Biology subjects

Cho, D.-Y.

Publications and source records attributed to Cho, D.-Y..

4 recordsLinked to original sources

bioRxiv2025

Gene-Corrected Basal Cells Restore CFTR In Vitro; Transplants Regenerate Epithelium in a Preclinical Sinus Model

BackgroundCystic fibrosis (CF) is caused by mutations in the CFTR gene, leading to epithelial dysfunction and progressive lung disease. Although CFTR modulators have transformed care, [~]10% of people with CF remain without effective therapy. Durable, mutation-agnostic approaches are urgently needed. MethodWe used a lentiviral (LV) vector to deliver wild-type CFTR to airway basal cells derived from 13 paediatric CF participants with a range of genotypes. Transduced cells were assessed for transgene expression, epithelial differentiation, and CFTR function using air-liquid interface (ALI) cultures. Separately, to evaluate regenerative capacity in vivo, LVGFP-transduced rabbit airway basal cells were transplanted into the denuded nasal septum of healthy New Zealand white rabbits using a biocompatible scaffold. ResultsTransduced basal cells retained multilineage differentiation capacity, forming well-organized, pseudostratified epithelium with intact barrier function and ciliary activity. CFTR channel activity was restored to levels comparable to or exceeding those achieved with elexacaftor/tezacaftor/ivacaftor (ETI), including in individuals with nonsense mutations. Combined CFTR transduction plus ETI treatment showed additive benefit. In vivo, transplanted rabbit basal cells engrafted and differentiated to regenerate a mucociliary epithelium, with improved nasal potential difference and mucociliary clearance compared to scaffold-only controls. ConclusionOur study demonstrates that LV-mediated CFTR gene addition restores CFTR function in vitro across genotypes and supports epithelial regeneration in a clinically relevant animal airway model. This two-part platform offers a scalable path toward cell therapies for all people with CF and may have broader applications in upper airway epithelial repair.

cell biology↗

bioRxiv2023

Genomic hypomethylation in cell-free DNA predicts responses to checkpoint blockade in lung and breast cancer

Genomic hypomethylation has recently been identified as a determinant of therapeutic responses to immune checkpoint blockade (ICB). However, tumor tissue is often unattainable, and tissue-based methylation profiling suffers from low tumor purity. In this study, we developed an assay named iMethyl to estimate the genomic hypomethylation status from cell-free DNA (cfDNA) as well as tissue by deep targeted sequencing of young LINE-1 elements with > 400,000 reads per sample. iMethyl was applied to a total of 653 ICB samples encompassing lung cancer (cfDNA n=167; tissue n=137; cfDNA early during treatment n=40), breast cancer (cfDNA n=91; tissue n=50; PBMC n=50; cfDNA at progression n=44), and ovarian cancer (tissue n=74). iMethyl-tissue had better predictive power than tumor mutation burden and PD-L1 expression. Furthermore, iMethyl-liquid predicted ICB responses accurately regardless of the tumor purity of tissue samples. iMethyl-liquid was also able to monitor therapeutic responses early during treatment (3 or 6 weeks after initiation of ICB) and detect progressive hypomethylation accompanying tumor progression. In conclusion, our method allows for reliable noninvasive prediction, early evaluation, and monitoring of clinical responses to ICB therapy.

cancer biology↗

bioRxiv2020

Inhibition of Severe Acute Respiratory Syndrome Coronavirus 2 main protease by tafenoquine in vitro

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing the current pandemic, coronavirus disease 2019 (COVID-19), has taken a huge toll on human lives and the global economy. Therefore, effective treatments against this disease are urgently needed. Here, we established a fluorescence resonance energy transfer (FRET)-based high-throughput screening platform to screen compound libraries to identify drugs targeting the SARS-CoV-2 main protease (Mpro), in particular those which are FDA-approved, to be used immediately to treat patients with COVID-19. Mpro has been shown to be one of the most important drug targets among SARS-related coronaviruses as impairment of Mpro blocks processing of viral polyproteins which halts viral replication in host cells. Our findings indicate that the anti-malarial drug tafenoquine (TFQ) induces significant conformational change in SARS-CoV-2 Mpro and diminishes its protease activity. Specifically, TFQ reduces the -helical content of Mpro, which converts it into an inactive form. Moreover, TFQ greatly inhibits SARS-CoV-2 infection in cell culture system. Hence, the current study provides a mechanistic insight into the mode of action of TFQ against SARS-CoV-2 Mpro. Moreover, the low clinical toxicity of TFQ and its strong antiviral activity against SARS-CoV-2 should warrant further testing in clinical trials.

biochemistry↗

bioRxiv2017

NetREX: Network Rewiring using EXpression - Towards Context Specific Regulatory Networks

Understanding gene regulation is a fundamental step towards understanding of how cells function and respond to environmental cues and perturbations. An important step in this direction is the ability to infer the transcription factor (TF)-gene regulatory network (GRN). However gene regulatory networks are typically constructed disregarding the fact that regulatory programs are conditioned on tissue type, developmental stage, sex, and other factors. Due to lack of the biological context specificity, these context-agnostic networks may not provide insight for revealing the precise actions of genes for a specific biological system under concern. Collecting multitude of features required for a reliable construction of GRNs such as physical features (TF binding, chromatin accessibility) and functional features (correlation of expression or chromatin patterns) for every context of interest is costly. Therefore we need methods that is able to utilize the knowledge about a context-agnostic network (or a network constructed in a related context) for construction of a context specific regulatory network.\n\nTo address this challenge we developed a computational approach that utilizes expression data obtained in a specific biological context such as a particular development stage, sex, tissue type and a GRN constructed in a different but related context (alternatively an incomplete or a noisy network for the same context) to construct a context specific GRN. Our method, NetREX, is inspired by network component analysis (NCA) that estimates TF activities and their influences on target genes given predetermined topology of a TF-gene network. To predict a network under a different condition, NetREX removes the restriction that the topology of the TF-gene network is fixed and allows for adding and removing edges to that network. To solve the corresponding optimization problem, which is non-convex and non-smooth, we provide a general mathematical framework allowing use of the recently proposed Proximal Alternative Linearized Maximization technique and prove that our formulation has the properties required for convergence.\n\nWe tested our NetREX on simulated data and subsequently applied it to gene expression data in adult females from 99 hemizygotic lines of the Drosophila deletion (DrosDel) panel. The networks predicted by NetREX showed higher biological consistency than alternative approaches. In addition, we used the list of recently identified targets of the Doublesex (DSX) transcription factor to demonstrate the predictive power of our method.

bioinformatics↗