Chimeric antigen receptor-T cell (CAR-T) therapy has been effective in the treatment of hematologic malignancies, but it has shown limited efficacy against solid tumors. Here we demonstrate an ...approach to enhancing CAR-T function in solid tumors by directly vaccine-boosting donor cells through their chimeric receptor in vivo. We designed amphiphile CAR-T ligands (amph-ligands) that, upon injection, trafficked to lymph nodes and decorated the surfaces of antigen-presenting cells, thereby priming CAR-Ts in the native lymph node microenvironment. Amph-ligand boosting triggered massive CAR-T expansion, increased donor cell polyfunctionality, and enhanced antitumor efficacy in multiple immunocompetent mouse tumor models. We demonstrate two approaches to generalizing this strategy to any chimeric antigen receptor, enabling this simple non-human leukocyte antigen-restricted approach to enhanced CAR-T functionality to be applied to existing CAR-T designs.
Gold and carbon make it together: Gold nanoclusters (GNCs) impregnated onto reduced graphene oxide (RGO) nanosheets cross swiftly across HepG2 hepatocarcinoma cell membranes to alter proteins and DNA ...and transport anticancer molecular drugs, such as doxorubicin (DOX).
Supramolecular self-assembly offers a powerful strategy to produce high-performance, stimuli-responsive nanomaterials. However, lack of molecular understanding of stimulated responses frequently ...hampers our ability to rationally design nanomaterials with sharp responses. Here we elucidated the molecular pathway of pH-triggered supramolecular self-assembly of a series of ultra-pH sensitive (UPS) block copolymers. Hydrophobic micellization drove divergent proton distribution in either highly protonated unimer or neutral micelle states along the majority of the titration coordinate unlike conventional small molecular or polymeric bases. This all-or-nothing two-state solution is a hallmark of positive cooperativity. Integrated modelling and experimental validation yielded a Hill coefficient of 51 in pH cooperativity for a representative UPS block copolymer, by far the largest reported in the literature. These data suggest hydrophobic micellization and resulting positive cooperativity offer a versatile strategy to convert responsive nanomaterials into binary on/off switchable systems for chemical and biological sensing, as demonstrated in an additional anion sensing model.
A multispectral hybrid nanotransistor consisting of modular fluorescent block copolymers with discrete and sharp pH transitions in one nanoparticluate system is presented. This nanotransistor probe ...allows digitized reporting of dynamic maturation at single‐organelle resolution over time. This nanotechnology platform offers a powerful tool in fundamental studies of organelle biology, cell signaling in diseases characterized by pH dysregulation in the endosomes or lysosomes.
Drugs that mirror the cellular effects of starvation mimics are considered promising therapeutics for common metabolic disorders, such as obesity, liver steatosis, and for ageing. Starvation, or ...caloric restriction, is known to activate the transcription factor EB (TFEB), a master regulator of lipid metabolism and lysosomal biogenesis and function. Here, we report a nanotechnology-enabled high-throughput screen to identify small-molecule agonists of TFEB and discover three novel compounds that promote autophagolysosomal activity. The three lead compounds include the clinically approved drug, digoxin; the marine-derived natural product, ikarugamycin; and the synthetic compound, alexidine dihydrochloride, which is known to act on a mitochondrial target. Mode of action studies reveal that these compounds activate TFEB via three distinct Ca
-dependent mechanisms. Formulation of these compounds in liver-tropic biodegradable, biocompatible nanoparticles confers hepatoprotection against diet-induced steatosis in murine models and extends lifespan of Caenorhabditis elegans. These results support the therapeutic potential of small-molecule TFEB activators for the treatment of metabolic and age-related disorders.
Nitrogen permease regulator-like 2 (NPRL2) is a component of a conserved complex that inhibits mTORC1 (mammalian Target Of Rapamycin Complex 1) in response to amino acid insufficiency. Here, we show ...that NPRL2 is required for mouse viability and that its absence significantly compromises fetal liver hematopoiesis in developing embryos. Moreover, NPRL2 KO embryos have significantly reduced methionine levels and exhibit phenotypes reminiscent of cobalamin (vitamin B12) deficiency. Consistent with this idea, NPRL2 KO liver and mouse embryonic fibroblasts (MEFs) show defective processing of the cobalamin-transport protein transcobalamin 2, along with impaired lysosomal acidification and lysosomal gene expression. NPRL2 KO MEFs exhibit a significant defect in the cobalamin-dependent synthesis of methionine from homocysteine, which can be rescued by supplementation with cyanocobalamin. Taken together, these findings demonstrate a role for NPRL2 and mTORC1 in the regulation of lysosomal-dependent cobalamin processing, methionine synthesis, and maintenance of cellular re-methylation potential, which are important during hematopoiesis.
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•Loss of NPRL2 results in defective liver hematopoiesis in the developing embryo•NPRL2 is necessary to repress mTORC1 activity during nutrient limitation•NPRL2 KO compromises lysosomal acidification•Lysosomal processing of cobalamin and methionine synthase are defective in NPRL2 KO
NPRL2 is a constituent of the conserved GATOR1 complex that inhibits mTORC1 signaling during amino acid starvation. Dutchak et al. show that loss of NPRL2 results in defective fetal liver hematopoiesis and compromises lysosomal acidification and processing of cobalamin, an essential cofactor for methionine synthase.
The challenge of data-driven synthesis of advanced nanomaterials can be minimized by using machine learning algorithms to optimize synthesis parameters and expedite the innovation process. In this ...study, a high-throughput robotic platform was employed to synthesize over 1356 gold nanorods with varying aspect ratios via a seedless approach. The developed models guided us in synthesizing gold nanorods with customized morphology, resulting in highly repeatable morphological yield with quantifiable structure-modulating precursor adjustments. The study provides insight into the dynamic relationships between key structure-modulating precursors and the structural morphology of gold nanorods based on the expected aspect ratio. The high-throughput robotic platform-fabricated gold nanorods demonstrated precise aspect ratio control when spectrophotometrically investigated and further validated with the transmission electron microscopy characterization. These findings demonstrate the potential of high-throughput robot-assisted synthesis and machine learning in the synthesis optimization of gold nanorods and aided in the development of models that can aid such synthesis of as-desired gold nanorods.
Technological advancements in recent decades have greatly transformed the field of material chemistry. Juxtaposing the accentuating energy demand with the pollution associated, urgent measures are ...required to ensure energy maximization, while reducing the extended experimental time cycle involved in energy production. In lieu of this, the prominence of catalysts in chemical reactions, particularly energy related reactions cannot be undermined, and thus it is critical to discover and design catalyst, towards the optimization of chemical processes and generation of sustainable energy. Most recently, artificial intelligence (AI) has been incorporated into several fields, particularly in advancing catalytic processes. The integration of intensive data set, machine learning models and robotics, provides a very powerful tool in modifying material synthesis and optimization by generating multifarious dataset amenable with machine learning techniques. The employment of robots automates the process of dataset and machine learning models integration in screening intermetallic surfaces of catalyst, with extreme accuracy and swiftness comparable to a number of human researchers. Although, the utilization of robots in catalyst discovery is still in its infancy, in this review we summarize current sway of artificial intelligence in catalyst discovery, briefly describe the application of databases, machine learning models and robots in this field, with emphasis on the consolidation of these monomeric units into a tripartite flow process. We point out current trends of machine learning and hybrid models of first principle calculations (DFT) for generating dataset, which is integrable into autonomous flow process of catalyst discovery. Also, we discuss catalyst discovery for renewable energy related reactions using this tripartite flow process with predetermined descriptors.
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BackgroundA major goal in cancer immunology is to rationally design combination therapies that lead to a higher response rate, especially for poorly immunogenic tumors that do not respond to immune ...checkpoint blockade therapy alone. We previously developed a combination therapeutic strategy, termed AIPV, consisting of a tumor-targeting antibody, a recombinant interleukin-2 with an extended half-life, an anti-PD-1 antibody, and a T cell vaccine 1. The full AIPV therapy can eradicate large, aggressive, poorly immunogenic tumors in multiple mouse tumor models. However, the exact cellular and molecular pathways involved in such an effective response remain poorly understood.MethodsIn this study, we used single-cell RNA-sequencing to define the detailed cellular and molecular changes in tumors and tumor-draining lymph nodes following the full AIPV therapy or a less effective sub-combination therapy in mice with poorly immunogenic B16F10 tumors.ResultsUsing our approach, we were able to uncover T cells, NK cells, neutrophils, macrophages/monocytes, classical dendritic cells, and plasmacytoid dendritic cells in tumors. We observed profound remodeling of every immune cell type following the effective therapeutic treatment. In particular, we found that classical dendritic cells take up tumor antigens, become activated, and migrate to draining lymph nodes following the AIPV therapy, but not following the less effective IPV therapy. We characterized the transcriptomic changes of these dendritic cells and found that they over-express molecules involved in antigen uptake.ConclusionsOur study comprehensively characterized a system that can overcome resistance to immune checkpoint blockade therapy, paving a cellular and molecular roadmap for immune-based therapeutic strategies that offer clinical benefits for poorly immunogenic tumors.ReferencesMoynihan KD, Opel CF, Szeto GL, Tzeng A, Zhu EF, Engreitz JM, et al. Eradication of large established tumors in mice by combination immunotherapy that engages innate and adaptive immune responses. Nat Med. 2016;22: 1402–1410.Ethics ApprovalAll mouse experiments were reviewed and approved by the Koch Institute and Broad Institute Animal Care and Use Committee (IACUC) (ID 0222-08-18).
Nature Communications 7: Article number: 13214 (2016); Published: 27 October 2016; Updated: 16 December 2016 Figure 5 of this article contained errors introduced during the production process. In ...Fig. 5c, the minimum value of the x axis (left hand side) should be −1.0 and not 1.0. Additionally, the maximum value of the y axis in Fig.
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