Biology subjects

Jun, M.

Publications and source records attributed to Jun, M..

3 recordsLinked to original sources

bioRxiv2025

Rational Design of Immunogenic Nanoparticles as a Platform for Enhanced Ovarian Cancer Immunotherapy in Mice

Ovarian cancer immunotherapy remains a challenge based on the "cold" tumor microenvironment. Herein we present a rational design to create immunogenic nanoparticles as a multi-agent platform that promotes immune response in a mouse model of ovarian cancer. The hybrid lipid-silica nanosystem is capable of co-loading four types of cargo molecules including a model antigen, nucleic acid-based adjuvant Cytosine-p-linked to Guanine (CpG, TLR3/9 agonist), lipid-based adjuvant (MPLA, TLR4 agonist) integrated into the lipid coat, and optionally a small molecule drug, such as the chemotherapeutic agent oxaliplatin, a well-established treatment for ovarian cancer. The optimization of the nanoplatform in terms of lipid composition, functionalized silica dendritic core formation, and final charge, as well as their compatibility with the complex loading profile highlights an opportunity for enhanced survival of mice with advanced ovarian cancer compared to monotherapy. Furthermore, intraperitoneal administration led to preferential accumulation within tumor-burdened tissues with selective accumulation in myeloid cells. High myeloid cell cytotoxicity negated the benefits of oxaliplatin. The inclusion of CpG in the nanoparticle formulation enhanced the survival of mice with ovarian cancer. To interpret these outcomes and guide future design, we also developed a mathematical model of nanoparticle-driven immune activation, which quantified treatment efficacy and identified key parameters governing tumor response. The presented hybrid nanoparticle i tunable, enabling delivery of alternative molecules therefore, thereby highlighting a promising platform for the treatment of peritoneal cancers. Graphical TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=69 SRC="FIGDIR/small/657862v1_ufig1.gif" ALT="Figure 1000"> View larger version (26K): org.highwire.dtl.DTLVardef@1434599org.highwire.dtl.DTLVardef@18e79e6org.highwire.dtl.DTLVardef@e5285corg.highwire.dtl.DTLVardef@bcc604_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2023

Discovery of an APP-Selective BACE1 Inhibitor for Alzheimer's Disease

Inhibition of amyloid precursor protein (APP) beta-site cleaving enzyme 1 (BACE1; BACE) has been a target for Alzheimers disease (AD) therapeutic development, but has been impaired by off-target effects of clinically evaluated inhibitors, including inhibition of cleavage of non-APP substrates. Here, we report our identification of a BACE inhibitors series that are not only selective for the APP substrate, but also for BACE1 as the targeted enzyme. These APP-selective fluoro aminohydantoin (FAH) inhibitor compounds were identified by screening a compound library for inhibition of BACE cleavage of a maltose binding protein (MBP)-conjugated-APPC125 substrate followed by IC50 determination using the P5-P5 substrate assay. In multiple substrate and enzyme cell-free assays, the lead compound FAH65 displayed substrate selectivity for inhibition of APP cleavage, with little activity against BACE substrates neuregulin 1 (NRG1) or p-selectin glycoprotein ligand -1 (PSGL1). We also demonstrate FAH65 shows little inhibitory activity against the enzyme cathepsin D (Cat D) or BACE2. FAH65 inhibits production of BACE cleavage products soluble APP{beta} (sAPP{beta}) and the {beta} C-terminal fragment ({beta}CTF), as well as amyloid-{beta} (A{beta})1-40 and 1-42, in vitro in cells and in vivo in an animal model of AD. In a murine model of AD, FAH65 improved the discrimination score in the Novel Object Recognition (NOR) memory testing paradigm. The active enantiomer of FAH65, FAH65E(-), was obtained and tested in in vivo pharmacokinetic and pharmacodynamic (PK/PD) analysis, wherein it displayed good brain-penetrance and target engagement. Given its demonstrated selectivity for both enzyme and substrate, along with evidence it can improve cognitive performance in an animal model, FAH65 and its E(-) enantiomer merit continued pre-clinical development towards clinical testing as an APP-selective BACE1 inhibitor. Such a candidate would reduce A{beta} levels and overcome the deleterious effects of the non-selective BACE1 inhibitors that have failed in the clinic and potentially could be used as a maintenance therapy along with or following clearance of A{beta} from the brain with the approved antibody therapy for AD.

neuroscience↗

bioRxiv2020

OmicPioneer-sc: an integrated, interactive visualization environment for single-cell sequencing data

OmicPioneer-sc is an open-source data visualization/analysis package that integrates dimensionality-reduction plots (DRPs) such as t-SNE and UMAP with Next-Generation Clustered Heat Maps (NGCHMs) and Pathway Visualization Modules (PVMs) in a seamless, highly interactive exploratory environment. It includes fluent zooming and navigation, a statistical toolkit, dozens of link-outs to external public bioinformatic resources, high-resolution graphics that meet the requirements of all major journals, and the ability to store all metadata needed to reproduce the visualizations at a later time. A user-friendly, multi-panel graphical interface enables non-informaticians to interact with the system without programming, asking and answering questions that require navigation among the three types of modules or extension from them to the Gene Ontology or information on therapies. The visual integration can be useful for detective work to identify and annotate cell-types for color-coding of the DRPs, and multiple NGCHMs can be layered on top of each other (with toggling among them) as an aid to multi-omic analysis. The tools are available in containerized form with APIs to facilitate incorporation as a plug-in to other bioinformatic environments. The capabilities of OmicPioneer-sc are illustrated here through application to a single-cell RNA-seq airway dataset pertinent to the biology of both cancer and COVID-19. [Supplemental material is available for this article.]

bioinformatics↗