B7-H3-Targeting Chimeric Antigen Receptors Epstein Barr Virus Specific T Cells Provides a Tumor Agnostic Off-The-Shelf Therapy Against B7-H3 Positive Solid Tumors.

Encouraged by our observations of pronounced B7-H3 protein over-expression in many human solid tumors compared to healthy tissues, we focused on targeting B7-H3 with CAR T cells. We utilized a nanobody as the t B7-H3 targeting domain in our CAR construct to circumvent the stability issues associated with scFv-based domains. In efforts to expand patient access to CAR T cell therapy, we engineered our nanobody-based CAR into human Epstein-Barr Virus Specific T Cells (EBVSTs), offering a readily available off-the-shelf treatment. B7H3.CAR-armored EBVSTs demonstrated potent in vitro and in vivo activities against multiple B7-H3-positive human tumor cell lines and patient-derived xenograft models. Murine T cells expressing a murine equivalent of our B7H3.CAR exhibited no life-threatening toxicities in immunocompetent mice bearing syngeneic tumors. Further in vitro evaluation revealed that while human T, B and NK cells were unaffected by B7H3.CAR EBVSTs, monocytes were targeted due to upregulation of B7-H3. Such targeting of myeloid cells, which are key mediators of cytokine release syndrome (CRS), contributed to a low incidence of CRS in humanized mice after B7H3.CAR EBVST treatment. Notably, we showed that B7H3.CAR EBVSTs can target B7-H3 expressing myeloid-derived suppressor cells (MDSCs), thereby mitigating MDSC-driven immune suppression. In summary, our data demonstrate that our nanobody-based B7H3.CAR EBVSTs are effective as an off-the-shelf therapy for B7-H3 positive solid tumors. These cells also offer an avenue to modulate the immunosuppressive tumor microenvironment, highlighting their promising clinical potential in targeting solid tumors.

IBPGNET: lung adenocarcinoma recurrence prediction based on neural network interpretability.

Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer. Early-stage patients have a 30-50% probability of metastatic recurrence after surgical treatment. Here, we propose a new computational framework, Interpretable Biological Pathway Graph Neural Networks (IBPGNET), based on pathway hierarchy relationships to predict LUAD recurrence and explore the internal regulatory mechanisms of LUAD. IBPGNET can integrate different omics data efficiently and provide global interpretability. In addition, our experimental results show that IBPGNET outperforms other classification methods in 5-fold cross-validation. IBPGNET identified PSMC1 and PSMD11 as genes associated with LUAD recurrence, and their expression levels were significantly higher in LUAD cells than in normal cells. The knockdown of PSMC1 and PSMD11 in LUAD cells increased their sensitivity to afatinib and decreased cell migration, invasion and proliferation. In addition, the cells showed significantly lower EGFR expression, indicating that PSMC1 and PSMD11 may mediate therapeutic sensitivity through EGFR expression.

Deep learning of pretreatment multiphase CT images for predicting response to lenvatinib and immune checkpoint inhibitors in unresectable hepatocellular carcinoma.

Objectives: Combination therapy of lenvatinib and immune checkpoint inhibitors (CLICI) has emerged as a promising approach for managing unresectable hepatocellular carcinoma (HCC). However, the response to such treatment is observed in only a subset of patients, underscoring the pressing need for reliable methods to identify potential responders. Materials & methods: This was a retrospective analysis involving 120 patients with unresectable HCC. They were divided into training (n = 72) and validation (n = 48) cohorts. We developed an interpretable deep learning model using multiphase computed tomography (CT) images to predict whether patients will respond or not to CLICI treatment, based on the Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST v1.1). We evaluated the models' performance and analyzed the impact of each CT phase. Critical regions influencing predictions were identified and visualized through heatmaps. Results: The multiphase model outperformed the best biphase and uniphase models, achieving an area under the curve (AUC) of 0.802 (95% CI = 0.780-0.824). The portal phase images were found to significantly enhance the model's predictive accuracy. Heatmaps identified six critical features influencing treatment response, offering valuable insights to clinicians. Additionally, we have made this model accessible via a web server at http://uhccnet.com/ for ease of use. Conclusions: The integration of multiphase CT images with deep learning-generated heatmaps for predicting treatment response provides a robust and practical tool for guiding CLICI therapy in patients with unresectable HCC.

DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery.

Deep learning-based multi-omics data integration methods have the capability to reveal the mechanisms of cancer development, discover cancer biomarkers and identify pathogenic targets. However, current methods ignore the potential correlations between samples in integrating multi-omics data. In addition, providing accurate biological explanations still poses significant challenges due to the complexity of deep learning models. Therefore, there is an urgent need for a deep learning-based multi-omics integration method to explore the potential correlations between samples and provide model interpretability. Herein, we propose a novel interpretable multi-omics data integration method (DeepKEGG) for cancer recurrence prediction and biomarker discovery. In DeepKEGG, a biological hierarchical module is designed for local connections of neuron nodes and model interpretability based on the biological relationship between genes/miRNAs and pathways. In addition, a pathway self-attention module is constructed to explore the correlation between different samples and generate the potential pathway feature representation for enhancing the prediction performance of the model. Lastly, an attribution-based feature importance calculation method is utilized to discover biomarkers related to cancer recurrence and provide a biological interpretation of the model. Experimental results demonstrate that DeepKEGG outperforms other state-of-the-art methods in 5-fold cross validation. Furthermore, case studies also indicate that DeepKEGG serves as an effective tool for biomarker discovery. The code is available at https://github.com/lanbiolab/DeepKEGG.

Comparison of the effect between traditional conservation and nasointestinal tube placement in adhesive small bowel obstruction: A matched case-control study.

Adhesive small bowel obstruction (ASBO) causes a major burden in emergency medicine. Owing to in situ decompression, nasointestinal tube (NIT) placement has been increasingly used in clinical practice compared with traditional conservation (TC); however, the indications remain controversial. This study was designed to explore the indications for each treatment in ASBOs and then suggest the optimal strategy. After propensity score matching, 128 pairs were included (the NIT and TC groups). The occurrence of severe adverse events (SAEs), peri-treatment clinical parameters, and radiological features were compared between the successful and failed treatment groups. According to different stages of the entire treatment, the independent risk factors for adverse effects for ASBO were analysed in phase I and phase II. In phase I, normal red blood cells (RBC) levels (p = 0.011) and a balanced sodium ion level (p = 0.016) positively affected the outcomes of TC treatment. In phase II, for the TC group, the successful treatment rate reached 79.5% for patients with ASBOs whose normal RBC levels (p = 0.006) or decreasing white blood cells (WBC) levels (p = 0.014) after treatment. For the NIT group, the treatment success rate was 68.1% for patients whose electrolyte imbalance could be reversed or whose neutrophil count/lymphocyte ratio (NLR) levels was lower than 4.3 (p = 0.018). TC treatment is highly recommended for patients with normal RBC counts and sodium levels pretreatment. After dynamic monitoring of the treatment process, for both the TC and NIT groups, once ASBOs had elevated inflammatory biomarkers or irreversible electrolyte disturbances, surgical interference was preferred.

Aberrant non-canonical NF-κB signalling reprograms the epigenome landscape to drive oncogenic transcriptomes in multiple myeloma.

In multiple myeloma, abnormal plasma cells establish oncogenic niches within the bone marrow by engaging the NF-κB pathway to nurture their survival while they accumulate pro-proliferative mutations. Under these conditions, many cases eventually develop genetic abnormalities endowing them with constitutive NF-κB activation. Here, we find that sustained NF-κB/p52 levels resulting from such mutations favours the recruitment of enhancers beyond the normal B-cell repertoire. Furthermore, through targeted disruption of p52, we characterise how such enhancers are complicit in the formation of super-enhancers and the establishment of cis-regulatory interactions with myeloma dependencies during constitutive activation of p52. Finally, we functionally validate the pathological impact of these cis-regulatory modules on cell and tumour phenotypes using in vitro and in vivo models, confirming RGS1 as a p52-dependent myeloma driver. We conclude that the divergent epigenomic reprogramming enforced by aberrant non-canonical NF-κB signalling potentiates transcriptional programs beneficial for multiple myeloma progression.

IL-37 dampens immunosuppressive functions of MDSCs via metabolic reprogramming in the tumor microenvironment.

Interleukin-37 (IL-37) has been shown to inhibit tumor growth in various cancer types. However, the immune regulatory function of IL-37 in the tumor microenvironment is unclear. Here, we established a human leukocyte antigen-I (HLA-I)-matched humanized patient-derived xenograft hepatocellular carcinoma (HCC) model and three murine orthotopic HCC models to study the function of IL-37 in the tumor microenvironment. We found that IL-37 inhibited HCC growth and promoted T cell activation. Further study revealed that IL-37 impaired the immunosuppressive capacity of myeloid-derived suppressor cells (MDSCs). Pretreatment of MDSCs with IL-37 before adoptive transfer attenuated their tumor-promoting function in HCC tumor-bearing mice. Moreover, IL-37 promoted both glycolysis and oxidative phosphorylation in MDSCs, resulting in the upregulation of ATP release, which impaired the immunosuppressive capacity of MDSCs. Collectively, we demonstrated that IL-37 inhibited tumor development through dampening MDSCs' immunosuppressive capacity in the tumor microenvironment via metabolic reprogramming, making it a promising target for future cancer immunotherapy.

What are exposure biomarkers of rare earth elements for the ionic rare earth occupational population?

Rare earth elements (REEs) are widely utilized in industries. However, The specific exposure features of REEs and potential biomarkers of exposure in occupational populations remain unclear. In this study, we evaluated the external and internal REEs exposure levels among the participants working in the ionic rare earth smelting plant. For the external exposure, the concentrations of 14 REEs and total rare earth elements (ΣREEs) in airborne particles were significantly elevated in the REEs-exposed versus non-exposed group (P < 0.05). Meanwhile, the levels of Yttrium (Y), Gadolinium (Gd), Terbium (Tb), Dysprosium (Dy), Holmium (Ho), Thulium (Tm), Ytterbium (Yb), and ΣREEs in urine were higher in the REEs-exposed group compared to the non-exposed group (P < 0.05). Notably, a significant positive correlation was observed between Y in both the airborne particles and urine samples as well as Gd, and the Spearman correlation coefficient was 0.53 and 0.39 respectively, both P < 0.05. Conversely, no statistically significant differences were found in the levels of 15 REEs or ΣREEs in the blood samples between the REEs-exposed group and non-exposed group. Moreover, the concentrations of ΣREEs and 9 REEs in nail samples of the exposed group were significantly higher than those of the non-exposed group (P < 0.05), and the composition ratios of REEs in the nail samples closely resembled those found in individual airborne particles. Therefore, nail and urine samples were proposed to reflect long-term and short-term exposure to ionic rare earth respectively. Exposure biomarkers confirmed by external and internal exposure characteristics accurately provide the situation of human exposure to REEs environment, and have profound significance for monitoring and evaluating the level of REEs pollution in human body. It also provides a vital basis to find out the effect biomarkers, susceptible biomarkers and the health effects of rare earth environment for the future research.

Metformin-Mediated Fast Charge-Reversal Nanohybrid for Deep Penetration Piezocatalysis-Augmented Chemodynamic Immunotherapy of Cancer.

Immune checkpoint blockade (ICB) therapy still suffers from insufficient immune response and adverse effect of ICB antibodies. Chemodynamic therapy (CDT) has been demonstrated to be an effective way to synergize with ICB therapy. However, a low generation rate of reactive oxygen species and poor tumor penetration of CDT platforms still decline the immune effects. Herein, a charge-reversal nanohybrid Met@BF containing both Fe3O4 and BaTiO3 nanoparticles in the core and Metformin (Met) on the surface was fabricated for tumor microenvironment (TME)- and ultrasound (US)-activated piezocatalysis-chemodynamic immunotherapy of cancer. Interestingly, Met@BF had a negative charge in blood circulation, which was rapidly changed into positive when exposed to acidic TME attributed to quaternization of tertiary amine in Met, facilitating deep tumor penetration. Subsequently, with US irradiation, Met@BF produced H2O2 based on piezocatalysis of BaTiO3, which greatly enhanced the Fenton reaction of Fe3O4, thus boosting robust antitumor immune response. Furthermore, PD-L1 expression was inhibited by the local released Met to further augment the antitumor immune effect, achieving effective inhibitions for both primary and metastatic tumors. Such a combination of piezocatalysis-enhanced chemodynamic therapy and Met-mediated deep tumor penetration and downregulation of PD-L1 provides a promising strategy to augment cancer immunotherapy.

A semi-supervised approach for the integration of multi-omics data based on transformer multi-head self-attention mechanism and graph convolutional networks.

BACKGROUND AND OBJECTIVES: Comprehensive analysis of multi-omics data is crucial for accurately formulating effective treatment plans for complex diseases. Supervised ensemble methods have gained popularity in recent years for multi-omics data analysis. However, existing research based on supervised learning algorithms often fails to fully harness the information from unlabeled nodes and overlooks the latent features within and among different omics, as well as the various associations among features. Here, we present a novel multi-omics integrative method MOSEGCN, based on the Transformer multi-head self-attention mechanism and Graph Convolutional Networks(GCN), with the aim of enhancing the accuracy of complex disease classification. MOSEGCN first employs the Transformer multi-head self-attention mechanism and Similarity Network Fusion (SNF) to separately learn the inherent correlations of latent features within and among different omics, constructing a comprehensive view of diseases. Subsequently, it feeds the learned crucial information into a self-ensembling Graph Convolutional Network (SEGCN) built upon semi-supervised learning methods for training and testing, facilitating a better analysis and utilization of information from multi-omics data to achieve precise classification of disease subtypes. RESULTS: The experimental results show that MOSEGCN outperforms several state-of-the-art multi-omics integrative analysis approaches on three types of omics data: mRNA expression data, microRNA expression data, and DNA methylation data, with accuracy rates of 83.0% for Alzheimer's disease and 86.7% for breast cancer subtyping. Furthermore, MOSEGCN exhibits strong generalizability on the GBM dataset, enabling the identification of important biomarkers for related diseases. CONCLUSION: MOSEGCN explores the significant relationship information among different omics and within each omics' latent features, effectively leveraging labeled and unlabeled information to further enhance the accuracy of complex disease classification. It also provides a promising approach for identifying reliable biomarkers, paving the way for personalized medicine.

Potentiating Gilteritinib Efficacy Using Nanocomplexation with a Hyaluronic Acid-Epigallocatechin Gallate Conjugate.

Acute myeloid leukemia carrying FMS-like tyrosine kinase receptor-3 (FLT3) mutations is a fatal blood cancer with a poor prognosis. Although the FLT3 inhibitor gilteritinib has recently been approved, it still suffers from limited efficacy and relatively high nonresponse rates. In this study, we report the potentiation of gilteritinib efficacy using nanocomplexation with a hyaluronic acid-epigallocatechin gallate conjugate. The self-assembly, colloidal stability, and gilteritinib loading capacity of the nanocomplex were characterized by reversed-phase high-performance liquid chromatography and dynamic light scattering technique. Flow cytometric analysis revealed that the nanocomplex efficiently internalized into FLT3-mutated leukemic cells via specific interactions between the surface-exposed hyaluronic acid and CD44 receptor overexpressed on the cells. Moreover, this nanocomplex was found to induce an eradication of the leukemic cells in a synergistic manner by elevating the levels of reactive oxygen species and caspase-3/7 activities more effectively than free gilteritinib. This study may provide a useful strategy to design nanomedicines capable of augmenting the therapeutic efficacy of FLT3 inhibitors for effective leukemia therapy.

Quercetin ameliorates ferroptosis of rat cardiomyocytes via activation of the SIRT1/p53/SLC7A11 signaling pathway to alleviate sepsis­induced cardiomyopathy.

Sepsis­induced cardiomyopathy (SIC) is a manifestation of multiple organ failure as a result of sepsis and is a serious threat to life. Here, the effect and mechanisms of quercetin (QUE) in SIC were assessed. It was found that patients with SIC expressed lower serum levels of glutathione peroxidase 4 (GPX4) and SIRT1 but higher levels of CK­MB, cTnI, TNF­α, and IL­6 compared with healthy individuals. A dose of 80 µM QUE increased the viability and reduced the ferroptosis of H9C2 cells treated with 1.0 µg/ml LPS in vitro. The administration of QUE decreased the levels of MDA, NADPH, lipid peroxidation and cytoplasmic cytochrome C and upregulated the levels of GSH and TOM 20, thus exerting an anti­oxidative effect via mediating SIRT1 expression. It also activated the SIRT1/p53/SLC7A11 signaling pathway to reduce cellular Fe2+ and PTGS2 levels, decreased cell apoptosis rate, and upregulated the levels of GPX4 and ferritin to inhibit ferroptosis of H9C2 cells in vitro. Injection of QUE into rats activated the SIRT1/p53/SLC7A11 signaling pathway, reduced the levels of CK­MB, cTnI, inflammatory cell infiltration, MDA, NADPH, cytoplasmic cytochrome C, cellular Fe2+, and PTGS2 but upregulated the levels of GSH, TOM 20, GPX4, and ferritin to alleviate SIC in a dose­dependent manner in vivo. To conclude, QUE exerted an anti­ferroptotic effect via activation of the SIRT1/p53/SLC7A11 signaling pathway to dampen SIC both in vivo and in vitro. These findings highlighted a potential therapeutic strategy for the management of SIC.

Towards a better preclinical cancer model - human immune aging in humanized mice.

BACKGROUND: Preclinical models are often used for cancer studies and evaluation of novel therapeutics. The relevance of these models has vastly improved with mice bearing a human immune system, especially in the context of immunotherapy. Nonetheless, cancer is an age-related disease, and studies often overlook the effects of aging. Here we have established a humanized mouse model of human immune aging to investigate the role of this phenomenon on liver tumor dynamics. METHODS: Multiple organs and tissues (blood, thymus, lung, liver, spleen and bone marrow) were harvested from NOD-scid IL2rγ-/- (NIKO) mice reconstituted with human immune cells, over a period of 60 weeks post-birth, for immune profiling. Young and aging immune cells were compared for transcriptomic changes and functional differences. Effect of immune aging was investigated in a liver cancer humanized mouse model. RESULTS: Focusing on the T cell population, which is central to cancer immunosurveillance and immunotherapy, we showed that the proportion of naïve T cells declined while memory subsets and senescent-like cells increased with age. RNA-sequencing revealed that downregulated genes were related to immune responses and processes, and this was corroborated by reduced cytokine production in aging T cells. Finally, we showed faster liver tumor growth in aging than younger humanized mice, which could be attributed to specific pathways of aging T cell exhaustion. CONCLUSION: Our work improves on existing humanized (immune) mouse model and highlights the importance of considering immune aging in liver cancer modeling.

Expansion of human bone marrow-derived mesenchymal stromal cells with enhanced immunomodulatory properties.

BACKGROUND: Mesenchymal stromal cells (MSCs) have broad potential as a cell therapy including for the treatment of drug-resistant inflammatory conditions with abnormal T cell proliferation such as graft-versus-host disease (GVHD). Clinical success, however, has been complicated by the heterogeneity of culture-expanded MSCs as well as donor variability. Here, we devise culture conditions that promote expansion of MSCs with enhanced immunomodulatory functions both in vitro and in animal models of GVHD. METHODS: Human bone marrow-derived MSCs were expanded at high-confluency (MSCHC) and low-confluency state (MSCLC). Their immunomodulatory properties were evaluated with in vitro co-culture assays based on suppression of activated T cell proliferation and secretion of pro-inflammatory cytokines from activated T cells. Metabolic state of these cells was determined, while RNA sequencing was performed to explore transcriptome of these MSCs. Ex vivo expanded MSCHC or MSCLC was injected into human peripheral blood mononuclear cells (PBMC)-induced GVHD mouse model to determine their in vivo therapeutic efficacy based on clinical grade scoring, human CD45+ blood count and histopathological examination. RESULTS: As compared to MSCLC, MSCHC significantly reduced both the proliferation of anti-CD3/CD28-activated T cells and secretion of pro-inflammatory cytokines upon MSCHC co-culture across several donors even in the absence of cytokine priming. Mechanistically, metabolic analysis of MSCHC prior to co-culture with activated T cells showed increased glycolytic metabolism and lactate secretion compared to MSCLC, consistent with their ability to inhibit T cell proliferation. Transcriptome analysis further revealed differential expression of immunomodulatory genes including TRIM29, BPIFB4, MMP3 and SPP1 in MSCHC as well as enriched pathways including cytokine-cytokine receptor interactions, cell adhesion and PI3K-AKT signalling. Lastly, we demonstrate in a human PBMC-induced GVHD mouse model that delivery of MSCHC showed greater suppression of inflammation and improved outcomes compared to MSCLC and saline controls. CONCLUSION: Our study provides evidence that ex vivo expansion of MSCs at high confluency alters the metabolic and transcriptomic states of these cells. Importantly, this approach maximizes the production of MSCs with enhanced immunomodulatory functions without priming, thus providing a non-invasive and generalizable strategy for improving the use of MSCs for the treatment of inflammatory diseases.

Comparison of infection and human immune responses of two SARS-CoV-2 strains in a humanized hACE2 NIKO mouse model.

The COVID-19 pandemic has sickened millions, cost lives and has devastated the global economy. Various animal models for experimental infection with SARS-CoV-2 have played a key role in many aspects of COVID-19 research. Here, we describe a humanized hACE2 (adenovirus expressing hACE2) NOD-SCID IL2Rγ-/- (NIKO) mouse model and compare infection with ancestral and mutant (SARS-CoV-2-∆382) strains of SARS-CoV-2. Immune cell infiltration, inflammation, lung damage and pro-inflammatory cytokines and chemokines was observed in humanized hACE2 NIKO mice. Humanized hACE2 NIKO mice infected with the ancestral and mutant SARS-CoV-2 strain had lung inflammation and production of pro-inflammatory cytokines and chemokines. This model can aid in examining the pathological basis of SARS-CoV-2 infection in a human immune environment and evaluation of therapeutic interventions.

Cell Granularity Reflects Immune Cell Function and Enables Selection of Lymphocytes with Superior Attributes for Immunotherapy.

In keeping with the rule of "form follows function", morphological aspects of a cell can reflect its role. Here, it is shown that the cellular granularity of a lymphocyte, represented by its intrinsic side scatter (SSC), is a potent indicator of its cell state and function. The granularity of a lymphocyte increases from naïve to terminal effector state. High-throughput cell-sorting yields a SSChigh population that can mediate immediate effector functions, and a highly prolific SSClow population that can give rise to the replenishment of the memory pool. CAR-T cells derived from the younger SSClow population possess desirable attributes for immunotherapy, manifested by increased naïve-like cells and stem cell memory (TSCM )-like cells together with a balanced CD4/CD8 ratio, as well as enhanced target-killing in vitro and in vivo. Altogether, lymphocyte segregation based on biophysical properties is an effective approach for label-free selection of cells that share collective functions and can have important applications for cell-based immunotherapies.

Emerging Preclinical Applications of Humanized Mouse Models in the Discovery and Validation of Novel Immunotherapeutics and Their Mechanisms of Action for Improved Cancer Treatment.

Cancer therapeutics have undergone immense research over the past decade. While chemotherapies remain the mainstay treatments for many cancers, the advent of new molecular techniques has opened doors for more targeted modalities towards cancer cells. Although immune checkpoint inhibitors (ICIs) have demonstrated therapeutic efficacy in treating cancer, adverse side effects related to excessive inflammation are often reported. There is a lack of clinically relevant animal models to probe the human immune response towards ICI-based interventions. Humanized mouse models have emerged as valuable tools for pre-clinical research to evaluate the efficacy and safety of immunotherapy. This review focuses on the establishment of humanized mouse models, highlighting the challenges and recent advances in these models for targeted drug discovery and the validation of therapeutic strategies in cancer treatment. Furthermore, the potential of these models in the process of uncovering novel disease mechanisms is discussed.

Cryo-EM structure of the polyphosphate polymerase VTC reveals coupling of polymer synthesis to membrane transit.

The eukaryotic vacuolar transporter chaperone (VTC) complex acts as a polyphosphate (polyP) polymerase that synthesizes polyP from adenosine triphosphate (ATP) and translocates polyP across the vacuolar membrane to maintain an intracellular phosphate (Pi ) homeostasis. To discover how the VTC complex performs its function, we determined a cryo-electron microscopy structure of an endogenous VTC complex (Vtc4/Vtc3/Vtc1) purified from Saccharomyces cerevisiae at 3.1 Å resolution. The structure reveals a heteropentameric architecture of one Vtc4, one Vtc3, and three Vtc1 subunits. The transmembrane region forms a polyP-selective channel, likely adopting a resting state conformation, in which a latch-like, horizontal helix of Vtc4 limits the entrance. The catalytic Vtc4 central domain is located on top of the pseudo-symmetric polyP channel, creating a strongly electropositive pathway for nascent polyP that can couple synthesis to translocation. The SPX domain of the catalytic Vtc4 subunit positively regulates polyP synthesis by the VTC complex. The noncatalytic Vtc3 regulates VTC through a phosphorylatable loop. Our findings, along with the functional data, allow us to propose a mechanism of polyP channel gating and VTC complex activation.

Nanocomplexes of Biodegradable Anticancer Macromolecules: Prolonged Plasma Half-Life, Reduced Toxicity, and Increased Tumor Targeting.

Anticancer drug resistance is a large contributing factor to the global mortality rate of cancer patients. Anticancer macromolecules such as polymers have been recently reported to overcome this issue. Anticancer macromolecules have unselective toxicity because they are highly positively charged. Herein, an anionic biodegradable polycarbonate carrier is synthesized and utilized to form nanocomplexes with an anticancer polycarbonate via self-assembly to neutralize its positive charges. Biotin is conjugated to the anionic carrier and serves as cancer cell-targeting moiety. The nanoparticles have sizes of < 130 nm with anticancer polymer loading levels of 38-49%. Unlike the small molecular anticancer drug doxorubicin, the nanocomplexes effectively inhibit the growth of both drug-susceptible MCF7 and drug-resistant MCF7/ADR human breast cancer cell lines with low half maximal inhibitory concentration (IC50 ). The nanocomplexes increase the anticancer polymer's in vivo half-life from 1 to 6-8 h, and rapidly kill BT474 human breast cancer cells primarily via an apoptotic mechanism. The nanocomplexes significantly increase the median lethal dose (LD50 ) and reduce the injection site toxicity of the anticancer polymer. They suppress tumor growth by 32-56% without causing any damage to the liver and kidneys. These nanocomplexes may potentially be used for cancer treatment to overcome drug resistance.

IL12/18/21 Preactivation Enhances the Antitumor Efficacy of Expanded γδT Cells and Overcomes Resistance to Anti-PD-L1 Treatment.

γδT cells are promising candidates for cellular immunotherapy due to their immune regulation through cytokine production and MHC-independent direct cytotoxicity against a broad spectrum of tumors. However, current γδT cell-based cancer immunotherapy has limited efficacy, and novel strategies are needed to improve clinical outcomes. Here, we report that cytokine pretreatment with IL12/18, IL12/15/18, IL12/18/21, and IL12/15/18/21 effectively enhanced the activation and cytotoxicity of in vitro-expanded murine and human γδT cells. However, only adoptive transfer of IL12/18/21 preactivated γδT cells significantly inhibited tumor growth in a murine melanoma model and a hepatocellular carcinoma model. Both IL12/18/21 preactivated antibody-expanded and zoledronate-expanded human γδT cells effectively controlled tumor growth in a humanized mouse model. IL12/18/21 preactivation promoted γδT cell proliferation and cytokine production in vivo and enhanced IFNγ production and activation of endogenous CD8+ T cells in a cell-cell contact- and ICAM-1-dependent manner. Furthermore, the adoptive transfer of IL12/18/21 preactivated γδT cells could overcome the resistance to anti-PD-L1 therapy, and the combination therapy had a synergistic effect on the therapeutic outcomes. Moreover, the enhanced antitumor function of adoptively transferred IL12/18/21 preactivated γδT cells was largely diminished in the absence of endogenous CD8+ T cells when administered alone or in combination with anti-PD-L1, suggesting a CD8+ T cell-dependent mechanism. Taken together, IL12/18/21 preactivation can promote γδT cell antitumor function and overcome the resistance to checkpoint blockade therapy, indicating an effective combinational cancer immunotherapeutic strategy.