Biology subjects

Guan, N.

Publications and source records attributed to Guan, N..

8 recordsLinked to original sources

bioRxiv2026

Early dynamics of a neutrophil interferon program drive immunotherapy resistance and limit durable anti-tumor immunity

Despite the remarkable success of immune checkpoint blockade (ICB), durable clinical benefit remains limited to a subset of patients, highlighting the need for predictive biomarkers and new therapeutic targets. Here, we investigated the early immune dynamics associated with anti-PD1 responsiveness using longitudinal single-cell transcriptomics, spatial transcriptomics, and neutrophil-specific genetic perturbations in preclinical models of triple-negative breast cancer. We identified a conserved neutrophil interferon-stimulated gene (ISG) program that emerges before overt tumor divergence and predicts resistance to anti-PD1 therapy. Successful treatment was associated with an early reduction of IFN-responsive neutrophils in both blood and tumor tissues, whereas persistent neutrophil IFN signaling correlated with therapeutic resistance. Mechanistically, genetic disruption of either type I or type II interferon signaling in neutrophils enhanced anti-PD1 efficacy and promoted durable anti-tumor immune memory. Spatial analyses further revealed an inverse association between IFN-responsive neutrophils and tertiary lymphoid structure-enriched regions during effective therapy. Together, these findings identify IFN-responsive neutrophils as early determinants of immunotherapy outcome and establish dynamic neutrophil interferon programs as candidate blood-based biomarkers and therapeutic targets for cancer immunotherapy.

cancer biology↗

bioRxiv2026

MERTK inhibition cooperates with immunomodulatory cyclophosphamide to induce CXCL9⁺ monocyte-macrophage programming and durable anti-tumor immunity in triple negative breast cancer

Triple-negative breast cancer (TNBC) has high rates of recurrence despite chemotherapy and immune checkpoint blockade (ICB). Tumor-associated macrophages (TAMs) can either suppress or support anti-tumor immunity, but the mechanisms governing these states and therapeutic targets remain unclear. Here, integrating public scRNAseq datasets with TNBC cohorts, we identify a prognostic myeloid signature defined by CXCL9hi/C1Qlow TAM programs, associated with improved survival and increased lymphocyte activation pathways. Using immunocompetent p53-null syngeneic TNBC models spanning basal-like (2153L) and claudin-low (T12) subtypes, we show that immunomodulatory cyclophosphamide (CTX) reprograms hematopoiesis toward the monocytic lineage and induces an interferon (IFN) conditioned tumor milieu that supports CXCL9 monocyte-derived macrophages (Mo.Macs) in basal-like disease. Combining CTX with the next generation MERTK-selective inhibitor UNC2371 (MRX-2843) drives complete remissions in both models, but durable long-term responses occurred selectively in the basal-like subtype model. The expansion of antigen-presenting CXCL9 Mo.Macs and reduction of C1q phagocytic TAMs are observed in responding tumors. Mechanistically, MERTK inhibition relieves MAPK/SOCS1 mediated restraint of IFN signaling driving a positive feedback loop of IRF7/STAT1/IRF1 driven CXCL9 induction. Functionally, tumor control requires CXCL9-CXCR3 dependent CD4 T cell recruitment, accumulation of stem-like memory CD4 T cells, and germinal center like immune organization in tumor-draining lymph nodes. PD-1 blockade further increases durability, preventing recurrence in most treated basal-like tumors. Together, these findings define an IFN licensed, MERTK regulated myeloid checkpoint that can be therapeutically targeted to convert suppressive TNBC microenvironments into durable adaptive immunity, supporting clinical translation of CTX + MRX-2843 based combinations in basal-like TNBC. SignificanceSuppressive myeloid programing limits effective adaptive immune engagement in TNBC usually resulting in ICB treatment resistance and tumor recurrence. This study identifies a therapeutically actionable myeloid interferon checkpoint in which MERTK inhibition stabilizes CXCL9 monocyte-macrophage programming to promote CD4 T cell dependent immune memory and durable tumor control in basal-like TNBC.

cancer biology↗

bioRxiv2025

A rapid and efficient red-light-activated Cre recombinase system for genome engineering in mammalian cells and transgenic mice

The Cre-loxP recombination system enables precise genome engineering; however, existing photoactivatable Cre tools suffer from several limitations, including low DNA recombination efficiency, background activation, slow activation kinetics, and poor tissue penetration. Here, we present REDMAPCre, a red-light-controlled split-Cre system based on the {Delta}PhyA/FHY1 interaction. REDMAPCre enables rapid activation (1-second illumination) and achieves an 85-fold increase in recombination efficiency. We demonstrate its efficient regulation of DNA recombination in mammalian cells and mice, as well as its compatibility with other inducible recombinase systems for Boolean logic-gated DNA recombination. Using a single-vector adeno-associated virus (AAV) delivery system, we successfully induced REDMAPCre-mediated DNA recombination in mice. Furthermore, we generated a REDMAPCre transgenic mouse line and validated its efficient, light-dependent recombination across multiple organs. To explore its functional applications, REDMAPCre transgenic mice were crossed with the relative Cre-dependent reporter mice, enabling optogenetic induction of insulin resistance and hepatic lipid accumulation via Cre-dependent overexpression of ubiquitin-like with PHD and ring finger domains 1 (UHRF1), as well as targeted cell ablation through diphtheria toxin fragment A (DTA) expression. Collectively, REDMAPCre provides a powerful tool for achieving remote control of recombination and facilitating functional genetic studies in living systems.

synthetic biology↗

bioRxiv2022

An unbiased characterization of the HLA-E and CD94/NKG2x peptide repertoire reveals peptide ligands that skew NK cell activation

HLA-E is a non-classical class I MHC protein involved in innate and adaptive immune recognition. While recent studies have shown HLA-E can present diverse peptides to NK cells and T cells, the HLA-E and NK receptor peptide repertoire has remained poorly defined, with only a limited number of peptide ligands identified. Here we screen a yeast-displayed peptide library in the context of HLA-E to identify 500 high-confidence unique peptides that bind both HLA-E and CD94/NKG2A or CD94/NKG2C. Utilizing the sequences identified via yeast display selections, we train prediction algorithms and identify human and cytomegalovirus (CMV) proteome-derived, HLA-E-presented peptides capable of binding and signaling through both CD94/NKG2A and CD94/NKG2C. In addition, we identify peptides which selectively activate NKG2C+ NK cells. Taken together, characterization of the HLA-E-binding peptide repertoire and identification of NK activity-modulating peptides present opportunities for studies of NK cell regulation in health and disease, in addition to vaccine and therapeutic design.

immunology↗

bioRxiv2022

Porous microneedle patch with sustained exosomes delivery repairs severe spinal cord injury

1.Mesenchymal stem cell-derived exosome (MSC-EXO) transplantation has been suggested as an efficacious treatment to suppress spinal cord injury (SCI)-triggered neuroinflammation. However, an ethically acceptable method to continuously deliver MSC-EXOs to acute spinal lesions, without damaging nearby tissues/axons, has never been achieved. In this study, we fabricated a device comprising a patch containing MSCs and a microneedle array (MN-MSC patch) to treat severe SCI. When topically applied to an acute spinal lesion beneath the spinal dura, the soft microneedle (MN) array with reasonable mechanical strength avoided damaging the nearby spinal tissues, and the porous microstructure of MNs facilitated highly efficient MSC-EXO delivery. With the capacity for sustained delivery of MSC-EXOs, the MN-MSC patch was evaluated in a contusive rat SCI model. The MSCs encapsulated in the patch could survive for at least 7 days, encompassing the optimal time window for downregulating SCI-triggered neuroinflammation. As a result, MN-MSC patch treatment led to reduced cavity and scar tissue formation, greater angiogenesis, and improved survival of nearby tissues/axons. Remarkably, rats treated by this method achieved superior muscle control and exhibited robust hindlimb locomotion functional recovery. Conclusively, the MN-MSC patch device proposed here overcomes the current dilemma between treatment efficacy and ethical issues in treating acute SCI.

bioengineering↗

bioRxiv2022

Protein 3D structure-based neural networks highly improve the accuracy in compound-protein binding affinity prediction

Due to the lack of a method to efficiently represent the multimodal information of a protein, including its structure and sequence information, predicting compound-protein binding affinity (CPA) still suffers from low accuracy when applying machine learning methods. To overcome this limitation, in a novel end-to-end architecture (named FeatNN), we develop a coevolutionary strategy to jointly represent the structure and sequence features of proteins and ultimately optimize the mathematical models for predicting CPA. Furthermore, from the perspective of data-driven approach, we proposed a rational method that can utilize both high- and low-quality databases to optimize the accuracy and generalization ability of FeatNN in CPA prediction tasks. Notably, we visually interpret the feature interaction process between sequence and structure in the rationally designed architecture. As a result, FeatNN considerably outperforms the state-of-the-art (SOTA) baseline in virtual drug screening tasks, indicating the feasibility of this approach for practical use. FeatNN provides an outstanding method for higher CPA prediction accuracy and better generalization ability by efficiently representing multimodal information of proteins via a coevolutionary strategy.

bioinformatics↗

bioRxiv2019

Measurement and models accounting for cell death capture hidden variation in compound response

Cancer cell sensitivity or resistance is almost universally quantified through a direct or surrogate measure of cell number. However, compound responses can occur through many distinct phenotypic outcomes including changes in cell growth, apoptosis, and non-apoptotic cell death. These outcomes have distinct effects on the tumor microenvironment, immune responses, and resistance mechanisms. Here, we show that quantifying cell viability alone is insufficient to distinguish between these compound responses. Using an alternative assay and drug response analysis amenable to high-throughput measurement, we find that compounds with identical viability outcomes can have very different effects on cell growth and death. Moreover, compound pairs with additive cell growth and death effects can appear synergistic when only assessed by viability. Overall, these results demonstrate an approach to incorporating measurements of cell death when characterizing a pharmacologic response. Summary PointsO_LIMeasurements of solely live cell numbers mask important differences in compound effects. C_LIO_LIAdditive effects on growth and death rates can appear synergistic when analyzed solely via live cell number. C_LIO_LIAutomated imaging can provide reasonable throughput to analyze cell response in terms of cell growth and death, and endpoint analysis is similarly informative. C_LI

cancer biology↗

bioRxiv2017

Dissecting FcγR Regulation Through a Multivalent Binding Model

Many immune receptors transduce activation across the plasma membrane through their clustering. With Fc{gamma} receptors, this clustering is driven by binding to antibodies of differing affinities that are in turn bound to multivalent antigen. As a consequence of this activation mechanism, accounting for and rationally manipulating IgG effector function is complicated by, among other factors, differing affinities between Fc{gamma}R species and changes in the valency of antigen binding. In this study, we show that a model of multivalent receptor-ligand binding can effectively account for the contribution of IgG-Fc{gamma}R affinity and immune complex valency. This model in turn enables us to make specific predictions about the effect of immune complexes of defined composition. In total, these results enable both rational immune complex design for a desired IgG effector function and the deconvolution of effector function by immune complexes.\n\nSummary pointsO_LIAvidity most prominently modulates low-affinity Fc{gamma}R-immune complex binding\nC_LIO_LIA multivalent binding model can quantitatively predict Fc{gamma}R-immune complex binding\nC_LIO_LIImmune complex avidity has an outsized contribution to Fc{gamma}R multimerizationas compared to binding\nC_LIO_LIA binding model deconvoles and predicts the influence of interventions modulating in vivo Fc{gamma}R-driven effector function\nC_LI

immunology↗