Lance Cameron Kam

Biomaterials provide a powerful tool for directing the function of T cells with applications from fundamental immunology research to immunotherapy. Intriguingly, controlling the mechanical stiffness of biomaterials used to activate T cells modulates a range of subsequent functions from early activation to differentiation. However, it is not fully understood whether the effect of initial, short-term mechanosensing is limited to immediate impacts on cell function or imparts a long-lasting imprint on cell function. This report demonstrates such a mechanomemory in the context of expansion; T cells activated on mechanically soft surfaces exhibit an extended proliferative phase for multiple generations following removal from the substrate. This effect results from a combination of cell-intrinsic changes and extrinsic factors associated with cell-cell signaling. Specifically, activation using a soft elastomer substrate extends subsequent proliferation over multiple cell divisions. This programming can initially be modified by extrinsic soluble factors secreted into the media; the conditioned media carries information about early mechanosensitive activation, as demonstrated using media exchange experiments. Notably, the impact of extrinsic factors on proliferation decreases over the course of expansion, showing that reinforcement of mechanosensing leads to establishment of mechanomemory. Together, these results suggest that populations of T cells can be trained to retain the mechanical imprint of an activating surface through continued reinforcement, potentially directing later function in a range of immunotherapy applications.

Variability in T cell performance presents a major challenge to adoptive cellular immunotherapy (ACT). This includes expansion of a small starting population into therapeutically effective numbers, which can fail due to differences between individuals and disease states. Intriguingly, modulating the mechanical stiffness of materials used to activate T cells can rescue subsequent expansion. However, the magnitude of this effect and the optimal stiffnesses differ between individuals, complicating the use of mechanosensing to improve cell production. The ability to predict this long‐term, substrate‐dependent expansion from a short‐term assay would accelerate the deployment of immunotherapy. Here, it is demonstrated that short‐term cell spreading predicts subsequent, mechanosensitive expansion. As an initial task, cell spreading is used to identify whether a sample of cells came from a healthy donor or a Chronic Lymphocytic Leukemia (CLL) patient. Notably, a deep learning (DL) model outperforms morphometric approaches to this classification task. This system also successfully predicts the long‐term expansion potential of cells as a function of both source and mechanical stiffness of the activating substrate. By predicting long‐term T cell function from small, diagnostic samples, this approach will improve the reliability and efficacy of cell production and immunotherapy.

Variability in T cell performance presents a major challenge to adoptive cellular immunotherapy (ACT). This includes expansion of a small starting population into therapeutically effective numbers, which can fail due to differences between individuals and disease states. Intriguingly, modulating the mechanical stiffness of materials used to activate T cells can rescue subsequent expansion. However, the magnitude of this effect and the optimal stiffnesses differ between individuals, complicating the use of mechanosensing to improve cell production. The ability to predict this long‐term, substrate‐dependent expansion from a short‐term assay would accelerate the deployment of immunotherapy. Here, it is demonstrated that short‐term cell spreading predicts subsequent, mechanosensitive expansion. As an initial task, cell spreading is used to identify whether a sample of cells came from a healthy donor or a Chronic Lymphocytic Leukemia (CLL) patient. Notably, a deep learning (DL) model outperforms morphometric approaches to this classification task. This system also successfully predicts the long‐term expansion potential of cells as a function of both source and mechanical stiffness of the activating substrate. By predicting long‐term T cell function from small, diagnostic samples, this approach will improve the reliability and efficacy of cell production and immunotherapy.

A central step in T-cell immunotherapy is the expansion of a starting population into therapeutically potent numbers of these “living drugs”. This process can be enhanced by replacing the mechanically stiff materials used for activation with softer counterparts. However, this mechanosensitive expansion response varies between individuals, impeding the full deployment of potential cell immunotherapy. This report identifies the sources of this variability, ultimately improving the reliability of T-cell expansion. T cells from a cohort of healthy donors were phenotypically characterized, activated, and expanded in vitro on soft and hard substrates, capturing and quantifying a wide range of mechanosensing responses. An analysis of expansion against demographic and phenotypic features correlated mechanosensing with the percentage of effector T cells (T_Effs) in the starting population. Depletion experiments confirmed that T_Effs mediate mechanosensitive expansion but also suggest that these cells are not responsible for large-scale cell production. Instead, population-level expansion results from interactions between T-cell subtypes. By providing a framework and experimental approach to understanding donor variability, the results of this study will improve the success and reliability of T-cell immunotherapy.

Professional phagocytes like neutrophils and macrophages tightly control what they consume, how much they consume, and when they move after cargo uptake. We show that plasma membrane abundance is a key arbiter of these cellular behaviors. Neutrophils and macrophages lacking the G protein subunit Gβ ₄ exhibited profound plasma membrane expansion, accompanied by marked reduction in plasma membrane tension. These biophysical changes promoted the phagocytosis of bacteria, fungus, apoptotic corpses, and cancer cells. We also found that Gβ ₄ -deficient neutrophils are defective in the normal inhibition of migration following cargo uptake. Sphingolipid synthesis played a central role in these phenotypes by driving plasma membrane accumulation in cells lacking Gβ ₄ . In Gβ ₄ knockout mice, neutrophils not only exhibited enhanced phagocytosis of inhaled fungal conidia in the lung but also increased trafficking of engulfed pathogens to other organs. Together, these results reveal an unexpected, biophysical control mechanism central to myeloid functional decision-making.

Immune cell function varies tremendously between individuals, posing a major challenge to emerging cellular immunotherapies. This report pursues the use of cell morphology as an indicator of high-level T cell function. Short-term spreading of T cells on planar, elastic surfaces was quantified by 11 morphological parameters and analyzed to identify effects of both intrinsic and extrinsic factors. Our findings identified morphological features that varied between T cells isolated from healthy donors and those from patients being treated for Chronic Lymphocytic Leukemia (CLL). This approach also identified differences between cell responses to substrates of different elastic modulus. Combining multiple features through a machine learning approach such as Decision Tree or Random Forest provided an effective means for identifying whether T cells came from healthy or CLL donors. Further development of this approach could lead to a rapid assay of T cell function to guide cellular immunotherapy.

During vertebrate organogenesis, increases in morphological complexity are tightly coupled to morphogen expression. In this work, we studied how morphogens influence self-organizing processes at the collective or “supra”-cellular scale in avian skin. We made physical measurements across length scales, which revealed morphogen-enabled material property differences that were amplified at supracellular scales in comparison to cellular scales. At the supracellular scale, we found that fibroblast growth factor (FGF) promoted “solidification” of tissues, whereas bone morphogenetic protein (BMP) promoted fluidity and enhanced mechanical activity. Together, these effects created basement membrane–less compartments within mesenchymal tissue that were mechanically primed to drive avian skin tissue budding. Understanding this multiscale process requires the ability to distinguish between proximal effects of morphogens that occur at the cellular scale and their functional effects, which emerge at the supracellular scale.

The ability of cells to recognize and respond to the mechanical properties of their environment is of increasing importance in T cell physiology. However, initial studies in this direction focused on planar hydrogel and elastomer surfaces, presenting several challenges in interpretation including difficulties in separating mechanical stiffness from changes in chemistry needed to modulate this property. We introduce here the use of magnetic fields to change the structural rigidity of microscale elastomer pillars loaded with superparamagnetic nanoparticles, independent of substrate chemistry. This magnetic modulation of rigidity, embodied as the pillar spring constant, changed the interaction of mouse naïve CD4⁺ T cells from a contractile morphology to one involving deep embedding into the array. Furthermore, increasing spring constant was associated with higher IL-2 secretion, showing a functional impact on mechanosensing. The system introduced here thus separates local substrate stiffness and long-range structural rigidity, revealing new facets of T cell interaction with their environment.