Biology subjects

Mollbrink, A.

Publications and source records attributed to Mollbrink, A..

6 recordsLinked to original sources

bioRxiv2026

Spatial mapping of pediatric brain tumors across diagnoses and relapses

We present a spatial transcriptomic atlas of 19 pediatric brain tumor patients spanning nine major and rare diagnoses, including seven relapses, revealing their spatial cellular and molecular organization. Each tumor section resolves into 2 - 4 recurrent spatial archetypes across 11 biological themes, with some mirroring developmental lineage patterns - for example, oligodendrocyte-lineage programs in pilocytic astrocytomas. Spatially inferred copy-number analysis identifies relapse-associated putative clones. In one rare embryonal tumor, spatial niches in the primary tumor harboring putative clones colocalized with an archetype enriched for nervous system development and glioblast-lineage programs. In one ependymoma and one pilocytic astrocytoma, relapse-associated putative clones preferentially localized to the vasculature, suggesting regrowth during relapse may be seeded by clonal selection of residual tumor cells within specialized microenvironmental niches. This resource provides an open-access spatially resolved map via an interactive viewer to inform research on pediatric brain tumor ecosystems, relapse biology, and therapeutic strategies.

cancer biology↗

bioRxiv2025

The germline-restricted chromosome orchestrates germ cell development in passerine birds

While the definition of germ cell fate has been extensively studied in model organisms, evolutionary innovations and mechanistic novelties may remain hidden in understudied systems. The phenomenon of programmed DNA elimination allows germ cells to acquire germline-restricted genes, offering a novel paradigm of germ cell specificity. In passerine birds, the germline-restricted chromosome (GRC) is eliminated from somatic cells in early embryogenesis, yet the role and consequences of its maintenance in the germ cells remain poorly understood. Here, using the zebra finch Taeniopygia guttata as a model, we combined RNA-seq and Spatial Transcriptomics to construct a high-resolution spatiotemporal expression map to understand the role of the GRC across germ cell development. We found a GRC-linked integrin-BMP signaling in maturing oocytes and tfebGRC upregulation at blastoderm embryos, suggesting the involvement of the GRC in oocyte maturation and germ cell determination. We also identified developmental specialization of GRC-linked gene expression relative to their paralogs on the autosomes and sex chromosomes, revealing a gene repertoire which promotes germline stemness and germline/soma distinction. Together, the passerine GRC constitutes a unique system that manifests germ cell complexity, whilst allowing pinpointing the effects on gene expression that may elucidate vertebrate germ cell fate.

developmental biology↗

bioRxiv2024

AAnet resolves a continuum of spatially-localized cell states to unveil tumor complexity

Identifying functionally important cell states and structure within a heterogeneous tumor remains a significant biological and computational challenge. Moreover, current clustering or trajectory-based computational models are ill-equipped to address the notion that cancer cells reside along a phenotypic continuum. To address this, we present Archetypal Analysis network (AAnet), a neural network that learns key archetypal cell states within a phenotypic continuum of cell states in single-cell data. Applied to single-cell RNA sequencing data from pre-clinical models and a cohort of 34 clinical breast cancers, AAnet identifies archetypes that resolve distinct biological cell states and processes, including cell proliferation, hypoxia, metabolism and immune interactions. Notably, archetypes identified in primary tumors are recapitulated in matched liver, lung and lymph node metastases, demonstrating that a significant component of intratumoral heterogeneity is driven by cell intrinsic properties. Using spatial transcriptomics as orthogonal validation, AAnet-derived archetypes show discrete spatial organization within tumors, supporting their distinct archetypal biology. We further reveal that ligand:receptor cross-talk between cancer and adjacent stromal cells contributes to intra-archetypal biological mimicry. Finally, we use AAnet archetype identifiers to validate GLUT3 as a critical mediator of a hypoxic cell archetype harboring a cancer stem cell population, which we validate in human triple-negative breast cancer specimens. AAnet is a powerful tool to reveal functional cell states within complex samples from multimodal single-cell data.

bioinformatics↗

bioRxiv2021

Spatial Transcriptomics to define transcriptional patterns of zonation and structural components in the liver

Reconstruction of heterogeneity through single-cell transcriptional profiling has greatly advanced our understanding of the spatial liver transcriptome in recent years. However, global transcriptional differences across lobular units remain elusive in physical space. Here, we implement Spatial Transcriptomics to perform transcriptomic analysis across sectioned liver tissue. We confirm that the heterogeneity in this complex tissue is predominantly determined by lobular zonation. By introducing novel computational approaches, we enable transcriptional gradient measurements between tissue structures, including several lobules in a variety of orientations. Further, our data suggests the presence of previously transcriptionally uncharacterized structures within liver tissue, contributing to the overall spatial heterogeneity of the organ. This study demonstrates how comprehensive spatial transcriptomic technologies can be used to delineate extensive spatial gene expression patterns in the liver, indicating its future impact for studies of liver function, development and regeneration as well as its potential in pre-clinical and clinical pathology.

genomics↗

bioRxiv2020

The spatial landscape of gene expression isoforms in tissue sections

In situ capturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and fulllength sequence heterogeneity cannot be characterized at spatial resolution with current transcriptome profiling methods. To that end, we introduce Spatial Isoform Transcriptomics (SiT), an explorative method for characterizing spatial isoform variation and sequence heterogeneity. We show in mouse brain how SIT can be used to profile isoform expression and sequence heterogeneity in different areas of the tissue. SiT reveals regional isoform switching of Plp1 gene between different layers of the olfactory bulb, and use of external single cell data allowed to nominate cell types expressing each isoform. Furthermore, SiT identifies differential isoform usage for several major genes implicated in brain function (Snap25, Bin1, Gnas) that we independently validated by in situ sequencing. SiT also provides for the first time an in-depth A-to-I RNA editing map of the adult mouse brain. Data exploration can be performed through an online resource (https://www.isomics.eu), where isoform expression and RNA editing can be visualized in a spatial context.

genomics↗

bioRxiv2018

Spatiotemporal Dynamics of Molecular Pathology in Amyotrophic Lateral Sclerosis

Paralysis occurring in amyotrophic lateral sclerosis (ALS) results from denervation of skeletal muscle as a consequence of motor neuron degeneration. Interactions between motor neurons and glia contribute to motor neuron loss, but the spatiotemporal ordering of molecular events that drive these processes in intact spinal tissue remains poorly understood. Here, we use spatial transcriptomics to obtain gene expression measurements of mouse spinal cords over the course of disease, as well as of postmortem tissue from ALS patients, to characterize the underlying molecular mechanisms in ALS. We identify novel pathway dynamics, regional differences between microglia and astrocyte populations at early time-points, and discern perturbations in several transcriptional pathways shared between murine models of ALS and human postmortem spinal cords.\n\nOne Sentence SummaryAnalysis of the ALS spinal cord using Spatial Transcriptomics reveals spatiotemporal dynamics of disease driven gene regulation.

neuroscience↗