcomes. As the only benchtop platform capable of multiplexing >40 markers in tissue, CODEX® (rebranded to PhenoCycler™) uniquely enables these observations by assaying tissue biopsies using fluidics, an inverted microscope, oligo-conjugated antibodies, and fluorescent reporters.

In this webinar Dr. Jonah Cool, Program Officer for Single-Cell Biology at the Chan Zuckerberg Initiative, provides an overview of single-cell efforts at CZI; and Dr. Oliver Braubach, Head of Research Applications at Akoya Biosciences, introduces the CODEX solution and shares case studies on how single-cell, spatial phenotyping applications can push the boundaries of discovery biology in human health and disease.

Immune checkpoint inhibitors are revolutionizing cancer therapy for many. But robust biomarkers are needed to predict which patients will likely benefit from these therapies. A team of investigators at the Mayo Clinic is trying to close this gap by developing a catalog of the human immune system in cancer patients, appropriately called “The Cancer Immunome Project. By analyzing the spatial architecture of FFPE tumor sections across the entire tumor microenvironment, the team is generating a comprehensive map of the cancer immunome. In this webcast, Dr. JC Villasboas shares how his team is using the CODEX® System to deepen our knowledge about the composition, architecture and interactions of the tumor microenvironment.

Hear from Oliver Braubach, Ph.D., Senior Manager, Applications at Akoya Biosciences on the importance of single cell resolution in spatial biology , how to discover single cell contextual phenotypes and the many single-cell, spatial phenotyping applications.