Morphological profiling using machine learning reveals emergent subpopulations of interferon-γ–stimulated mesenchymal stromal cells that predict immunosuppression

Abstract

Background: Although a preponderance of pre-clinical data demonstrates the immunosuppressive potential of mesenchymal stromal cells (MSCs), significant heterogeneity and lack of critical quality attributes (CQAs) based on immunosuppressive capacity likely have contributed to inconsistent clinical outcomes. This heterogeneity exists not only between MSC lots derived from different donors, tissues and manufacturing conditions, but also within a given MSC lot in the form of functional subpopulations. We therefore explored the potential of functionally relevant morphological profiling (FRMP) to identify morphological subpopulations predictive of the immunosuppressive capacity of MSCs derived from multiple donors, manufacturers and passages. Methods: We profiled the single-cell morphological response of MSCs from different donors and passages to the functionally relevant inflammatory cytokine interferon (IFN)-g. We used the machine learning approach visual stochastic neighbor embedding (viSNE) to identify distinct morphological subpopulations that could predict suppression of activated CD4 + and CD8 + T cells in a multiplexed quantitative assay. Results: Multiple IFN-gÀstimulated subpopulations significantly correlated with the ability of MSCs to inhibit CD4 + and CD8 + T-cell activation and served as effective CQAs to predict the immunosuppressive capacity of additional manufactured MSC lots. We further characterized the emergence of morphological heterogeneity following IFN-g stimulation, which provides a strategy for identifying functional subpopulations for future single-cell characterization and enrichment techniques. Discussion: This work provides a generalizable analytical platform for assessing functional heterogeneity based on single-cell morphological responses that could be used to identify novel CQAs and inform cell manufacturing decisions.

Computational analysis of morphological and molecular features in gastric cancer tissues

“…Cytoskeletal networks construct cytoplasmic structures and support signal transduction from the extracellular environment to gene expression and chromatin formation in the nucleus . In fact, soluble factors such as cytokines and growth factors affect cellular structure and function . Since monoclonal antibodies against PD‐L1 have been approved for cancer immunotherapy, it is important to investigate effective methods to predict identification of responders using IHC slides .…”

“…2 In fact, soluble factors such as cytokines and growth factors affect cellular structure and function. 39,40,54 Since monoclonal antibodies against PD-L1 have been approved for cancer immunotherapy, it is important to investigate effective methods to predict identification of responders using IHC slides. 55,56 Interestingly, the levels of PD-L1 expression served to classify tissue morphology in H&E images ( Figure 5).…”

Single-cell high-content imaging parameters predict functional phenotype of cultured human bone marrow stromal stem cells

“…These studies actively modified cell shape by culturing the cells on a number of micropatterned surfaces, initiating differentiation or stimulating with IFNγ, which all induces morphological changes in the hBM‐MSCs. These changes could either be used to alter the differentiation outcome or predict the BM‐MSC biology . The novelty of the current study lays in the use of naive hBM‐MSC morphology.…”

“…We have previously demonstrated that changes in cell shape induced by alternations in the actin cytoskeleton structure determine differentiation outcome of hBM‐MSCs with cellular changes associated with actin de‐polymerization led to enhanced adipocytic differentiation, whereas inhibition of actin de‐polymerization increased osteoblast formation of hBM‐MSCs . Furthermore, one study also shows that stimulation of a immunomodulating pathway can lead to a morphological response in BM‐MSCs . Thus, culturing hBM‐MSCs on biomaterials with specific microstructure or stimulation of certain pathways could be used to obtained clinically relevant cell population with high OB differentiation potential or immunomodulatory properties suitable for clinical transplantation.…”

“…These changes could either be used to alter the differentiation outcome or predict the BM-MSC biology. 23,29,32,[56][57][58] The novelty of the current study lays in the use of naive hBM-MSC morphology.…”