Biology subjects

Barrera Roman, M.

Publications and source records attributed to Barrera Roman, M..

4 recordsLinked to original sources

bioRxiv2025

De novo H3.3K27M-altered Diffuse Midline Glioma in human brainstem organoids to dissect GD2 CAR T cell function

Diffuse midline glioma (DMG) is a rare yet highly aggressive paediatric cancer primarily arising in the pontine region of the brainstem, necessitating the development of scalable patient-representative models for treatment advance1,2. Here, we developed an FGF4-driven human brainstem organoid model, with high representation of pontine glial lineages. By genetically engineering de novo H3.3K27M-altered DMG, we show that this brainstem glial specification is essential for driving DMG tumorigenesis, resulting in tumours that recapitulate the infiltrative nature and molecular heterogeneity of patient samples. By performing prolonged GD2 CAR T cell treatment in this model, we could mirror variable treatment outcomes as observed in the clinic3,4 and demonstrate a high level of CAR T cell transcriptional heterogeneity. From these CAR T cell functional states, we could identify the most potent effector population and validated NCAM1 as a selection marker for their enrichment. In contrast, NCAM1- cells were linked to a cellular stress response, previously associated to immunotherapy resistance5. Furthermore, incorporating the brain-resident myeloid compartment resulted in DMG-specific, largely immunosuppressive microglia subtypes6. These disease-representative microglia reduced GD2 CAR T cell treatment efficacy and we identified the functional profiles most susceptible to this microglia-dependent immune modulation. Thus, we present a scalable human DMG model with critical applications towards understanding CAR T cell functionality to aid therapy development for this detrimental disease.

cancer biology↗

bioRxiv2024

BEHAV3D Tumor Profiler to map heterogeneous cancer cell behavior in the tumor microenvironment

Intravital microscopy (IVM) enables live imaging of animals at single-cell level, offering essential insights into cancer progression. This technique allows for the observation of single-cell behaviors within their natural 3D tissue environments, shedding light on how genetic and microenvironmental changes influence the complex dynamics of tumors. IVM generates highly complex datasets that often exceed the analytical capacity of traditional uni-parametric approaches, which can neglect single-cell heterogeneous in vivo behavior and limit insights into microenvironmental influences on cellular behavior. To overcome these limitations, we present BEHAV3D Tumor Profiler (BEHAV3D-TP), a computational framework that enables unbiased single-cell classification based on a range of morphological, environmental and dynamic single cell features. BEHAV3D-TP integrates with widely used 2D and 3D image processing pipelines, enabling researchers without advanced computational expertise to profile cancer and healthy cell dynamics in IVM data. Here, we apply BEHAV3D-TP to study diffuse midline glioma (DMG), a highly aggressive pediatric brain tumor characterized by invasive progression. By extending BEHAV3D-TP to incorporate tumor microenvironment (TME) data from IVM or fixed correlative imaging, we demonstrate that distinct migratory behaviors of DMG cells are associated with specific TME components, including tumor-associated macrophages and vasculature. BEHAV3D-TP enhances the accessibility of computational tools for analyzing the complex behaviors of cancer cells and their interactions with the TME in IVM data.

cancer biology↗

bioRxiv2024

Functional avidity of anti-B7H3 CAR-T constructs predicts antigen density thresholds for triggering effector function

Chimeric Antigen receptor T cell (CAR-T) treatments for solid cancers have been compromised by limited expansion and survival in the tumor microenvironment following interaction with antigen-expressing target cells. Using B7H3 as a model antigen with broad clinical applicability, we evaluated the relationship between the antibody/antigen affinity of three clinical candidate binders and the three following functional characteristics: functional avidity, prolonged cytotoxicity in tumoroid re-stimulation assays, and in vivo anti-tumoral responses. BEHAV3D video-microscopy assessed distinct CAR-T cell behaviors at single cell resolution. T cell exhaustion did not dictate effector function. Rather, we demonstrated a threshold avidity of CAR-T / tumor cell interaction, characterized by longer cumulative CD8+ CAR-T / tumor target interaction times, and required for adequate CAR-T cell expansion to result in sustained tumor control upon re-challenge. These results provide new insights into design of CAR-T cells for antigen-dim cell targeting, and avoidance of antigen-dim tumor relapse.

bioengineering↗

bioRxiv2021

Behavioral-transcriptomic landscape of engineered T cells targeting human cancer organoids

Cellular immunotherapies are rapidly gaining clinical importance, yet predictive platforms for modeling their mode of action are lacking. Here, we developed a dynamic immuno-organoid 3D imaging-transcriptomics platform; BEHAV3D, to unravel the behavioral and underlying molecular mechanisms of solid tumor targeting. Applied to an emerging cancer metabolome-sensing immunotherapy: TEGs, we first demonstrate targeting of multiple breast cancer subtypes. Live-tracking of over 120,000 TEGs revealed a diverse behavioral landscape and identified a super engager cluster with serial killing capability. Inference of single-cell behavior with transcriptomics identified the gene signature of super engager killer TEGs, which contained 27 genes with no previously described T cell function. Furthermore, guided by a dynamic type 1 interferon (IFN-I) signaling module induced by high TEG-sensitive organoids, we show that IFN-I can prime resistant organoids for TEG-mediated killing. Thus, BEHAV3D characterizes behavioral-phenotypic heterogeneity of cellular immunotherapies and holds promise for improving solid tumor-targeting in a patient-specific manner.

cancer biology↗