Biology subjects

Glass, R.

Publications and source records attributed to Glass, R..

4 recordsLinked to original sources

bioRxiv2026

Human cerebral assembloids as a model to study the interaction of glioblastoma with resident glial cells

Glioblastoma (GB) is a highly invasive brain cancer characterized by extensive peritumoral glial reactivity. Although GB infiltration and recurrence remain major therapeutic challenges, the contribution of GB-induced gliosis to tumor progression is poorly understood. To investigate glia-GB interactions, we developed human iPSC-derived cerebral forebrain assembloids containing innate microglia and macroglia and transplanted them with GB cells. The model recapitulates key tumor features observed in patients, including distinct tumor regions, reactive gliosis, and altered tissue stiffness. Single-cell RNA sequencing revealed an unexpected enrichment of extracellular vesicles (EVs) in peritumoral reactive glia, which we validated in patient samples. EV inhibition impaired formation of the peritumoral niche, whereas EVs from GB-containing assembloids induced glial reactivity in GB-free assembloids. Furthermore, the modularity of our system enables incorporation of additional niche components, such as monocytes, allowing investigation of the monocyte-glia-tumor axis and providing a powerful platform to dissect mechanisms regulating the GB microenvironment.

neuroscience↗

bioRxiv2026

The brain-meningeal interface functions as a reservoir and entry site for brain parenchymal macrophages

Microglia are regarded as self-maintaining brain parenchymal macrophages without contribution from adult hematopoiesis. Nevertheless, peripheral macrophage engraftment into the brain has been reported, but the biological variables governing central nervous system (CNS) macrophage niche access remain unclear. We show that CNS macrophage engraftment is determined by the balance between tissue-resident macrophage (TRM) self-renewal and the temporal alignment of niche opening with the availability of engraftment-competent cells and proximity to the vacated niche, rather than prolonged niche vacancy. Fate mapping revealed that monocytes entering the subdural space undergo border-associated macrophage (BAM)-like differentiation, clonal expansion, and transpial migration into the parenchyma, whereas mature BAMs directly repopulate selectively vacated parenchymal niches. We further identify a parenchymal macrophage population with a peripheral BAM-like transcriptional program in aged and neurodegenerative human brains, challenging the dogma of MG-exclusivity. Together, these findings establish a predictive framework for interpreting macrophage maintenance and replacement and for developing macrophage-based therapies.

neuroscience↗

bioRxiv2022

Uncovering Additional Predictors of Urothelial Carcinoma from Voided Urothelial Cell Clusters Through a Deep Learning Based Image Preprocessing Technique

Urine cytology is commonly used as a screening test for high grade urothelial carcinoma for patients with risk factors or hematuria and is an essential step in longitudinal monitoring of patients with a prior bladder cancer history. However, the semi-subjective nature of current reporting systems for urine cytology (e.g., The Paris System) can hamper reproducibility. For instance, the incorporation of urothelial cell clusters into the classification schema is still an item of debate and perplexity amongst expert cytopathologists, as several previous works have disputed their diagnostic relevance. Recently, several machine learning and morphometric algorithms have been proposed to provide quantitative descriptors of urine cytology specimens in an effort to reduce subjectivity and include automated assessments of cell clusters. However, it remains unclear how these computer algorithms interpret/analyze cell clusters. In this work, we have developed an automated preprocessing tool for urothelial cell cluster assessment that divides urothelial cell clusters into meaningful components for downstream assessment (i.e., population-based studies, workflow automation). Results indicate that cell cluster atypia (i.e., defined by whether the cell cluster harbored multiple atypical cells, thresholded by a minimum number of cells), cell border overlap and smoothness, and total number of clusters are important markers of specimen atypia when considering assessment of urothelial cell clusters. Markers established through techniques to separate cell clusters may have wider applicability for the design and implementation of machine learning approaches for urine cytology assessment.

pathology↗

bioRxiv2020

A liquid biopsy platform for detecting gene-gene fusions as glioma diagnostic biomarkers and drug targets

Gliomas account for about 80% of all malignant brain tumours. Diagnosis is achieved by radiographic imaging followed by tumour resection, to determine tumour cell type, grade and molecular characteristics. Glioblastoma multiforme (GBM) is the most common type of glioma, and is uniformly fatal. The median survival of treated GBM patients is 12-15 months. Standard modalities of therapy are unselective and include surgery, radiation therapy and chemotherapy, while precision medicine has yet to demonstrate improvements in disease outcome. We therefore selected GBM as a model to develop a precision medicine methodology for monitoring patients using blood plasma circulating cell-free DNA (cfDNA). Currently, tumour heterogeneity, clonal diversity and mutation acquisition are the major impedances for tailoring personalized therapy in gliomas in general, and particularly in GBM. Thus, a liquid biopsy diagnostics platform based on cfDNA sequencing may improve treatment outcome for GBM patients, by guiding therapy selection. In this study, we processed from 27 patients with glioma, 27 plasma samples for cfDNA isolation and 5 tissue biopsy samples for tumour DNA isolation. From a control group of 14 healthy individuals, 14 plasma samples were processed for cfDNA isolation. In glioma patients, cfDNA concentration was elevated compared to controls. Point mutations found in glioma tissue biopsies were also found in the cfDNA samples (95% identity). Finally, we identified novel chimeric genes (gene-gene fusions) in both tumour and cfDNA samples. These fusions are predicted to alter protein interaction networks, by removing tumour suppressors and adding oncoproteins. Indeed, several of these fusions are potential drug targets, particularly, NTRK or ROS1 fusions, specifically for crizotinib analogues (like entrectinib and larotrectinib) with enhanced penetration of the central nervous system. Taken together, our results demonstrate that novel druggable targets in gliomas can be identified by liquid biopsy using cfDNA in patient plasma. These results open new perspectives and abilities of precision medicine in GBM.

cancer biology↗