In a cutting-edge approach to looking at patient stratification data from a paper jointly published in Blood with researchers from Kite in 2018, this Proteomics and Systems Biology publication applies IsoPlexis’ new advanced single-cell mapping tools to the datasets from the original study using more advanced analytical algorithms for more intuitive insight into the underlying mechanisms of patient responses to their CAR-T therapy product.
“Using this powerful while user-friendly analytical tool, we can dissect the multi-dimensional single-cell data from complex immune response to immunotherapies and uncover critical underlying mechanisms, which can promote enhanced correlative biomarker discovery, improved bioprocessing, and further personalized treatment development.”
In the previous Blood publication, researchers used IsoPlexis’ platform to characterize a next generation CAR product, pre-infusion. It was discovered that T cell polyfunctionality correlated with clinical outcome. The Polyfunctional Strength Index (PSI), “combined with conditioning-driven IL-15, a cytokine with potent T cell proliferative capabilities, or CAR-T cell expansion in vivo, is associated with clinical outcomes post-CAR-T therapy.”1 One of the major findings of this study was identifying the “potential usefulness of monitoring CAR-T cell polyfunctionality as a key product attribute, complementing other characteristics including T cell proliferative capability.”1
There are critical challenges when it comes to data analysis and visualization with multi-dimensional datasets. IsoPlexis’ single-cell functional proteomics technology has established an ability to identify deep functional heterogeneity (where none was previously detected) and reveal clinical correlates. A comprehensive visualization toolkit was developed to complement the clinical relevance of the PSI by “integrating 3D Uniform Manifold Approximation and Projection (UMAP) and t-distributed stochastic neighbor embedding (t-SNE) visualizations into a proteomic analysis pipeline, which provides more advanced and analytical algorithms for more intuitive data visualization and interpretation.”2
Visualizing the Future of Biomarkers
This recently published article highlights the cutting-edge analytics for next generation visualizations of clinical biomarkers. Some of the key points are:
- Functional 3D UMAP and 3D t-SNE visualization by the single-cell 32-plex proteomic measurement, for the first time, dissects heterogeneous cytokine responses and enables more intuitively visual stratification of patient response to anti-CD19 CAR-T cell immunotherapies.
- State-of-the-art data visualization platforms used to address the increasing challenges of identifying immune cell subset clinical biomarkers in immune-oncology, from high dimensional single-cell proteomic data.
- A first proteomic analysis pipeline with a comprehensive built-in visualization toolkit unprecedently reveals functional complexity and clinical correlates in more intuitive data visualization and interpretation.
- Next generation algorithms integrated into the IsoSpeak software suite transform complex, multi-dimensional single-cell proteomic data into intuitive graphical representations including 3D UMAP, 3D t-SNE, heatmaps, and polyfunctional activation topology – principal component analysis (PAT-PCA), to simplify complex underlying biological systems and their interactions.
- The fully automated, highly multiplexed single-cell proteomic platform with a user-friendly IsoSpeak software suite simplifies high dimensional data acquisition and bioinformatic analysis, leading to a higher level of flexibility, and robust, statistically supported, and interpretable results for future development of personalized therapeutic approaches and clinical biomarker discovery.
Single-cell functional data produced by the IsoCode chip has correlated with patient response. Single-cell data is complicated, which means it can be difficult to visualize with traditional methods. IsoPlexis solves this problem with straightforward and intuitive visualizations. Both UMAP and t-SNE are machine-learning algorithms that are used for visualizing multi-dimensional data in a two- or three-dimensional space. The integration of UMAP and t-SNE in a push-button manner into IsoSpeak means that there is no need for users to have experience with programming or deep informatics. IsoPlexis is democratizing next-genetation bioinformatics, and users can now obtain this data with the automated IsoLight platform on the same day with the push of a button.
State-of-the-Art Data Visualization for Clinical Biomarkers Enabling Patient Stratification
These researchers expanded their previous study to “analyze the single-cell data, measured by the 32-plex IsoCode chip, of the pre-infusion anti-CD19 CAR-T cells manufactured from NHL patients, who either responded or did not respond to the therapy, and to visualize this multi-dimensional space in three dimensions.”2 The same patient cohort was used for this study, and the new UMAP and t-SNE visualizations were used to analyze the single-cell data.
There were distinct secretion profiles between patients who responded to the therapy and those who did not respond, and new insights into the underlying mechanisms of these different responses were gained with the UMAP and t-SNE visualizations. The patient secretion profiles were heterogeneous with the responding patients showing an upregulation of polyfunctional cells as well as a more diverse secretion profile, when compared to the non-responding patients. Responders secreted upregulated effector cytokines and stimulatory cytokines usually associated with anti-tumor immunity.
The IsoSpeak software suite can be used to generate complex, but easily interpretable and meaningful data visualizations that can simplify users’ workflows, which can lead to the development of next generation therapies. “3D UMAP and t-SNE visualizations generated by single-cell functional proteomics have provided a powerful tool for stratifying patient response to therapies and significantly improved the understanding of multi-dimensional datasets and related biological processes for new biomarker discovery.”2
- Rossi et al, “Preinfusion polyfunctional anti-CD19 chimeric antigen receptor T cells are associated with clinical outcomes in NHL,” Blood 132:804-814, 2018.
- Bowman et al, “Advanced Cell Mapping Visualizations for Single Cell Functional Proteomics Enabling Patient Stratification,” Proteomics and Systems Biology 2020.