Biology subjects

Sunwoo, J. B.

Publications and source records attributed to Sunwoo, J. B..

10 recordsLinked to original sources

bioRxiv2025

LabOS: The AI Co-Scientist That Sees and Works With Humans

Modern science advances fastest when thought meets action. LabOS represents the first AI co-scientist that unites computational reasoning with physical experimentation through multimodal perception, self-evolving agents, and XR-enabled, embodied human-AI collaboration. To empower agentic AI with embodied intelligence, we built LabSuperVision, the first vision-language-model (VLM) benchmark spanning biomedical and materials science laboratories, designed to evaluate scientific perception and reasoning. This endowed LabOS with visual reasoning capabilities that surpass those of general-purpose models on laboratory-specific tasks. By connecting multi-model AI agents, smart glasses, and human-AI-robot collaboration, LabOS allows AI to see what scientists see, understand experimental context, and participate in real-time execution through immersive XR interaction and robotic autonomation. Across applications-from cancer immunotherapy target discovery to cell engineering-LabOS shows that AI can move beyond computational design to participation, turning the laboratory into an intelligent, collaborative environment where human and machine discovery evolve together.

bioengineering↗

bioRxiv2025

Surfaceome CRISPR activation screening uncovers ligands regulating tumor sensitivity to NK cell killing

Natural killer (NK) cell-based immunotherapies represent a promising avenue for cancer treatment due to their ability to eliminate cancer cells independently of antigen presentation and potential for "off-the-shelf" use. However, the molecular determinants governing tumor cell susceptibility to NK cell-mediated cytotoxicity remain incompletely understood. Here we employed CRISPR activation (CRISPRa) screening to systematically identify cancer cell surface regulators of NK cell killing across multiple cancer types. Using a comprehensive surfaceome-focused library, we screened human and murine cancer cell lines co-cultured with NK cells, identifying both known and novel ligands that modulate NK cell cytotoxicity. Our screens revealed established factors including CD43 (encoded by SPN), while uncovering previously uncharacterized regulators such as CD44, PDPN, and Siglec-1/CD169. Validation through complementary cDNA overexpression and genetic knockout approaches confirmed that disruption of CD43, CD44, PDPN, and Siglec-1 significantly altered cancer cell susceptibility to NK killing both in vitro and in humanized mouse models. Analysis of clinical datasets show that expression of identified factors correlates with patient survival outcomes in an NK-context dependent manner supporting their therapeutic relevance. Most notably, our mechanistic studies demonstrate that CD43-mediated NK cell resistance operates independently of its previously proposed interaction with Siglec-7 on NK cells. Furthermore, we find that targeting CD43 on either NK cells or engineered T cells substantially enhances their cytotoxic activity against leukemia cell lines. These results establish gain-of-function screening as a powerful approach for discovering immunoregulatory surface proteins and identify multiple promising targets for enhancing NK cell-based cancer immunotherapies.

immunology↗

bioRxiv2025

Alphavirus replicon particle expressing IL-12 reprograms tumor-associated macrophages and neutrophils and induces anti-tumor immunity

Cancers evade anti-tumor immunity by the infiltration of immunosuppressive myeloid cells such as macrophages and neutrophils into the tumor microenvironment (TME). The limited efficacy of current immunotherapy is attributed to the presence of these immunosuppressive cells. Here, we describe a novel immunotherapy approach, using a single-cycle alphavirus replicon particle (VRP) that carries a self-amplifying RNA encoding interleukin-12 (IL-12). Leveraging the natural tropism of alphavirus to myeloid cells, single cell transcriptomic analyses of mouse tumor tissues demonstrated that intratumoral (i.t.) injection of the vector effectively reprogrammed tumor-associated macrophages and neutrophils toward a pro-inflammatory, anti-tumor phenotype via interferon signaling, further enhanced by IL-12 expression. The treatment also induced cytotoxic NK and T cell responses, resulting in a significant reduction of tumor growth and effectively preventing nodal and distant metastases in solid tumor mouse models. By targeting tumor-supporting myeloid cells to transform the TME into an immune-active state, our myeloid modulation approach has the potential to enhance the efficacy of current immunotherapies.

cancer biology↗

bioRxiv2025

MONTAGE: A Computation Framework to Identify Spatially Resolved Functional Enrichment Gradients in the Tissue Microenvironment via Spatial Communities

Single-cell spatial-omics has advanced our understanding of how tumor microenvironment contributes to cancer progression. However, most single-cell spatial-omics studies focus on cell types and neighborhoods, offering limited information about functional and clinical relevance of cellular organization. We introduce MONTAGE, a computational framework to reconstruct, functionally analyze, and identify clinically relevant cellular spatial communities (SCs). MONTAGE generates a gene signature matrix of SCs from integrated atlases that offer single-cell resolution with transcriptomics, and reconstructs tissue maps ("montages"), reflecting sequential SC compositional changes along spatial gradients of biological function enrichments. The MONTAGE signature matrix can also be used to deconvolve bulk and spot-based spatial transcriptomic data, and combining with clinical metadata, allows assessing SC clinical relevance. In a head and neck cancer study, MONTAGE reveals SCs enriched with malignant cells and granulocytes shifting to SCs enriched with macrophages and fibroblasts along gradient of epithelial-mesenchymal transition, and clinical prognostic significance of the SCs.

systems biology↗

bioRxiv2023

Integrating Multiplexed Imaging and Multiscale Modeling Identifies Tumor Phenotype Transformation as a Critical Component of Therapeutic T Cell Efficacy

Cancer progression is a complex process involving interactions that unfold across molecular, cellular, and tissue scales. These multiscale interactions have been difficult to measure and to simulate. Here we integrated CODEX multiplexed tissue imaging with multiscale modeling software, to model key action points that influence the outcome of T cell therapies with cancer. The initial phenotype of therapeutic T cells influences the ability of T cells to convert tumor cells to an inflammatory, anti-proliferative phenotype. This T cell phenotype could be preserved by structural reprogramming to facilitate continual tumor phenotype conversion and killing. One takeaway is that controlling the rate of cancer phenotype conversion is critical for control of tumor growth. The results suggest new design criteria and patient selection metrics for T cell therapies, call for a rethinking of T cell therapeutic implementation, and provide a foundation for synergistically integrating multiplexed imaging data with multiscale modeling of the cancer-immune interface.

systems biology↗

bioRxiv2022

Epigenetic silencing by SMYD3 represses tumor intrinsic interferon response in HPV-negative squamous cell carcinoma of the head and neck.

Cancers often display immune escape, but the mechanisms and potential for reversibility are incompletely understood. Epigenetic dysregulation has been implicated in the immune escape of various cancer types. We have identified the epigenetic modifier SET and MYND-domain containing protein 3 (SMYD3) as a mediator of immune escape in human papilloma virus (HPV)- negative head and neck squamous cell carcinoma (HNSCC), an aggressive disease with poor prognosis and low response to immunotherapy with pembrolizumab, a programmed-death-1 (PD-1) targeting antibody. SMYD3 loss increased the sensitivity of HNSCC cancer cells to IFN-{beta}, resulting in upregulation of type I IFN response and antigen presentation machinery genes. We found that SMYD3 regulates the transcription of Ubiquitin-Like PHD And RING Finger Domain- Containing Protein 1 (UHRF1), a key epigenetic reader of trimethylated lysine 9 on histone H3 (H3K9me3), which binds to H3K9me3-enriched promoters of key immune-related genes and silences their expression. SMYD3 further maintains the repression of immune-related genes through the deposition of H4K20me3 within the gene body regions of these genes. In an anti-PD-1 immune checkpoint resistant syngeneic mouse model of HPV-negative HNSCC, Smyd3 depletion induced influx of CD8+ T-cells, upregulated PD-L1 and MHC class I molecules, and increased sensitivity to anti-PD-1 therapy. SMYD3 overexpression was associated with decreased CD8 T-cell infiltration in tumor samples from patients with HPV-negative HNSCC, and was associated with poor response to pembrolizumab. Overall, these data highlight a previously unreported function of SMYD3 as a master epigenetic regulator of anti-tumor immune response in HPV-negative HNSCC and provide a rationale for translational approaches combining SMYD3 depletion strategies with checkpoint blockade to overcome anti-PD-1 resistance in this devastating disease.

cancer biology↗

bioRxiv2022

7-UP: generating in silico CODEX from a small set of immunofluorescence markers

Multiplex immunofluorescence (mIF) assays multiple protein biomarkers on a single tissue section. Recently, high-plex CODEX (co-detection by indexing) systems enable simultaneous imaging of 40+ protein biomarkers, unlocking more detailed molecular phenotyping, leading to richer insights into cellular interactions and disease. However, high-plex imaging can be slower and more costly to collect, limiting its applications, especially in clinical settings. We propose a machine learning framework, 7-UP, that can computationally generate in silico 40-plex CODEX at single-cell resolution from a standard 7-plex mIF panel by leveraging cellular morphology. We demonstrate the usefulness of the imputed biomarkers in accurately classifying cell types and predicting patient survival outcomes. Furthermore, 7-UPs imputations generalize well across samples from different clinical sites and cancer types. 7-UP opens the possibility of in silico CODEX, making insights from high-plex mIF more widely available.

bioinformatics↗

bioRxiv2022

Identification of cell types in multiplexed in situ images by combining protein expression and spatial information using CELESTA reveals novel spatial biology

Advances in multiplexed in situ imaging are revealing important insights in spatial biology. However, cell type identification remains a major challenge in imaging analysis, with most existing methods involving substantial manual assessment and subjective decisions for thousands of cells. We propose a novel machine learning algorithm, CELESTA, which uses both cells protein expression and spatial information to identify cell type of individual cells. We demonstrate the performance of CELESTA on multiplexed immunofluorescence in situ images of colorectal cancer and head and neck cancer. Using the cell types identified by CELESTA, we identify tissue architecture associated with lymph node metastasis in HNSCC, which we validate in an independent cohort. By coupling our in situ spatial analysis with single-cell RNA-sequencing data on proximal sections of the same tissue specimens, we identify and validate cell-cell crosstalk associated with lymph node metastasis, demonstrating the power of spatial biology to reveal clinically-relevant cellular interactions.

bioinformatics↗

bioRxiv2020

High-resolution positron emission microscopy of patient-derived tumor organoids

Organoid tumor models have found application in a growing array of cancer studies due to their ability to closely recapitulate the structural and functional characteristics of solid tumors. However, organoids are too small to be compatible with common radiological tools used in oncology clinics. Here, we present a microscopy method to image 18F-fluorodeoxyglucose in patient-derived tumor organoids with spatial resolution up to 100-fold better than that of clinical positron emission tomography (PET). When combined with brightfield imaging, this metabolic imaging approach functionally mirrors clinical PET/CT scans and provides a quantitative readout of cell glycolysis. In particular, the specific avidity of a tumor for FDG, or lack thereof, was maintained when the tumor cells were grown ex vivo as tumor organoids. In addition, cisplatin treatment caused a dose-dependent decrease in the metabolic activity of these organoids, with the exception of one patient whose tumor was also resistant to cisplatin treatment. Thus, FDG-imaging of organoids could be used to predict the response of individual patients to different treatments and provide a more personalized approach to cancer care.

cancer biology↗

bioRxiv2017

NSD1 inactivation defines an immune cold, DNA hypomethylated subtype in squamous cell carcinoma

Chromatin modifying enzymes are frequently mutated in cancer, resulting in a cascade of epigenetic deregulation. Recent reports indicate that inactivating mutations in the histone methyltransferase NSD1 define an intrinsic subtype of head and neck squamous cell carcinoma (HNSC) that features widespread DNA hypomethylation. Here, we describe a similar DNA hypomethylated subtype of lung squamous cell carcinoma (LUSC) that is enriched for both inactivating mutations and deletions in NSD1. The NSD1 subtype of HNSC and LUSC are highly correlated at the DNA methylation and gene expression levels, with concordant DNA hypomethylation and overexpression of a strongly overlapping set of genes, a subset of which are also hypomethylated in Sotos syndrome, a congenital growth disorder caused by germline NSD1 mutations. Further, the NSD1 subtype of HNSC displays an immune cold phenotype characterized by low infiltration of tumor-associated leukocytes, particularly macrophages and CD8+ T cells, as well as low expression of genes encoding the immunotherapy target PD-1 immune checkpoint receptor and its ligands PD-L1 and PD-L2. Using an in vivo model, we demonstrate that NSD1 inactivation results in a reduction in the degree of T cell infiltration into the tumor microenvironment, implicating NSD1 as a tumor cell-intrinsic driver of an immune cold phenotype. These data have important implications for immunotherapy and reveal a general role of NSD1 in maintaining epigenetic repression.

cancer biology↗