Publications by authors named "Gary Luker"

Synthetic cells offer a versatile platform for addressing biomedical and environmental challenges, due to their modular design and capability to mimic cellular processes such as biosensing, intercellular communication, and metabolism. Constructing synthetic cells capable of stimuli-responsive secretion is vital for applications in targeted drug delivery and biosensor development. Previous attempts at engineering secretion for synthetic cells have been confined to non-specific cargo release via membrane pores, limiting the spatiotemporal precision and specificity necessary for selective secretion.

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Cell microencapsulation technologies allow non-autologous implantation of therapeutic cells for sustained drug delivery purposes. The perm-selective membrane of these systems provides resistance to rupture, stablishes the upper molecular weight limit in bidirectional diffusion of molecules, and affects biocompatibility. Thus, despite being a decisive factor to succeed in terms of biosafety and therapeutic efficacy, little progress has been made in its optimization so far.

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Article Synopsis
  • - A new method for portable near-infrared (NIR) fluorescence microscopy is presented, designed to improve imaging of biological samples using the NIR-II window.
  • - The integration of a superconducting nanowire single-photon detector (SNSPD) enhances the detection efficiency of the fluorescent dye indocyanine green (ICG), allowing for better imaging quality.
  • - This technique yields high-resolution images and a better signal-to-noise ratio, which could significantly benefit future clinical studies in fluorescence microscopy.
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Targeting signaling pathways that drive cancer cell migration or proliferation is a common therapeutic approach. A popular experimental technique, the scratch assay, measures the migration and proliferation-driven cell closure of a defect in a confluent cell monolayer. These assays do not measure dynamic effects.

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Article Synopsis
  • Tissue chip and organs-on-chip technologies are becoming important in preclinical cancer research due to the high failure rates of new drugs in clinical trials.
  • A new 32-unit tissue chip designed to fit standard 96-well plates simplifies automation and uses 3D printing and gravity-driven flow for better functionality.
  • This tissue chip allows for the simultaneous analysis of drug efficacy and toxicity, focusing on liver and bone marrow interactions, thereby improving the selection of potential treatments in early drug discovery stages.
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Estrogen receptor-positive (ER+) breast cancer commonly disseminates to bone marrow, where interactions with mesenchymal stromal cells (MSCs) shape disease trajectory. We modeled these interactions with tumor-MSC co-cultures and used an integrated transcriptome-proteome-network-analyses workflow to identify a comprehensive catalog of contact-induced changes. Conditioned media from MSCs failed to recapitulate genes and proteins, some borrowed and others tumor-intrinsic, induced in cancer cells by direct contact.

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Synthetic cells offer a versatile platform for addressing biomedical and environmental challenges, due to their modular design and capability to mimic cellular processes such as biosensing, intercellular communication, and metabolism. Constructing synthetic cells capable of stimuli-responsive secretion is vital for applications in targeted drug delivery and biosensor development. Previous attempts at engineering secretion for synthetic cells have been confined to non-specific cargo release via membrane pores, limiting the spatiotemporal precision and specificity necessary for selective secretion.

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Cellular, extracellular matrix (ECM), and spatial heterogeneity of tumor microenvironments (TMEs) regulate disease progression and treatment efficacy. Developing in vitro models that recapitulate the TME promises to accelerate studies of tumor biology and identify new targets for therapy. Here, we used extrusion-based, multi-nozzle 3D bioprinting to spatially pattern triple-negative MDA-MB-231 breast cancer cells, endothelial cells (ECs), and human mammary cancer-associated fibroblasts (HMCAFs) with biomimetic ECM inks.

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Single cancer cells within a tumor exhibit variable levels of resistance to drugs, ultimately leading to treatment failures. While tumor heterogeneity is recognized as a major obstacle to cancer therapy, standard dose-response measurements for the potency of targeted kinase inhibitors aggregate populations of cells, obscuring intercellular variations in responses. In this work, we develop an analytical and experimental framework to quantify and model dose responses of individual cancer cells to drugs.

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Evaluating the response to immune checkpoint inhibitors (ICIs) remains an unmet challenge in triple-negative breast cancer (TNBC). The requirement for cholesterol in the activation and function of T cells led us to hypothesize that quantifying cellular accumulation of this molecule could distinguish successful from ineffective checkpoint immunotherapy. To analyze accumulation of cholesterol by T cells in the immune microenvironment of breast cancer, we leveraged the PET radiotracer, eFNP-59.

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Purpose: Myeloproliferative neoplasms (MPN) are characterized by the overproduction of differentiated myeloid cells. Mutations in JAK2, CALR, and MPL are considered drivers of Bcr-Abl-ve MPN, including essential thrombocythemia (ET), polycythemia vera (PV), prefibrotic primary myelofibrosis (prePMF), and overt myelofibrosis (MF). However, how these driver mutations lead to phenotypically distinct and/or overlapping diseases is unclear.

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Eukaryotic cells learn and adapt via unknown network architectures. Recent work demonstrated a circuit of two GTPases used by cells to overcome growth factor scarcity, encouraging our view that artificial and biological intelligence share strikingly similar design principles and that cells function as deep reinforcement learning (RL) agents in uncertain environments.

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Self-sufficiency (autonomy) in growth signaling, the earliest recognized hallmark of cancer, is fueled by the tumor cell's ability to "secrete-and-sense" growth factors (GFs); this translates into cell survival and proliferation that is self-sustained by autocrine/paracrine secretion. A Golgi-localized circuitry comprised of two GTPase switches has recently been implicated in the orchestration of growth signaling autonomy. Using breast cancer cells that are either endowed or impaired (by gene editing) in their ability to assemble the circuitry for growth signaling autonomy, here we define the transcriptome, proteome, and phenome of such an autonomous state, and unravel its role during cancer progression.

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Purpose: Analyzing bone marrow in the hematologic cancer myelofibrosis requires endpoint histology in mouse models and bone marrow biopsies in patients. These methods hinder the ability to monitor therapy over time. Preclinical studies typically begin treatment before mice develop myelofibrosis, unlike patients who begin therapy only after onset of disease.

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Ongoing discoveries in cancer genomics and epigenomics have revolutionized clinical oncology and precision health care. This knowledge provides unprecedented insights into tumor biology and heterogeneity within a single tumor, among primary and metastatic lesions, and among patients with the same histologic type of cancer. Large-scale genomic sequencing studies also sparked the development of new tumor classifications, biomarkers, and targeted therapies.

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Predicting the response to cancer immunotherapy remains an unmet challenge in triple-negative breast cancer (TNBC) and other malignancies. T cells, the major target of current checkpoint inhibitor immunotherapies, accumulate cholesterol during activation to support proliferation and signaling. The requirement of cholesterol for anti-tumor functions of T cells led us to hypothesize that quantifying cellular accumulation of this molecule could distinguish successful from ineffective checkpoint immunotherapy.

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Drug resistance is a major barrier against successful treatments of cancer patients. Gain of stemness under drug pressure is a major mechanism that renders treatments ineffective. Identifying approaches to target cancer stem cells (CSCs) is expected to improve treatment outcomes for patients.

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Cell migration is a complex process that plays a crucial role in normal physiology and pathologies such as cancer, autoimmune diseases, and mental disorders. Conventional cell migration assays face limitations in tracking a large number of individual migrating cells. To address this challenge, we have developed a high-throughput microfluidic cell migration chip, which seamlessly integrates robotic liquid handling and computer vision to swiftly monitor the movement of 3200 individual cells, providing unparalleled single-cell resolution for discerning distinct behaviors of the fast-moving cell population.

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Patients with triple-negative breast cancer remain at risk for metastatic disease despite treatment. The acquisition of chemoresistance is a major cause of tumor relapse and death, but the mechanisms are far from understood. We have demonstrated that breast cancer cells (BCCs) can engulf mesenchymal stem/stromal cells (MSCs), leading to enhanced dissemination.

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Chemokine receptors constitute an important subfamily of G protein-coupled receptors (GPCRs), and they are critically involved in a broad range of immune response mechanisms. Ligand promiscuity among these receptors makes them an interesting target to explore multiple aspects of biased agonism. Here, we comprehensively characterize two chemokine receptors namely, CXCR4 and CXCR7, in terms of their transducer-coupling and downstream signaling upon their stimulation by a common chemokine agonist, CXCL12, and a small molecule agonist, VUF11207.

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Article Synopsis
  • Multispectral optoacoustic tomography (MSOT) is a valuable technique for understanding biological samples, but it typically takes a long time to capture high-resolution images.
  • This study introduces a deep learning model that combines recurrent and convolutional neural networks to efficiently generate cross-sectional images, allowing for a faster scan using multiple imaging modalities in one go.
  • By utilizing a contrast agent called ICG-conjugated nanoworms and reducing the number of necessary images, the new approach can cut down acquisition time by about 71%.
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