Mechanical forces amplify TCR mechanotransduction in T cell activation and function.

Adoptive T cell immunotherapies, including engineered T cell receptor (eTCR) and chimeric antigen receptor (CAR) T cell immunotherapies, have shown efficacy in treating a subset of hematologic malignancies, exhibit promise in solid tumors, and have many other potential applications, such as in fibrosis, autoimmunity, and regenerative medicine. While immunoengineering has focused on designing biomaterials to present biochemical cues to manipulate T cells ex vivo and in vivo, mechanical cues that regulate their biology have been largely underappreciated. This review highlights the contributions of mechanical force to several receptor-ligand interactions critical to T cell function, with central focus on the TCR-peptide-loaded major histocompatibility complex (pMHC). We then emphasize the role of mechanical forces in (i) allosteric strengthening of the TCR-pMHC interaction in amplifying ligand discrimination during T cell antigen recognition prior to activation and (ii) T cell interactions with the extracellular matrix. We then describe approaches to design eTCRs, CARs, and biomaterials to exploit TCR mechanosensitivity in order to potentiate T cell manufacturing and function in adoptive T cell immunotherapy.

Microporogen-Structured Collagen Matrices for Embedded Bioprinting of Tumor Models for Immuno-Oncology.

Embedded bioprinting enables the rapid design and fabrication of complex tissues that recapitulate in vivo microenvironments. However, few biological matrices enable good print fidelity, while simultaneously facilitate cell viability, proliferation, and migration. Here, a new microporogen-structured (µPOROS) matrix for embedded bioprinting is introduced, in which matrix rheology, printing behavior, and porosity are tailored by adding sacrificial microparticles composed of a gelatin-chitosan complex to a prepolymer collagen solution. To demonstrate its utility, a 3D tumor model is created via embedded printing of a murine melanoma cell ink within the µPOROS collagen matrix at 4 °C. The collagen matrix is subsequently crosslinked around the microparticles upon warming to 21 °C, followed by their melting and removal at 37 °C. This process results in a µPOROS matrix with a fibrillar collagen type-I network akin to that observed in vivo. Printed tumor cells remain viable and proliferate, while antigen-specific cytotoxic T cells incorporated in the matrix migrate to the tumor site, where they induce cell death. The integration of the µPOROS matrix with embedded bioprinting opens new avenues for creating complex tissue microenvironments in vitro that may find widespread use in drug discovery, disease modeling, and tissue engineering for therapeutic use.

Chemotherapy Dose Shapes the Expression of Immune-Interacting Markers on Cancer Cells.

Introduction: Tumor and immune cells interact through a variety of cell-surface proteins that can either restrain or promote tumor progression. The impacts of cytotoxic chemotherapy dose and delivery route on this interaction profile remain incompletely understood, and could support the development of more effective combination therapies for cancer treatment. Methods and Results: Here, we found that exposure to the anthracycline doxorubicin altered the expression of numerous immune-interacting markers (MHC-I, PD-L1, PD-L2, CD47, Fas, and calreticulin) on live melanoma, breast cancer, and leukemia cells in a dose-dependent manner in vitro. Notably, an intermediate dose best induced immunogenic cell death and the expression of immune-activating markers without maximizing expression of markers associated with immune suppression. Bone marrow-derived dendritic cells exposed to ovalbumin-expressing melanoma treated with intermediate doxorubicin dose became activated and best presented tumor antigen. In a murine melanoma model, both the doxorubicin dose and delivery location (systemic infusion versus local administration) affected the expression of these markers on live tumor cells. Particularly, local release of doxorubicin from a hydrogel increased calreticulin expression on tumor cells without inducing immune-suppressive markers, in a manner dependent on the loaded dose. Doxorubicin exposure also altered the expression of immune-interacting markers in patient-derived melanoma cells. Conclusions: Together, these results illustrate how standard-of-care chemotherapy, when administered in various manners, can lead to distinct expression of immunogenic markers on cancer cells. These findings may inform development of chemo-immunotherapy combinations for cancer treatment. Supplementary Information: The online version contains supplementary material available at 10.1007/s12195-022-00742-y.

Metabolically driven maturation of human-induced-pluripotent-stem-cell-derived cardiac microtissues on microfluidic chips.

The immature physiology of cardiomyocytes derived from human induced pluripotent stem cells (hiPSCs) limits their utility for drug screening and disease modelling. Here we show that suitable combinations of mechanical stimuli and metabolic cues can enhance the maturation of hiPSC-derived cardiomyocytes, and that the maturation-inducing cues have phenotype-dependent effects on the cells' action-potential morphology and calcium handling. By using microfluidic chips that enhanced the alignment and extracellular-matrix production of cardiac microtissues derived from genetically distinct sources of hiPSC-derived cardiomyocytes, we identified fatty-acid-enriched maturation media that improved the cells' mitochondrial structure and calcium handling, and observed divergent cell-source-dependent effects on action-potential duration (APD). Specifically, in the presence of maturation media, tissues with abnormally prolonged APDs exhibited shorter APDs, and tissues with aberrantly short APDs displayed prolonged APDs. Regardless of cell source, tissue maturation reduced variabilities in spontaneous beat rate and in APD, and led to converging cell phenotypes (with APDs within the 300-450 ms range characteristic of human left ventricular cardiomyocytes) that improved the modelling of the effects of pro-arrhythmic drugs on cardiac tissue.

Viscoelastic Biomaterials for Tissue Regeneration.

The extracellular matrix (ECM) mechanical properties regulate key cellular processes in tissue development and regeneration. The majority of scientific investigation has focused on ECM elasticity as the primary mechanical regulator of cell and tissue behavior. However, all living tissues are viscoelastic, exhibiting both solid- and liquid-like mechanical behavior. Despite increasing evidence regarding the role of ECM viscoelasticity in directing cellular behavior, this aspect is still largely overlooked in the design of biomaterials for tissue regeneration. Recently, with the emergence of various bottom-up material design strategies, new approaches can deliver unprecedented control over biomaterial properties at multiple length scales, thus enabling the design of viscoelastic biomaterials that mimic various aspects of the native tissue ECM microenvironment. This review describes key considerations for the design of viscoelastic biomaterials for tissue regeneration. We provide an overview of the role of matrix viscoelasticity in directing cell behavior toward regenerative outcomes, highlight recent strategies utilizing viscoelastic hydrogels for regenerative therapies, and outline remaining challenges, potential solutions, and emerging applications for viscoelastic biomaterials in tissue engineering and regenerative medicine. Impact statement All living tissues are viscoelastic. As we design viscoelastic biomaterials for tissue engineering and regenerative medicine, we must understand the effect of matrix viscoelasticity on in vitro cell behavior and in vivo regenerative outcomes. Engineering the next generation of biomaterials with tunable viscoelasticity to direct cell and tissue behavior will contribute to the development of in vitro tissue models and in vivo regenerative therapies to address unmet clinical needs.

Risk quantification for SARS-CoV-2 infection through airborne transmission in university settings.

The COVID-19 pandemic has significantly impacted learning as many institutions switched to remote or hybrid instruction. An in-depth assessment of the risk of infection that considers environmental setting and mitigation strategies is needed to make safe and informed decisions regarding reopening university spaces. A quantitative model of infection probability that accounts for space-specific parameters is presented to enable assessment of the risk in reopening university spaces at given densities. The model uses the fraction of the campus population that are viral shedders, room capacity, face covering filtration efficiency, air exchange rate, room volume, and time spent in the space as parameters to calculate infection probabilities in teaching spaces, dining halls, dorms, and shared bathrooms. The model readily calculates infection probabilities in various university spaces, with face covering filtration efficiency and air exchange rate being among the dominant variables. When applied to university spaces, this model demonstrated that, under specific conditions that are feasible to implement, in-person classes could be held in large lecture halls with an infection risk over the semester <1%. Meal pick-ups from dining halls and usage of shared bathrooms in residential dormitories among small groups of students could also be accomplished with low risk. The results of applying this model to spaces at Harvard University (Cambridge and Allston campuses) and Stanford University are reported. Finally, a user-friendly web application was developed using this model to calculate infection probability following input of space-specific variables. The successful development of a quantitative model and its implementation through a web application may facilitate accurate assessments of infection risk in university spaces. However, since this model is thus far unvalidated, validation using infection rate and contact tracing data from university campuses will be crucial as such data becomes available at larger scales. In light of the impact of the COVID-19 pandemic on universities, this tool could provide crucial insight to students, faculty, and university officials in making informed decisions.