Biology subjects

Chang, C.-J.

Publications and source records attributed to Chang, C.-J..

9 recordsLinked to original sources

bioRxiv2025

Targeting MDM2 homodimer and heterodimer disruption with DRx-098D in TP53 wild-type and mutant cancer cells

Novel pharmacological strategies capable of inhibiting pro-oncogenic MDM2 beyond its p53-dependent functions represents an increasingly attractive therapeutic strategy to treating solid and haematological cancers that are depdendent upon MDM2/MDMX, regardless of TP53 mutational status. Utilising a novel first-in-class cell-penetrating peptide disruptor of MDM2 homo- and heterodimerisation (DRx-098D), we demonstrate the anti-proliferative effect of blocking MDM2 dimerisation against a a panel of human cancer cell lines that are TP53 wild-type, mutant or null. DRx-098D elicits its anti-cancer activity via a differentiated mechanism vs. Idasanutlin (a Phase III clinical candidate MDM2-p53 small molecule inhibitor), inducing significantly superior growth inhibition against TP53 null HCT116 cells. Our preliminary data highlight, for the first time, the potential therapeutic utility of exploiting MDM2 dimerisation in TP53 wild-type and mutant cancers.

cancer biology↗

bioRxiv2024

DriverOmicsNet: An Integrated Graph Convolutional Network for Multi-Omics Exploration of Cancer Driver Genes

BackgroundCancer is a complex and heterogeneous group of diseases driven by genetic mutations and molecular changes. Identifying and characterizing cancer driver genes (CDgs) is crucial for understanding cancer biology and guiding precision oncology. Integrating multi-omics data can reveal the intricate molecular interactions underlying cancer progression and treatment responses. MethodsWe developed a graph convolutional network (GCN) framework, DriverOmicsNet, that integrates multi-omics data using STRING protein-protein interaction (PPI) networks and correlation-based weighted correlation network analysis (WGCNA). We applied this framework to 15 cancer types, analyzing 5555 tumor samples to predict cancer-related features such as homologous recombination deficiency (HRD), cancer stemness, immune clusters, tumor stage, and survival outcomes. FindingsDriverOmicsNet demonstrated superior predictive accuracy and model performance metrics across all target labels when compared with GCN models based on STRING network alone. Gene expression emerged as the most significant feature, reflecting the dynamic and functional state of cancer cells. The combined use of STRING PPI and WGCNA networks enhanced the identification of key driver genes and their interactions. InterpretationOur study highlights the effectiveness of using GCNs to integrate multi-omics data for precision oncology. The integration of STRING PPI and WGCNA networks provides a comprehensive framework that improves predictive power and facilitates the understanding of cancer biology, paving the way for more tailored treatments.

cancer biology↗

bioRxiv2023

Predictive Systems Biology Modeling: Unraveling Host Metabolic Disruptions and Potential Drug Targets in SARS-CoV-2 and Its Variants

BackgroundHost response is critical to the onset, progression, and outcome of viral infections. Since viruses hijack the host cellular metabolism for their replications, we hypothesized that restoring host cell metabolism can efficiently reduce viral production. ResultsHere, we present a viral-host Metabolic Modeling (vhMM) method to systematically evaluate the disturbances in host metabolism in viral infection and computationally identify targets for modulation by integrating genome-wide precision metabolic modeling and cheminformatics. We applied vhMM to SARS-CoV-2 infections and identified consistent changes in host metabolism and gene and endogenous metabolite targets between the original SARS-COV-2 and different variants (Alpha, Delta, and Omicron). Among six compounds predicted for repurposing, methotrexate, cinnamaldehyde, and deferiprone were tested in vitro and effective in inhibiting viral production with IC50 less than 4uM. Further, an analysis of real-world patient data showed that cinnamon usage significantly reduced the SARS-CoV-2 infection rate with an odds ratio of 0.65 [95%CI: 0.55[~]0.75]. ConclusionsThese results demonstrated that vhMM is an efficient method for predicting targets and drugs for viral infections.

systems biology↗

bioRxiv2021

Behavioral clusters revealed by end-to-end decoding from microendoscopic imaging

In vivo calcium imaging using head-mounted miniature microscopes enables tracking activity from neural populations over weeks in freely behaving animals. Previous studies focus on inferring behavior from a population of neurons, yet it is challenging to extract neuronal signals given out-of-focus fluorescence in endoscopic data. Existing analysis pipelines include regions of interest (ROIs) identification, which might lose relevant information from false negatives or introduce unintended bias from false positives. Moreover, these methods often require prior knowledge for parameter tuning and are time-consuming for implementation. Here, we develop an end-to-end decoder to predict the behavioral variables directly from the raw microendoscopic images. Our framework requires little user input and outperforms existing decoders that need ROI extraction. We show that neuropil/background residuals carry additional behaviorally relevant information. Video analysis further reveals an optimal decoding window and dynamics between residuals and cells. Critically, saliency maps reveal the emergence of video-decomposition across our decoder, and identify distinct clusters representing different behavioral aspects. Together, we present a framework that is efficient for decoding behavior from microendoscopic imaging, and may help discover functional clustering for a variety of imaging studies.

neuroscience↗

bioRxiv2020

Segmentation boosting with compensation methods in optical coherence tomography angiography images

Optical coherence tomography angiography is a noninvasive imaging modality to establish the diagnosis of retinal vascular diseases. However, angiography images are significantly interfered if patients jitter or blink. In this study, a novel retinal image analysis method to accurately detect blood vessels and compensate the effect of interference was proposed. We call this the patch U-Net compensation (PUC) system, which is based on the famous U-Net. Several techniques, including a better training mechanism, direction criteria, area criteria, gap criteria, and probability map criteria, have been proposed to improve its accuracy. Simulations show that the proposed PUC achieves much better performance than state-of-art methods.

bioengineering↗

bioRxiv2019

Redundancy and specificity of type VI secretion vgrG loci in antibacterial activity of Agrobacterium tumefaciens 1D1609 strain

Type VI secretion system (T6SS) is a contractile nanoweapon employed by many Proteobacteria to deliver effectors to kill or inhibit their competitors. One T6SS gene, vgrG, encodes a spike protein for effector translocation and is often present as multiple copies in bacterial genomes. Our phylogenomic analyses sampled 48 genomes across diverse Proteobacteria lineages and found [~]70% of them encode multiple VgrGs, yet only four genomes have nearly identical paralogs. Among these four, Agrobacterium tumefaciens 1D1609 has the highest vgrG redundancy. Compared to A. tumefaciens model strain C58 which harbors two vgrG genes, 1D1609 encodes four vgrG genes (i.e. vgrGa-d) with each adjacent to different putative effector genes. Thus, 1D1609 was selected to investigate the functional redundancy and specificity of multiple vgrG genes and their associated effectors. Secretion assay of single and multiple vgrG deletion mutants demonstrated that these four vgrGs are functionally redundant in mediating T6SS secretion. By analyzing various vgrG mutants, we found that all except for the divergent vgrGb could contribute to 1D1609s antibacterial activity. Further characterizations of putative effector-immunity gene pairs revealed that vgrGa-associated gene 2 (v2a) encodes an AHH family nuclease and serves as the major antibacterial toxin. Interestingly, C58s VgrG2 shares 99% amino acid sequence identity with 1D1609s VgrGa, VgrGc and VgrGd. This high sequence similarity allows 1D1609 to use an exogenous VgrG delivered from C58 to kill another competing bacterium. Taken together, Agrobacterium can use highly similar VgrGs, either produced endogenously or injected from its close relatives, for T6SS-mediated interbacterial competition. Authors SummarySelective pressure drives bacteria to develop adaptive strategies, which include competitive and cooperative behaviors. Type VI secretion system (T6SS) is one powerful antibacterial and anti-host nanoweapon employed by many Gram-negative bacteria for growth advantages or pathogenesis. A T6SS-harboring bacterium can encode one to multiple VgrG proteins for delivery of cognate effector(s) but the prevalence and biological significance of having sequence redundant vgrGs have not been comprehensively explored. In this study, we investigated the extensiveness of having multicopy vgrG genes for effector delivery among diverse Proteobacteria with T6SS. Moreover, a plant pathogenic bacterium Agrobacterium tumefaciens strain 1D1609 with highest vgrG redundancy was selected for detailed characterization of the roles of multiple VgrGs in T6SS secretion and antibacterial activity. We revealed that the majority of Proteobacterial genomes harbor multiple copies of vgrG and the expansion of vgrG gene clusters contributed to effector diversity and functional redundancy. Furthermore, the near identical VgrG proteins between 1D1609 and its sibling strain C58 can be exchanged for effector delivery in killing another competing bacterium. Such strategy in using exchangeable effector carriers injected from its isogenic sibling or close relatives during T6SS attacks may be a beneficial strategy for agrobacteria to compete in their ecological niche.

microbiology↗

bioRxiv2018

Acute Food Deprivation Rapidly Modifies Valence-Coding Microcircuits in the Amygdala

In the quest for food, we may expend effort and increase our vulnerability to potential threats. Motivation to seek food is dynamic, varying with homeostatic need. What mechanisms underlie these changes? Basolateral amygdala neurons projecting to the nucleus accumbens (BLA[->]NAc) preferentially encode positive valence, whereas those targeting the centromedial amygdala (BLA[->]CeM) preferentially encode negative valence. Longitudinal in vivo two-photon calcium imaging revealed that BLA[->]NAc neurons were more active, while BLA[->]CeM neurons were less active, following just 1 day of food deprivation. Photostimulating BLA[->]CeM neurons inhibited BLA[->]NAc neurons at baseline, but food deprivation rapidly converted this inhibition into facilitation, supporting a model wherein BLA[->]NAc excitability mediates invigorated food-seeking behavior after deprivation. Indeed, inhibiting BLA[->]NAc reduced motivation for a caloric reinforcer in food deprived animals. Taken together, negative valence overrides positive valence processing in satiety, but changing homeostatic needs alter reward value via a rapid shift in the balance between projection-defined populations of BLA neurons.

neuroscience↗

bioRxiv2017

Collection and Storage of HLA NGS Genotyping Data for the 17th International HLA and Immunogenetics Workshop

For over 50 years, the International HLA and Immunogenetics Workshops (IHIW) have advanced the fields of histocompatibility and immunogenetics (H&I) via community sharing of technology, experience and reagents, and the establishment of ongoing collaborative projects. In the fall of 2017, the 17th IHIW will focus on the application of next generation sequencing (NGS) technologies for clinical and research goals in the H&I fields. NGS technologies have the potential to allow dramatic insights and advances in these fields, but the scope and sheer quantity of data associated with NGS raise challenges for their analysis, collection, exchange and storage. The 17 th IHIW has adopted a centralized approach to these issues, and we have been developing the tools, services and systems to create an effective system for capturing and managing these NGS data. We have worked with NGS platform and software developers to define a set of distinct but equivalent NGS typing reports that record NGS data in a uniform fashion. The 17th IHIW database applies our standards, tools and services to collect, validate and store those structured, multi-platform data in an automated fashion. We are creating community resources to enable exploration of the vast store of curated sequence and allele-name data in the IPD-IMGT/HLA Database, with the goal of creating a long-term community resource that integrates these curated data with new NGS sequence and polymorphism data, for advanced analyses and applications.\n\nAbbreviations

bioinformatics↗

bioRxiv2017

An integral role for timing in interception

Timing is critical for myriad behaviors in dynamic environments. For example, to intercept an object, the brain must compute a reliable estimate of time-to-contact (TTC). Prior work suggests that humans compute TTC using kinematic information such as distance and speed without explicitly relying on temporal cues, just as one would do in a physics classroom using kinematic equations. Considering the inherent uncertainty associated with estimates of speed and distance and the ability of human brain to combine different sources of information, we asked whether humans additionally rely on temporal cues. We found that humans actively integrate speed information with both explicit and implicit timing cues. Analysis of behavior in relation to a Bayesian model revealed that the additional temporal information helps subjects optimize their performance in the presence of measurement uncertainty. These findings suggest that brains timing mechanisms are actively engaged while interacting with dynamic stimuli.

animal behavior and cognition↗