We sat down with Dr. Christopher Kerfoot, Global Strategic Advisor of Histopathology at CellCarta & Co-founder of Mosaic Laboratories, who provided an in-depth examination of the cutting-edge multiplex technology that is being deployed at CellCarta to generate advanced spatial biology data and revolutionize global healthcare.
Interest in spatial biology is expanding rapidly. Can you describe the capabilities and spatial biology platforms available at CellCarta?
Multiplex immunofluorescence (mIF) and immunohistochemistry (mIHC) have jumped to the forefront of tissue-based analysis due to the success of immuno-oncology therapeutics. Multiplex IF allows evaluation of immunophenotyped cell density, investigation of spatial biology and characterization of the activation state of proteins in specific cells. CellCarta currently provides mIF services using Akoya Opal™ and Ultivue technologies combined with extensive machine learning and artificial intelligence (ML/AI) data capabilities to quantify, explore and predict patient outcomes.
The Opal chemistry allows flexible development of mIF panels for the detection of up to 8 analytes, although we typically limit this to 6 analytes due to dramatic increases in imaging time once you exceed 6-plex assays. The Opal procedure contains multiple rounds of incubations with a primary antibody, a horse-radish peroxidase (HRP)-based detection reagent, and tyramide coupled to an Opal fluorophore. The fluor-conjugated tyramide deposits in the region of the bound antibody. Between each assay round, the slide is heated to remove the primary antibody and detection reagent, but the fluor-conjugated tyramide remains bound.
Ultivue uses a different technique that is based on an oligonucleotide-tagged primary antibody, an amplification step, and detection using a complementary nucleotide sequence conjugated to a fluorophore. Ultivue has developed optimized conditions for many 4-plex FixVUE™ panels including panels to characterize MDSCs, T-regs, Activated T cells, antigen presenting cells, PD-L1 expressing cells, and PD-1 expressing cells. They also have an Immuno8 FixVUE panel and a FlexVUE™ offering that allows you to replace 2 antibodies from the Immuno8 panel with 2 antibodies from a list of at least 13 antibodies that have been optimized for detection. Through the U-VUE™ program, a client can have Ultivue customize a 4 or 8-plex panel from over 98 available markers. Ultivue has taken the optimization steps out of the process and allows rapid implementation of FixVUE and FlexVUE panels.
What are the pros and cons of the Akoya and Ultivue platforms? How do you recommend which technology to use?
The benefits of the Akoya Opal system include: 1) Ability to use antibodies of your choosing, 2) ability to start assay optimization promptly, 3) very bright signal, 4) fluors are reasonably stable, 4) and lower cost of reagents. The primary drawback of Akoya Opal chemistry is that the precipitated tyramide can decrease the ability of antibodies in future rounds to bind to the same cell. As a result, some panels are challenging to create if they have multiple markers on the same cells. Another drawback is that Opal assays can exceed 12 hours on an instrument. The Ultivue technology has the benefit of pre-optimized panels and lack of interference. This latter quality allows you to better detect overlapping analytes (e.g. CD3, CD8, PD-L1).
The drawbacks of Ultivue technology include expensive kit cost, limited off-the-shelf conjugated antibodies, delays and expense if new antibodies need to be conjugated, and that the signal is generally dimmer than the Opal technology. Also, when performing 8-plex assays, the first 4 targets are visualized on day 1 and the slide is scanned. The probes are stripped, a second set of fluorescent probes is added and the slide is re-scanned. The images must then be aligned and merged to prepare the 8-plex image. These extra steps take time, and care must be taken to QC the first image before the first-round probes are stripped off.
When evaluating the best system for a client, we typically recommend the Akoya Opal technology if a custom panel needs to be created or if we have an existing optimized panel. We recommend Ultivue if one of the pre-existing panels is perfectly suited. If FlexVue is an option, the determination is often made based on the number of overlapping markers and number of samples to be analyzed. For smaller studies, the pre-optimized Ultivue panels can lead to overall lower costs than performing a full assay development and validation, even though the reagent cost is higher. Both systems are a good fit for AI-powered data analysis.
Which validated antibody panels do you offer? Can you also develop custom assays?
We offer the Akoya Motif PD-L1 Panel (PD-L1+CD3+CD68+FoxP3+PD-1+Cytokeratin), Ultivue MDSC panel. We can rapidly deploy any of the additional Ultivue panels. In addition to this, we have numerous lab-developed tests using the Akoya Opal technology including a myeloid characterization panel (CD80+CD68+CD206+MHCII+Cytokeratin), an activated T-cell panel (GrB+Ki67+CD8+CD3+Cytokeratin), a CD8+GrB+NKp46+IFNg panel, with multiple other immuno-oncology panels in development. There is a lot of interest in customized intrinsic and adaptive immune panels. As we continue to expand our assay list, the time and cost to develop new panels decreases.
The multiplex IF images are really beautiful, but can you describe how quantitative and spatial data is generated?
Multiplex IF images are stunning. As I walked through the Novel Drug poster session at the 2022 ASCO meeting, I was drawn to the numerous mIF biomarker images. This technology is being incorporated in numerous clinical trials to immunophenotype cells, to characterize their density and determine spatial relationships. Basic analyses include characterization of cell density and percent positive for cells of each biologically relevant immunophenotype. Using either a cancer- marker (cytokeratin or Sox10) or machine learning, the tissue in a cancer biopsy can be segmented into the cancer and stromal regions and cell density is reported in both regions. We are also able to further refine cell densities in a biomarker-positive classified region (e.g. the density of cytotoxic T cells in a PD-L1-positive region). Spatial analysis can include the distance between two cell types (e.g. cytotoxic T cells and macrophages) or the distance to a tumor border.
Methods for analysis include standard image analysis using commercially available software and platforms that use machine learning and artificial intelligence (ML/AI) such as Reveal Biosciences imageDx PRISM. ML/AI does a superior job of segmenting cell nuclei, provides the ability to train on nuclear size/shapes to identify cell types, classify tissue types such as tumor vs. stroma, and classify autofluorescence. It can also generate proximity data or be used to develop predictive models when combined with multi-omic data sets or patient outcomes. The imageDx platform also provides the ability to customize or configure analytical outputs and reportables and review cellular heat maps, making it a flexible option when rich data sets are required.
How are these quantitative assays validated for clinical use?
Assay development includes two phases, optimization (for Opal assays) and validation. The Opal technology allows CellCarta to rapidly leverage the knowledge that we have gained testing and optimizing over a thousand antibodies for immunohistochemistry (IHC), including best-in-class antibody clones, antibody titers and detection methods. If we are including a new antibody, we optimize it by chromogenic IHC before proceeding with mIF optimization. We use this IHC knowledge to optimally pair antibodies with fluors, determine the proper titer of antibody, and the order of analyte detection.
We include careful evaluation of each round of assay development with special attention paid to specificity, sensitivity, signal:noise (autofluorescence), detection system cross-reactivity and fluorophore bleed-through. Once optimized, we perform “drop controls” where we use each primary antibody individually and include all the detection chemistry and Opals. This helps demonstrate the lack of cross-reactivity and fluorophore bleed through.
The validation process includes two levels: technical assay validation and algorithm validation. For technical validation, we compare cell density results for each analyte to the single-stain IHC slide from a serial section. We plot the density of these, perform a linear regression and evaluate the slope of the line and r2 value to determine how well correlate the techniques are. Algorithm and ML/AI validation is performed by selecting a small region of interest, having the cells manually enumerated (ground truth) and comparing the image analysis result to this ground truth through linear regression analysis.
In addition to these steps, we characterize the sensitivity, specificity and inter-day precision of the assay. For sensitivity analysis, we evaluate at least 20 cancer samples of the indication(s) of interest. For specificity characterization, we evaluate 32 normal tissues types from a normal tissue array. Inter-day precision is evaluated by analyzing 4 samples on 5 days and calculating the percent coefficient of variance (%CV) for each analyte. Currently, mIF assays are being used for exploratory or secondary endpoint purposes, and are not being used for inclusion testing in clinical trials.
Connect with an expert to apply multiplex IHC/IF and generate AI-powered spatial biology data.
Christopher Kerfoot, Ph.D.
Global Strategic Advisor, Histopathology at CellCarta
Co-Founder, Mosaic Laboratories
Dr. Kerfoot co-founded Mosaic Laboratories and has an established track record in oncology research, clinical testing and product development. Dr. Kerfoot has developed methods, reagents and image analysis methods for multiplex immunohistochemistry and had a leading role in multispectral imaging of chromogenic stains. Previously, Dr. Kerfoot served as Director of Product Development at US Labs, Director of Pharmaceutical Services at Oncotech, and Director of Molecular Oncology at IMPATH.
These efforts have led to patent applications, the development of many diagnostic assays as well as added value to experimental therapeutics. His broad-based expertise in assay development includes immunohistochemistry, chemosensitivity testing, in situ hybridization, flow cytometry, quantitative PCR, and other proteomic and molecular techniques. Dr. Kerfoot has published numerous peer-reviewed articles, abstracts and other publications in the areas of chemosensitivity, molecular and immunohistochemical testing. Dr. Kerfoot received his doctoral degree in Experimental Pathology in the Department of Pathology and Laboratory Medicine at UCLA. He was awarded fellowships from Leslie and Susan Gonda and The National Institute for Global Environmental Change. He received his B.S. in chemistry at the University of Illinois – Champaign/Urbana. His professional memberships include the American Association for Cancer Research and American Society of Clinical Oncology.