Biology subjects

Zhu, I.

Publications and source records attributed to Zhu, I..

6 recordsLinked to original sources

bioRxiv2026

Synthetic Hybrid Receptors for Safer and Programmable T Cell Therapy

Engineered T cell therapies have achieved significant clinical success in hematological malignancies but remain largely ineffective in solid tumors. Overcoming this limitation requires strategies that enhance T cell function while avoiding systemic immune toxicities and pathological T cell states. Existing approaches typically rely on constitutive gene overexpression or suppression to augment potency or remodel the tumor microenvironment, but these strategies frequently lead to dysregulated immune activation and dose-limiting toxicity. Here, we present Hybrid Receptors (Hybrid-Rs), a modular receptor platform that integrates features of chimeric antigen receptors (CARs) and SyNthetic Intramembrane Proteolysis Receptors (SNIPRs) to couple antigen-dependent T cell activation with programmable gene regulation. Hybrid-Rs enable precise, context-dependent control of T cell potency, differentiation states, and conditional expression of secreted immunotherapeutic payloads with otherwise prohibitive toxicity. Hybrid-Rs are readily humanized and compatible with precision genome editing in primary human T cells, providing a direct and practical path to clinical translation.

bioengineering↗

bioRxiv2025

Optimizing the Characterization and Quantification of Retinal Ganglion Cell Somas in Healthy and Injured Retinas Using Cellpose

Quantification of retinal ganglion cell (RGC) soma number and characterization of somal features are commonly used output metrics for investigation of optic neuropathies. Many investigators still perform these quantifications by hand, which is time consuming and prone to bias. Cellpose is an open-source Python package that can perform cellular segmentation and holds promise for automating somal analyses. Here, we designed a custom script incorporating the Cellpose package and custom-trained Cellpose models that are capable of automatic characterization and quantification of RGC somas. Our script, using our models, is capable of automatically counting RGC somas, along with characterizing RGC somal size. Further, we show that Cellpose can quantify RGCs using multiple cell-type specific markers and has the potential to quantify RGCs across the entire retina. Together, our custom Cellpose models and script which generates and analyzes Cellpose outputs provides a powerful tool for all-in-one RGC somal analysis.

neuroscience↗

bioRxiv2025

Interferon signaling underlies radiotherapy responses in malignant peripheral nerve sheath tumors (MPNSTs)

Malignant peripheral nerve sheath tumors (MPNSTs) have poor outcomes despite multimodal treatment with surgery, radiation, and systemic therapy. Here, we combine bulk and single cell transcriptomics, genome wide CRISPRi screens, and multiplatform molecular analysis across MPNST cells, mouse allograft models, and human patient samples to understand the mediators of radiation response. Our data reveal MPNSTs induce a type I interferon signature that functionally underlies radiation response. Moreover, irradiation of immunocompetent mouse MPNST allografts leads to interferon mediated T-cell recruitment and activation. Analysis of human MPNST resection specimens demonstrates increased microenvironmental and CD8+ T-cell infiltration are associated with improved local control following radiotherapy while chromosome 9p loss, which harbors an interferon gene cluster, is associated with poor radiotherapy response and decreased CD8+ T-cell infiltration. Taken together, these results provide preclinical rationale for combining immunomodulatory agents targeting interferon signaling to improve radiation responses in MPNSTs, which may be broadly applicable to other soft tissue sarcomas.

cancer biology↗

bioRxiv2024

Engineered Receptors for Soluble Cell-to-Cell Communication

Despite recent advances in mammalian synthetic biology, there remains a lack of modular synthetic receptors that can robustly respond to soluble ligands and in turn activate cellular functions. Such receptors would have extensive clinical potential to regulate the activity of engineered therapeutic cells, but to date only receptors against cell surface targets have approached clinical translation. To address this gap, we developed a receptor architecture based on synNotch, called SyNthetic Intramembrane Proteolysis Receptor (SNIPR), that has the added ability to be activated by soluble ligands, both natural and synthetic, with remarkably low baseline activity and high fold activation. SNIPRs are able to access an endocytic, pH-dependent cleavage mechanism to achieve soluble ligand sensing, in addition to employing a canonical-like pathway for detecting surface-bound ligands. We demonstrate the therapeutic capabilities of the receptor platform by localizing the activity of CAR T-cells to solid tumors where soluble disease-associated factors are expressed, bypassing the major hurdle of on-target off-tumor toxicity in bystander organs. We further applied the SNIPR platform to engineer fully synthetic signaling networks between cells orthogonal to natural signaling pathways, expanding the scope of synthetic biology. Our design framework enables cellular communication and environmental interactions, extending the capabilities of synthetic cellular networking in clinical and research contexts.

bioengineering↗

bioRxiv2022

Antigen-dependent inducible T cell reporter system for PET imaging of breast cancer and glioblastoma

For the past several decades, chimeric antigen receptor T cell (CAR T) therapies have shown promise in the treatment of cancers. These treatments would greatly benefit from companion imaging biomarkers to follow the trafficking of T cells in vivo. Using synthetic biology, we engineered T cells with a chimeric receptor SyNthetic Intramembrane Proteolysis Receptor (SNIPR) that induces overexpression of an exogenous reporter gene cassette upon recognition of specific tumor markers. We then applied a SNIPR-based positron emission tomography (PET) reporter system to two cancer-relevant antigens, human epidermal growth factor receptor 2 (HER2) and epidermal growth factor receptor variant III (EGFRvIII), commonly expressed in breast and glial tumors respectively. Antigen-specific reporter induction of the SNIPR-PET T cells was confirmed in vitro using GFP fluorescence, luciferase luminescence, and the HSV-TK PET reporter with [18F]FHBG. T cells associated with their target antigens were successfully imaged using PET in dual xenograft HER2+/HER2- and EGFRvIII+/EGFRvIII-animal models, with > 10-fold higher [18F]FHBG signals seen in antigen-expressing tumors versus the corresponding controls. The main innovation described is therefore PET detection of T cells via specific antigen-induced signals, in contrast to reporter systems relying on constitutive gene expression.

synthetic biology↗

bioRxiv2021

Design and modular assembly of synthetic intramembrane proteolysis receptors for custom gene regulation in therapeutic cells

Synthetic biology has established powerful tools to precisely control cell function. Engineering these systems to meet clinical requirements has enormous medical implications. Here, we adopted a clinically driven design process to build receptors for the autonomous control of therapeutic cells. We examined the function of key domains involved in regulated intramembrane proteolysis and showed that systematic modular engineering can generate a class of receptors we call SyNthetic Intramembrane Proteolysis Receptors (SNIPRs) that have tunable sensing and transcriptional response abilities. We demonstrate the potential transformative utility of the receptor platform by engineering human primary T cells for multi-antigen recognition and production of dosed, bioactive payloads relevant to the treatment of disease. Our design framework enables the development of fully humanized and customizable transcriptional receptors for the programming of therapeutic cells suitable for clinical translation.

synthetic biology↗