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Scott C McCormick,1,* Namid Stillman,1,* Matthew Hockley,1 Adam W Perriman,2 Sabine Hauert1 1Engineering Mathematics, University of Bristol, Bristol, BS8 1UB, UK; 2Biomedical Sciences, University of Bristol, Bristol, BS8 1TD, UK*These authors contributed equally to this workCorrespondence: Sabine HauertEngineering Mathematics, University of Bristol, Bristol, BS8 1UB, UKEmail sabine.hauert@bristol.ac.ukBackground: In cancer nanomedicine, drugs are transported by nanocarriers through a biological system to produce a therapeutic effect. The efficacy of the treatment is affected by the ability of the nanocarriers to overcome biological transport barriers to reach their target. In this work, we focus on the process of nanocarrier penetration through tumour tissue after extravasation. Visualising the dynamics of nanocarriers in tissue is difficult in vivo, and in vitro assays often do not capture the spatial and physical constraints relevant to model tissue penetration.Methods: We propose a new simple, low-cost method to observe the transport dynamics of nanoparticles through a tissue-mimetic microfluidic chip. After loading a chip with triplicate conditions of gel type and loading with microparticles, microscopic analysis allows for tracking of fluorescent nanoparticles as they move through hydrogels (Matrigel and Collagen I) with and without cell-sized microparticles. A bespoke image-processing codebase written in MATLAB allows for statistical analysis of this tracking, and time-dependent dynamics can be determined.Results: To demonstrate the method, we show size-dependence of transport mechanics can be observed, with diffusion of fluorescein dye throughout the channel in 8 h, while 20 nm carboxylate FluoSphere diffusion was hindered through both Collagen I and Matrigel™. Statistical measurements of the results are generated through the software package and show the significance of both size and presence of microparticles on penetration depth.Conclusion: This provides an easy-to-understand output for the end user to measure nanoparticle tissue penetration, enabling the first steps towards future automated experimentation of transport dynamics for rational nanocarrier design.Keywords: nanomedicine, microfluidics, transport barriers, tissue penetration, image processing, fast-prototyping

Receptor tyrosine kinase-like orphan receptor 1 (ROR1) is a tumour target currently used for the development of novel therapeutic modalities, such as antibody-drug conjugates, chimeric antigen receptor T-cell therapies, and others. Success of these new drugs depends on the selection of relevant indications based on ROR1 tumour prevalence, staining heterogeneity, and subcellular localization, among other parameters. We investigated ROR1 immunophenotype using validated antibody clones for immunohistochemistry (IHC) and flow cytometry (FC), analyzing 292 tumour specimens from 7 haematological malignancies and triple negative breast cancer (TNBC) as a reference solid tumour indication. ROR1 prevalence varied significantly across distinct tumour types, showing 100% of ROR1 positivity in all chronic lymphocytic leukaemia (n = 48) and hairy cell leukaemia (n = 14) specimens analyzed via FC with ranges between 1.1-99.8% and 0.8-62.1%, respectively. Samples analysed via IHC showed ROR1 membrane/cytoplasmic positivity in 44% of mantle cell lymphoma tumour samples (n = 27; H-score range: 10-285 in positive cases); 30% in TNBC (n = 46; H-score range: 1-200); 15% in diffuse large B-cell lymphoma (n = 45; H-score: 40-250); and 11% in follicular lymphoma (n = 34; H-score: 2-300). Finally, all acute myeloid leukaemia (n = 52) and most T-cell non-Hodgkin lymphoma (n = 31/32) tested samples were negative for ROR1 via IHC. In conclusion, ROR1 shows a heterogeneous tumour cell expression profile across multiple leukaemias and lymphomas, making it a tumour target that would require different patient selection strategies to develop novel therapeutic modalities., Competing Interests: This work was funded by Boehringer-Ingelheim GmbH, the employer of Manuel A. Silva, Lorenz Waldmeier and Yarúa Jaimes. Shuntae Williams, Sylvie Hauert, and Hytham Al-Masri are employed by Hematogenix. Benjamin Ovadia and Indu Gupta are employed by NeoGenomics. There are no patents, products in development or marketed products to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2024 Silva et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The past decade has seen efforts to develop new forms of autonomous systems with varying applications in different domains, from underwater search and rescue to clinical diagnosis. All of these applications require risk analyses, but such analyses often focus on technical sources of risk without acknowledging its wider systemic and organizational dimensions. In this article, we illustrate this deficit and a way of redressing it by offering a more systematic analysis of the sociotechnical sources of risk in an autonomous system. To this end, the article explores the development, deployment, and operation of an autonomous robot swarm for use in a public cloakroom in light of Macrae's structural, organizational, technological, epistemic, and cultural framework of sociotechnical risk. We argue that this framework provides a useful tool for capturing the complex "nontechnical" dimensions of risk in this domain that might otherwise be overlooked in the more conventional risk analyses that inform regulation and policymaking., (© 2024 The Author(s). Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.)

Biofilms are responsible for most chronic infections and are highly resistant to antibiotic treatments. Previous studies have demonstrated that periodic dosing of antibiotics can help sensitize persistent subpopulations and reduce the overall dosage required for treatment. Because the dynamics and mechanisms of biofilm growth and the formation of persister cells are diverse and are affected by environmental conditions, it remains a challenge to design optimal periodic dosing regimens. Here, we develop a computational agent-based model to streamline this process and determine key parameters for effective treatment. We used our model to test a broad range of persistence switching dynamics and found that if periodic antibiotic dosing was tuned to biofilm dynamics, the dose required for effective treatment could be reduced by nearly 77%. The biofilm architecture and its response to antibiotics were found to depend on the dynamics of persister cells. Despite some differences in the response of biofilm governed by different persister switching rates, we found that a general optimized periodic treatment was still effective in significantly reducing the required antibiotic dose. As persistence becomes better quantified and understood, our model has the potential to act as a foundation for more effective strategies to target bacterial infections.

The ability to optically interact with cells on both an individual and collective level has applications from wound healing to cancer treatment. Building systems that can facilitate both localised light illumination and visualisation of cells can, however, be challenging and costly. This work takes the Dynamic Optical MicroEnvironment (DOME), an existing platform for the closed-loop optical control of microscale agents, and adapts the design to support live-cell imaging. Through modifications made to the imaging and projection systems within the DOME, a significantly higher resolution, alternative imaging channels and the ability to customise light wavelengths are achieved (Bio-DOME). This is accompanied by an interactive calibration procedure that is robust to changes in the hardware configuration and provides fluorescence imaging (Fluoro-DOME). These alterations to the fundamental design allow for long-term use of the DOME in an environment of higher temperature and humidity. Thus, long-term imaging of living cells in a wound, with closed-loop control of real-time frontier illumination via projected light patterns, is facilitated., Supplementary Information: The online version contains supplementary material available at 10.1007/s12213-024-00165-0., Competing Interests: Competing interestsThe authors declare no competing interests., (© The Author(s) 2024.)

In recent years it has become possible to design snakebite antivenoms with diverse pharmacokinetic properties. Owing to the pharmacokinetic variability of venoms, the choice of antivenom scaffold may influence a treatment's neutralisation coverage. Computation offers a useful medium through which to assess the pharmacokinetics and pharmacodynamics of envenomation-treatment systems, as antivenoms with identical neutralising capacities can be simulated. In this study, we simulate envenomation and treatment with a variety of antivenoms, to define the properties of effective antivenoms. Systemic envenomation and treatment were described using a two-compartment pharmacokinetic model. Treatment of Naja sumatrana and Cryptelytrops purpureomaculatus envenomation was simulated with a set of 200,000 theoretical antivenoms across 10 treatment time delays. These two venoms are well-characterised and have differing pharmacokinetic properties. The theoretical antivenom set varied across molecular weight, dose, k on , k off , and valency. The best and worst treatments were identified using an area under the curve metric, and a global sensitivity analysis was performed to quantify the influence of the input parameters on treatment outcome. The simulations show that scaffolds of diverse molecular formats can be effective. Molecular weight and valency have a negligible direct impact on treatment outcome, however low molecular weight scaffolds offer more flexibility across the other design parameters, particularly when treatment is delayed. The simulations show k on to primarily mediate treatment efficacy, with rates above 10 5  M -1 s -1 required for the most effective treatments. k off has the greatest impact on the performance of less effective scaffolds. While the same scaffold preferences for improved treatment are seen for both model snakes, the parameter bounds for C. purpureomaculatus envenomation are more constrained. This paper establishes a computational framework for the optimisation of antivenom design., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Immune checkpoint immunotherapy (ICI) can re-activate immune reactions against neoantigens, leading to remarkable remission in cancer patients. Nevertheless, only a minority of patients are responsive to ICI, and approaches for prediction of responsiveness are needed to improve the success of cancer treatments. While the tumor mutational burden (TMB) correlates positively with responsiveness and survival of patients undergoing ICI, the influence of the subcellular localizations of the neoantigens remains unclear. Here, we demonstrate in both a mouse melanoma model and human clinical datasets of 1,722 ICI-treated patients that a high proportion of membrane-localized neoantigens, particularly at the plasma membrane, correlate with responsiveness to ICI therapy and improved overall survival across multiple cancer types. We further show that combining membrane localization and TMB analyses can enhance the predictability of cancer patient response to ICI. Our results may have important implications for establishing future clinical guidelines to direct the choice of treatment toward ICI., Competing Interests: Declaration of interests The University of Chicago has filed for patent protection for biomarkers described in this work, of which P.S.B., Z.G., S.H., and J.A.H. are inventors., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Many invertebrates are ideal model systems on which to base robot design principles due to their success in solving seemingly complex tasks across domains while possessing smaller nervous systems than vertebrates. Three areas are particularly relevant for robot designers: Research on flying and crawling invertebrates has inspired new materials and geometries from which robot bodies (their morphologies) can be constructed, enabling a new generation of softer, smaller, and lighter robots. Research on walking insects has informed the design of new systems for controlling robot bodies (their motion control) and adapting their motion to their environment without costly computational methods. And research combining wet and computational neuroscience with robotic validation methods has revealed the structure and function of core circuits in the insect brain responsible for the navigation and swarming capabilities (their mental faculties) displayed by foraging insects. The last decade has seen significant progress in the application of principles extracted from invertebrates, as well as the application of biomimetic robots to model and better understand how animals function. This Perspectives paper on the past 10 years of the Living Machines conference outlines some of the most exciting recent advances in each of these fields before outlining lessons gleaned and the outlook for the next decade of invertebrate robotic research., (Creative Commons Attribution license.)

The lateral line system of fishes provides cues for collective behaviour, such as shoaling, but it remains unclear how anatomical lateral line variation leads to behavioural differences among species. Here we studied associations between lateral line morphology and collective behaviour using two morphologically divergent species and their second-generation hybrids. We identify collective behaviours associated with variation in canal and superficial lateral line morphology, with closer proximities to neighbouring fish associated with larger canal pore sizes and fewer superficial neuromasts. A mechanistic understanding of the observed associations was provided by hydrodynamic modelling of an artificial lateral line sensor, which showed that simulated canal-based neuromasts were less susceptible to saturation during unidirectional movement than simulated superficial neuromasts, while increasing the canal pore size of the simulated lateral line sensor elevated sensitivity to vortices shed by neighbouring fish. Our results propose a mechanism behind lateral line flow sensing during collective behaviour in fishes., (© 2023 The Authors.)

Recent technological advances in micro-robotics have demonstrated their immense potential for biomedical applications. Emerging micro-robots have versatile sensing systems, flexible locomotion and dexterous manipulation capabilities that can significantly contribute to the healthcare system. Despite the appreciated and tangible benefits of medical micro-robotics, many challenges still remain. Here, we review the major challenges, current trends and significant achievements for developing versatile and intelligent micro-robotics with a focus on applications in early diagnosis and therapeutic interventions. We also consider some recent emerging micro-robotic technologies that employ synthetic biology to support a new generation of living micro-robots. We expect to inspire future development of micro-robots toward clinical translation by identifying the roadblocks that need to be overcome., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhang, Gorochowski, Marucci, Lee, Gil, Li, Hauert and Yeatman.)

Underwater robot sensing is challenging due to the complex and noisy nature of the environment. The lateral line system in fish allows them to robustly sense their surroundings, even in turbid and turbulent environments, allowing them to perform tasks such as shoaling or foraging. Taking inspiration from the lateral line system in fish to design robot sensors could help to power underwater robots in inspection, exploration, or environmental monitoring tasks. Previous studies have designed systems that mimic both the design and the configuration of the lateral line and neuromasts, but at high cost or using complex procedures. Here, we present a simple, low cost, bio-inspired sensor, that can detect passing vortices shed from surrounding obstacles or upstream fish or robots. We demonstrate the importance of the design elements used, and show a minimum 20% reduction in residual error over sensors lacking these elements. Results were validated in reality using a prototype of the artificial lateral line sensor. These results mark an important step in providing alternate methods of control in underwater vehicles that are simultaneously inexpensive and simple to manufacture., (Creative Commons Attribution license.)

Brain tumours are the biggest cancer killer in those under 40 and reduce life expectancy more than any other cancer. Blood-based liquid biopsies may aid early diagnosis, prediction and prognosis for brain tumours. It remains unclear whether known blood-based biomarkers, such as glial fibrillary acidic protein (GFAP), have the required sensitivity and selectivity. We have developed a novel in silico model which can be used to assess and compare blood-based liquid biopsies. We focused on GFAP, a putative biomarker for astrocytic tumours and glioblastoma multi-formes (GBMs). In silico modelling was paired with experimental measurement of cell GFAP concentrations and used to predict the tumour volumes and identify key parameters which limit detection. The average GBM volumes of 449 patients at Leeds Teaching Hospitals NHS Trust were also measured and used as a benchmark. Our model predicts that the currently proposed GFAP threshold of 0.12 ng ml -1 may not be suitable for early detection of GBMs, but that lower thresholds may be used. We found that the levels of GFAP in the blood are related to tumour characteristics, such as vasculature damage and rate of necrosis, which are biological markers of tumour aggressiveness. We also demonstrate how these models could be used to provide clinical insight.

Snakebite envenomation is responsible for over 100,000 deaths and 400,000 cases of disability annually, most of which are preventable through access to safe and effective antivenoms. Snake venom toxins span a wide molecular weight range, influencing their absorption, distribution, and elimination within the body. In recent years, a range of scaffolds have been applied to antivenom development. These scaffolds similarly span a wide molecular weight range and subsequently display diverse pharmacokinetic behaviours. Computational simulations represent a powerful tool to explore the interplay between these varied antivenom scaffolds and venoms, to assess whether a pharmacokinetically optimal antivenom exists. The purpose of this study was to establish a computational model of systemic snakebite envenomation and treatment, for the quantitative assessment and comparison of conventional and next-generation antivenoms. A two-compartment mathematical model of envenomation and treatment was defined and the system was parameterised using existing data from rabbits. Elimination and biodistribution parameters were regressed against molecular weight to predict the dynamics of IgG, F(ab') 2 , Fab, scFv, and nanobody antivenoms, spanning a size range of 15-150 kDa. As a case study, intramuscular envenomation by Naja sumatrana (equatorial spitting cobra) and its treatment using Fab, F(ab') 2 , and IgG antivenoms was simulated. Variable venom dose tests were applied to visualise effective antivenom dose levels. Comparisons to existing antivenoms and experimental rescue studies highlight the large dose reductions that could result from recombinant antivenom use. This study represents the first comparative in silico model of snakebite envenomation and treatment., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In melanoma, the induction of lymphatic growth (lymphangiogenesis) has long been correlated with metastasis and poor prognosis, but we recently showed it can synergistically enhance cancer immunotherapy and boost T cell immunity. Here, we develop a translational approach for exploiting this "lymphangiogenic potentiation" of immunotherapy in a cancer vaccine using lethally irradiated tumor cells overexpressing vascular endothelial growth factor C (VEGF-C) and topical adjuvants. Our "VEGFC vax" induced extensive local lymphangiogenesis and promoted stronger T cell activation in both the intradermal vaccine site and draining lymph nodes, resulting in higher frequencies of antigen-specific T cells present systemically than control vaccines. In mouse melanoma models, VEGFC vax elicited potent tumor-specific T cell immunity and provided effective tumor control and long-term immunological memory. Together, these data introduce the potential of lymphangiogenesis induction as a novel immunotherapeutic strategy to consider in cancer vaccine design., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

Many complex behaviors in biological systems emerge from large populations of interacting molecules or cells, generating functions that go beyond the capabilities of the individual parts. Such collective phenomena are of great interest to bioengineers due to their robustness and scalability. However, engineering emergent collective functions is difficult because they arise as a consequence of complex multi-level feedback, which often spans many length-scales. Here, we present a perspective on how some of these challenges could be overcome by using multi-agent modeling as a design framework within synthetic biology. Using case studies covering the construction of synthetic ecologies to biological computation and synthetic cellularity, we show how multi-agent modeling can capture the core features of complex multi-scale systems and provide novel insights into the underlying mechanisms which guide emergent functionalities across scales. The ability to unravel design rules underpinning these behaviors offers a means to take synthetic biology beyond single molecules or cells and toward the creation of systems with functions that can only emerge from collectives at multiple scales., (Copyright © 2020 Gorochowski, Hauert, Kreft, Marucci, Stillman, Tang, Bandiera, Bartoli, Dixon, Fedorec, Fellermann, Fletcher, Foster, Giuggioli, Matyjaszkiewicz, McCormick, Montes Olivas, Naylor, Rubio Denniss and Ward.)

Many real-world applications have been suggested in the swarm robotics literature. However, there is a general lack of understanding of what needs to be done for robot swarms to be useful and trusted by users in reality. This paper aims to investigate user perception of robot swarms in the workplace, and inform design principles for the deployment of future swarms in real-world applications. Three qualitative studies with a total of 37 participants were done across three sectors: fire and rescue, storage organization, and bridge inspection. Each study examined the users' perceptions using focus groups and interviews. In this paper, we describe our findings regarding: the current processes and tools used in these professions and their main challenges; attitudes toward robot swarms assisting them; and the requirements that would encourage them to use robot swarms. We found that there was a generally positive reaction to robot swarms for information gathering and automation of simple processes. Furthermore, a human in the loop is preferred when it comes to decision making. Recommendations to increase trust and acceptance are related to transparency, accountability, safety, reliability, ease of maintenance, and ease of use. Finally, we found that mutual shaping, a methodology to create a bidirectional relationship between users and technology developers to incorporate societal choices in all stages of research and development, is a valid approach to increase knowledge and acceptance of swarm robotics. This paper contributes to the creation of such a culture of mutual shaping between researchers and users, toward increasing the chances of a successful deployment of robot swarms in the physical realm., (Copyright © 2020 Carrillo-Zapata, Milner, Hird, Tzoumas, Vardanega, Sooriyabandara, Giuliani, Winfield and Hauert.)

Therapeutic cancer vaccines constitute a valuable tool to educate the immune system to fight tumors and prevent cancer relapse. Nevertheless, the number of cancer vaccines in the clinic remains very limited to date, highlighting the need for further technology development. Recently, cancer vaccines have been improved by the use of materials, which can strongly enhance their intrinsic properties and biodistribution profile. Moreover, vaccine efficacy and safety can be substantially modulated through selection of the site at which they are delivered, which fosters the engineering of materials capable of targeting cancer vaccines to specific relevant sites, such as within the tumor or within lymphoid organs, to further optimize their immunotherapeutic effects. In this review, we aim to give the reader an overview of principles and current strategies to engineer therapeutic cancer vaccines, with a particular focus on the use of site-specific targeting materials. We will first recall the goal of therapeutic cancer vaccination and the type of immune responses sought upon vaccination, before detailing key components of cancer vaccines. We will then present how materials can be engineered to enhance the vaccine's pharmacokinetic and pharmacodynamic properties. Finally, we will discuss the rationale for site-specific targeting of cancer vaccines and provide examples of current targeting technologies., (Copyright © 2020 Briquez, Hauert, de Titta, Gray, Alpar, Swartz and Hubbell.)

Area coverage and collective exploration are key challenges for swarm robotics. Previous research in this field has drawn inspiration from ant colonies, with real, or more commonly virtual, pheromones deposited into a shared environment to coordinate behaviour through stigmergy. Repellent pheromones can facilitate rapid dispersal of robotic agents, yet this has been demonstrated only for relatively small swarm sizes ( N < 30). Here, we report findings from swarms of real robots (Kilobots) an order of magnitude larger ( N > 300) and from realistic simulation experiments up to N = 400. We identify limitations to stigmergy in a spatially constrained, high-density environment-a free but bounded two-dimensional workspace-using repellent binary pheromone. At larger N and higher densities, a simple stigmergic avoidance algorithm becomes first no better, then inferior to, the area coverage of non-interacting random walkers. Thus, the assumption of robustness and scalability for such approaches may need to be re-examined when they are working at a high density caused by ever-increasing swarm sizes. Instead, subcellular biology, and diffusive processes, may prove a better source of inspiration at large N in high agent density environments., Competing Interests: We declare we have no competing interests., (© 2019 The Authors.)

Treatment of patients bearing human papillomavirus (HPV)-related cancers with synthetic long-peptide (SLP) therapeutic vaccines has shown promising results in clinical trials against premalignant lesions, whereas responses against later stage carcinomas have remained elusive. We show that conjugation of a well-documented HPV-E7 SLP to ultra-small polymeric nanoparticles (NP) enhances the antitumor efficacy of therapeutic vaccination in different mouse models of HPV + cancers. Immunization of TC-1 tumor-bearing mice with a single dose of NP-conjugated E7LP (NP-E7LP) generated a larger pool of E7-specific CD8 + T cells with increased effector functions than unconjugated free E7LP. At the tumor site, NP-E7LP prompted a robust infiltration of CD8 + T cells that was not accompanied by concomitant accumulation of regulatory T cells (Tregs), resulting in a higher CD8 + T-cell to Treg ratio. Consequently, the amplified immune response elicited by the NP-E7LP formulation led to increased regression of large, well-established tumors, resulting in a significant percentage of complete responses that were not achievable by immunizing with the non-NP-conjugated long-peptide. The partial responses were characterized by distinct phases of regression, stable disease, and relapse to progressive growth, establishing a platform to investigate adaptive resistance mechanisms. The efficacy of NP-E7LP could be further improved by therapeutic activation of the costimulatory receptor 4-1BB. This NP-E7LP formulation illustrates a "solid-phase" antigen delivery strategy that is more effective than a conventional free-peptide ("liquid") vaccine, further highlighting the potential of using such formulations for therapeutic vaccination against solid tumors. Cancer Immunol Res; 6(11); 1301-13. ©2018 AACR ., (©2018 American Association for Cancer Research.)

We introduce the Xpuck swarm, a research platform with an aggregate raw processing power in excess of two teraflops. The swarm uses 16 e-puck robots augmented with custom hardware that uses the substantial CPU and GPU processing power available from modern mobile system-on-chip devices. The augmented robots, called Xpucks, have at least an order of magnitude greater performance than previous swarm robotics platforms. The platform enables new experiments that require high individual robot computation and multiple robots. Uses include online evolution or learning of swarm controllers, simulation for answering what-if questions about possible actions, distributed super-computing for mobile platforms, and real-world applications of swarm robotics that requires image processing, or SLAM. The teraflop swarm could also be used to explore swarming in nature by providing platforms with similar computational power as simple insects. We demonstrate the computational capability of the swarm by implementing a fast physics-based robot simulator and using this within a distributed island model evolutionary system, all hosted on the Xpucks., (Copyright © 2018 Jones, Studley, Hauert and Winfield.)

In melanoma, vascular endothelial growth factor-C (VEGF-C) expression and consequent lymphangiogenesis correlate with metastasis and poor prognosis. VEGF-C also promotes tumor immunosuppression, suggesting that lymphangiogenesis inhibitors may be clinically useful in combination with immunotherapy. We addressed this concept in mouse melanoma models with VEGF receptor-3 (VEGFR-3)-blocking antibodies and unexpectedly found that VEGF-C signaling enhanced rather than suppressed the response to immunotherapy. We further found that this effect was mediated by VEGF-C-induced CCL21 and tumor infiltration of naïve T cells before immunotherapy because CCR7 blockade reversed the potentiating effects of VEGF-C. In human metastatic melanoma, gene expression of VEGF-C strongly correlated with CCL21 and T cell inflammation, and serum VEGF-C concentrations associated with both T cell activation and expansion after peptide vaccination and clinical response to checkpoint blockade. We propose that VEGF-C potentiates immunotherapy by attracting naïve T cells, which are locally activated upon immunotherapy-induced tumor cell killing, and that serum VEGF-C may serve as a predictive biomarker for immunotherapy response., (Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Nanoparticle delivery systems are known to enhance the immune response to soluble antigens (Ags) and are thus a promising tool for the development of new vaccines. Our laboratory has engineered two different nanoparticulate systems in which Ag is either encapsulated within the core of polymersomes (PSs) or decorated onto the surface of nanoparticles (NPs). Previous studies showed that PSs are better at enhancing CD4 T cells and antibody titers, while NPs preferentially augment cytotoxic CD8 T cells. Herein, we demonstrate that the differential activation of T cell immunity reflects differences in the modes of intracellular trafficking and distinct biodistribution of the Ag in lymphoid organs, which are both driven by the properties of each nanocarrier. Furthermore, we found that Ags within PSs promoted better CD4 T cell activation and induced a higher frequency of CD4 T follicular helper (Tfh) cells. These differences correlated with changes in the frequency of germinal center B cells and plasma cell formation, which reflects the previously observed antibody titers. Our results show that PSs are a promising vector for the delivery of Ags for B cell vaccine development. This study demonstrates that nanocarrier design has a large impact on the quality of the induced adaptive immune response., (Copyright © 2017. Published by Elsevier Ltd.)

Nanoparticles are designed to deliver therapeutics and diagnostics selectively to tumors. Their size, shape, charge, material, coating, and cargo determine their individual functionalities. A systems approach could help predict the behavior of trillions of nanoparticles interacting in complex tumor environments. Engineering these nanosystems may lead to biomimetic strategies where interactions between nanoparticles and their environment give rise to cooperative behaviors typically seen in natural self-organized systems. Examples include nanoparticles that communicate the location of a tumor to amplify tumor homing or self-assemble and disassemble to optimize nanoparticle transport. The challenge is to discover which nanoparticle designs lead to a desired system behavior. To this end, novel nanomaterials, deep understanding of biology, and computational tools are emerging as the next frontier., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Targeted nanoparticles are increasingly being engineered for the treatment of cancer. By design, they can passively accumulate in tumors, selectively bind to targets in their environment, and deliver localized treatments. However, the penetration of targeted nanoparticles deep into tissue can be hindered by their slow diffusion and a high binding affinity. As a result, they often localize to areas around the vessels from which they extravasate, never reaching the deep-seeded tumor cells, thereby limiting their efficacy. To increase tissue penetration and cellular accumulation, we propose generalizable guidelines for nanoparticle design and validate them using two different computer models that capture the potency, motion, binding kinetics, and cellular internalization of targeted nanoparticles in a section of tumor tissue. One strategy that emerged from the models was delaying nanoparticle binding until after the nanoparticles have had time to diffuse deep into the tissue. Results show that nanoparticles that are designed according to these guidelines do not require fine-tuning of their kinetics or size and can be administered in lower doses than classical targeted nanoparticles for a desired tissue penetration in a large variety of tumor scenarios. In the future, similar models could serve as a testbed to explore engineered tissue-distributions that arise when large numbers of nanoparticles interact in a tumor environment.

Tumor-targeted delivery of siRNA remains a major barrier in fully realizing the therapeutic potential of RNA interference. While cell-penetrating peptides (CPP) are promising siRNA carrier candidates, they are universal internalizers that lack cell-type specificity. Herein, we design and screen a library of tandem tumor-targeting and cell-penetrating peptides that condense siRNA into stable nanocomplexes for cell type-specific siRNA delivery. Through physiochemical and biological characterization, we identify a subset of the nanocomplex library of that are taken up by cells via endocytosis, trigger endosomal escape and unpacking of the carrier, and ultimately deliver siRNA to the cytosol in a receptor-specific fashion. To better understand the structure-activity relationships that govern receptor-specific siRNA delivery, we employ computational regression analysis and identify a set of key convergent structural properties, namely the valence of the targeting ligand and the charge of the peptide, that help transform ubiquitously internalizing cell-penetrating peptides into cell type-specific siRNA delivery systems.

The consistency of care brought about by the AHA standards created order from the chaos that previously existed in the areas of BLS, CPR, and ACLS. But significant difficulties arise when they are applied directly to pre-arrival instructions given by EMSs.