Assessing micrometastases as a target for nanoparticles using 3D microscopy and machine learning.

Metastasis of solid tumors is a key determinant of cancer patient survival. Targeting micrometastases using nanoparticles could offer a way to stop metastatic tumor growth before it causes excessive patient morbidity. However, nanoparticle delivery to micrometastases is difficult to investigate because micrometastases are small in size and lie deep within tissues. Here, we developed an imaging and image analysis workflow to analyze nanoparticle-cell interactions in metastatic tumors. This technique combines tissue clearing and 3D microscopy with machine learning-based image analysis to assess the physiology of micrometastases with single-cell resolution and quantify the delivery of nanoparticles within them. We show that nanoparticles access a higher proportion of cells in micrometastases (50% nanoparticle-positive cells) compared with primary tumors (17% nanoparticle-positive cells) because they reside close to blood vessels and require a small diffusion distance to reach all tumor cells. Furthermore, the high-throughput nature of our image analysis workflow allowed us to profile the physiology and nanoparticle delivery of 1,301 micrometastases. This enabled us to use machine learning-based modeling to predict nanoparticle delivery to individual micrometastases based on their physiology. Our imaging method allows researchers to measure nanoparticle delivery to micrometastases and highlights an opportunity to target micrometastases with nanoparticles. The development of models to predict nanoparticle delivery based on micrometastasis physiology could enable personalized treatments based on the specific physiology of a patient's micrometastases.

The entry of nanoparticles into solid tumours.

The concept of nanoparticle transport through gaps between endothelial cells (inter-endothelial gaps) in the tumour blood vessel is a central paradigm in cancer nanomedicine. The size of these gaps was found to be up to 2,000 nm. This justified the development of nanoparticles to treat solid tumours as their size is small enough to extravasate and access the tumour microenvironment. Here we show that these inter-endothelial gaps are not responsible for the transport of nanoparticles into solid tumours. Instead, we found that up to 97% of nanoparticles enter tumours using an active process through endothelial cells. This result is derived from analysis of four different mouse models, three different types of human tumours, mathematical simulation and modelling, and two different types of imaging techniques. These results challenge our current rationale for developing cancer nanomedicine and suggest that understanding these active pathways will unlock strategies to enhance tumour accumulation.

Liposome Imaging in Optically Cleared Tissues.

Three-dimensional (3D) optical microscopy can be used to understand and improve the delivery of nanomedicine. However, this approach cannot be performed for analyzing liposomes in tissues because the processing step to make tissues transparent for imaging typically removes the lipids. Here, we developed a tag, termed REMNANT, that enables 3D imaging of organic materials in biological tissues. We demonstrated the utility of this tag for the 3D mapping of liposomes in intact tissues. We also showed that the tag is able to monitor the release of entrapped therapeutic agents. We found that liposomes release their cargo >100-fold faster in tissues in vivo than in conventional in vitro assays. This allowed us to design a liposomal formulation with enhanced ability to kill tumor associated macrophages. Our development opens up new opportunities for studying the chemical properties and pharmacodynamics of administered organic materials in an intact biological environment. This approach provides insight into the in vivo behavior of degradable materials, where the newly discovered information can guide the engineering of the next generation of imaging and therapeutic agents.

Engineering Steps for Mobile Point-of-Care Diagnostic Devices.

Mobile phone technology is a perfect companion for point-of-care diagnostics as they come equipped with advanced processors, high resolution cameras, and network connectivity. Despite several academic pursuits, only a few mobile phone diagnostics have been tested in the field, commercialized or achieved regulatory approval. This review will address the challenges associated with developing mobile diagnostics and suggest strategies to overcome them. We aim to provide a resource for researchers to accelerate the development of new diagnostics. Our Account includes an overview of published mobile phone diagnostics and highlights lessons learned from their approach to diagnostic development. Also, we have included recommendations from regulatory and public health agencies, such as the U.S. Food and Drug Administration and World Health Organization, to further guide researchers. We believe that the development of mobile phone point-of-care diagnostics takes place in four distinct steps: (1) Needs and Value Assessment, (2) Technology Development, (3) Preclinical Verification, and (4) Clinical Validation and Field Trials. During each step, we outline developmental strategies to help researchers avoid potential challenges. (1) Researchers commonly develop devices to maximize technical parameters such as sensitivity and time which do not necessarily translate to increased clinical impact. Researchers must focus on assessing specific diagnostic needs and the value which a potential device would offer. (2) Often, researchers claim they have developed devices for feasible implementation at the point-of-care, yet they rely on laboratory resources. Researchers must develop equipment-free devices which are agnostic to any mobile phone. (3) Another challenge researchers face is decreased performance during field evaluations relative to initial laboratory verification. Researchers must ensure that they simulate the field conditions during laboratory verification to achieve successful translation. (4) Finally, proper field testing of devices must be performed in conditions which match that of the final intended use. The future of mobile phone point-of-care diagnostic devices is bright and has the potential to radically change how patients are diagnosed. Before we reach this point, researchers must take a step backward and focus on the first-principles of basic research. The widespread adoption and rapid scaling of these devices can only be achieved once the fundamentals have been considered. The insights and strategies provided here will help researchers avoid pitfalls, streamline development and make better decisions during the development of new diagnostics. Further, we believe this Account can help push the field of mobile diagnostics toward increased productivity, leading to more approved devices and ultimately helping curb the burden of disease worldwide.

Clarifying intact 3D tissues on a microfluidic chip for high-throughput structural analysis.

On-chip imaging of intact three-dimensional tissues within microfluidic devices is fundamentally hindered by intratissue optical scattering, which impedes their use as tissue models for high-throughput screening assays. Here, we engineered a microfluidic system that preserves and converts tissues into optically transparent structures in less than 1 d, which is 20× faster than current passive clearing approaches. Accelerated clearing was achieved because the microfluidic system enhanced the exchange of interstitial fluids by 567-fold, which increased the rate of removal of optically scattering lipid molecules from the cross-linked tissue. Our enhanced clearing process allowed us to fluorescently image and map the segregation and compartmentalization of different cells during the formation of tumor spheroids, and to track the degradation of vasculature over time within extracted murine pancreatic islets in static culture, which may have implications on the efficacy of beta-cell transplantation treatments for type 1 diabetes. We further developed an image analysis algorithm that automates the analysis of the vasculature connectivity, volume, and cellular spatial distribution of the intact tissue. Our technique allows whole tissue analysis in microfluidic systems, and has implications in the development of organ-on-a-chip systems, high-throughput drug screening devices, and in regenerative medicine.

Three-Dimensional Imaging of Transparent Tissues via Metal Nanoparticle Labeling.

Chemical probes are key components of the bioimaging toolbox, as they label biomolecules in cells and tissues. The new challenge in bioimaging is to design chemical probes for three-dimensional (3D) tissue imaging. In this work, we discovered that light scattering of metal nanoparticles can provide 3D imaging contrast in intact and transparent tissues. The nanoparticles can act as a template for the chemical growth of a metal layer to further enhance the scattering signal. The use of chemically grown nanoparticles in whole tissues can amplify the scattering to produce a 1.4 million-fold greater photon yield than obtained using common fluorophores. These probes are non-photobleaching and can be used alongside fluorophores without interference. We demonstrated three distinct biomedical applications: (a) molecular imaging of blood vessels, (b) tracking of nanodrug carriers in tumors, and (c) mapping of lesions and immune cells in a multiple sclerosis mouse model. Our strategy establishes a distinct yet complementary set of imaging probes for understanding disease mechanisms in three dimensions.

Exploring Passive Clearing for 3D Optical Imaging of Nanoparticles in Intact Tissues.

The three-dimensional (3D) optical imaging of nanoparticle distribution within cells and tissues can provide insights into barriers to nanoparticle transport in vivo. However, this approach requires the preparation of optically transparent samples using harsh chemical and physical methods, which can lead to a significant loss of nanoparticles and decreased sensitivity of subsequent analyses. Here, we investigate the influence of electrophoresis and clearing time on nanoparticle retention within intact tissues and the impact of these factors on the final 3D image quality. Our findings reveal that longer clearing times lead to a loss of nanoparticles but improved transparency of tissues. We discovered that passive clearing improved nanoparticle retention 2-fold compared to results from electrophoretic clearing. Using the passive clearing approach, we were able to observe a small population of nanoparticles undergoing hepatobiliary clearance, which could not be observed in liver tissues that were prepared by electrophoretic clearing. This strategy enables researchers to visualize the interface between nanomaterials and their surrounding biological environment with high sensitivity, which enables quantitative and unbiased analysis for guiding the next generation of nanomedicine designs.

Gold Nanoparticle Smartphone Platform for Diagnosing Urinary Tract Infections.

Current urinary tract infection (UTI) diagnostic methods are slow or provide limited information, resulting in prescribing antibiotic therapy before bacterial pathogen identification. Here, we adapted a gold nanoparticle colorimetric approach and developed a smartphone platform for UTI detection. We show the parallel identification of five major UTI pathogens at clinically relevant concentrations of 105 bacteria/mL using bacteria-specific and universal probes. We validated the diagnostic technology using 115 positive and 19 negative samples from patients with Escherichia coli, Proteus mirabilis, and Klebsiella pneumoniae infections. The assay successfully identified the infecting pathogen (specificity: >98% and sensitivity: 51-73%) in 3 h. Our platform is faster than culturing and can wirelessly store and transmit results at the cost of $0.38 per assay.

Specific Endothelial Cells Govern Nanoparticle Entry into Solid Tumors.

The successful delivery of nanoparticles to solid tumors depends on their ability to pass through blood vessels and into the tumor microenvironment. Here, we discovered a subset of tumor endothelial cells that facilitate nanoparticle transport into solid tumors. We named these cells nanoparticle transport endothelial cells (N-TECs). We show that only 21% of tumor endothelial cells located on a small number of vessels are involved in transporting nanoparticles into the tumor microenvironment. N-TECs have an increased expression of genes related to nanoparticle transport and vessel permeability compared to other tumor endothelial cells. The N-TECs act as gatekeepers that determine the entry point, distribution, cell accessibility, and number of nanoparticles that enter the tumor microenvironment.

Flow Rate Affects Nanoparticle Uptake into Endothelial Cells.

Nanoparticles are commonly administered through systemic injection, which exposes them to the dynamic environment of the bloodstream. Injected nanoparticles travel within the blood and experience a wide range of flow velocities that induce varying shear rates to the blood vessels. Endothelial cells line these vessels, and have been shown to uptake nanoparticles during circulation, but it is difficult to characterize the flow-dependence of this interaction in vivo. Here, a microfluidic system is developed to control the flow rates of nanoparticles as they interact with endothelial cells. Gold nanoparticle uptake into endothelial cells is quantified at varying flow rates, and it is found that increased flow rates lead to decreased nanoparticle uptake. Endothelial cells respond to increased flow shear with decreased ability to uptake the nanoparticles. If cells are sheared the same way, nanoparticle uptake decreases as their flow velocity increases. Modifying nanoparticle surfaces with endothelial-cell-binding ligands partially restores uptake to nonflow levels, suggesting that functionalizing nanoparticles to bind to endothelial cells enables nanoparticles to resist flow effects. In the future, this microfluidic system can be used to test other nanoparticle-endothelial cell interactions under flow. The results of these studies can guide the engineering of nanoparticles for in vivo medical applications.

Supervised Learning and Mass Spectrometry Predicts the in Vivo Fate of Nanomaterials.

The surface of nanoparticles changes immediately after intravenous injection because blood proteins adsorb on the surface. How this interface changes during circulation and its impact on nanoparticle distribution within the body is not understood. Here, we developed a workflow to show that the evolution of proteins on nanoparticle surfaces predicts the biological fate of nanoparticles in vivo. This workflow involves extracting nanoparticles at multiple time points from circulation, isolating the proteins off the surface and performing proteomic mass spectrometry. The mass spectrometry protein library served as inputs, while blood clearance and organ accumulation were used as outputs to train a supervised deep neural network that predicts nanoparticle biological fate. In a double-blinded study, we tested the network by predicting nanoparticle spleen and liver accumulation with upward of 94% accuracy. Our neural network discovered that the mechanism of liver and spleen uptake is due to patterns of a multitude of nanoparticle surface adsorbed proteins. There are too many combinations to change these proteins manually using chemical or biological inhibitors to alter clearance. Therefore, we developed a technique that uses the host to act as a bioreactor to prepare nanoparticles with predictable clearance patterns that reduce liver and spleen uptake by 50% and 70%, respectively. These techniques provide opportunities to both predict nanoparticle behavior and also to engineer surface chemistries that are specifically designed by the body.

Quantifying the Ligand-Coated Nanoparticle Delivery to Cancer Cells in Solid Tumors.

Coating the nanoparticle surface with cancer cell recognizing ligands is expected to facilitate specific delivery of nanoparticles to diseased cells in vivo. While this targeting strategy is appealing, no nanoparticle-based active targeting formulation for solid tumor treatment had made it past phase III clinical trials. Here, we quantified the cancer cell-targeting efficiencies of Trastuzumab (Herceptin) and folic acid coated gold and silica nanoparticles in multiple mouse tumor models. Surprisingly, we showed that less than 14 out of 1 million (0.0014% injected dose) intravenously administrated nanoparticles were delivered to targeted cancer cells, and that only 2 out of 100 cancer cells interacted with the nanoparticles. The majority of the intratumoral nanoparticles were either trapped in the extracellular matrix or taken up by perivascular tumor associated macrophages. The low cancer cell targeting efficiency and significant uptake by noncancer cells suggest the need to re-evaluate the active targeting process and therapeutic mechanisms using quantitative methods. This will be important for developing strategies to deliver emerging therapeutics such as genome editing, nucleic acid therapy, and immunotherapy for cancer treatment using nanocarriers.

Three-Dimensional Optical Mapping of Nanoparticle Distribution in Intact Tissues.

The role of tissue architecture in mediating nanoparticle transport, targeting, and biological effects is unknown due to the lack of tools for imaging nanomaterials in whole organs. Here, we developed a rapid optical mapping technique to image nanomaterials in intact organs ex vivo and in three-dimensions (3D). We engineered a high-throughput electrophoretic flow device to simultaneously transform up to 48 tissues into optically transparent structures, allowing subcellular imaging of nanomaterials more than 1 mm deep into tissues which is 25-fold greater than current techniques. A key finding is that nanomaterials can be retained in the processed tissue by chemical cross-linking of surface adsorbed serum proteins to the tissue matrix, which enables nanomaterials to be imaged with respect to cells, blood vessels, and other structures. We developed a computational algorithm to analyze and quantitatively map nanomaterial distribution. This method can be universally applied to visualize the distribution and interactions of materials in whole tissues and animals including such applications as the imaging of nanomaterials, tissue engineered constructs, and biosensors within their intact biological environment.