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Hammond, P. T.

Publications and source records attributed to Hammond, P. T..

7 recordsLinked to original sources

'Target-and-release' nanoparticles for effective immunotherapy of metastatic ovarian cancer

Immunotherapies such as checkpoint inhibitors (CPI) are effective in treating several advanced cancers, but these treatments have had limited success in metastatic ovarian cancer (OC). Here, we engineered liposomal nanoparticles (NPs) carrying a layer-by-layer (LbL) polymer coating that promotes their binding to the surface of OC cells. Covalent anchoring of the potent immunostimulatory cytokine interleukin-12 (IL-12) to phospholipid headgroups of the liposome core enabled the LbL particles to concentrate IL-12 in disseminated OC tumors following intraperitoneal administration. Shedding of the LbL coating and serum protein-mediated extraction of IL-12-conjugated lipids from the liposomal core over time enabled IL-12 to disseminate in the tumor bed following rapid NP localization in tumor nodules. Optimized IL-12 LbL-NPs promoted robust T cell accumulation in ascites and tumors in mouse models, extending survival compared to free IL-12 and remarkedly sensitizing tumors to CPI, leading to curative treatments and immune memory.

bioengineering↗

Ether lipids influence cancer cell fate by modulating iron uptake

Cancer cell fate has been widely ascribed to mutational changes within proteincoding genes associated with tumor suppressors and oncogenes. In contrast, the mechanisms through which the biophysical properties of membrane lipids influence cancer cell survival, dedifferentiation and metastasis have received little scrutiny. Here, we report that cancer cells endowed with high metastatic ability and cancer stem celllike traits employ ether lipids to maintain low membrane tension and high membrane fluidity. Using genetic approaches and lipid reconstitution assays, we show that these ether lipid-regulated biophysical properties permit non-clathrin-mediated iron endocytosis via CD44, resulting in significant increases in intracellular redox-active iron and enhanced ferroptosis susceptibility. Using a combination of in vitro threedimensional microvascular network systems and in vivo animal models, we show that loss of ether lipids from plasma membranes also strongly attenuates extravasation, metastatic burden and cancer stemness. These findings illuminate a mechanism whereby ether lipids in carcinoma cells serve as key regulators of malignant progression while conferring a unique vulnerability that can be exploited for therapeutic intervention.

cancer biology↗

Electrophoresis-Based Approach for Characterizing Dendrimer-Protein Interactions: A Proof-of-Concept Study

Improving the clinical translation of nanomedicine requires better knowledge about how nanoparticles interact with biological environments. As researchers are recognizing the importance of understanding the protein corona and characterizing how nanocarriers respond in biological systems, new tools and techniques are needed to analyze nanocarrier-protein interactions, especially for smaller-size (<10nm) nanoparticles like polyamidoamine (PAMAM) dendrimers. Here we developed a streamlined, semi-quantitative approach to assess dendrimer-protein interactions using a non-denaturing electrophoresis technique combined with mass spectrometry. With this protocol, we detect fluorescently tagged dendrimers and proteins simultaneously, enabling us to analyze when dendrimers migrate with proteins. We found PAMAM dendrimers mostly interact with complement proteins, particularly C3 and C4a, which aligns with previously published data, verifying our approach can be used to isolate and identify dendrimer-protein interactions. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/555747v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@102bdeeorg.highwire.dtl.DTLVardef@103914corg.highwire.dtl.DTLVardef@138402eorg.highwire.dtl.DTLVardef@1fdbbd2_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

A new label-free optical imaging method for the lymphatic system enhanced by deep learning

Our understanding of the lymphatic vascular system lags far behind that of the blood vascular system, limited by available imaging technologies. We present a label-free optical imaging method that visualizes the lymphatic system with high contrast. We developed an orthogonal polarization imaging (OPI) in the shortwave infrared range (SWIR) and imaged both lymph nodes and lymphatic vessels of mice and rats in vivo through intact skin, as well as human mesenteric lymph nodes in colectomy specimens. By integrating SWIR-OPI with U-Net, a deep learning image segmentation algorithm, we automated the lymph node size measurement process. Changes in lymph nodes in response to cancer progression were monitored in two separate mouse cancer models, through which we obtained insights into pre-metastatic niches and correlation between lymph node masses and many important biomarkers. In a human pilot study, we demonstrated the effectiveness of SWIR-OPI to detect human lymph nodes in real time with clinical colectomy specimens. One Sentence SummaryWe develop a real-time high contrast optical technique for imaging the lymphatic system, and apply it to anatomical pathology gross examination in a clinical setting, as well as real-time monitoring of tumor microenvironment in animal studies.

bioengineering↗

Core material and surface chemistry of Layer-by-Layer (LbL) nanoparticles independently direct uptake, transport, and trafficking in preclinical blood-brain barrier (BBB) models

Development of new treatments for neurological disorders, especially brain tumors and neurodegenerative diseases, is hampered by poor accumulation of new therapeutic candidates in the brain. Drug carrying nanoparticles are a promising strategy to deliver therapeutics, but there is a major need to understand interactions between nanomaterials and the cells of the blood-brain barrier (BBB), and to what degree these interactions can be predicted by preclinical models. Here, we use a library of eighteen layer-by-layer electrostatically assembled nanoparticles (LbL-NPs) to independently assess the impact of nanoparticle core stiffness and surface chemistry on in vitro uptake and transport in three common assays, as well as intracellular trafficking in hCMEC/D3 endothelial cells. We demonstrate that nanoparticle core stiffness impacts the magnitude of material transported, while surface chemistry influences how the nanoparticles are trafficked within the cell. Finally, we demonstrate that these factors similarly dictate in vivo BBB transport using intravital imaging through cranial windows in mice, and we discover that a hyaluronic acid surface chemistry provides an unpredicted boost to transport. Taken together, these findings highlight the importance of considering factors such as assay geometry, nanomaterial labelling strategies, and fluid flow in designing preclinical assays to improve nanoparticle screening throughput for drug delivery to the brain.

bioengineering↗

A predictive microfluidic model of human glioblastoma to assess trafficking of blood-brain barrier penetrant nanoparticles

The blood-brain barrier represents a significant challenge for the treatment of high-grade gliomas, and our understanding of drug transport across this critical biointerface remains limited. To advance preclinical therapeutic development for gliomas, there is an urgent need for predictive in vitro models with realistic blood-brain barrier vasculature. Here, we report a vascularized human glioblastoma (GBM) model in a microfluidic device that accurately recapitulates brain tumor vasculature with self-assembled endothelial cells, astrocytes, and pericytes to investigate the transport of targeted nanotherapeutics across the blood-brain barrier and into GBM cells. Using modular layer-by-layer assembly, we functionalized the surface of nanoparticles with GBM-targeting motifs to improve trafficking to tumors. We directly compared nanoparticle transport in our in vitro platform with transport across mouse brain capillaries using intravital imaging, validating the ability of the platform to model in vivo blood-brain barrier transport. We investigated the therapeutic potential of functionalized nanoparticles by encapsulating cisplatin and showed improved efficacy of these GBM-targeted nanoparticles both in vitro and in an in vivo orthotopic xenograft model. Our vascularized GBM model represents a significant biomaterials advance, enabling in-depth investigation of brain tumor vasculature and accelerating the development of targeted nanotherapeutics. Significance StatementThe blood-brain barrier represents a major therapeutic challenge for the treatment of glioblastoma, and there is an unmet need for in vitro models that recapitulate human biology and are predictive of in vivo response. Here we present a new microfluidic model of vascularized glioblastoma featuring a tumor spheroid in direct contact with self-assembled vascular networks comprised of human endothelial cells, astrocytes, and pericytes. This model was designed to accelerate the development of targeted nanotherapeutics, and enabled rigorous assessment of a panel of surface-functionalized nanoparticles designed to exploit a receptor overexpressed in tumor-associated vasculature. Trafficking and efficacy data in the in vitro model compared favorably to parallel in vivo data, highlighting the utility of the vascularized glioblastoma model for therapeutic development.

bioengineering↗

Massively parallel pooled screening reveals genomic determinants of nanoparticle-cell interactions

To accelerate the translation of cancer nanomedicine, we hypothesize that integrated genomic screens will improve understanding of the cellular processes governing nanoparticle trafficking. We developed a massively parallel high-throughput screening method leveraging barcoded, pooled cancer cell lines annotated with multi-omic data to investigate cell association patterns across a nanoparticle library spanning a range of formulations with clinical potential. This approach identified both the materials properties and cell-intrinsic features mediating nanoparticle-cell association. Coupling the data with machine learning algorithms, we constructed genomic nanoparticle trafficking networks and identified nanoparticle-specific biomarkers, including gene expression of SLC46A3. We engineered cell lines to validate SLC46A3 as a biomarker whose expression inversely predicts liposomal nanoparticle uptake both in vitro and in vivo. We further demonstrated the predictive capabilities extend beyond liposomal nanoparticles, regulating both uptake and transfection efficacy of solid lipid nanoparticles. Our work establishes the power of massively parallel pooled cell screens for nanoparticle delivery and enables the identification and utilization of biomarkers to rationally design nanoformulations for specific patient populations.

bioengineering↗