Biology subjects

Chen, A. X.

Publications and source records attributed to Chen, A. X..

5 recordsLinked to original sources

bioRxiv2026

Functional evaluation of a natural AAV capsid liver targeting motif in human hepatocytes

Background & Aims: Adeno-associated virus (AAV) vectors are attractive delivery vehicles for therapeutic gene delivery, and a notable feature of most AAVs is their natural tropism for the liver, which leads to significant hepatic uptake following systemic administration. In previous work, we identified 266G as a conserved motif on a variable region on the capsid of many commonly used AAV variants that controls liver uptake in both mice and non-human primates. This single amino acid could be functionally leveraged to engineer AAVs to either de-target from or enhance tropism to the liver. Here, we explored whether these observations extended to the human context. Methods: Two human hepatocyte models were tested: Fah-/-/Rag2-/-/Il2rg-/- (FRG) mice with humanized livers and a bioengineered human microliver platform in vitro. A barcoded AAV capsid library including standard control serotypes were used to assess the role of the 266G motif on gene transfer and transgene expression in both liver systems. Results: In vivo, 266G containing AAVs indeed targeted human hepatocytes superiorly, with some noted dependency on the degree of human-hepatocyte replacement in the chimeric mouse model. Initial studies in the micropatterned primary human hepatocyte co-culture model however demonstrated enrichment of heparin-binding AAVs, and not 266G variants. Notably, incorporation of polyethylene glycol (PEG) into the system modified the AAV transduction potential of those capsids including the liver-targeting motif, recapitulating the hepatocyte transduction pattern observed in vivo. Importantly, when PEG was used, the two human models, both at the DNA and RNA level, did correlate significantly. Conclusions: Our results showed the potential of a combinatorial AAV library for model validation and revealed the human microliver platform-PEG as a reliable system for the development of AAV therapeutics.

molecular biology↗

bioRxiv2026

Paired Tumor Biopsies Reveal Spatiotemporal Myeloid Remodeling After Local Chemotherapy in Glioblastoma

BackgroundStandard-of-care chemotherapy for glioblastoma induces inflammation that may contribute to disease recurrence. Although recurrent tumors are enriched with myeloid cells, the early cellular response to chemotherapy and the mechanisms that initiate this inflammatory remodeling remain poorly understood. In particular, it is unknown how neoplastic and tumor-associated myeloid populations respond during the immediate post-treatment period, and whether tumor-associated myeloid cells directly experience chemotherapy-induced genotoxic stress that contributes to inflammatory state transitions. MethodsWe performed sequencing-based analysis of neoplastic and immune populations following topotecan exposure using multiple complementary model systems and time points. We first analyzed MRI-localized, paired pre- and post-treatment biopsies from a first-in-human trial of 28-day convection enhanced delivery (CED) of topotecan (n=5) using cell-type-deconvolved bulk-RNA-sequencing and immunofluorescence. We then treated syngeneic murine gliomas using an in vivo model of CED-topotecan and measured acute 3-day and 7-day treatment responses by single cell RNA-sequencing. We additionally conducted sequencing analysis of patient-derived slice cultures and in vitro human microglial and glioma cell lines following 24-hour topotecan treatment. ResultsIn paired human biopsies, CED-topotecan induced spatially restricted transcriptional remodeling within the infusion zone, characterized by suppression of proliferative tumor programs and enrichment of inflammatory, interferon, hypoxia, and mesenchymal signatures. Cell-type deconvolution and immunofluorescence linked this response to myeloid remodeling, including enrichment of monocyte-derived tumor-associated macrophage states, increased MARCO-positive myeloid populations, and pH2AX-positive genotoxic stress within Iba1-positive myeloid cells. In the murine CED model, topotecan prolonged survival and reduced tumor cellularity, while also inducing inflammatory and DNA-damage programs in tumor-associated macrophages that evolved by 7-days toward hypoxia, angiogenesis, TGF-{beta} signaling, and mesenchymal/tissue-remodeling programs. Human slice culture and in vitro microglial systems confirmed stress-coupled inflammatory and DNA-damage responses in human myeloid cells. ConclusionsChemotherapy exposure induces a spatially structured inflammatory myeloid response characterized by early genotoxic stress and inflammatory activation, with later emergence of mesenchymal and tissue-remodeling macrophage programs. Across model systems, our analysis supports a model in which chemotherapy-associated damage in both tumor and myeloid cells contributes to an evolving inflammatory microenvironment after treatment.

neuroscience↗

bioRxiv2024

Decoupling Coldness and Softness in Tactile Wetness Perception Using Tunable Hydrogels

This study investigates the perception of tactile wetness, a complex sensation experienced by humans. Previous research has primarily focused on either thermal or mechanical cues separately, or has used textiles as stimuli whose parameters are difficult to control. Here, we employed polyacrylamide hydrogels with varying stiffness levels soaked in liquids of distinct thermal conductivities. By psychophysically evaluating participants perception of wetness, we showed that the wetness judgments for the samples exhibit a transitive relationship based on the mechanical and thermal cues from an intrinsically tunable organic material. We developed a prediction model of human wetness judgment with an accuracy of 90% and found that the best metrics for the most accurate model were those that were the most human-adjacent: change in temperature at the skin-sample interface (thermal) and compressive force from 2 mm indentation of the sample (mechanical). Given these parameters, we developed a perceptual space capable of recreating 7 distinct levels of wetness perception with the physical parameters used in this study. The results provide insights into the relative contributions of mechanical and thermal stimulus properties in wetness perception. Most notably, this work highlights that the physical characteristics of the skin-stimulus interface can provide ample information for creating a wetness perceptual space, as opposed to the chemical composition of the hydrogels.

neuroscience↗

bioRxiv2020

Scale-free structure of cancer networks and their vulnerability to hub-directed combination therapy

Background The effectiveness of many targeted therapies is limited by toxicity and the rise of drug resistance. A growing appreciation of the inherent redundancies of cancer signaling has led to a rise in the number of combination therapies under development, but a better understanding of the overall cancer network topology would provide a conceptual framework for choosing effective combination partners. In this work, we explore the scale-free nature of cancer protein-protein interaction networks in 14 indications. Scale-free networks, characterized by a power-law degree distribution, are known to be resilient to random attack on their nodes, yet vulnerable to directed attacks on their hubs (their most highly connected nodes).Results Consistent with the properties of scale-free networks, we find that lethal genes are associated with ∼5-fold higher protein connectivity partners than non-lethal genes. This provides a biological rationale for a hub-centered combination attack. Our simulations show that combinations targeting hubs can efficiently disrupt 50% of network integrity by inhibiting less than 1% of the connected proteins, whereas a random attack can require inhibition of more than 30% of the connected proteins.Conclusions We find that the scale-free nature of cancer networks makes them vulnerable to focused attack on their highly connected protein hubs. Thus, we propose a new strategy for designing combination therapies by targeting hubs in cancer networks that are not associated with relevant toxicity networks.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

bioRxiv2019

Machine learning guided association of adverse drug reactions with in vitro target-based pharmacology

Adverse drug reactions (ADRs) are one of the leading causes of morbidity and mortality in health care. Understanding which drug targets are linked to ADRs can lead to the development of safer medicines. Here, we analyze in vitro secondary pharmacology of common (off) targets for 2134 marketed drugs. To associate these drugs with human ADRs, we utilized FDA Adverse Event Reports and developed random forest models that predict ADR occurrences from in vitro pharmacological profiles. By evaluating Gini importance scores of model features, we identify 221 target-ADR associations, which co-occur in PubMed abstracts to a greater extent than expected by chance. Among these are established relations, such as the association of in vitro hERG binding with cardiac arrhythmias, which further validate our machine learning approach. Evidence on bile acid metabolism supports our identification of associations between the Bile Salt Export Pump and renal, thyroid, lipid metabolism, respiratory tract and central nervous system disorders. Unexpectedly, our model suggests PDE3 is associated with 40 ADRs. These associations provide a comprehensive resource to support drug development and human biology studies.

pharmacology and toxicology↗