Biology subjects

Cubela, I.

Publications and source records attributed to Cubela, I..

7 recordsLinked to original sources

bioRxiv2026

Organoid-based colorectal tumor microenvironment model for immuno-oncology research

The development of cancer immunotherapies is hindered by the lack of human-relevant models that accurately translate to patient outcomes. We combine patient-derived colorectal tumor organoids (PDOs) and cancer-associated fibroblasts (CAFs) into floating extracellular matrix drops to form miniature colorectal tumors. These SHaking Organoid CO-cultures (SHOCOs) reproducibly capture key features of the tumor microenvironment (TME), including physiologically relevant ECM, hypoxic regions, and a diversified stromal compartment that captures primary CAF states. Compared with traditional PDO-based co-culture models, SHOCOs maintain immune cells in numbers, states and functional interactions that more closely reflect the physiological tumor microenvironment. The modularity of the system allowed controlled simulation of diverse patient tumor archetypes, and defining how TME components shape therapy response. Immune-rich SHOCOs treated with T-cell bispecific antibodies exhibited robust anti-tumor responses that were stronger and more rapid than their PDO-based counterparts. Stroma-rich tumors, on the other hand, diminished therapy responses by physically hindering both immune cell recruitment and limiting antibody penetration. Thus, SHOCOs enable the construction of modular tumor microenvironments, providing a versatile platform to dissect immune and stromal tumor biology and to catalyze the discovery of novel therapeutic approaches.

cancer biology↗

bioRxiv2025

An integrated platform for high-throughput phenospace learning of 3D multilineage organoid systems

Complex multilineage organoid systems lack quantitative phenotyping methods preserving spatial architecture at high throughput. Current approaches compromise biological complexity, spatial resolution, or robust homogeneous multilineage assembly. We establish an integrated experimental-computational platform for high-throughput spatial phenotyping of multilineage organoids through developing a modular tumoroid culture system incorporating pancreatic ductal adenocarcinoma (PDAC) cells and cancer-associated fibroblasts (CAFs) in 384-well format with multiplexed whole-mount imaging. We developed Phenocoder, a machine learning framework combining conditional variational autoencoders with spatial graph analysis to extract multiscale organoid features. Rigorous validation demonstrates robust performance in PDAC tumoroids. The platform identifies pathway modulators that disrupt the fibrotic microenvironment and discovers stroma-dependent vulnerabilities, undetectable in monocultures. Extending to immuno-competent tumoroids, we assess fibrosis modulators in combination with T cell bispecific antibodies, identifying treatments that enhance immune cell proliferation and infiltration inducing cancer cell death, validated in patient-derived explants. This platform establishes a generalizable framework for multilineage organoid phenotyping.

cancer biology↗

bioRxiv2025

Unified Generation of Regionalized Neural Organoids from Single-Lumen Neuroepithelium

Human brain development begins with the formation of the neural tube, a neuroepithelium organized around a single continuous lumen that is patterned to specify distinct brain regions. Human pluripotent stem cell (hPSC)-derived neural organoids offer powerful models to study this process and its disruption in disease. However, most existing protocols rely on stochastic self-organization of hPSC aggregates, leading to high variability in tissue architecture and cell type composition, which limits reproducibility and fidelity to natural development. This variability has also hindered the broader adoption of brain organoid technology in translational and pharmaceutical research, where robustness and standardization are critical. Here, we present a scalable and reproducible platform that uses uniform, single-lumen neuroepithelium (SLN) as a standardized starting point for generating diverse, regionally specified neural organoids. SLNs form with high efficiency and reproducibility, can be patterned along dorso-ventral and anterior-posterior axes, and mature in suspension culture into organoids representing forebrain, midbrain, hindbrain, and neural retina. This unified and scalable approach provides a reproducible foundation for modeling human brain development, offering broad translational potential for mechanistic studies, disease modeling, and drug discovery.

developmental biology↗

bioRxiv2025

Integrated Microfluidic Platform for High-Throughput Generation of Intestinal Organoids in Hydrogel Droplets

Organoid research offers valuable insights into human biology and disease, but reproducibility and scalability remain significant challenges, particularly for epithelial organoids. Here, we present an integrated microfluidic platform that addresses these limitations by enabling high-throughput generation of uniform hydrogel microparticles embedded with intestinal stem cells. Our platform includes a cell distribution system for homogenous cell encapsulation and a microfluidic oil removal module for efficient particle transfer to aqueous media. We demonstrate the successful culture and differentiation of both healthy and tumor-derived intestinal organoids within these microparticles, achieving high homogeneity and reproducibility. This integrated microfluidic approach holds promise for scalable and standardized organoid production, with potential applications in drug screening, disease modeling, and personalized medicine.

bioengineering↗

bioRxiv2025

Modeling host-microbe interactions in immunocompetent engineered human gut tissues

The intestinal mucosal barrier contains microbial organisms within the lumen while preserving the ability to absorb nutrients. Dietary, microbial, and other exposures shaped human barrier evolution and continue to impact disease susceptibility. Here, we established engineered barrier models of the human small intestine and colon composed of a multilineage epithelium, mucus layer, accessible microbial compartment and autologous tissue-resident immune cells. The epithelium has crypt- and villus-like topological domains, with stem cells differentiating into absorptive and secretory lineages with region-specific identities. Secreted mucins accumulate apically, forming a dense mucus layer separating the epithelium from colonizing commensal and pathogenic bacteria. Intestinal memory T cells integrate into and interact with the epithelium. We use the engineered intestinal tissues to identify an epithelial gene regulatory network underlying response to Salmonella Typhimurium infection, and uncover epithelial-immune-pathogen crosstalk coordinating cytokine release and epithelial damage. Overall, this work allows for the modular integration of epithelial, microbial, and immune compartments providing a versatile system for studying human intestinal physiology and pathologies.

bioengineering↗

bioRxiv2025

High-throughput histopathology for complex in vitro models

Human complex in vitro models (CIVMs) have demonstrated remarkable potential to study tissue development, physiology and disease at high-throughput. To effectively employ these miniaturized systems in translational preclinical research, their in-depth benchmarking is pivotal. Histology has been the core of tissue characterization for centuries and the foundation of spatial phenotyping. However, standard histology workflows are inherently low-throughput and centered on large tissue pieces. This does not match the high sample volumes and small sample sizes in CIVM research. Here, we introduce a holistic histo-workflow, utilizing 3D-printed histomolds that facilitate co-planar embedding of CIVMs at high-throughput, resulting in up to 48 samples in one section. We developed a variety of model-specific histomold designs that enable spatially controlled histological sectioning and downstream analyses. We describe these workflows, including mold generation, highplex staining and image analysis, and exemplify their application to histological analyses of various CIVMs. Altogether, the histomolds introduced here afford opportunities for CIVM processing and analysis, while significantly reducing labor and reagent resources, thereby democratizing high-throughput CIVM in histopathology.

pathology↗

bioRxiv2025

Human Lung Alveolar Model with an Autologous Innate and Adaptive Immune Compartment

Lung-resident immune cells, spanning both innate and adaptive compartments, preserve the integrity of the respiratory barrier, but become pathogenic if dysregulated1. Current in vitro organoid models aim to replicate interactions between the alveolar epithelium and immune cells but have not yet incorporated lung-specific immune cells critical for tissue residency2. Here we address this shortcoming by describing human lung alveolar immuno-organoids (LIO) that contain an autologous tissue-resident lymphoid compartment, primarily composed of tissue-resident memory T cells (TRMs). Additionally, we introduce lung alveolar immuno-organoids with myeloid cells (LIOM), which include both TRMs and a macrophage-rich alveolar myeloid compartment. The resident immune cells formed a stable immune-epithelial system, frequently interacting with the epithelium and promoting a regenerative alveolar transcriptomic profile. To understand how dysregulated inflammation perturbed the respiratory barrier, we simulated T-cell-mediated inflammation in LIOs and LIOMs and used single-cell transcriptomic analyses to uncover the molecular mechanisms driving immune responses. The presence of innate cells induced a shift in T cell identity from cytotoxic to immunosuppressive, reducing epithelial cell killing and inflammation. Based on insights obtained with bulk RNA-seq data from the phase 3 IMpower150 trial, we tested whether LIOM cultures could model clinically-relevant but poorly understood pulmonary side effects caused by immunotherapies such as the checkpoint inhibitor atezolizumab3. We observed a decrease in immunosuppressive T cells and identified gene signatures that matched the transcriptomic profile of patients with drug-induced pneumonitis. Given its effectiveness in capturing outcomes and mechanisms associated with a prevalent pulmonary disease, this system unlocks opportunities for studying a wide range of immune-related pathologies in the lung.

cell biology↗