PhenoCycler®

Biological systems are complex, and full spatial understanding of tissue heterogeneity and cellular microenvironments has been hampered by trade-offs that are forced by the available analytical technologies.

All of which has given rise to the concept of the ‘iron triangle’ – the hard problem of improving resolution, plex and throughput simultaneously in one analytical solution.

But the world is set to change with the advent of new spatial phenotyping approaches that enable viewing, characterization and quantification of cells by lineage and variant with single-cell resolution, all in the context of an intact tissue sample.

From capturing tumor heterogeneity and validating cancer models, to teasing out how the cellular microenvironment impacts disease progression and treatment response, this guide will explain how spatial phenotyping can deliver advances in automation, efficiency, tunability, and speed that are set to transform how we study tissue biology.

Spatial phenotyping of whole tissue sections enables the study of different cell phenotypes and how they interact in situ to impact disease pathology and progression. In areas such as oncology, immunology, and neurodegenerative disease, this is rapidly increasing our understanding of underlying cell-level biology and holds the potential to drive a new wave of therapeutic discovery.

In this new eBook, we provide a user guide to spatial phenotyping and highlight a range of its benefits and applications, including how it can enable researchers to:

• Unlock single-cell discoveries in FFPE tissues
• Explore tumor heterogeneity
• Visualize tumor-infiltrating lymphocytes
• Perform highly multiplexed hypothesis-free biomarker discovery
• Conduct hypothesis-driven biomarker discovery and high-throughput translational research

Spatial phenotyping allows a researcher to view, characterize, and quantify cells by lineage and variant with single-cell resolution in the context of an intact tissue sample. In areas such as oncology, immunology, and neurodegenerative disease it has opened new insights into the interplay between different cellular actors in promoting or suppressing disease.

This white paper offers examples of how spatial phenotyping can impact your research tool kit.

In this infographic, discover how spatial phenotypic signatures can act as invaluable whole slide image-based quantitative biomarkers to predict immunotherapy response, and learn more about Akoya Biosciences’ comprehensive multiplex immunofluorescence solutions for spatial phenotyping.

This application note outlines the results of an in-depth study comparing immuno-oncology biomarker types by scientists at Johns Hopkins University, Yale University, and other institutions. Here, Akoya Biosciences shows that the study determined that multiplex immunofluorescence with spatial characterization significantly outperformed other biomarker testing approaches for predicting patient response to treatments targeting PD-1/PD-L1.

Innovations include a novel spatial transcriptomics chemistry and universal protein chemistry for accelerated biomarker discovery and validation

The partnership pairs Akoya’s spatial phenotyping solutions and PathAI’s AI-based algorithms to elucidate spatial biomarker signatures for biopharma partners

Collaboration aims to provide new workflows, faster acquisition speeds and deeper resolution

The Proxima spatial analysis software solution integrates image acquisition to data analysis in the secure cloud for rapid access by any user

Akoya Biosciences determines that multiplex immunofluorescence technology preserves critical data missed by other biomarker strategies