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Multi-Institutional Efforts to Standardize Multiplex Immunofluorescence for Spatial Biomarker Analysis

In the era of immunotherapy, it’s essential to match the right patient to the right treatment. Effective biomarkers are needed to enable patient stratification and ensure that more patients benefit from precision medicine.

While many novel techniques have been developed to aid scientists in their hunt for better immunotherapy biomarkers, spatial phenotyping has emerged as a frontrunner in this quest. A comprehensive meta-analysis published in JAMA Oncology shows that multiplex immunofluorescence (mIF)  more accurately predicts patient response to anti-PD-1/PD-L1 therapy compared to other biomarker assays, including PD-L1 IHC, tumor mutational burden (TMB), and gene expression profiling.

These results suggest that analyzing multiple markers with spatial resolution provides important information that is lacking in other approaches. The goal of immunotherapy is to activate the body’s immune system against the tumor. To accurately predict how a patient will respond to such activation, spatial context is essential to mapping the organization and interactions of immune and tumor cells in the tumor microenvironment. Through spatial phenotyping, enabled by mIF, we can now profile novel phenotypic signatures with single-cell, spatial resolution to reveal cell type, functional state, and intercellular interactions in situ.

In a seminal, first-of-its-kind approach, Johns Hopkins investigators demonstrated the predictive value of spatial phenotypic signatures in melanoma using AstroPath, a novel platform which combines the Phenoptics™ mIF workflow with sky-mapping algorithms derived from astronomy to perform deep spatial profiling of tumor sections.

But before spatial phenotypic signatures can enter the clinic and make an impact on immunotherapy outcomes, the scientific community must validate and standardize the mIF workflow that can measure this new biomarker class. Keep reading to learn about several groups currently working towards standardization, and how Phenoptics – a robust, established mIF platform – is playing a pivotal role in these efforts.

First Analytical Demonstration of a Spatial Biology Workflow Published in JITC

The Phenoptics mIF workflow was recently validated across multiple institutions in a study published in the Journal for ImmunoTherapy of Cancer (JITC). The Multi-Institutional TSA-amplified Multiplexed Immunofluorescence Reproducibility Evaluation, or MITRE study, is the result of a collaboration between six sites: The Johns Hopkins Hospital, Earle A. Chiles Research Institute, MD Anderson Cancer Center, Bristol Myers Squibb, Yale University School of Medicine, and Akoya Biosciences.

These six sites optimized and assessed the inter- and intra- site reproducibility of an automated 6-plex, 7-color assay focused on the PD-1/PD-L1 axis, measuring PD-1, PD-L1, CD8, CD68, FoxP3, Cytokeratin, and DAPI. Staining parameters for each antibody were optimized using single stain, chromogenic IHC on tonsil sections. After markers were combined into a multiplex panel, the percent positive cells for each marker demonstrated equivalence across chromogenic DAB, monoplex IF, and multiplex IF.

The panel was applied to serial sections from tonsil, breast carcinoma, and non-small cell lung cancer (NSCLC) tissue microarrays (TMAs) using the Phenoptics workflow. Staining was performed with Opal reagents on an autostainer, and tissues were imaged with the Vectra Polaris multispectral imaging platform.

MITRE TMA site comparison

Serial sections from a breast carcinoma TMA core stained at each site (The Johns Hopkins Hospital, Earle A. Chiles Research Institute, MD Anderson Cancer Center, Bristol Myers Squibb, Yale University School of Medicine, and Akoya Biosciences), showing visual consistency of automated mIF assay staining results. Source: Taube et. al, JITC / CC BY-NC.

The authors found high inter-site concordance for tumor cell and immune cell subset densities. Inter-site concordance for %PD-L1 expression by immune cells had an average R2 value of 0.88 and a slope of 0.92. PD-1/PD-L1 proximity assessments also showed strong concordance (R2 = 0.82, slope = 0.75).

site1v3 concordance

Inter-site cell density concordance plots for each marker, CD68, CD8, FOXP3, PD-1, PD-L1, and CK (tumor cells). Source: Taube et al, JITC / CC BY-NC.

mitre pd1pdl1

Left: Tissue microarray core showing proximity map overlay with PD-1+ and PD-L1+ cells represented in orange and green, respectively. Right: Inter-site comparison demonstrating reproducibility of PD-1/PD-L1 proximity assessment. Source: Taube et. al, JITC / CC BY-NC.

These findings demonstrate that multiplex IF methods are robust enough to support translation into clinical trials and eventually, clinical practice. The approach described by this study may serve as a template for assessing reproducibility of emerging multiplex IF panels for other investigative teams.

Other multi-institutional efforts to standardize mIF

Multiplex immunofluorescence is quickly becoming a mainstay in immunotherapy translational research, and there are several other multi-institutional groups making strides towards standardizing the workflow.

The Cancer Immune Monitoring and Analysis Centers-Cancer Immunologic Data Commons

Launched as part of the NIH’s Cancer Moonshot Initiative, The Cancer Immune Monitoring and Analysis Centers-Cancer Immunologic Data Commons (CIMAC-CIDC) Network is focused on advancing translational research efforts by identifying predictive biomarkers for immunotherapy. In a recent paper in Clinical Cancer Research, the group outlined the results of a multi-institutional study which sought to harmonize mIF and multiplex immunohistochemistry (mIHC) assays and informatics pipelines across sites.

Three CIMAC sites – the Icahn School of Medicine at Mt. Sinai, MD Anderson Cancer Center, and Dana-Farber Cancer institute – compared image analysis algorithms, image acquisition platforms, and multiplex staining protocols for mIHC and mIF (using the Phenoptics platform). They applied a multi-step harmonization process which integrated laboratory-specific protocols, while still producing highly concordant data across sites.

SITC Pathology Task Force

In 2019, the Society for ImmunoTherapy of Cancer (SITC) assembled the SITC Pathology Task Force, a group of pathologists and experts from academic centers and pharmaceutical and diagnostic companies, to develop best practices on the use of various multiplex IF analysis tools.

Accordingly, the group published a statement in the Journal for ImmunoTherapy of Cancer outlining their recommendations and guidelines for multiplex IF staining and validation. They recognize the growing use of multiplex IF technologies in biomarker studies and anticipate its entry into clinical practice in the near future. Their statement is an important step in bringing together the immuno-oncology community to a consensus around these technologies.

Next, the group aims to tackle considerations for quantitative image analysis and management of mIHC/mIF data. We look forward to seeing how the outcomes from this task force move the field of pathology and immuno-oncology biomarkers forward.

JEDI Council

Another task force is working towards the goal of mIF standardization, with over 30 members from around the world. We learned about this group, called the “JEDI Council” in an interview with Dr. Joe Yeong, Research Immunopathologist from Singapore General Hospital. He co-founded the task force with other leaders in the field of immunology.

In Dr. Yeong’s view, the Opal chemistry is best suited for clinical research use, because he finds the staining process similar to that of conventional IHC, which pathologists are familiar with. However, several pathology experts and publications have demonstrated that while the Phenoptics mIF workflow bears similarities to standard IHC, the quantitative nature of mIF generates more robust and reproducible readouts.

It’s clear that the spatial phenotypic signatures generated by mIF have a future in the clinic. Spatial phenotyping has the potential to identify better, more predictive biomarkers to help healthcare providers make effective treatment decisions for their patients. As more research groups work towards standardizing mIF, we get closer to making this potential a reality.

Get in touch with us to learn how the Phenoptics workflow can support your biomarker discovery and development studies.

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