Rac1/ROCK-driven membrane dynamics promote natural killer cell cytotoxicity via granzyme-induced necroptosis

RAC1high NK cell-based immunotherapy in hepatocellular carcinoma via STAT3-NKG2D axis

Natural killer (NK) cells exert an indispensable role in innate immune responses against cancer progression, however NK cell dysfunction has been rarely reported in hepatocellular carcinoma (HCC). This study sought to uncover the immunoregulatory mechanisms of tumor-infiltrating NK cells in HCC. A consensus NK cell-based signature (NKS) was constructed using integrative machine learning algorithms based on multi-omics data of HCC patients. HCC tumors had lower numbers of infiltrating NK cells than para-tumor normal liver tissues. Based on the NK cell-associated genes, the NKS was built for HCC prognostic prediction and clinical utilities. Drug targets and novel compounds were then identified for high-NKS groups. RAC1 was confirmed as the hub gene in the NKS genes. RAC1 was upregulated in HCC tumors and positively correlated with shorter survival time. RAC1 overexpression in NK-92 cells facilitated the cancer-killing capacity by the anticancer cytotoxic effectors and the upregulated NKG2D. The survival time of PDX-bearing mice was also prolonged upon NK-92RAC1 cells. Mechanistically, RAC1 interacted with STAT3 and facilitated its activation, thereby enabling its binding to the promoter region of NKG2D and functioning as a transcriptional regulator in NK-92 via molecular docking, Co-IP assay, CHIP and luciferase experiments. Collectively, our study describes a novel function of RAC1 in potentiating NK cell-mediated cytotoxicity against HCC, highlighting the clinical utilities of NKS score and RAC1high NK cell subset in HCC immunotherapy.

An Improved Two-Shot Tracking Algorithm for Dynamics Analysis of Natural Killer Cells in Tumor Contexts

Natural killer cells (NKCs) are non-specific immune lymphocytes with diverse morphologies. Their broad killing effect on cancer cells has led to increased attention towards activating NKCs for anticancer immunotherapy. Consequently, understanding the motion characteristics of NKCs under different morphologies and modeling their collective dynamics under cancer cells has become crucial. However, tracking small NKCs in complex backgrounds poses significant challenges, and conventional industrial tracking algorithms often perform poorly on NKC tracking datasets. There remains a scarcity of research on NKC dynamics. In this paper, we utilize deep learning techniques to analyze the morphology of NKCs and their key points. After analyzing the shortcomings of common industrial multi-object tracking algorithms like DeepSORT in tracking natural killer cells, we propose Distance Cascade Matching and the Re-Search method to improve upon existing algorithms, yielding promising results. Through processing and tracking over 5000 frames of images, encompassing approximately 300,000 cells, we preliminarily explore the impact of NKCs' cell morphology, temperature, and cancer cell environment on NKCs' motion, along with conducting basic modeling. The main conclusions of this study are as follows: polarized cells are more likely to move along their polarization direction and exhibit stronger activity, and the maintenance of polarization makes them more likely to approach cancer cells; under equilibrium, NK cells display a Boltzmann distribution on the cancer cell surface.

Membrane Fluctuation Model for Understanding the Effect of Receptor Nanoclustering on the Activation of Natural Killer Cells through Biomechanical Feedback

We investigated the role of ligand clustering and density in the activation of natural killer (NK) cells. To that end, we designed reductionist arrays of nanopatterned ligands arranged with different cluster geometries and densities and probed their effects on NK cell activation. We used these arrays as an artificial microenvironment for the stimulation of NK cells and studied the effect of the array geometry on the NK cell immune response. We found that ligand density significantly regulated NK cell activation while ligand clustering had an impact only at a specific density threshold. We also rationalized these findings by introducing a theoretical membrane fluctuation model that considers biomechanical feedback between ligand-receptor bonds and the cell membrane. These findings provide important insight into NK cell mechanobiology, which is fundamentally important and essential for designing immunotherapeutic strategies targeting cancer.

The mechanobiology of NK cells- 'Forcing NK to Sense' target cells

Natural killer (NK) cells are innate immune lymphocytes that recognize and kill cancer and infected cells, which makes them unique 'off-the-shelf' candidates for a new generation of immunotherapies. Biomechanical forces in homeostasis and pathophysiology accrue additional immune regulation for NK immune responses. Indeed, cellular and tissue biomechanics impact NK receptor clustering, cytoskeleton remodeling, NK transmigration through endothelial cells, nuclear mechanics, and even NK-dendritic cell interaction, offering a plethora of unexplored yet important dynamic regulation for NK immunotherapy. Such events are made more complex by the heterogeneity of human NK cells. A significant question remains on whether and how biochemical and biomechanical cues collaborate for NK cell mechanotransduction, a process whereby mechanical force is sensed, transduced, and translated to downstream mechanical and biochemical signalling. Herein, we review recent advances in understanding how NK cells perceive and mechanotransduce biophysical cues. We focus on how the cellular cytoskeleton crosstalk regulates NK cell function while bearing in mind the heterogeneity of NK cells, the direct and indirect mechanical cues for NK anti-tumor activity, and finally, engineering advances that are of translational relevance to NK cell biology at the systems level.

Cytotoxic and chemotactic dynamics of NK cells quantified by live-cell imaging

Natural Killer (NK) cells detect and eliminate virus-infected cells and cancer cells, and are crucial players of the human immune defense system. Although the relevant molecular machineries involved in NK cell activation and NK-target cell interactions are largely known, how their collective signaling modulates the dynamic behaviors of NK cells, e.g., motility and cytotoxicity, and the rate-limiting kinetics involved are still in need of comprehensive investigations. In traditional bulk killing assays, heterogeneity and kinetic details of individual NK-target cell interactions are masked, seriously limiting analysis of the underlying dynamic mechanisms. Here we present detailed protocols of a number of live-cell imaging assays using fluorescent protein reporters and/or a live-cell dye that enable the acquisition of quantitative kinetic data at the single cell level for elucidating the mechanism underlying the interaction dynamics of primary human NK cells and epithelial cancer cells. Moreover, we discuss how the imaging data can be analyzed either alone or in combination to quantify and determine the key dynamic steps/intermediates involved in specific NK cell activity, e.g., NK cell cytotoxic modes and their associated kinetics, and NK cell motility toward different cancer targets. These live-cell imaging assays can be easily adapted to analyze the rate-limiting kinetics and heterogeneity of other cell-cell interaction dynamics, e.g., in T cell function.

Single-cell RNA sequencing of CSF reveals neuroprotective RAC1+ NK cells in Parkinson’s disease

Brain infiltration of the natural killer (NK) cells has been observed in several neurodegenerative disorders, including Parkinson’s disease (PD). In a mouse model of α-synucleinopathy, it has been shown that NK cells help in clearing α-synuclein (α-syn) aggregates. This study aimed to investigate the molecular mechanisms underlying the brain infiltration of NK cells in PD. Immunofluorescence assay was performed using the anti-NKp46 antibody to detect NK cells in the brain of PD model mice. Next, we analyzed the publicly available single-cell RNA sequencing (scRNA-seq) data (GSE141578) of the cerebrospinal fluid (CSF) from patients with PD to characterize the CSF immune landscape in PD. Results showed that NK cells infiltrate the substantia nigra (SN) of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD model mice and colocalize with dopaminergic neurons and α-syn. Moreover, the ratio of NK cells was found to be increased in the CSF of PD patients. Analysis of the scRNA-seq data revealed that Rac family small GTPase 1 (RAC1) was the most significantly upregulated gene in NK cells from PD patients. Furthermore, genes involved in regulating SN development were enriched in RAC1⁺ NK cells and these cells showed increased brain infiltration in MPTP-induced PD mice. In conclusion, NK cells actively home to the SN of PD model mice and RAC1 might be involved in regulating this process. Moreover, RAC1⁺ NK cells play a neuroprotective role in PD.

Cross-talk between necroptosis-related lncRNAs to construct a novel signature and predict the immune landscape of lung adenocarcinoma patients

Background: As a new style of cell death, necroptosis plays a crucial role in tumor immune microenvironment. LncRNAs have been identified to act as competitive RNAs to influence genes involved in necroptosis. Therefore, we aim to create a signature based on necroptosis-related lncRNAs to predict the prognosis and immune landscape of lung adenocarcinoma (LUAD) patients in this study.

Methods: TCGA database was used to acquire RNA sequencing (RNA-Seq) data and clinical information for 59 lung normal samples and 535 lung adenocarcinoma samples. The Pearson correlation analysis, univariate cox regression analysis and least absolute shrinkage and selection operator (LASSO) cox regression were performed to construct the prognostic NRlncRNAs signature. Then we used Kaplan-Meier (K-M) analysis, time-dependent ROC curves, univariate and multivariate cox regression analysis, and nomogram to validate this signature. In addition, GO, KEGG, and GSVA were analyzed to investigate the potential molecular mechanism. Moreover, we analyzed the relationship between our identified signature and immune microenvironment, TMB, and some clinical characteristics. Finally, we detected the expression of the six necroptosis-related lncRNAs in cells and tissues.

Results: We constructed a NRlncRNAs signature consisting of six lncRNAs (FRMD6-AS1, LINC01480, FAM83A-AS1, FRMD6-AS1, MED4-AS1, and LINC01415) in LUAD. LUAD patients with high risk scores had lower chance of survival with an AUC of 0.739, 0.709, and 0.733 for 1-year, 3-year, and 5-year respectively. The results based on GO, KEGG, and GSVA enrichment analysis demonstrated that NRlncRNAs signature-related genes were mainly correlated with immune pathways, metabolic-and cell growth-related pathways, cell cycle, and apoptosis. Moreover, the risk score was correlated with the immune status of LUAD patients. Patients with higher risk scores had lower ESTIMATE scores and higher TIDE scores. The risk score was positively correlated with TMB. LINC01415, FRMD6-AS1 and FAM83A-AS1 were significantly overexpressed in lung adenocarcinoma, while the expression levels of MED4-AS1 and LINC01480 were lower in lung adenocarcinoma.

Conclusion: Overall, an innovative prognostic signature based on NRlncRNAs was developed for LUAD through comprehensive bioinformatics analysis, which can act as a predictor of immunotherapy and may provide guidance for clinicians.

Phosphatidylcholine Liposomes Down-Modulate CD4 Expression Reducing HIV Entry in Human Type-1 Macrophages

A strategy adopted to combat human immunodeficiency virus type-1 (HIV-1) infection is based on interfering with virus entry into target cells. In this study, we found that phosphatidylcholine (PC) liposomes reduced the expression of the CD4 receptor in human primary type-1 macrophages but not in CD4⁺ T cells. The down-regulation was specific to CD4, as any effect was not observed in CCR5 membrane expression. Moreover, the reduction of membrane CD4 expression required the Ca²⁺-independent protein kinase C (PKC), which in turn mediated serine phosphorylation in the intracytoplasmic tail of the CD4 receptor. Serine phosphorylation of CD4 was also associated with its internalization and degradation in acidic compartments. Finally, the observed CD4 downregulation induced by PC liposomes in human primary macrophages reduced the entry of both single-cycle replication and replication competent R5 tropic HIV-1. Altogether, these results show that PC liposomes reduce HIV entry in human macrophages and may impact HIV pathogenesis by lowering the viral reservoir.

Rho-Kinase as a Target for Cancer Therapy and Its Immunotherapeutic Potential

Cancer immunotherapy is fast rising as a prominent new pillar of cancer treatment, harnessing the immune system to fight against numerous types of cancer. Rho-kinase (ROCK) pathway is involved in diverse cellular activities, and is therefore the target of interest in various diseases at the cellular level including cancer. Indeed, ROCK is well-known for its involvement in the tumor cell and tumor microenvironment, especially in its ability to enhance tumor cell progression, migration, metastasis, and extracellular matrix remodeling. Importantly, ROCK is also considered to be a novel and effective modulator of immune cells, although further studies are needed. In this review article, we describe the various activities of ROCK and its potential to be utilized in cancer treatment, particularly in cancer immunotherapy, by shining a light on its activities in the immune system.

So many ways to naturally kill a cancer cell

Natural killer (NK) cells participate in cancer immunosurveillance and cancer immunotherapy. Live cell imaging of cancer cells targeted by NK cells, published today in BMC Biology by Zhu et al., reveals a remarkable diversity of programmed cell death pathways induced in individual cells. Pathway choice depends on the state of the target cell actin cytoskeleton and a novel death pathway, granzyme-induced necroptosis, could be of broad importance in cancer immunotherapy.