Ensure Consistent Flow Cytometry & Optimize Clinical Trials

September 18, 2024

As more novel therapeutics have entered the drug development pipeline in recent years, flow cytometry has become a core analytical method for characterizing cells, molecules, and biomarkers for therapy evaluation. The technique is especially effective at assessing drugs targeting the immune system, and therefore particularly valuable in the areas of autoimmunity, oncology, and infectious diseases.

However, drug developers face a key challenge when using flow cytometry in clinical research: consistency. Why is this a hurdle, and how can we overcome it?

The challenges of using flow cytometry for clinical trial analysis

Clinical trials are often global in nature, with participants located across multiple sites. While data analysis for such trials is typically centralized, the data itself is produced at many different labs by various operators and instruments. As flow cytometry readouts (mean fluorescence intensity, or MFI) can vary between instruments and sites, it’s difficult and labor-intensive to ensure that they are standardized.

Inter- and intra-site variability of MFI readouts is a major issue for drug developers. Producing standardized measurements across sites is a crucial aspect of conducting successful clinical trials, and therefore key to progressing efficiently along the drug development pipeline.

Our preferred method to help address the issue of inconsistency is to ship reagents from the same lot between sites every time an assay is shared, to provide every lab with the same initial analytical tools. But this is an inefficient and unreliable solution that falls short of facilitating truly consistent analysis, with MFI readouts still potentially differing between stainings and operators.

However, new methods are being tested to bring greater consistency to multi-site flow cytometry, with promising results.

A new way to align flow cytometry instruments from lab to lab

CellCarta recently trialed a new approach to centralizing and standardizing flow cytometry assays across five global sites

A set of CD4 antibodies was stained on polystyrene microbeads (BD™ CompBeads) in fluorescent dyes (fluorochromes) covering the 18 colors of CellCarta’s flow cytometer (a BD LSRFortessa™). These beads were then lyophilized (freeze-dried), after which they were stable at room temperature for 18 months.

The stained and lyophilized beads were then shipped to five sites simultaneously for instrument alignment. Due to the long-term stability of the beads they only had to be shipped once, rather than a new reagent needing to be shipped per round of analysis.

After an initial setup and harmonization process, the beads were used to produce and adjust target values for 12 months (with a key criterion being stability of the MFI signal). Sites were able to create a baseline from which to detect and correct instrument fluctuations and eliminate any differences when these were used for sample analysis. In total, 10+ assays were standardized across five global locations.

The precision and performance of the lyophilized beads was tested over time to assure ongoing MFI stability, with any fluorochromes that were deemed to be underperforming swapped for more stable alternatives.

Fig 1: The assay was successfully shared across all our active sites. Nine fluorescence parameters were aligned using lyophilized BD™ CompBeads, before the assay’s precision was further tested by comparing 14 inter- and intra-site readouts of a reference sample and three healthy donors. To be deemed acceptable, the assays needed at least 80% of the predetermined readouts to have less than 25% CV when comparing reference and receiving laboratories.

The results? More reliable, consistent flow cytometry data across sites

The approach proved robust and reliable for multi-site instrument alignment, harmonizing numerous flow cytometric assays across sites (see Figure 1). Overall, the new approach demonstrated:

  • Long-term stability and precision, with comparable performance after one year and across fluorochromes (with all dyes remaining stable for 8 hours and most remaining stable for up to 48 hours post-resuspension)
  • Less variability in MFIs, by standardizing the analysis process and reducing any fluctuations arising from operator, instrument, or site differences. Using the transferred assays, 80%+ of readouts showed a coefficient of variation (CV) of less than 30% when comparing reference and receiving laboratories
  • Reliable assay transfer and alignment, with more than 10 flow cytometric assays successfully shared and implemented across 5 global site
  •  Time and cost savings, with reduced shipping and logistics requirements due to the 18-month stability of the lyophilized beads

While achieving reliable, standardized, high-quality flow cytometry data across lab locations can be challenging, this approach demonstrates a potential way to generate consistent data independent of location, instrument, and operator. Such a method could offer peace of mind to drug developers by supporting global clinical trials that require cost-efficient analysis and highly comparable data across geographical sites.

For more details on the alignment project, including its full aims, method, and results, see our research poster Multi-Site Instrument Alignment Using Lyophilized BD™ CompBeads.

 

About the author

author photo

Dominic Gagnon M.Sc. SCYM (ASCP)CM is the global flow cytometry Associate director at CellCarta. With a twenty years background in immune monitoring by flow cytometry as well as managing flow core, Dominic guides the team in the harmonization and standardization of cytometers and assays across all sites.

References

[1] Gagnon, D., and Lo, K. (2024) Multi-Site Instrument Alignment Using Lyophilized BDTM CompBeads. Available at: https://cellcarta.com/science-hub/multi-site-flow-compbeads.

Ensure Consistent Flow Cytometry & Optimize Clinical Trials

September 18, 2024

As more novel therapeutics have entered the drug development pipeline in recent years, flow cytometry has become a core analytical method for characterizing cells, molecules, and biomarkers for therapy evaluation. The technique is especially effective at assessing drugs targeting the immune system, and therefore particularly valuable in the areas of autoimmunity, oncology, and infectious diseases.

However, drug developers face a key challenge when using flow cytometry in clinical research: consistency. Why is this a hurdle, and how can we overcome it?

The challenges of using flow cytometry for clinical trial analysis

Clinical trials are often global in nature, with participants located across multiple sites. While data analysis for such trials is typically centralized, the data itself is produced at many different labs by various operators and instruments. As flow cytometry readouts (mean fluorescence intensity, or MFI) can vary between instruments and sites, it’s difficult and labor-intensive to ensure that they are standardized.

Inter- and intra-site variability of MFI readouts is a major issue for drug developers. Producing standardized measurements across sites is a crucial aspect of conducting successful clinical trials, and therefore key to progressing efficiently along the drug development pipeline.

Our preferred method to help address the issue of inconsistency is to ship reagents from the same lot between sites every time an assay is shared, to provide every lab with the same initial analytical tools. But this is an inefficient and unreliable solution that falls short of facilitating truly consistent analysis, with MFI readouts still potentially differing between stainings and operators.

However, new methods are being tested to bring greater consistency to multi-site flow cytometry, with promising results.

A new way to align flow cytometry instruments from lab to lab

CellCarta recently trialed a new approach to centralizing and standardizing flow cytometry assays across five global sites

A set of CD4 antibodies was stained on polystyrene microbeads (BD™ CompBeads) in fluorescent dyes (fluorochromes) covering the 18 colors of CellCarta’s flow cytometer (a BD LSRFortessa™). These beads were then lyophilized (freeze-dried), after which they were stable at room temperature for 18 months.

The stained and lyophilized beads were then shipped to five sites simultaneously for instrument alignment. Due to the long-term stability of the beads they only had to be shipped once, rather than a new reagent needing to be shipped per round of analysis.

After an initial setup and harmonization process, the beads were used to produce and adjust target values for 12 months (with a key criterion being stability of the MFI signal). Sites were able to create a baseline from which to detect and correct instrument fluctuations and eliminate any differences when these were used for sample analysis. In total, 10+ assays were standardized across five global locations.

The precision and performance of the lyophilized beads was tested over time to assure ongoing MFI stability, with any fluorochromes that were deemed to be underperforming swapped for more stable alternatives.

Fig 1: The assay was successfully shared across all our active sites. Nine fluorescence parameters were aligned using lyophilized BD™ CompBeads, before the assay’s precision was further tested by comparing 14 inter- and intra-site readouts of a reference sample and three healthy donors. To be deemed acceptable, the assays needed at least 80% of the predetermined readouts to have less than 25% CV when comparing reference and receiving laboratories.

The results? More reliable, consistent flow cytometry data across sites

The approach proved robust and reliable for multi-site instrument alignment, harmonizing numerous flow cytometric assays across sites (see Figure 1). Overall, the new approach demonstrated:

  • Long-term stability and precision, with comparable performance after one year and across fluorochromes (with all dyes remaining stable for 8 hours and most remaining stable for up to 48 hours post-resuspension)
  • Less variability in MFIs, by standardizing the analysis process and reducing any fluctuations arising from operator, instrument, or site differences. Using the transferred assays, 80%+ of readouts showed a coefficient of variation (CV) of less than 30% when comparing reference and receiving laboratories
  • Reliable assay transfer and alignment, with more than 10 flow cytometric assays successfully shared and implemented across 5 global site
  •  Time and cost savings, with reduced shipping and logistics requirements due to the 18-month stability of the lyophilized beads

While achieving reliable, standardized, high-quality flow cytometry data across lab locations can be challenging, this approach demonstrates a potential way to generate consistent data independent of location, instrument, and operator. Such a method could offer peace of mind to drug developers by supporting global clinical trials that require cost-efficient analysis and highly comparable data across geographical sites.

For more details on the alignment project, including its full aims, method, and results, see our research poster Multi-Site Instrument Alignment Using Lyophilized BD™ CompBeads.

 

About the author

author photo

Dominic Gagnon M.Sc. SCYM (ASCP)CM is the global flow cytometry Associate director at CellCarta. With a twenty years background in immune monitoring by flow cytometry as well as managing flow core, Dominic guides the team in the harmonization and standardization of cytometers and assays across all sites.

References

[1] Gagnon, D., and Lo, K. (2024) Multi-Site Instrument Alignment Using Lyophilized BDTM CompBeads. Available at: https://cellcarta.com/science-hub/multi-site-flow-compbeads.

Drug Target Engagement with Flow Cytometry Receptor Occupancy Assays

September 17, 2024

Damien Montamat-Sicotte, Scientific Business Director

Receptor Occupancy Assays by Flow Cytometry

A crucial step in the drug development process involves optimizing drug-target engagement for your biotherapeutic and gaining valuable pharmacodynamic biomarker data. High-quality receptor occupancy assays (RO assays) are vital tools in this process.

Reliable and accurate results in the design, development, and implementation of receptor occupancy assays can seem to be a tasking prospect, as they are prone to numerous technical and logistical challenges, requiring-

  • expert assay design
  • optimal matrix selection
  • data normalization/reporting
  • and rigorous quality control1, 2

Such challenges can escalate further in difficult development scenarios, such as when the target antigen is expressed at low levels, where there is receptor modulation, or when the therapeutic molecules are bi-specific and bind multiple targets2.

Types and Methodologies

RO assays can be classified into two main types: competitive assays and saturation assays. Competitive assays involve the use of competitive and non-competitive antibodies to the drug, to note that the competitive antibody can also be substituted by an anti-drug antibody. Saturation assays use a competitive antibody and the drug product itself detected by an antibody as a reference point.

Type of Assay Description
Competing vs. non-competing antibodies Competing and non-competing antibodies are added to a sample. Competing antibodies bind to the drug's target site, indicating unbound targets. Non-competing antibodies bind elsewhere on the target, showing total available targets. Alternatively, the competing antibody can be substituted for a anti-drug antibody
Saturation assay Half of the sample is saturated with the drug, mimicking 100% RO, showing the total number of available target sites. The other half remains unsaturated, reflecting drug binding in the patient.
A secondary antibody detects the drug, this can be done using an anti-drug or an anti-Ig antibody, and the ratio of unsaturated to saturated samples reveals the drug's receptor occupancy (RO) level.

Custom RO Strategies for Enhanced Drug Development

CellCarta’s flow-cytometry-based receptor occupancy (RO) assays are designed to overcome these challenges and accelerate your efforts, providing you with the critical information needed to demonstrate target engagement, and gain insight into what degree and how long your biotherapeutic binds its target.

Our RO assays can also be used to complement your pharmacokinetic profiling to provide valuable information on dose selection and frequency of drug infusion. Additionally, RO assays can be validated to support secondary endpoints.

One of our RO strategies starts with the identification of both a competitive and a non-competitive antibody. The competitive antibody will only bind to its target if it is not currently bound by the drug, allowing identification of free receptors, while the non-competitive antibody identifies the total amount of target receptors.

We monitor receptor occupancy only in cell populations of interest by combining target-specific reagents into a flow cytometry panel of phenotypic markers. Competitive and non-competitive antibodies can even be used in the same panel.

When competitive or non-competitive antibodies cannot be identified, or when antibodies to the receptor are not available, we use a saturating vs. non-saturating approach to determine the receptor occupancy or RO.

The strategy involves saturation of half of the sample, mimicking a 100% RO. The other half is not saturated, allowing us to perform a ratio of drug-binding between the two halves to accurately determine the receptor occupancy of the sample.

Pharmacokinetic and Pharmacodynamic Insights

RO assays are integrated with pharmacokinetic (PK) and pharmacodynamic (PD) models to inform dosing strategies and optimize drug efficacy. These assays help determine the relationship between drug concentration and its biological effect, providing critical data for dose selection and frequency of administration. This integration is particularly valuable in clinical trials, where RO assays can serve as pharmacodynamic biomarker measurements to assess drug efficacy.

Choosing the ideal sample matrix for accurate RO Assays

The choice of sample matrix can have a profound effect on the quality of a RO assay. For example, PBMC processing can negatively impact the binding of the drug, resulting in an underestimation of the RO. We also typically test different vacutainers to maximize the stability and precision of the RO measurement.

Our experienced scientists develop and validate different RO strategies to address a variety of drug types and reagent availabilities, drawing on our extensive experience in deploying RO assay strategies in clinical trials.

Challenges and Considerations

Despite their importance, RO assays present several challenges. The development and optimization of these assays are complex and demand high-quality reagents and rigorous controls. Additionally, interpreting the data can be complicated by factors such as receptor internalization and degradation, necessitating a thorough understanding of the underlying biological processes.

Emerging Trends and Technological Breakthroughs in Receptor Occupancy Assays

Advanced technologies and methodologies are continually enhancing the accuracy and reliability of RO assays. Complex RO assays can provide additional insights into receptor internalization and shedding, contributing to a more comprehensive understanding of drug-target interactions. These advancements hold the potential to revolutionize drug development by providing more precise and detailed pharmacodynamic data.

CellCarta exemplifies these advancements with state-of-the-art flow cytometry and custom panels that ensure precise measurements, even in complex scenarios. This accuracy is crucial for informing dose selection and optimizing therapeutic efficacy. Emerging technologies like single-cell RNA sequencing and high-dimensional flow cytometry promise even deeper insights into drug-receptor interactions.

Step Up to the Next Level in Your RO Assay Development and Validation

Enhance the robustness of your RO assay development with our custom-designed panels and expert guidance, ensuring accurate and reliable data that drives informed decision-making in your drug development process.

Expert Insights: Watch the following video from our expert to mastering receptor occupancy assays with Flow Cytometry

 

 

About the author:

author photo

Damien Montamat-Sicotte is a Scientific Business Director at CellCarta, specializing in the flow cytometry platform. With a PhD in immunology and post-doctoral expertise from various institutions, Damien has profuse experience in managing the processing and analysis of clinical samples by flow cytometry in an immune monitoring context.

References

  1. Liang M, Schwickart M, Schneider AK, et al. Receptor occupancy assessment by flow cytometry as a pharmacodynamic biomarker in biopharmaceutical development. Cytometry B Clin Cytom 2016;90:117-27.
  2. Hilt E, Sun YS, McCloskey TW, et al. Best practices for optimization and validation of flow cytometry-based receptor occupancy assays. Cytometry B Clin Cytom 2021;100:63-71.

Drug Target Engagement with Flow Cytometry Receptor Occupancy Assays

September 17, 2024

Damien Montamat-Sicotte, Scientific Business Director

Receptor Occupancy Assays by Flow Cytometry

A crucial step in the drug development process involves optimizing drug-target engagement for your biotherapeutic and gaining valuable pharmacodynamic biomarker data. High-quality receptor occupancy assays (RO assays) are vital tools in this process.

Reliable and accurate results in the design, development, and implementation of receptor occupancy assays can seem to be a tasking prospect, as they are prone to numerous technical and logistical challenges, requiring-

  • expert assay design
  • optimal matrix selection
  • data normalization/reporting
  • and rigorous quality control1, 2

Such challenges can escalate further in difficult development scenarios, such as when the target antigen is expressed at low levels, where there is receptor modulation, or when the therapeutic molecules are bi-specific and bind multiple targets2.

Types and Methodologies

RO assays can be classified into two main types: competitive assays and saturation assays. Competitive assays involve the use of competitive and non-competitive antibodies to the drug, to note that the competitive antibody can also be substituted by an anti-drug antibody. Saturation assays use a competitive antibody and the drug product itself detected by an antibody as a reference point.

Type of Assay Description
Competing vs. non-competing antibodies Competing and non-competing antibodies are added to a sample. Competing antibodies bind to the drug's target site, indicating unbound targets. Non-competing antibodies bind elsewhere on the target, showing total available targets. Alternatively, the competing antibody can be substituted for a anti-drug antibody
Saturation assay Half of the sample is saturated with the drug, mimicking 100% RO, showing the total number of available target sites. The other half remains unsaturated, reflecting drug binding in the patient.
A secondary antibody detects the drug, this can be done using an anti-drug or an anti-Ig antibody, and the ratio of unsaturated to saturated samples reveals the drug's receptor occupancy (RO) level.

Custom RO Strategies for Enhanced Drug Development

CellCarta’s flow-cytometry-based receptor occupancy (RO) assays are designed to overcome these challenges and accelerate your efforts, providing you with the critical information needed to demonstrate target engagement, and gain insight into what degree and how long your biotherapeutic binds its target.

Our RO assays can also be used to complement your pharmacokinetic profiling to provide valuable information on dose selection and frequency of drug infusion. Additionally, RO assays can be validated to support secondary endpoints.

One of our RO strategies starts with the identification of both a competitive and a non-competitive antibody. The competitive antibody will only bind to its target if it is not currently bound by the drug, allowing identification of free receptors, while the non-competitive antibody identifies the total amount of target receptors.

We monitor receptor occupancy only in cell populations of interest by combining target-specific reagents into a flow cytometry panel of phenotypic markers. Competitive and non-competitive antibodies can even be used in the same panel.

When competitive or non-competitive antibodies cannot be identified, or when antibodies to the receptor are not available, we use a saturating vs. non-saturating approach to determine the receptor occupancy or RO.

The strategy involves saturation of half of the sample, mimicking a 100% RO. The other half is not saturated, allowing us to perform a ratio of drug-binding between the two halves to accurately determine the receptor occupancy of the sample.

Pharmacokinetic and Pharmacodynamic Insights

RO assays are integrated with pharmacokinetic (PK) and pharmacodynamic (PD) models to inform dosing strategies and optimize drug efficacy. These assays help determine the relationship between drug concentration and its biological effect, providing critical data for dose selection and frequency of administration. This integration is particularly valuable in clinical trials, where RO assays can serve as pharmacodynamic biomarker measurements to assess drug efficacy.

Choosing the ideal sample matrix for accurate RO Assays

The choice of sample matrix can have a profound effect on the quality of a RO assay. For example, PBMC processing can negatively impact the binding of the drug, resulting in an underestimation of the RO. We also typically test different vacutainers to maximize the stability and precision of the RO measurement.

Our experienced scientists develop and validate different RO strategies to address a variety of drug types and reagent availabilities, drawing on our extensive experience in deploying RO assay strategies in clinical trials.

Challenges and Considerations

Despite their importance, RO assays present several challenges. The development and optimization of these assays are complex and demand high-quality reagents and rigorous controls. Additionally, interpreting the data can be complicated by factors such as receptor internalization and degradation, necessitating a thorough understanding of the underlying biological processes.

Emerging Trends and Technological Breakthroughs in Receptor Occupancy Assays

Advanced technologies and methodologies are continually enhancing the accuracy and reliability of RO assays. Complex RO assays can provide additional insights into receptor internalization and shedding, contributing to a more comprehensive understanding of drug-target interactions. These advancements hold the potential to revolutionize drug development by providing more precise and detailed pharmacodynamic data.

CellCarta exemplifies these advancements with state-of-the-art flow cytometry and custom panels that ensure precise measurements, even in complex scenarios. This accuracy is crucial for informing dose selection and optimizing therapeutic efficacy. Emerging technologies like single-cell RNA sequencing and high-dimensional flow cytometry promise even deeper insights into drug-receptor interactions.

Step Up to the Next Level in Your RO Assay Development and Validation

Enhance the robustness of your RO assay development with our custom-designed panels and expert guidance, ensuring accurate and reliable data that drives informed decision-making in your drug development process.

Expert Insights: Watch the following video from our expert to mastering receptor occupancy assays with Flow Cytometry

 

 

About the author:

author photo

Damien Montamat-Sicotte is a Scientific Business Director at CellCarta, specializing in the flow cytometry platform. With a PhD in immunology and post-doctoral expertise from various institutions, Damien has profuse experience in managing the processing and analysis of clinical samples by flow cytometry in an immune monitoring context.

References

  1. Liang M, Schwickart M, Schneider AK, et al. Receptor occupancy assessment by flow cytometry as a pharmacodynamic biomarker in biopharmaceutical development. Cytometry B Clin Cytom 2016;90:117-27.
  2. Hilt E, Sun YS, McCloskey TW, et al. Best practices for optimization and validation of flow cytometry-based receptor occupancy assays. Cytometry B Clin Cytom 2021;100:63-71.

Cell Doublets in Flow Cytometry Data | Benefits & Challenges CellCarta

August 15, 2024

Author: Roxanne Collin, PhD

doublets in flow cytometry

Flow cytometry (including cell sorting) provides unprecedented levels of detail about blood samples for both research and clinical applications, allowing for instance the unraveling of phenotypic heterogeneity of human immune cells.

However, research from the Burel group , La Jolla Institute for Immunology, highlighted that blood-derived cell doublets can be present in single-cell data derived from flow cytometry analyses.

Doublet exclusion methods, commonly based on Forward Scatter (FSC)/Side Scatter (SSC) Area/Width/Height measurements, can partly remove cell doublets, but some complexes remain undetected, leading to data misinterpretation.

While cell doublets often need removing, interestingly, Burel reported that some doublets form naturally — which could provide greater disease understanding.

Here we look at what cell doublets are, their risk and promise, and how analysts can ensure accurate results.

Seeing Double: Identifying Cell Doublets in Flow Cytometry

While dual lineage co-expressing cell populations (also called dual expressor cells) exist in human peripheral blood samples analysed by flow cytometry, Burel’s team recently unveiled through imaging that some of these events are actually cell-cell complexes.

In the live singlet gate of blood-derived samples, T cells can still be bound to other immune cells, such as antigen-presenting cells (APC), de facto forming a cell doublet. But without deeper analysis, it can be easy to analyze cell doublets as single cells.

In cell sorting applications, the cell doublets can subsequently generate atypical gene signatures of mixed cell lineage, meaning that data misinterpretation can occur, including:

  • Specific cell population percentage deflation,
  • Novel immune cell type misidentification, and
  • Incorrect functional marker expression attribution.

Distinguishing cell-cell complexes for more accurate Flow Cytometry results

Experimental and data analysis strategies can distinguish between singlets and cell doublets for more accurate data.

To detect the presence of cell-cell complexes within potential dual-expressing cells, Burel’s team used two different approaches:

  • Cell sorting followed by direct microscopy imaging to confirm the expression of markers on distinct cells
  • Imaging flow cytometry to generate metrics from pictures of the detected events, enabling doublet exclusion using brightfield area and aspect ratio parameter calculation.

Notably, Burel’s team found that cell-cell complexes have molecular signatures that clearly distinguish them from singlets at both protein and mRNA levels, providing analysts with a way to avoid data misinterpretation.

When looking at cell–cell complex signatures with SSC/FSC and SSC/CD45, the team discovered that the complexes had higher levels of CD45, SSC, and FSC expression compared to single cells.

Importantly, cell doublets aren’t always just contaminants. The team found that T cell-APC complexes that form in vivo as a natural immunological process can be detected in the singlet gate of ex vivo human blood samples analyzed by flow cytometry, in quantities that vary over time depending on the disease state.

As such, it is therefore believed that they could provide deeper insights into research and diagnosis.

Integration of Techniques from Doublet Discrimination and Exclusion: Techniques and Detailed Process

Practical Applications of Doublet Discrimination in Flow Cytometry Analyses

Proper doublet discrimination ensures increased data accuracy and enhanced data quality. Therefore, proper singlet gating strategies in flow cytometry analyses are essential for ensuring that only single-cell events are analyzed, leading to more reliable and reproducible results.

There are essentially two main techniques for identifying and gating singlet events in flow cytometry data:

  •  Pulse Processing: incorporating Area, Height and Width bi-variate plots for FSC and SSC parameters in the hierarchical gating strategy can help identify and exclude doublets based in their distinct scatter profiles.
  •  Autofluorescence extraction: in full-spectrum cytometry, a technology that captures the entire fluorescence spectrum emitted by each fluorochrome, the autofluorescence of the sample (natural emission of light by biological structures) can be extracted as well and used to discriminate doublets. This is particularly useful for analyzing tissues or cells with high levels of autofluorescence, such as lung tissues or certain cell types in immunology and oncology research.

Singlet vs. Doublet Flow Cytometry Analysis

Understanding the differences between singlets and doublets is crucial for precise flow cytometry analysis. The following table highlights key distinctions:

Feature Singlet Flow Cytometry Doublet Flow Cytometry
Cell Type Single cells Doublet cells
Identification Method Linear relationship in FSC and SSC pulse dimensions (Area, Height, Width) Deviations from linear relationship
Data Accuracy High Can lead to data misinterpretation
Analysis Focus Individual cell analysis Potentially confounded by cell aggregates
Impact on Results Accurate cell population quantification Potentially confounded by cell aggregates

Leverage expertise for maximum data confidence in Flow Cytometry

Addressing the issue of cell doublets in flow cytometry is essential for maintaining data accuracy and quality.

By employing effective doublet discrimination and singlet gating techniques, researchers can ensure that their flow cytometry data reflects true single-cell events. This leads to more reliable and reproducible results, ultimately advancing our understanding of complex biological systems.

Our analytical team has the expertise to tailor gating strategies based on the presence of cell-cell complex doublets. CellCarta offers a broad range of advanced services using robust techniques to get greater insights from your studies. Contact the team to learn more.

 

About the author:

author photo

Roxanne Collin is a Research Scientist within the Development group of the Data Analysis Unit at CellCarta. She holds a PhD in immunology with a focus on the immunogenetics of rare cell populations. At CellCarta, she is participating in the optimisation of flow cytometry panels and gating strategies for a broad variety of immune cell types.

Cell Doublets in Flow Cytometry Data | Benefits & Challenges CellCarta

August 15, 2024

Author: Roxanne Collin, PhD

doublets in flow cytometry

Flow cytometry (including cell sorting) provides unprecedented levels of detail about blood samples for both research and clinical applications, allowing for instance the unraveling of phenotypic heterogeneity of human immune cells.

However, research from the Burel group , La Jolla Institute for Immunology, highlighted that blood-derived cell doublets can be present in single-cell data derived from flow cytometry analyses.

Doublet exclusion methods, commonly based on Forward Scatter (FSC)/Side Scatter (SSC) Area/Width/Height measurements, can partly remove cell doublets, but some complexes remain undetected, leading to data misinterpretation.

While cell doublets often need removing, interestingly, Burel reported that some doublets form naturally — which could provide greater disease understanding.

Here we look at what cell doublets are, their risk and promise, and how analysts can ensure accurate results.

Seeing Double: Identifying Cell Doublets in Flow Cytometry

While dual lineage co-expressing cell populations (also called dual expressor cells) exist in human peripheral blood samples analysed by flow cytometry, Burel’s team recently unveiled through imaging that some of these events are actually cell-cell complexes.

In the live singlet gate of blood-derived samples, T cells can still be bound to other immune cells, such as antigen-presenting cells (APC), de facto forming a cell doublet. But without deeper analysis, it can be easy to analyze cell doublets as single cells.

In cell sorting applications, the cell doublets can subsequently generate atypical gene signatures of mixed cell lineage, meaning that data misinterpretation can occur, including:

  • Specific cell population percentage deflation,
  • Novel immune cell type misidentification, and
  • Incorrect functional marker expression attribution.

Distinguishing cell-cell complexes for more accurate Flow Cytometry results

Experimental and data analysis strategies can distinguish between singlets and cell doublets for more accurate data.

To detect the presence of cell-cell complexes within potential dual-expressing cells, Burel’s team used two different approaches:

  • Cell sorting followed by direct microscopy imaging to confirm the expression of markers on distinct cells
  • Imaging flow cytometry to generate metrics from pictures of the detected events, enabling doublet exclusion using brightfield area and aspect ratio parameter calculation.

Notably, Burel’s team found that cell-cell complexes have molecular signatures that clearly distinguish them from singlets at both protein and mRNA levels, providing analysts with a way to avoid data misinterpretation.

When looking at cell–cell complex signatures with SSC/FSC and SSC/CD45, the team discovered that the complexes had higher levels of CD45, SSC, and FSC expression compared to single cells.

Importantly, cell doublets aren’t always just contaminants. The team found that T cell-APC complexes that form in vivo as a natural immunological process can be detected in the singlet gate of ex vivo human blood samples analyzed by flow cytometry, in quantities that vary over time depending on the disease state.

As such, it is therefore believed that they could provide deeper insights into research and diagnosis.

Integration of Techniques from Doublet Discrimination and Exclusion: Techniques and Detailed Process

Practical Applications of Doublet Discrimination in Flow Cytometry Analyses

Proper doublet discrimination ensures increased data accuracy and enhanced data quality. Therefore, proper singlet gating strategies in flow cytometry analyses are essential for ensuring that only single-cell events are analyzed, leading to more reliable and reproducible results.

There are essentially two main techniques for identifying and gating singlet events in flow cytometry data:

  •  Pulse Processing: incorporating Area, Height and Width bi-variate plots for FSC and SSC parameters in the hierarchical gating strategy can help identify and exclude doublets based in their distinct scatter profiles.
  •  Autofluorescence extraction: in full-spectrum cytometry, a technology that captures the entire fluorescence spectrum emitted by each fluorochrome, the autofluorescence of the sample (natural emission of light by biological structures) can be extracted as well and used to discriminate doublets. This is particularly useful for analyzing tissues or cells with high levels of autofluorescence, such as lung tissues or certain cell types in immunology and oncology research.

Singlet vs. Doublet Flow Cytometry Analysis

Understanding the differences between singlets and doublets is crucial for precise flow cytometry analysis. The following table highlights key distinctions:

Feature Singlet Flow Cytometry Doublet Flow Cytometry
Cell Type Single cells Doublet cells
Identification Method Linear relationship in FSC and SSC pulse dimensions (Area, Height, Width) Deviations from linear relationship
Data Accuracy High Can lead to data misinterpretation
Analysis Focus Individual cell analysis Potentially confounded by cell aggregates
Impact on Results Accurate cell population quantification Potentially confounded by cell aggregates

Leverage expertise for maximum data confidence in Flow Cytometry

Addressing the issue of cell doublets in flow cytometry is essential for maintaining data accuracy and quality.

By employing effective doublet discrimination and singlet gating techniques, researchers can ensure that their flow cytometry data reflects true single-cell events. This leads to more reliable and reproducible results, ultimately advancing our understanding of complex biological systems.

Our analytical team has the expertise to tailor gating strategies based on the presence of cell-cell complex doublets. CellCarta offers a broad range of advanced services using robust techniques to get greater insights from your studies. Contact the team to learn more.

 

About the author:

author photo

Roxanne Collin is a Research Scientist within the Development group of the Data Analysis Unit at CellCarta. She holds a PhD in immunology with a focus on the immunogenetics of rare cell populations. At CellCarta, she is participating in the optimisation of flow cytometry panels and gating strategies for a broad variety of immune cell types.

How cell therapy developers are future-proofing clinical monitoring of B-cell aplasia

July 11, 2024

Liesbet Vervoort, PhD

As cell therapies become more complex, the pressures facing clinical developers are rising. A greater number and diversity of cell therapy products are progressing to clinical stages, all requiring comprehensive, accurate, and yet rapid characterization to ensure that the journey from bench to bedside is as fast, safe, and effective as possible.

To accommodate this ever-growing number of new cell therapy concepts, clinical developers need robust, adaptive, affordable testing strategies for extensive yet efficient characterization. To realize these, developers are turning to complementary methods and modularized testing, and working to identify the most high-value readouts. Taking such an approach allows developers to assess aspects such as B-cell aplasia, even as the parameters monitored in B-cell populations expand as cell therapies address new indications.

Our new Cell Therapy Trend Report reveals how clinical testing is adapting to the rapidly changing cell therapy landscape. Download the report now to learn more and explore several broad trends to be aware of within the space, spanning the testing areas of HLA typing, cytokine profiling, cell enumeration and vector copy number determination, single-cell analytics, and B-cell aplasia.

Bringing complementary testing to B-cell aplasia

We anticipate that B-cell monitoring will soon become a standard part of clinical testing programs for new cell therapies and indications. Because of this, identifying the most efficient, effective, and appropriate monitoring approaches is of undeniable value.

Complementarity in particular offers huge promise here. By leveraging the synergies and capabilities of different established testing methods, developers can evaluate B-cell therapies more comprehensively to paint a detailed picture of how cell therapies act against B-cells. Such an approach could help to identify differences in body tissues, discriminate between on- and off-tumor activity, and shed light on off-tumor effects (such as the depletion of healthy B cells).

Additionally, as cell therapies increasingly address new indications and therapeutic areas — including autoimmune diseases and solid tumors — complementary assays can adapt to address a wider array of parameters, creating exciting new opportunities for in-depth analysis. Developers will also be able to mine the knowledge gleaned from previous testing to inform the design of new adaptive assays, enhance their clinical testing, and improve specificity.

B-cell aplasia: Understanding its role in cell therapy clinical testing

As well as improving our understanding of how cell therapies act against B cells, the fast, unambiguous enumeration of B cell populations and their depletion can…

  • Inform study inclusion
  • Help reveal the mechanisms behind autoreactivity
  • Support the development of new therapies
  • Potentially serve complementary purposes in the assessment of therapeutic efficacy and disease progression

Complementarity and other approaches to optimize and future-proof the clinical characterization of novel cell therapies, are discussed in our Cell Therapy Trend Report. Download the report now, or contact our team to speak to an expert about your cell therapy clinical testing needs.

 

About the author

author photo

Liesbet Vervoort is a Group Lead Program Management at CellCarta. With a PhD in immune-oncology and expertise as an operational lab lead and hematopathology program lead, Liesbet has profuse experience in aligning and translating customers’ needs to clinical trial implementation.

How cell therapy developers are future-proofing clinical monitoring of B-cell aplasia

July 11, 2024

Liesbet Vervoort, PhD

As cell therapies become more complex, the pressures facing clinical developers are rising. A greater number and diversity of cell therapy products are progressing to clinical stages, all requiring comprehensive, accurate, and yet rapid characterization to ensure that the journey from bench to bedside is as fast, safe, and effective as possible.

To accommodate this ever-growing number of new cell therapy concepts, clinical developers need robust, adaptive, affordable testing strategies for extensive yet efficient characterization. To realize these, developers are turning to complementary methods and modularized testing, and working to identify the most high-value readouts. Taking such an approach allows developers to assess aspects such as B-cell aplasia, even as the parameters monitored in B-cell populations expand as cell therapies address new indications.

Our new Cell Therapy Trend Report reveals how clinical testing is adapting to the rapidly changing cell therapy landscape. Download the report now to learn more and explore several broad trends to be aware of within the space, spanning the testing areas of HLA typing, cytokine profiling, cell enumeration and vector copy number determination, single-cell analytics, and B-cell aplasia.

Bringing complementary testing to B-cell aplasia

We anticipate that B-cell monitoring will soon become a standard part of clinical testing programs for new cell therapies and indications. Because of this, identifying the most efficient, effective, and appropriate monitoring approaches is of undeniable value.

Complementarity in particular offers huge promise here. By leveraging the synergies and capabilities of different established testing methods, developers can evaluate B-cell therapies more comprehensively to paint a detailed picture of how cell therapies act against B-cells. Such an approach could help to identify differences in body tissues, discriminate between on- and off-tumor activity, and shed light on off-tumor effects (such as the depletion of healthy B cells).

Additionally, as cell therapies increasingly address new indications and therapeutic areas — including autoimmune diseases and solid tumors — complementary assays can adapt to address a wider array of parameters, creating exciting new opportunities for in-depth analysis. Developers will also be able to mine the knowledge gleaned from previous testing to inform the design of new adaptive assays, enhance their clinical testing, and improve specificity.

B-cell aplasia: Understanding its role in cell therapy clinical testing

As well as improving our understanding of how cell therapies act against B cells, the fast, unambiguous enumeration of B cell populations and their depletion can…

  • Inform study inclusion
  • Help reveal the mechanisms behind autoreactivity
  • Support the development of new therapies
  • Potentially serve complementary purposes in the assessment of therapeutic efficacy and disease progression

Complementarity and other approaches to optimize and future-proof the clinical characterization of novel cell therapies, are discussed in our Cell Therapy Trend Report. Download the report now, or contact our team to speak to an expert about your cell therapy clinical testing needs.

 

About the author

author photo

Liesbet Vervoort is a Group Lead Program Management at CellCarta. With a PhD in immune-oncology and expertise as an operational lab lead and hematopathology program lead, Liesbet has profuse experience in aligning and translating customers’ needs to clinical trial implementation.

Spectral Flow and Mass Cytometry: Select the Right Platform

July 2, 2024

Damien Montamat-Sicotte

Spectral-Flow-and-Mass-Cytometry

Choosing the right cytometry platform is crucial for optimizing your clinical study. Both mass cytometry (CyTOF) and spectral flow cytometry are widely used technologies for clinical single-cell analysis.

These platforms provide the ability to build panels of a size that go beyond conventional flow cytometry, allowing a stronger multi-parametric approach to data generation. However, selecting the appropriate technology is key to unlocking the complexities of clinical development.

This blog post compares the two platforms to help you make an informed decision for your clinical immune monitoring.

Sample matrix considerations for both spectral flow and mass cytometry

Both mass and spectral flow cytometry platforms can handle various sample types, including peripheral blood mononuclear cells (PBMCs), fresh whole blood, gently fixed samples, or frozen specimens that have undergone an initial fixation step.

When analyzing fixed frozen samples, it is important to fix the specimen soon after drawing the blood; ideally within two hours. Due to the unstable nature of granulocytes, they tend to degranulate and clump up if the specimen is not fixed and frozen in a timely manner.

Another important consideration is the amount of time the specimen is exposed to fixative prior to freezing. Over fixing the cells can lead to deleterious epitope alteration and incomplete hemolysis upon thawing. Failure to take these points into consideration could compromise data quality.

For PBMCs or fresh whole blood, the performance of both technologies is comparable. For these matrices, quality of samples, careful clone selection and fluorophores or heavy metal combination are the crucial elements to consider.

The choice between mass and spectral flow cytometry may also depend on the availability of cells.

Mass cytometry typically requires a higher cell input for samples (2-3 fold higher), which becomes crucial when working with low-yield samples like tumour-infiltrating lymphocytes (TILs) or cells taken from biopsies, as approximately 15-25% of cells are lost during acquisition.

In scenarios with limited cell availability, spectral flow cytometry is the preferred option to maximise the number of events analysed and generate quality data.

Markers, colours, and panel complexity are central to your platform choice

Both mass and spectral flow cytometry platforms can handle large panels of around 40 markers, but the intended use of the data should be considered when deciding on the panel size and complexity and may not be advisable for clinical settings.

Although most people associate spectral flow cytometry with large panels, it should also be considered that spectral flow cytometers, such as CYTEK Aurora, can excel with smaller panels (12 to 20 colours), especially for tracking lowly expressed markers, thanks to its ability to reduce overlap between fluorophores and autofluorescence.

Large panel sizes are made possible in mass cytometry given the platform has very minimal channel crosstalk as it is detecting highly purified isotopes of various heavy metals rather than a broad fluorescent spectrum.

It is important to carefully consider the intended use of the assay when deciding the size of the panel. For panels measuring target expression, receptor occupancy or providing absolute counts (through a lyse/no wash protocol) to support clinical decisions, creating a focused flow cytometry panel with fewer than 12 markers can provide more reliable results.

In these cases, a conventional flow cytometry instrument with easy standardization and built-in audit trails, such as the Lyric can be the better option.

It should also be noted that when your desired readout is the mean fluorescence intensity (MFI), conventional flow cytometry offers a more stable measurement across different runs than spectral flow cytometry.

Throughput for spectral flow and mass cytometry: acquisition rates, stability, and flexibility

Mass cytometry has slower acquisition rates compared to flow cytometry but has exceptionally long post-stain stability due to the stable nature of the reagents and the absence of autofluorescence which tends to gradually increase over time.

Conventional and spectral flow cytometry offer a higher comparable throughput but have more limited post-staining stability, typically lasting under 24 hours, which can be a drawback in certain scenarios.

Reflecting on spectral flow and mass cytometry reagents

With flow cytometry comes a wide selection of reagents, including a variety of clones and fluorochrome assignments offering more flexibility for panel design. In addition, customization of fluorochrome binding can be performed both through commercial sources or in-house, which is beneficial when specific fluorochromes are not commercially available or when using custom reagents from sponsors.

Mass cytometry has less commercially available reagents due to the sourcing of reagents being offered by only one company. Because of this limitation, custom conjugation with desired heavy metals is necessary for most panels. As a results, having the ability to perform custom conjugation in-house is a must to allow flexible panel design.

Both cytometry platforms can effectively integrate sponsors’ reagents, such as CAR detection reagents, ensuring seamless panel integration and compatibility with chosen platforms.

Mass  cytometry or flow cytometry? It depends on your clinical objective

Both mass and spectral flow cytometry are valuable technologies for clinical immune monitoring. Selecting the most suitable platform requires a solid understanding of the relevant considerations as the choice of platform will most often come down to what markers are included in the panel of choice.

Our analytical team has unparalleled expertise in cytometry and leverages various techniques to yield the most informative results and quality data.

You can take a quick look at the table below.

Key points to consider Spectral Flow Cytometry Mass Cytometry (CyTOF)
Cell Input Requirements Lower cell input required, suitable for low-yield samples Requires higher cell input, 2-3 times more than spectral flow cytometry
Panel Size and Complexity Can handle large panels (40+ markers), but smaller panels (12-20 colors) can show better resolution of lowly expressed markers compared to conventional flow cytometry. Large panels possible (40+ markers), minimal channel crosstalk due to heavy metal detection
Throughput and Acquisition Higher acquisition throughput (comparable to conventional flow cytometry) but limited post-stain stability (<24 hours) Slower acquisition rates but high post-stain stability due to the more stable nature of heavy metals compared to fluorochromes
Reagent Availability and Customization Wide selection of fluorochrome-bound antibodies, allows for diverse marker choices and customization Limited commercially available reagents, often require custom conjugation and offers limited clone selection

Contact us to get your cytometry analysis project started!

About the author: 

author photo

Damien Montamat-Sicotte is a Scientific Business Director at CellCarta, specializing in the flow Cytometry platform. With a PhD in immunology and post-doctoral expertise from various institutions, Damien has profuse experience in managing the processing and analysis of clinical samples by flow cytometry in an immune monitoring context.

Spectral Flow and Mass Cytometry: Select the Right Platform

July 2, 2024

Damien Montamat-Sicotte

Spectral-Flow-and-Mass-Cytometry

Choosing the right cytometry platform is crucial for optimizing your clinical study. Both mass cytometry (CyTOF) and spectral flow cytometry are widely used technologies for clinical single-cell analysis.

These platforms provide the ability to build panels of a size that go beyond conventional flow cytometry, allowing a stronger multi-parametric approach to data generation. However, selecting the appropriate technology is key to unlocking the complexities of clinical development.

This blog post compares the two platforms to help you make an informed decision for your clinical immune monitoring.

Sample matrix considerations for both spectral flow and mass cytometry

Both mass and spectral flow cytometry platforms can handle various sample types, including peripheral blood mononuclear cells (PBMCs), fresh whole blood, gently fixed samples, or frozen specimens that have undergone an initial fixation step.

When analyzing fixed frozen samples, it is important to fix the specimen soon after drawing the blood; ideally within two hours. Due to the unstable nature of granulocytes, they tend to degranulate and clump up if the specimen is not fixed and frozen in a timely manner.

Another important consideration is the amount of time the specimen is exposed to fixative prior to freezing. Over fixing the cells can lead to deleterious epitope alteration and incomplete hemolysis upon thawing. Failure to take these points into consideration could compromise data quality.

For PBMCs or fresh whole blood, the performance of both technologies is comparable. For these matrices, quality of samples, careful clone selection and fluorophores or heavy metal combination are the crucial elements to consider.

The choice between mass and spectral flow cytometry may also depend on the availability of cells.

Mass cytometry typically requires a higher cell input for samples (2-3 fold higher), which becomes crucial when working with low-yield samples like tumour-infiltrating lymphocytes (TILs) or cells taken from biopsies, as approximately 15-25% of cells are lost during acquisition.

In scenarios with limited cell availability, spectral flow cytometry is the preferred option to maximise the number of events analysed and generate quality data.

Markers, colours, and panel complexity are central to your platform choice

Both mass and spectral flow cytometry platforms can handle large panels of around 40 markers, but the intended use of the data should be considered when deciding on the panel size and complexity and may not be advisable for clinical settings.

Although most people associate spectral flow cytometry with large panels, it should also be considered that spectral flow cytometers, such as CYTEK Aurora, can excel with smaller panels (12 to 20 colours), especially for tracking lowly expressed markers, thanks to its ability to reduce overlap between fluorophores and autofluorescence.

Large panel sizes are made possible in mass cytometry given the platform has very minimal channel crosstalk as it is detecting highly purified isotopes of various heavy metals rather than a broad fluorescent spectrum.

It is important to carefully consider the intended use of the assay when deciding the size of the panel. For panels measuring target expression, receptor occupancy or providing absolute counts (through a lyse/no wash protocol) to support clinical decisions, creating a focused flow cytometry panel with fewer than 12 markers can provide more reliable results.

In these cases, a conventional flow cytometry instrument with easy standardization and built-in audit trails, such as the Lyric can be the better option.

It should also be noted that when your desired readout is the mean fluorescence intensity (MFI), conventional flow cytometry offers a more stable measurement across different runs than spectral flow cytometry.

Throughput for spectral flow and mass cytometry: acquisition rates, stability, and flexibility

Mass cytometry has slower acquisition rates compared to flow cytometry but has exceptionally long post-stain stability due to the stable nature of the reagents and the absence of autofluorescence which tends to gradually increase over time.

Conventional and spectral flow cytometry offer a higher comparable throughput but have more limited post-staining stability, typically lasting under 24 hours, which can be a drawback in certain scenarios.

Reflecting on spectral flow and mass cytometry reagents

With flow cytometry comes a wide selection of reagents, including a variety of clones and fluorochrome assignments offering more flexibility for panel design. In addition, customization of fluorochrome binding can be performed both through commercial sources or in-house, which is beneficial when specific fluorochromes are not commercially available or when using custom reagents from sponsors.

Mass cytometry has less commercially available reagents due to the sourcing of reagents being offered by only one company. Because of this limitation, custom conjugation with desired heavy metals is necessary for most panels. As a results, having the ability to perform custom conjugation in-house is a must to allow flexible panel design.

Both cytometry platforms can effectively integrate sponsors’ reagents, such as CAR detection reagents, ensuring seamless panel integration and compatibility with chosen platforms.

Mass  cytometry or flow cytometry? It depends on your clinical objective

Both mass and spectral flow cytometry are valuable technologies for clinical immune monitoring. Selecting the most suitable platform requires a solid understanding of the relevant considerations as the choice of platform will most often come down to what markers are included in the panel of choice.

Our analytical team has unparalleled expertise in cytometry and leverages various techniques to yield the most informative results and quality data.

You can take a quick look at the table below.

Key points to consider Spectral Flow Cytometry Mass Cytometry (CyTOF)
Cell Input Requirements Lower cell input required, suitable for low-yield samples Requires higher cell input, 2-3 times more than spectral flow cytometry
Panel Size and Complexity Can handle large panels (40+ markers), but smaller panels (12-20 colors) can show better resolution of lowly expressed markers compared to conventional flow cytometry. Large panels possible (40+ markers), minimal channel crosstalk due to heavy metal detection
Throughput and Acquisition Higher acquisition throughput (comparable to conventional flow cytometry) but limited post-stain stability (<24 hours) Slower acquisition rates but high post-stain stability due to the more stable nature of heavy metals compared to fluorochromes
Reagent Availability and Customization Wide selection of fluorochrome-bound antibodies, allows for diverse marker choices and customization Limited commercially available reagents, often require custom conjugation and offers limited clone selection

Contact us to get your cytometry analysis project started!

About the author: 

author photo

Damien Montamat-Sicotte is a Scientific Business Director at CellCarta, specializing in the flow Cytometry platform. With a PhD in immunology and post-doctoral expertise from various institutions, Damien has profuse experience in managing the processing and analysis of clinical samples by flow cytometry in an immune monitoring context.