CODEX Multiplexed Imaging - Entering the Age of Technicolor Histology
CODEX is a new multiplexed imaging technique that allows up to 60 markers to be viewed simultaneously in a tissue. This increases our spatial resolution of cell interactions in diseased and healthy tissues. Our recent paper focuses on the implementation of this multiplexed imaging technique.
The Nolan laboratory has pioneered multiplexed single-cell technologies to better understand complex biological systems. Since our first mass cytometry publication (Bendall et al., Science 2011), CyTOF has become widely used for high-parameter analysis of proteins in single cells. More recently, we published Multiplexed Ion Beam Imaging (MIBI) (Angelo et al., Nature Med 2014), CO-Detection by indEXing (CODEX) (Goltsev et al., Cell 2018), and together with the Deisseroth lab STARmap (Wang et al., Science 2018), which are tissue imaging approaches for high-parameter visualization of proteins in 2D (MIBI and CODEX) and RNA in 3D (STARmap).
CODEX is a high-parameter imaging technology that relies on DNA-conjugated antibodies and the cyclic addition and removal of complementary fluorescently labeled DNA probes, enabling up to 60 markers to be simultaneously visualized in situ. We have now used CODEX to image fresh-frozen, fixed-frozen, and formalin-fixed, paraffin-embedded (FFPE) tissues in the form of tissue microarrays and large tissue sections from mouse, monkey and human samples. This enables critical spatial biological and clinical insights that single-cell multiparameter technologies have previously been unable to provide, such as cell-cell contacts, environmental context, and overarching tissue structure.
Specifically, we look at the “cellular neighborhoods” where we identify common substructures of groups of different types of cells in either healthy or diseased tissue. We demonstrated the utility of CODEX applied to FFPE tissues using a retrospective cohort of colorectal cancer patients to deeply profile the immune tumor microenvironment (Schürch et al., Cell 2020). Our findings in this study underscore the importance of interrogating cellular composition, while preserving spatial information. We anticipate that CODEX will be applied by clinicians and researchers around the globe to study diseases and to perform biomarker discovery for clinical trials, revealing how cells are interrelated within a histological context and correlated with clinical outcome.
Since the original Cell publication in 2018, the CODEX technology has been re-engineered, simplified, and was adopted by numerous laboratories in the United States and Europe. This was spurred by the commercialization of the CODEX microfluidics instrument by Akoya Biosciences. The Nolan lab has contributed to this expansion by teaching the technique to researchers who have contacted our group and through our annual hands-on technology workshop hosted at Stanford University (through NIH sponsored in lab classwork).
Among those groups who are using CODEX, several are contributing to large consortia efforts to create 3D spatial single-cell maps of healthy and cancerous human tissues. These include HUBMAP (Human BioMolecular Atlas Program), HTAN (Human Tumor Atlas Network), and the Cancer Research UK (CRUK) Grand Challenge. The quality of this publicly available CODEX data will depend on standardized reporting and following of protocols.
With the recently expanded use of CODEX, there is a need to detail the experimental protocols for this method to help researchers get started and experienced users troubleshoot. Since our laboratory has spent 3 years refining the technique for day-to-day use, we expect the protocol presented here to be invaluable to the broader research community. Specifically, we provide the most current protocols for 1) antibody conjugation with DNA oligonucleotides, 2) validation and titration of conjugated antibodies by CODEX staining of fresh-frozen and FFPE tissues, 3) the CODEX multicycle reaction, and 4) a primer on CODEX multiplexed imaging data analysis, among other considerations.
We also discuss expected results and provide tips for troubleshooting critical steps where users are most likely to encounter problems. Furthermore, we describe how to use the open-sourced software and computational tools to analyze this type of complex spatial data. Ultimately, this more complete set of protocols will provide expert tips for novice users and establish a standardized reference protocol for users of the CODEX technology.