In silico modeling identifies CD45 as a regulator of IL-2 synergy in the NKG2D-mediated activation of immature human NK cells

Natural killer cells in cancer immunotherapy

Natural killer (NK) cells, as innate lymphocytes, possess cytotoxic capabilities and engage target cells through a repertoire of activating and inhibitory receptors. Particularly, natural killer group 2, member D (NKG2D) receptor on NK cells recognizes stress-induced ligands-the MHC class I chain-related molecules A and B (MICA/B) presented on tumor cells and is key to trigger the cytolytic response of NK cells. However, tumors have developed sophisticated strategies to evade NK cell surveillance, which lead to failure of tumor immunotherapy. In this paper, we summarized these immune escaping strategies, including the downregulation of ligands for activating receptors, upregulation of ligands for inhibitory receptors, secretion of immunosuppressive compounds, and the development of apoptosis resistance. Then, we focus on recent advancements in NK cell immune therapies, which include engaging activating NK cell receptors, upregulating NKG2D ligand MICA/B expression, blocking inhibitory NK cell receptors, adoptive NK cell therapy, chimeric antigen receptor (CAR)-engineered NK cells (CAR-NK), and NKG2D CAR-T cells, especially several vaccines targeting MICA/B. This review will inspire the research in NK cell biology in tumor and provide significant hope for improving cancer treatment outcomes by harnessing the potent cytotoxic activity of NK cells.

NK cell-based tumor immunotherapy

Natural killer (NK) cells display a unique inherent ability to identify and eliminate virus-infected cells and tumor cells. They are particularly powerful for elimination of hematological cancers, and have attracted considerable interests for therapy of solid tumors. However, the treatment of solid tumors with NK cells are less effective, which can be attributed to the very complicated immunosuppressive microenvironment that may lead to the inactivation, insufficient expansion, short life, and the poor tumor infiltration of NK cells. Fortunately, the development of advanced nanotechnology has provided potential solutions to these issues, and could improve the immunotherapy efficacy of NK cells. In this review, we summarize the activation and inhibition mechanisms of NK cells in solid tumors, and the recent advances in NK cell-based tumor immunotherapy boosted by diverse nanomaterials. We also propose the challenges and opportunities for the clinical application of NK cell-based tumor immunotherapy.

Computational Methods for Single-Cell Proteomics

Advances in single-cell proteomics technologies have resulted in high-dimensional datasets comprising millions of cells that are capable of answering key questions about biology and disease. The advent of these technologies has prompted the development of computational tools to process and visualize the complex data. In this review, we outline the steps of single-cell and spatial proteomics analysis pipelines. In addition to describing available methods, we highlight benchmarking studies that have identified advantages and pitfalls of the currently available computational toolkits. As these technologies continue to advance, robust analysis tools should be developed in tandem to take full advantage of the potential biological insights provided by these data.

Magnetic-Manipulated NK Cell Proliferation and Activation Enhance Immunotherapy of Orthotopic Liver Cancer

The immunotherapy of deep solid tumors in the human body, such as liver cancer, still faces great challenges, especially the inactivation and insufficient infiltration of immune cells in solid tumor microenvironment. Natural killer (NK) cells are gaining ever-increasing attention owing to their unique features and are expected to play an important role in the liver cancer immunotherapy. However, NK cells are severely insufficient and inactivated in solid liver tumor due to the highly immunosuppressive intratumor microenvironment, resulting in poor clinical therapeutic efficacy. Herein, we propose a mild magnetocaloric regulation approach using a magnetogenetic nanoplatform MNPs@PEI-FA/pDNA (MPFD), which is synthesized by loading a heat-inducible plasmid DNA (HSP70-IL-2-EGFP) on polyethyleneimine (PEI)- and folic acid (FA)-modified ZnCoFe₂O₄@ZnMnFe₂O₄ magnetic nanoparticles (MNPs) to promote the proliferation and activation of tumor-infiltrating NK cells under magnetic manipulation without the limitation of penetration depth for orthotopic liver cancer immunotherapy. The magnetothermally responsive MPFD serves as a magnetism-heat nanotransducer to induce the gene transcription of IL-2 cytokine in orthotopic liver tumor for NK cell proliferation and activation. Both in vitro and in vivo results demonstrate that the remote mild magnetocaloric regulation (∼40 °C) by MPFD initiates the HSP70 promoter to trigger the overexpression of IL-2 cytokine for subsequent secretion, leading to in situ expansion and activation of tumor-infiltrating NK cells through the IL-2/IL-2 receptor (IL-2R) pathways and the resulting prominent tumor inhibition. This work not only evidences the great potential of magnetogenetic nanoplatform but also reveals the underlying proliferation and activation mechanism of NK cells in liver cancer treatment by magnetogenetic nanoplatform.

McSNAC: A software to approximate first-order signaling networks from mass cytometry data

Background

Mass cytometry (CyTOF) gives unprecedented opportunity to simultaneously measure up to 40 proteins in single cells, with a theoretical potential to reach 100 proteins. This high-dimensional single-cell information can be very useful in dissecting mechanisms of cellular activity. In particular, measuring abundances of signaling proteins like phospho-proteins can provide detailed information on the dynamics of single-cell signaling processes. However, computational analysis is required to reconstruct such networks with a mechanistic model.

Methods

We propose our Mass cytometry Signaling Network Analysis Code (McSNAC), a new software capable of reconstructing signaling networks and estimating their kinetic parameters from CyTOF data. McSNAC approximates signaling networks as a network of first-order reactions between proteins. This assumption often breaks down as signaling reactions can involve binding and unbinding, enzymatic reactions, and other nonlinear constructions. Furthermore, McSNAC may be limited to approximating indirect interactions between protein species, as cytometry experiments are only able to assay a small fraction of protein species involved in signaling.

Results

We carry out a series of in silico experiments here to show (1) McSNAC is capable of accurately estimating the ground-truth model in a scalable manner when given data originating from a first-order system; (2) McSNAC is capable of qualitatively predicting outcomes to perturbations of species abundances in simple second-order reaction models and in a complex in silico nonlinear signaling network in which some proteins are unmeasured.

Conclusions

These findings demonstrate that McSNAC can be a valuable screening tool for generating models of signaling networks from time-stamped CyTOF data.

Contribution of natural killer cells in innate immunity against colorectal cancer

Natural killer cells are members of the innate immune system and promote cytotoxic activity against tumor or infected cells independently from MHC recognition. NK cells are modulated by the expression of activator/inhibitory receptors. The ratio of this activator/inhibitory receptors is responsible for the cytotoxic activity of NK cells toward the target cells. Owing to the potent anti-tumor properties of NK cells, they are considered as interesting approach in tumor treatment. Colorectal cancer (CRC) is the second most common cause of death in the world and the incidence is about 2 million new cases per year. Metastatic CRC is accompanied by a poor prognosis with less than three years of overall survival. Chemotherapy and surgery are the most adopted treatments. Besides, targeted therapy and immune checkpoint blockade are novel approach to CRC treatment. In these patients, circulating NK cells are a prognostic marker. The main target of CRC immune cell therapy is to improve the tumor cell's recognition and elimination by immune cells. Adaptive NK cell therapy is the milestone to achieve the purpose. Allogeneic NK cell therapy has been widely investigated within clinical trials. In this review, we focus on the NK related approaches including CAR NK cells, cell-based vaccines, monoclonal antibodies and immunomodulatory drugs against CRC tumoral cells.

Differential IL-12 signaling induces human natural killer cell activating receptor-mediated ligand-specific expansion

IL-12 is an essential cytokine involved in the generation of memory or memory-like NK cells. Mouse cytomegalovirus infection triggers NK receptor-induced, ligand-specific IL-12-dependent NK cell expansion, yet specific IL-12 stimulation ex vivo leading to NK cell proliferation and expansion is not established. Here, we show that IL-12 alone can sustain human primary NK cell survival without providing IL-2 or IL-15 but was insufficient to promote human NK cell proliferation. IL-12 signaling analysis revealed STAT5 phosphorylation and weak mTOR activation, which was enhanced by activating NK receptor upregulation and crosslinking leading to STAT5-dependent, rapamycin-sensitive, or TGFβ-sensitive NK cell IL-12-dependent expansion, independently of IL-12 receptor upregulation. Prolonged IL-2 culture did not impair IL-12-dependent ligand-specific NK cell expansion. These findings demonstrate that activating NK receptor stimulation promotes differential IL-12 signaling, leading to human NK cell expansion, and suggest adopting strategies to provide IL-12 signaling in vivo for ligand-specific IL-2-primed NK cell-based therapies.

NK cell receptor and ligand composition influences the clearance of SARS-CoV-2

To explore how the immune system controls clearance of SARS-CoV-2, we used a single-cell, mass cytometry-based proteomics platform to profile the immune systems of 21 patients who had recovered from SARS-CoV-2 infection without need for admission to an intensive care unit or for mechanical ventilation. We focused on receptors involved in interactions between immune cells and virus-infected cells. We found that the diversity of receptor repertoires on natural killer (NK) cells was negatively correlated with the viral clearance rate. In addition, NK subsets expressing the receptor DNAM1 were increased in patients who more rapidly recovered from infection. Ex vivo functional studies revealed that NK subpopulations with high DNAM1 expression had cytolytic activities in response to target cell stimulation. We also found that SARS-CoV-2 infection induced the expression of CD155 and nectin-4, ligands of DNAM1 and its paired coinhibitory receptor TIGIT, which counterbalanced the cytolytic activities of NK cells. Collectively, our results link the cytolytic immune responses of NK cells to the clearance of SARS-CoV-2 and show that the DNAM1 pathway modulates host-pathogen interactions during SARS-CoV-2 infection.

Epigenetic modulation of immune synaptic-cytoskeletal networks potentiates γδ T cell-mediated cytotoxicity in lung cancer

γδ T cells are a distinct subgroup of T cells that bridge the innate and adaptive immune system and can attack cancer cells in an MHC-unrestricted manner. Trials of adoptive γδ T cell transfer in solid tumors have had limited success. Here, we show that DNA methyltransferase inhibitors (DNMTis) upregulate surface molecules on cancer cells related to γδ T cell activation using quantitative surface proteomics. DNMTi treatment of human lung cancer potentiates tumor lysis by ex vivo-expanded Vδ1-enriched γδ T cells. Mechanistically, DNMTi enhances immune synapse formation and mediates cytoskeletal reorganization via coordinated alterations of DNA methylation and chromatin accessibility. Genetic depletion of adhesion molecules or pharmacological inhibition of actin polymerization abolishes the potentiating effect of DNMTi. Clinically, the DNMTi-associated cytoskeleton signature stratifies lung cancer patients prognostically. These results support a combinatorial strategy of DNMTis and γδ T cell-based immunotherapy in lung cancer management.

Harnessing the cDC1-NK Cross-Talk in the Tumor Microenvironment to Battle Cancer

Immunotherapeutic approaches have revolutionized the treatment of several diseases such as cancer. The main goal of immunotherapy for cancer is to modulate the anti-tumor immune responses by favoring the recognition and destruction of tumor cells. Recently, a better understanding of the suppressive effect of the tumor microenvironment (TME) on immune cells, indicates that restoring the suppressive effect of the TME is crucial for an efficient immunotherapy. Natural killer (NK) cells and dendritic cells (DCs) are cell types that are currently administered to cancer patients. NK cells are used because of their ability to kill tumor cells directly via cytotoxic granzymes. DCs are employed to enhance anti-tumor T cell responses based on their ability to present antigens and induce tumor-antigen specific CD8⁺ T cell responses. In preclinical models, a particular DC subset, conventional type 1 DCs (cDC1s) is shown to be specialized in cross-presenting extracellular antigens to CD8⁺ T cells. This feature makes them a promising DC subset for cancer treatment. Within the TME, cDC1s show a bidirectional cross-talk with NK cells, resulting in a higher cDC1 recruitment, differentiation, and maturation as well as activation and stimulation of NK cells. Consequently, the presence of cDC1s and NK cells within the TME might be of utmost importance for the success of immunotherapy. In this review, we discuss the function of cDC1s and NK cells, their bidirectional cross-talk and potential strategies that could improve cancer immunotherapy.

Convergent Evolution by Cancer and Viruses in Evading the NKG2D Immune Response

The natural killer group 2 member D (NKG2D) receptor and its family of NKG2D ligands (NKG2DLs) are key components in the innate immune system, triggering NK, γδ and CD8+ T cell-mediated immune responses. While surface NKG2DL are rarely found on healthy cells, expression is significantly increased in response to various types of cellular stress, viral infection, and tumour cell transformation. In order to evade immune-mediated cytotoxicity, both pathogenic viruses and cancer cells have evolved various mechanisms of subverting immune defences and preventing NKG2DL expression. Comparisons of the mechanisms employed following virus infection or malignant transformation reveal a pattern of converging evolution at many of the key regulatory steps involved in NKG2DL expression and subsequent immune responses. Exploring ways to target these shared steps in virus- and cancer-mediated immune evasion may provide new mechanistic insights and therapeutic opportunities, for example, using oncolytic virotherapy to re-engage the innate immune system towards cancer cells.

Paving the Way Towards Universal Chimeric Antigen Receptor Therapy in Cancer Treatment: Current Landscape and Progress

Chimeric antigen receptor (CAR) therapy has been proved effective in a stream of clinical trials, especially in hematologic malignancies. However, current CAR therapy is highly personalized as cells used are derived from patients themselves, which can be costly, time-consuming, and sometimes fails to achieve optimal therapeutic results due to poor quality/quantity of patient-derived cells. On the contrary, universal CAR therapy, which is based on healthy individuals’ cells, circumvents several limitations of current autologous CAR therapy. To achieve the universality of CAR therapy, the allogeneic cell transplantation related issues, such as graft-versus-host disease (GVHD) and host-versus-graft activities (HVGA), must be addressed. In this review, we focus on current progress regarding GVHD and HVGA in the universal CAR therapy, followed by a universal CAR design that may be applied to allogeneic cells and a summary of key clinical trials in this field. This review may provide valuable insights into the future design of universal CAR products.

Understanding the Dynamics of T-Cell Activation in Health and Disease Through the Lens of Computational Modeling

T cells in the immune system are activated by binding to foreign peptides (from an external pathogen) or mutant peptide (derived from endogenous proteins) displayed on the surface of a diseased cell. This triggers a series of intracellular signaling pathways, which ultimately dictate the response of the T cell. The insights from computational models have greatly improved our understanding of the mechanisms that control T-cell activation. In this review, we focus on the use of ordinary differential equation–based mechanistic models to study T-cell activation. We highlight several examples that demonstrate the models’ utility in answering specific questions related to T-cell activation signaling, from antigen discrimination to the feedback mechanisms that initiate transcription factor activation. In addition, we describe other modeling approaches that can be combined with mechanistic models to bridge time scales and better understand how intracellular signaling events, which occur on the order of seconds to minutes, influence phenotypic responses of T-cell activation, which occur on the order of hours to days. Overall, through concrete examples, we emphasize how computational modeling can be used to enable the rational design and optimization of immunotherapies.

Maximum Entropy Framework for Predictive Inference of Cell Population Heterogeneity and Responses in Signaling Networks

Predictive models of signaling networks are essential for understanding cell population heterogeneity and designing rational interventions in disease. However, using computational models to predict heterogeneity of signaling dynamics is often challenging because of the extensive variability of biochemical parameters across cell populations. Here, we describe a maximum entropy-based framework for inference of heterogeneity in dynamics of signaling networks (MERIDIAN). MERIDIAN estimates the joint probability distribution over signaling network parameters that is consistent with experimentally measured cell-to-cell variability of biochemical species. We apply the developed approach to investigate the response heterogeneity in the EGFR/Akt signaling network. Our analysis demonstrates that a significant fraction of cells exhibits high phosphorylated Akt (pAkt) levels hours after EGF stimulation. Our findings also suggest that cells with high EGFR levels predominantly contribute to the subpopulation of cells with high pAkt activity. We also discuss how MERIDIAN can be extended to accommodate various experimental measurements.

NK cells for cancer immunotherapy

Natural killer (NK) cells can swiftly kill multiple adjacent cells if these show surface markers associated with oncogenic transformation. This property, which is unique among immune cells, and their capacity to enhance antibody and T cell responses support a role for NK cells as anticancer agents. Although tumours may develop several mechanisms to resist attacks from endogenous NK cells, ex vivo activation, expansion and genetic modification of NK cells can greatly increase their antitumour activity and equip them to overcome resistance. Some of these methods have been translated into clinical-grade platforms and support clinical trials of NK cell infusions in patients with haematological malignancies or solid tumours, which have yielded encouraging results so far. The next generation of NK cell products will be engineered to enhance activating signals and proliferation, suppress inhibitory signals and promote their homing to tumours. These modifications promise to significantly increase their clinical activity. Finally, there is emerging evidence of increased NK cell-mediated tumour cell killing in the context of molecularly targeted therapies. These observations, in addition to the capacity of NK cells to magnify immune responses, suggest that NK cells are poised to become key components of multipronged therapeutic strategies for cancer.

Data analysis to modeling to building theory in NK cell biology and beyond: How can computational modeling contribute?

The use of mathematical and computational tools in investigating Natural Killer (NK) cell biology and in general the immune system has increased steadily in the last few decades. However, unlike the physical sciences, there is a persistent ambivalence, which however is increasingly diminishing, in the biology community toward appreciating the utility of quantitative tools in addressing questions of biological importance. We survey some of the recent developments in the application of quantitative approaches for investigating different problems in NK cell biology and evaluate opportunities and challenges of using quantitative methods in providing biological insights in NK cell biology.

Mathematical modeling identifies Lck as a potential mediator for PD-1 induced inhibition of early TCR signaling

Programmed cell death-1 (PD-1) is an inhibitory immune checkpoint receptor that negatively regulates the functioning of T cell. Although the direct targets of PD-1 were not identified, its inhibitory action on the TCR signaling pathway was known much earlier. Recent experiments suggest that the PD-1 inhibits the TCR and CD28 signaling pathways at a very early stage ─ at the level of phosphorylation of the cytoplasmic domain of TCR and CD28 receptors. Here, we develop a mathematical model to investigate the influence of inhibitory effect of PD-1 on the activation of early TCR and CD28 signaling molecules. Proposed model recaptures several quantitative experimental observations of PD-1 mediated inhibition. Model simulations show that PD-1 imposes a net inhibitory effect on the Lck kinase. Further, the inhibitory effect of PD-1 on the activation of TCR signaling molecules such as Zap70 and SLP76 is significantly enhanced by the PD-1 mediated inhibition of Lck. These results suggest a critical role for Lck as a mediator for PD-1 induced inhibition of TCR signaling network. Multi parametric sensitivity analysis explores the effect of parameter uncertainty on model simulations.

NKG2D and Its Ligands: "One for All, All for One"

The activating receptor NKG2D is peculiar in its capability to bind to numerous and highly diversified MHC class I-like self-molecules. These ligands are poorly expressed on normal cells but can be induced on damaged, transformed or infected cells, with the final NKG2D ligand expression resulting from multiple levels of regulation. Although redundant molecular mechanisms can converge in the regulation of all NKG2D ligands, different stimuli can induce specific cellular responses, leading to the expression of one or few ligands. A large body of evidence demonstrates that NK cell activation can be triggered by different NKG2D ligands, often expressed on the same cell, suggesting a functional redundancy of these molecules. However, since a number of evasion mechanisms can reduce membrane expression of these molecules both on virus-infected and tumor cells, the co-expression of different ligands and/or the presence of allelic forms of the same ligand guarantee NKG2D activation in various stressful conditions and cell contexts. Noteworthy, NKG2D ligands can differ in their ability to down-modulate NKG2D membrane expression in human NK cells supporting the idea that NKG2D transduces different signals upon binding various ligands. Moreover, whether proteolytically shed and exosome-associated soluble NKG2D ligands share with their membrane-bound counterparts the same ability to induce NKG2D-mediated signaling is still a matter of debate. Here, we will review recent studies on the NKG2D/NKG2D ligand biology to summarize and discuss the redundancy and/or diversity in ligand expression, regulation, and receptor specificity.

Connecting the dots across time: reconstruction of single-cell signalling trajectories using time-stamped data

Single-cell responses are shaped by the geometry of signalling kinetic trajectories carved in a multidimensional space spanned by signalling protein abundances. It is, however, challenging to assay a large number (more than 3) of signalling species in live-cell imaging, which makes it difficult to probe single-cell signalling kinetic trajectories in large dimensions. Flow and mass cytometry techniques can measure a large number (4 to more than 40) of signalling species but are unable to track single cells. Thus, cytometry experiments provide detailed time-stamped snapshots of single-cell signalling kinetics. Is it possible to use the time-stamped cytometry data to reconstruct single-cell signalling trajectories? Borrowing concepts of conserved and slow variables from non-equilibrium statistical physics we develop an approach to reconstruct signalling trajectories using snapshot data by creating new variables that remain invariant or vary slowly during the signalling kinetics. We apply this approach to reconstruct trajectories using snapshot data obtained from in silico simulations, live-cell imaging measurements, and, synthetic flow cytometry datasets. The application of invariants and slow variables to reconstruct trajectories provides a radically different way to track objects using snapshot data. The approach is likely to have implications for solving matching problems in a wide range of disciplines.