Cross-Modal Imaging Reveals Nanoparticle Uptake Dynamics in Hematopoietic Bone Marrow during Inflammation.

Nanoparticles have been employed to elucidate the innate immune cell biology and trace cells accumulating at inflammation sites. Inflammation prompts innate immune cells, the initial responders, to undergo rapid turnover and replenishment within the hematopoietic bone marrow. Yet, we currently lack a precise understanding of how inflammation affects cellular nanoparticle uptake at the level of progenitors of innate immune cells in the hematopoietic marrow. To bridge this gap, we aimed to develop imaging tools to explore the uptake dynamics of fluorescently labeled cross-linked iron oxide nanoparticles in the bone marrow niche under varying degrees of inflammation. The inflammatory models included mice that received intramuscular lipopolysaccharide injections to induce moderate inflammation and streptozotocin-induced diabetic mice with additional intramuscular lipopolysaccharide injections to intensify inflammation. In vivo magnetic resonance imaging (MRI) and fluorescence imaging revealed an elevated level of nanoparticle uptake at the bone marrow as the levels of inflammation increased. The heightened uptake of nanoparticles within the inflamed marrow was attributed to enhanced permeability and retention with increased nanoparticle intake by hematopoietic progenitor cells. Moreover, intravital microscopy showed increased colocalization of nanoparticles within slowly patrolling monocytes in these inflamed hematopoietic marrow niches. Our discoveries unveil a previously unknown role of the inflamed hematopoietic marrow in enhanced storage and rapid deployment of nanoparticles, which can specifically target innate immune cells at their production site during inflammation. These insights underscore the critical function of the hematopoietic bone marrow in distributing iron nanoparticles to innate immune cells during inflammation. Our findings offer diagnostic and prognostic value, identifying the hematopoietic bone marrow as an imaging biomarker for early detection in inflammation imaging, advancing personalized clinical care.

Extending the boundaries of cancer therapeutic complexity with literature text mining.

Drug combination therapy is a main pillar of cancer therapy. As the number of possible drug candidates for combinations grows, the development of optimal high complexity combination therapies (involving 4 or more drugs per treatment) such as RCHOP-I and FOLFIRINOX becomes increasingly challenging due to combinatorial explosion. In this paper, we propose a text mining (TM) based tool and workflow for rapid generation of high complexity combination treatments (HCCT) in order to extend the boundaries of complexity in cancer treatments. Our primary objectives were: (1) Characterize the existing limitations in combination therapy; (2) Develop and introduce the Plan Builder (PB) to utilize existing literature for drug combination effectively; (3) Evaluate PB's potential in accelerating the development of HCCT plans. Our results demonstrate that researchers and experts using PB are able to create HCCT plans at much greater speed and quality compared to conventional methods. By releasing PB, we hope to enable more researchers to engage with HCCT planning and demonstrate its clinical efficacy.

Linkage between Psychological Factors and Response to Immune Checkpoint Inhibitor Therapy: A Preliminary Study.

Substantial evidence has accumulated showing that psychological distress affects immune regulation, the response to cancer treatment, and survival. The effect of psychological parameters on the effectiveness of immune checkpoint inhibitor (ICI) treatment has not yet been studied. This preliminary study aimed to (a) examine the associations between psychological factors and responses to ICI treatment and (b) assess the associations between psychological factors and blood measures of sPD-1, sCTLA-4, and cytokines that may alter the effect of ICI treatment. The participants were 62 individuals with advanced cancer, aged 18 years or older, who were candidates for ICI treatment as a new line of treatment. The participants answered questionnaires and provided blood samples and medical data prior to the start of ICI treatment and 3 months after. Perceived health status was positively associated with better responses to ICI treatment. In the subsample of participants with biomarkers, worse health-related quality of life was associated with higher IL-6 and sCTLA-4; emotional distress and sleep difficulties were associated with higher sCTLA-4; and better perceived health was associated with lower IL-6 and TNFα. sPD-1 was not associated with psychological measures. This preliminary study found for the first time that some psychological measures could be linked to responses to cancer treatment, possibly via pro-inflammatory cytokines and sCTLA-4.

Prediction of cancer nanomedicines self-assembled from meta-synergistic drug pairs.

Combination therapy is widely used in cancer medicine due to the benefits of drug synergy and the reduction of acquired resistance. To minimize emergent toxicities, nanomedicines containing drug combinations are being developed, and they have shown encouraging results. However, developing multi-drug loaded nanoparticles is highly complex and lacks predictability. Previously, it was shown that single drugs can self-assemble with near-infrared dye, IR783, to form cancer-targeted nanoparticles. A structure-based predictive model showed that only 4% of the drug space self-assembles with IR783. Here, we mapped the self-assembly outcomes of 77 small molecule drugs and drug pairs with IR783. We found that the small molecule drug space can be divided into five types, and type-1 drugs self-assemble with three out of four possible drug types that do not form stable nanoparticles. To predict the self-assembly outcome of any drug pair, we developed a machine learning model based on decision trees, which was trained and tested with F1-scores of 89.3% and 87.2%, respectively. We used literature text mining to capture drug pairs with biological synergy together with synergistic chemical self-assembly and generated a database with 1985 drug pairs for 70 cancers. We developed an online search tool to identify cancer-specific, meta-synergistic drug pairs (both chemical and biological synergism) and validated three different pairs in vitro. Lastly, we discovered a novel meta-synergistic pair, bortezomib-cabozantinib, which formed stable nanoparticles with improved biodistribution, efficacy, and reduced toxicity, even over single drugs, in an in vivo model of head and neck cancer.

From centralized to ad-hoc knowledge base construction for hypotheses generation.

OBJECTIVE: To demonstrate and develop an approach enabling individual researchers or small teams to create their own ad-hoc, lightweight knowledge bases tailored for specialized scientific interests, using text-mining over scientific literature, and demonstrate the effectiveness of these knowledge bases in hypothesis generation and literature-based discovery (LBD). METHODS: We propose a lightweight process using an extractive search framework to create ad-hoc knowledge bases, which require minimal training and no background in bio-curation or computer science. These knowledge bases are particularly effective for LBD and hypothesis generation using Swanson's ABC method. The personalized nature of the knowledge bases allows for a somewhat higher level of noise than "public facing" ones, as researchers are expected to have prior domain experience to separate signal from noise. Fact verification is shifted from exhaustive verification of the knowledge base to post-hoc verification of specific entries of interest, allowing researchers to assess the correctness of relevant knowledge base entries by considering the paragraphs in which the facts were introduced. RESULTS: We demonstrate the methodology by constructing several knowledge bases of different kinds: three knowledge bases that support lab-internal hypothesis generation: Drug Delivery to Ovarian Tumors (DDOT); Tissue Engineering and Regeneration; Challenges in Cancer Research; and an additional comprehensive, accurate knowledge base designated as a public resource for the wider community on the topic of Cell Specific Drug Delivery (CSDD). In each case, we show the design and construction process, along with relevant visualizations for data exploration, and hypothesis generation. For CSDD and DDOT we also show meta-analysis, human evaluation, and in vitro experimental evaluation. CONCLUSION: Our approach enables researchers to create personalized, lightweight knowledge bases for specialized scientific interests, effectively facilitating hypothesis generation and literature-based discovery (LBD). By shifting fact verification efforts to post-hoc verification of specific entries, researchers can focus on exploring and generating hypotheses based on their expertise. The constructed knowledge bases demonstrate the versatility and adaptability of our approach to versatile research interests. The web-based platform, available at https://spike-kbc.apps.allenai.org, provides researchers with a valuable tool for rapid construction of knowledge bases tailored to their needs.

P-selectin-targeted nanocarriers induce active crossing of the blood-brain barrier via caveolin-1-dependent transcytosis.

Medulloblastoma is the most common malignant paediatric brain tumour, with ~30% mediated by Sonic hedgehog signalling. Vismodegib-mediated inhibition of the Sonic hedgehog effector Smoothened inhibits tumour growth but causes growth plate fusion at effective doses. Here, we report a nanotherapeutic approach targeting endothelial tumour vasculature to enhance blood-brain barrier crossing. We use fucoidan-based nanocarriers targeting endothelial P-selectin to induce caveolin-1-dependent transcytosis and thus nanocarrier transport into the brain tumour microenvironment in a selective and active manner, the efficiency of which is increased by radiation treatment. In a Sonic hedgehog medulloblastoma animal model, fucoidan-based nanoparticles encapsulating vismodegib exhibit a striking efficacy and marked reduced bone toxicity and drug exposure to healthy brain tissue. Overall, these findings demonstrate a potent strategy for targeted intracranial pharmacodelivery that overcomes the restrictive blood-brain barrier to achieve enhanced tumour-selective penetration and has therapeutic implications for diseases within the central nervous system.

Polydopamine Copolymers for Stable Drug Nanoprecipitation.

Polydopamine (PDA), a biomaterial inspired by marine mussels, has attracted interest in cancer nanomedicine due to its photothermal properties, nanoparticle coating, and pi-pi stacking-based drug encapsulation abilities. Despite numerous one-pot and post-polymerization modifications, PDA copolymers have not been sufficiently studied in the context of stabilizing hydrophobic drugs in the process of nanoprecipitation. In this study, we tested combinatorial panels of comonomers with PDA to optimize drug loading efficiency, particle size and stability of nano formulations made via drug nanoprecipitation. As a selection criterion for optimal comonomers, we used drug aggregation-induced emission (AIE). We identified 1,1,2-Trimethyl-3-(4-sulfobutyl)benz[e]indolium (In820) as a novel and highly useful comonomer for catecholamines and optimized the conditions for its incorporation into PDA copolymers used for drug nanoprecipitation. Surprisingly, it was superior to polyethylene glycol modifications in every aspect. The leading copolymer, poly(dopamine)-poly(L-dopa)-co-In820 (PDA-PDO-In820 1:1:1), was shown to be a good stabilizer for several hydrophobic drugs. The resulting nanoparticles showed stability for up to 15 days, high encapsulation efficiency of at least 80%, low toxicity, and high antitumor efficacy in vitro. Nanoprecipitation of hydrophobic drugs can be greatly enhanced by the use of PDA copolymers containing In820, which are easy-to-prepare and highly effective stabilizers.

Automated discovery of nanomaterials via drug aggregation induced emission.

Nanoformulations of small molecule drugs are essential to effectively deliver them and treat a wide range of diseases. They are normally complex to develop, lack predictability, and exhibit low drug loading. Recently, nanoparticles made via co-assembly of hydrophobic drugs and organic dyes, exhibited drug-loading of up to 90% with high predictability from the drug structure. However, these particles have relatively short stability and can formulate only a small fraction of the drug space. Here, we developed an automated workflow to synthesize and select novel dye stabilizers, based on their ability to inhibit drug aggregation-induced emission (AIE). We first screened and identified 10 drugs with previously unknown strong AIE activity and exploited this trait to automatically synthesize and select a new ultra-stabilizer named R595. Interestingly, it shares several synthetic similarities and advantages with polydopamine. We found that R595 is superior to myriad types of excipients and solubilizers such as cyclodextrins, poloxamers, albumin, and previously published organic dyes, in both long-term stability and drug compatibility. We investigated the biodistribution, pharmacokinetics, safety and efficacy of the AIEgenic MEK inhibitor trametinib-R595 nanoparticles in vitro and in vivo and demonstrated that they are non-toxic and effective in KRAS driven colon and lung cancer models.

Merging data curation and machine learning to improve nanomedicines.

Nanomedicine design is often a trial-and-error process, and the optimization of formulations and in vivo properties requires tremendous benchwork. To expedite the nanomedicine research progress, data science is steadily gaining importance in the field of nanomedicine. Recently, efforts have explored the potential to predict nanomaterials synthesis and biological behaviors via advanced data analytics. Machine learning algorithms process large datasets to understand and predict various material properties in nanomedicine synthesis, pharmacologic parameters, and efficacy. "Big data" approaches may enable even larger advances, especially if researchers capitalize on data curation methods. However, the concomitant use of data curation processes needed to facilitate the acquisition and standardization of large, heterogeneous data sets, to support advanced data analytics methods such as machine learning has yet to be leveraged. Currently, data curation and data analytics areas of nanotechnology-focused data science, or 'nanoinformatics', have been proceeding largely independently. This review highlights the current efforts in both areas and the potential opportunities for coordination to advance the capabilities of data analytics in nanomedicine.

Targeted drug delivery strategies for precision medicines.

Progress in the field of precision medicine has changed the landscape of cancer therapy. Precision medicine is propelled by technologies that enable molecular profiling, genomic analysis, and optimized drug design to tailor treatments for individual patients. Although precision medicines have resulted in some clinical successes, the use of many potential therapeutics has been hindered by pharmacological issues, including toxicities and drug resistance. Drug delivery materials and approaches have now advanced to a point where they can enable the modulation of a drug's pharmacological parameters without compromising the desired effect on molecular targets. Specifically, they can modulate a drug's pharmacokinetics, stability, absorption, and exposure to tumours and healthy tissues, and facilitate the administration of synergistic drug combinations. This Review highlights recent progress in precision therapeutics and drug delivery, and identifies opportunities for strategies to improve the therapeutic index of cancer drugs, and consequently, clinical outcomes.

Laser-induced thermal response and controlled release of copper oxide nanoparticles from multifunctional polymeric nanocarriers.

Multifunctional nanocarriers have attracted considerable interest in improving cancer treatment outcomes. Poly(lactide-co-glycolide) (PLGA) nanospheres encapsulating copper oxide nanoparticles (CuO-NPs) are characterized by antitumor activity and exhibit dual-modal contrast-enhancing capabilities. An in vitro evaluation demonstrates that this delivery system allows controlled and sustained release of CuO-NPs. To achieve localized release on demand, an external stimulation by laser irradiation is suggested. Furthermore, to enable simultaneous complementary photothermal therapy, polydopamine (PDA) coating for augmented laser absorption is proposed. To this aim, two formulations of CuO-NPs loaded nanospheres are prepared from PLGA polymers RG-504 H (H-PLGA) and RG-502 H (L-PLGA) as scaffolds for surface modification through in situ polymerization of dopamine and then PEGylation. The obtained CuO-NPs-based multifunctional nanocarriers are characterized, and photothermal effects are examined as a function of wavelength and time. The results show that 808 nm laser irradiation of the coated nanospheres yields maximal temperature elevation (T = 41°C) and stimulates copper release at a much faster rate compared to non-irradiated formulations. Laser-triggered CuO-NP release is mainly depended on the PLGA core, resulting in faster release with L-PLGA, which also yielded potent anti-tumor efficacy in head and neck cancer cell line (Cal-33). In conclusion, the suggested multifunctional nanoplatform offers the integrated benefits of diagnostic imaging and laser-induced drug release combined with thermal therapy.

From sleep medicine to medicine during sleep-a clinical perspective.

Objective. In this perspective paper, we aim to highlight the potential of sleep as an auspicious time for diagnosis, management and therapy of non-sleep-specific pathologies.Approach. Sleep has a profound influence on the physiology of body systems and biological processes. Molecular studies have shown circadian-regulated shifts in protein expression patterns across human tissues, further emphasizing the unique functional, behavioral and pharmacokinetic landscape of sleep. Thus, many pathological processes are also expected to exhibit sleep-specific manifestations. Modern advances in biosensor technologies have enabled remote, non-invasive recording of a growing number of physiologic parameters and biomarkers promoting the detection and study of such processes.Main results. Here, we introduce key clinical studies in selected medical fields, which leveraged novel technologies and the advantageous period of sleep to diagnose, monitor and treat pathologies. Studies demonstrate that sleep is an ideal time frame for the collection of long and clean physiological time series data which can then be analyzed using data-driven algorithms such as deep learning.Significance.This new paradigm proposes opportunities to further harness modern technologies to explore human health and disease during sleep and to advance the development of novel clinical applications - from sleep medicine to medicine during sleep.

An in Vivo Nanosensor Measures Compartmental Doxorubicin Exposure.

Preclinical measurements of drug exposure to specific organs and tissues is normally performed by destructive methods. Tissue-specific measurements are important, especially for drugs with intractable dose-limiting toxicities, such as doxorubicin-mediated cardiotoxicity. We developed a method to rapidly quantify doxorubicin exposure to tissues within living organisms using an implantable optical nanosensor that can be interrogated noninvasively following surgical implantation. The near-infrared fluorescence of single-walled carbon nanotubes functionalized with DNA was found to respond to doxorubicin via a large and uniform red-shift. We found this to be common to DNA-intercalating agents, including anthracycline compounds such as doxorubicin. Doxorubicin was measured in buffer and serum, intracellularly, and from single nanotubes on a surface. Doxorubicin adsorption to the DNA-suspended nanotubes did not displace DNA but bound irreversibly. We incorporated the nanosensors into an implantable membrane which allowed cumulative detection of doxorubicin exposure in vivo. On implanting the devices into different compartments, such as subcutaneously and within the peritoneal cavity, we achieved real-time, minimally invasive detection of doxorubicin injected into the peritoneal cavity, as well as compartment-specific measurements. We measured doxorubicin translocation across the peritoneal membrane in vivo. Robust, minimally invasive pharmacokinetic measurements in vivo suggest the suitability of this technology for preclinical drug discovery applications.

Quantitative self-assembly prediction yields targeted nanomedicines.

Development of targeted nanoparticle drug carriers often requires complex synthetic schemes involving both supramolecular self-assembly and chemical modification. These processes are generally difficult to predict, execute, and control. We describe herein a targeted drug delivery system that is accurately and quantitatively predicted to self-assemble into nanoparticles based on the molecular structures of precursor molecules, which are the drugs themselves. The drugs assemble with the aid of sulfated indocyanines into particles with ultrahigh drug loadings of up to 90%. We devised quantitative structure-nanoparticle assembly prediction (QSNAP) models to identify and validate electrotopological molecular descriptors as highly predictive indicators of nano-assembly and nanoparticle size. The resulting nanoparticles selectively targeted kinase inhibitors to caveolin-1-expressing human colon cancer and autochthonous liver cancer models to yield striking therapeutic effects while avoiding pERK inhibition in healthy skin. This finding enables the computational design of nanomedicines based on quantitative models for drug payload selection.

Tumour-specific PI3K inhibition via nanoparticle-targeted delivery in head and neck squamous cell carcinoma.

Alterations in PIK3CA, the gene encoding the p110α subunit of phosphatidylinositol 3-kinase (PI3Kα), are frequent in head and neck squamous cell carcinomas. Inhibitors of PI3Kα show promising activity in various cancer types, but their use is curtailed by dose-limiting side effects such as hyperglycaemia. In the present study, we explore the efficacy, specificity and safety of the targeted delivery of BYL719, a PI3Kα inhibitor currently in clinical development in solid tumours. By encapsulating BYL719 into P-selectin-targeted nanoparticles, we achieve specific accumulation of BYL719 in the tumour milieu. This results in tumour growth inhibition and radiosensitization despite the use of a sevenfold lower dose of BYL719 compared with oral administration. Furthermore, the nanoparticles abrogate acute and chronic metabolic side effects normally observed after BYL719 treatment. These findings offer a novel strategy that could potentially enhance the efficacy of PI3Kα inhibitors while mitigating dose-limiting toxicity in patients with head and neck squamous cell carcinomas.

P-selectin is a nanotherapeutic delivery target in the tumor microenvironment.

Disseminated tumors are poorly accessible to nanoscale drug delivery systems because of the vascular barrier, which attenuates extravasation at the tumor site. We investigated P-selectin, a molecule expressed on activated vasculature that facilitates metastasis by arresting tumor cells at the endothelium, for its potential to target metastases by arresting nanomedicines at the tumor endothelium. We found that P-selectin is expressed on cancer cells in many human tumors. To develop a targeted drug delivery platform, we used a fucosylated polysaccharide with nanomolar affinity to P-selectin. The nanoparticles targeted the tumor microenvironment to localize chemotherapeutics and a targeted MEK (mitogen-activated protein kinase kinase) inhibitor at tumor sites in both primary and metastatic models, resulting in superior antitumor efficacy. In tumors devoid of P-selectin, we found that ionizing radiation guided the nanoparticles to the disease site by inducing P-selectin expression. Radiation concomitantly produced an abscopal-like phenomenon wherein P-selectin appeared in unirradiated tumor vasculature, suggesting a potential strategy to target disparate drug classes to almost any tumor.

Assessing the therapeutic efficacy of VEGFR-1-targeted polymer drug conjugates in mouse tumor models.

Polymer-drug conjugates that can actively target the tumor vasculature have emerged as an attractive technology for improving the therapeutic efficacy of cytotoxic drugs. We have recently provided, for the first time, in vivo evidence showing the significant advantage of the E-selectin-targeted N-(2-hydroxypropyl)methacrylamide (HPMA) copolymer-doxorubicin conjugate, P-(Esbp)-DOX, in inhibiting primary tumor growth and preventing the formation and development of cancer metastases. Here, we describe the design of a vascular endothelial growth factor receptor (VEGFR)-1-targeted HPMA copolymer-DOX conjugate (P-(F56)-DOX) that can actively and simultaneously target different cell types in the tumor microenvironment, such as endothelial cells (ECs), bone marrow-derived cells and many human cancer cells of diverse tumor origin. The VEGFR-1-targeted copolymer was tested for its binding, internalization and in vitro cytotoxicity in ECs (bEnd.3 and cEND cells) and cancer cells (B16-F10, 3LL and HT29). The in vivo anti-cancer activity of P-(F56)-DOX was then tested in two tumor-bearing mice (TBM) models (i.e., primary Lewis lung carcinoma (3LL) tumors and B16-F10 melanoma pulmonary metastases), relative to that of the E-selectin-targeted system (P-(Esbp)-DOX) that solely targets ECs. Our results indicate that the binding and internalization profiles of the VEGFR-1-targeted copolymer were superior towards ECs as compared to cancer cells and correlated well to the level of VEGFR-1 expression in cells. Accordingly, the VEGFR-1-targeted copolymer (P-(F56)-DOX) was more toxic towards bEnd.3 cells than to cancer cells, and exhibited significantly higher cytotoxicity than did the non-targeted control copolymer. P-(F56)-DOX inhibited 3LL tumor growth and significantly prolonged the survival of mice with B16-F10 pulmonary metastases. When compared to a system that actively targets only tumor vascular ECs, P-(F56)-DOX and P-(Esbp)-DOX exhibited comparable efficacy in slowing the growth of primary 3LL tumors and prolonging the survival of these mice. Still, P-(Esbp)-DOX had more pronounced anti-tumor activity in mice bearing B16-F10 lung metastases after a single intravenous injection, at an equivalent DOX dose. Overall, our results indicate that the VEGFR-1- and E-selectin-targeted drug delivery systems evaluated here show enhanced anti-cancer activity, and prolonged the survival of mice after a single intravenous injection. This is thus the first study comparing the anti-tumor activity of VEGFR-1- and E-selectin-targeted polymer drug conjugates in the same TBM models at an equivalent drug dose.

Photoluminescent carbon nanotubes interrogate the permeability of multicellular tumor spheroids.

Nanomaterials have been extensively investigated for cancer drug delivery and imaging applications. Nanoparticles that show promise in two-dimensional cell culture systems often fail in more complex environments, possibly due to the lack of penetration in dense, three-dimensional structures. Multicellular tumor spheroids are an emerging model system to investigate interactions of nanoparticles with 3D in vitro cell culture environments. Using the intrinsic near-infrared emission of semiconducting carbon nanotubes to optically reconstruct their localization within a three-dimensional volume, we resolved the relative permeability of two different multicellular tumor spheroids. Nanotube photoluminescence revealed that nanotubes rapidly internalized into MCF-7 breast cancer cell-derived spheroids, whereas they exhibited little penetration into spheroids derived from SK-136, a cell line that we developed from murine liver cancer. Characterization of the spheroids by electron microscopy and immunohistochemistry revealed large differences in the extracellular matrix and interstitial spacing, which correlated directly with nanotube penetration. This platform portends a new approach to characterize the permeability of living multicellular environments.

Cell Membrane Proteins Modulate the Carbon Nanotube Optical Bandgap via Surface Charge Accumulation.

Cell adhesion is a protein-mediated process intrinsic to most living organisms. Dysfunction in cell adhesion processes is implicated in various diseases, including thrombosis and metastatic cancers. Using an approach to resolve spectral features from cell membrane-associated photoluminescent single-walled carbon nanotubes, we found that nanotube optical bandgaps respond to the electrostatic potential of the cell surface, which corresponds to cell adhesion properties. We studied the carbon nanotube emission energy response to solution ionic potentials, which suggests sensitivity to local charge accumulation. We conclude that nanotubes respond to cell surface electrostatic potentials that are mediated by membrane proteins, which vary significantly across cell types. These findings portend the optical measurement of surface electrostatic potentials for biophysical measurements and biomedical applications.