Unlocking the Power of Spectral Flow: High Parameter Immunophenotypic Analysis for Preclinical and Clinical Cell Therapy Research

Author: Gunisha Arora, Medical and Scientific Writer, Scientific Development
Date: February, 2024
 

Introduction

Medical research continues to uncover ever-increasing complexity in the cellular networks that contribute to disease. Building on this information, several cell therapies have been successful in harnessing the immune cells of patients or healthy donors to fight cancer. To deliver the full potential of these life-saving therapies, drug developers and clinicians alike need to monitor and analyze diverse aspects of the immune system.
Traditional analytical methods often fail to provide the detailed insights necessary to fully profile immune responses. This lack of comprehensive data can impede the development of effective therapies and accurate prediction of patient outcomes. Consequently, there is a critical need for advanced technologies that can offer comprehensive analysis of immune cells in both preclinical and clinical phases of drug development.

Flow cytometry has long been a fundamental tool for immune cell analysis. However, conventional methods are limited by the number of fluorescent markers they can analyze simultaneously, typically around 10–12 with a max around 28, due to overlapping emission spectra causing signal interference and inaccurate data. Recent advancements have led to the emergence of spectral flow cytometry, which captures the entire emission spectrum of each fluorochrome and uses sophisticated algorithms to separate overlapping spectra enabling detection of more fluorochromes per laser line and increased panel size.

Labcorp now offers spectral flow cytometry with the Cytek® Aurora. The platform effectively addresses the problem of limited marker analysis by enabling the simultaneous detection of up to 40 markers. The spectral instrument allows for autofluorescence to be detected and resolved from other fluorescent signatures, allowing for single cell high resolution data. A capability that is essential for understanding the intricate relationship between disease and the immune response. By offering a more detailed and accurate analysis, Labcorp spectral flow cytometry capabilities can enable sponsors to identify potential therapeutic targets, monitor treatment efficacy, and predict patient outcomes to drive the development of cell therapies for varied indications including oncology (see Table 1 for panels currently offered by Labcorp).

How Does Spectral Flow Cytometry Work?

A major advancement in spectral flow cytometry is the technique of spectral unmixing, which allows for the precise separation of overlapping emission spectra from multiple fluorochromes. By capturing the full emission spectrum and using sophisticated algorithms, researchers can accurately differentiate between markers, even when their emission profiles overlap (see Figure 1). This capability significantly increases the number of parameters that can be measured simultaneously and enhances sensitivity and accuracy. Traditional flow cytometry often faces challenges with signal interference from multiple markers, leading to less reliable data. Spectral unmixing addresses this issue by providing clearer signal separation, resulting in more precise data, which is crucial for detecting subtle changes in immune cell populations in cancer research (see Figure 2). This improved sensitivity enables a comprehensive analysis of the tumor microenvironment, helping to identify therapeutic targets and develop effective treatments.1,2
 

Figure 1. On a conventional flow cytometer, pacific blue and brilliant violet 421 (BV421) cannot be used together as the spectral signatures are too similar. On a spectral cytometer, spectral unmixing allows high parameter analysis of up to 40 colors including dyes such as pacific blue and BV421. This is due to pacific blue and BV421 having enough difference (a complexity index of 0.78) in their spectral signatures to be used in combination and with clearer resolution.

Preclinical and Clinical Applications

Spectral flow cytometry is a breakthrough in the advancement of probing into single cells to obtain deeper insights into protein expression and cell characterization. In preclinical studies, such as those involving humanized mice, spectral flow cytometry analysis allows researchers to track and characterize human immune cells within tumor- bearing mouse models. This provides critical insights into how these cells interact with cancer and therapeutic agents, ensuring the efficacy and safety of new treatments before clinical trials. For cell therapy products, spectral analysis provides deep phenotypic profiles to monitor the expansion, persistence, and functional activity of therapies in vivo as they target and destroy cancer cells. In clinical trials, spectral flow enables real-time monitoring of patient immune responses to immunotherapy drugs, helping to identify biomarkers of response or resistance. This facilitates the development of personalized treatment strategies, ensuring that patients receive the most effective therapies. Overall, flow cytometry is a vital tool that supports the entire spectrum of oncology drug development, from preclinical models to clinical applications, driving the creation of innovative cancer treatments.

Labcorp Discovery Oncology has developed off-the-shelf panels for the Cytek Aurora spectral analyzer to support these applications. Included are the Spectral Human CompLymphocyte™ panel and the Spectral Human CompLeukocyte™ panel (also configured for mouse cell analysis, see Table 1 and 2). Custom panel development is available, as well as method transfer services to bring spectral panels into the lab that were developed externally by drug sponsors or other third parties.

Figure 2. Memory T cell analysis using the Spectral CompLymphocyte panel demonstrates the ability of spectral analysis to resolve key differentiation markers for immune subset identification.

Advanced analysis tools can be leverged for spectral flow cytometry data sets. t-SNE (t-Distributed Stochastic Neighbor Embedding) is an invaluable technique, especially when handling high-dimensional data. By transforming complex, multi-dimensional datasets into two or three dimensions, t-SNE simplifies visualization and interpretation. This reduction in dimensionality allows researchers to identify distinct cell clusters based on marker expression, improving the resolution of subtle differences between similar cell populations. Unlike traditional methods, t-SNE maintains the local structure of the data, making it particularly effective for detailed immune profiling. Additionally, t-SNE excels at detecting rare cell populations that might be missed by conventional analysis methods, which is essential for discovering new cell types and understanding sample heterogeneity (see Figure 3). Moreover, t-SNE services from Labcorp can integrate data from multiple experiments or samples, facilitating comprehensive comparisons across different conditions or time points.

Figure 3. t-Distributed Stochastic Neighbor Embedding (tSNE). The above analysis demonstrates unbiased interrogation of all markers in the Spectral Human CompLymphocyte panel to reveal complex phenotypic changes between unstimulated and activated PBMCs. The circled events pinpoint the emergence of phenotypically exhausted CD8+ T cells that co-express the inhibitory receptors PD-1, LAG3, TIM3, and TIGIT at high levels following activation.

Explore our poster presented at the SITC 39th annual meeting held in Houston, TX for additional details on the Spectral CompLymphocyte panel method development.

The integration of spectral flow cytometry into cancer research represents a transformative advancement, offering unparalleled precision and depth in immune cell analysis. By enabling the simultaneous detection of up to 40 markers, this technology addresses the limitations of traditional methods and provides critical insights into the complex interactions between cancer and the immune system. As a result, spectral flow cytometry is
poised to significantly enhance the development of effective cancer therapies, from preclinical studies to clinical applications, ultimately improving patient outcomes and advancing the field of oncology.

Meet the Authors

David Draper has more than 25 years of immunology and general in vitro service experience in life science research, clinical hematology, and drug discovery. At Labcorp Discovery Oncology, he leads a team that manages client-engagement efforts to support proposal design for oncology/ immunology studies to ensure the best analytical service is utilized for the needs of the drug developer.

Anita J. Zaitouna has over 15 years of experience as a scientist with broad focusses in immunology and bioanalysis. At Labcorp, Dr. Zaitouna has been a leader in the discovery oncology in vitro services space, focusing on developing assays to characterize cell and gene therapy, antibody drug conjugates, and more. Additional focus has been on development of assays that can be paired with preclinical models.

Gunisha Arora has over eight years of in vitro and in vivo research experience in preclinical oncology and more than five years in medical and scientific writing, translating complex research into clear, impactful communication. At Labcorp, she plays a key role in research outreach and marketing, working collaboratively with the Scientific Development team to promote discovery services that support drug developers in advancing innovative cancer therapies.