IsoSpeak helps you make sense of complex data and instantly analyze your samples down to the individual cell, biomarker, and cytokine —all with a click of a button!
Choose from an expansive visualization library to track how each immune cell is functionally communicating, and to identify polyfunctional cell subsets.
This guided tour showcases a simplified environment of the IsoSpeak software.
You'll explore four of the most powerful visualizations available to researchers using the IsoPlexis platform.
Easily toggle on and off the data you wish to visualize and IsoSpeak will perform the analysis for you.
No more wasting precious time with tedious exports and data aggregation!
In this tour, you'll explore one of our internal case study data sets in the Cellular & Regenerative Medicine research area.
Read the short "Follow the Data" summary for each visualization type to learn more about the data you are seeing.
The t-SNE provides 3D visualizations of single-cell functional cytokines and high-dimensional mapping of the unique polyfunctional subsets.
You can select three views: Donor Groups, Polyfunctionality & Dominant Functional Group.
Identify Powerful Functional Drivers
Donor groups cell mapping helps you to stratify data points from your samples by responders and non-responders.
In the next visualization you can dive deeper into the data and discover the functional differences between responders and non-responders.
This demo data set shows six CD19 CAR-T cell products from three responders and three non-responders.
There are clear functional differences between the responders and non-responders.
But what are those differences?
Find out in the next t-SNE view.
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Non-Responders
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Responders
Polyfunctionality cell mapping helps you compare data points by the degree of the polyfunctionality of the samples.
The darker orange indicates a higher number of non-redundant cytokines secreted per single-cell.
We can see that the responders have the presence of highly polyfunctional CAR-T cells.
These highly polyfunctional cells have correlated to anti-tumor activity, persistence, and durability in a variety of studies.
What are the biological drivers of this increased polyfunctionality?
Find out in the next view.
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5+
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4
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3
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2
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1
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0
Dominant Functional Group cell mapping helps you explore a color-coded visualization of data points based on the cytokine profile being secreted.
These include inflammatory, regulatory, chemoattractive, stimulatory, and effector cytokine profiles. Non-secretors are displayed in grey.
The highly polyfunctional subsets of CAR-T cells in the responder groups are driven by a variety of cytokines.
As shown in this view, we can see that the stimulatory, effector, and chemoattractive cytokines play a dominant role.
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Inflammatory
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Regulatory
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Chemoattractive
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Stimulatory
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Effector
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Non-secretor
Use Polyfunctional Heatmaps to uncover the critical cell subpopulations that exist only in the condition/group of interest.
Polyfunctional Heatmap
Compare the frequency at which various functional and polyfunctional groups are secreted in your samples.
Select your desired condition/group of interest to automatically uncover the critical cell subpopulations.
Here you can see that the Responders have more polyfunctional cells than the Non-Responders.
The higher yellow density at the top displays the responders, showing that there are more polyfunctional subset of cells.
Each row corresponds to one sample and each column corresponds to a specific single cytokine or polyfunctional group.
The dots in each column indicate which cytokines are secreting.
This visualization reveals the polyfunctionality of your selected samples, calculated as the percentage of single cells secreting two or more cytokines.
Single-Cell Polyfunctional Overview
Here you can see the huge polyfunctional differences between the Non-Responders and the Responders groups.
It is clear that the percentage of polyfuctional cells in the Responders is much higher than in the Non-Responders.
- 2 cytokines
- 3 cytokines
- 4 cytokines
- 5+ cytokines
IsoSpeak helps you automatically filter and group your data by Conditions, Donors, Donor Groups, Biomarkers, and Cytokines.
Example: You can select the CD4+ & CD8+ biomarkers to filter this sample data set.
It is clear that the percentage of polyfuctional cells in the Responders is much higher than in the Non-Responders
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2 cytokines
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3 cytokines
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4 cytokines
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5+ cytokines
CD4+ & CD8+ Biomarkers: Toggle On
CD4+: Toggle On
CD8+: Toggle On
PSI is the most novel and revealing metric for measuring the potency of different immune cell types.
It can help you accelerate your immunotherapy programs from discovery to predicting response.
The Single-Cell Polyfunctional Strength Index (PSI) aggregates all single-cell, multi-dimensional secretions from a sample into a single index.
You can even instantly average your data without any manual exports or calculations!
Responders have higher polyfunctional immune response driven by primarily stimulatory and effector cytokines
Averaging Toggle On
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EffectorGranzyme B, IFN-g, MiIP-1a, Perforin, TNF-a, TNF-b
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StimulatoryGM-CSF, IL12, IL-15, IL-2, IL-21, IL-5, IL-8, IL-9
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ChemoattractiveCCL-11, IP-10, MIP-1b, RANTES
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RegulatoryIL-10, IL-13, IL-22, IL-4, TGF-b1, sCD137, sCD40L
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InflammatoryIL-17A, IL-17F, IL-1b, IL-6, MCP-1, MCP-4
Averaging Toggle On
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EffectorGranzyme B, IFN-g, MiIP-1a, Perforin, TNF-a, TNF-b
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StimulatoryGM-CSF, IL12, IL-15, IL-2, IL-21, IL-5, IL-8, IL-9
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ChemoattractiveCCL-11, IP-10, MIP-1b, RANTES
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RegulatoryIL-10, IL-13, IL-22, IL-4, TGF-b1, sCD137, sCD40L
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InflammatoryIL-17A, IL-17F, IL-1b, IL-6, MCP-1, MCP-4