Žaneta Andrusivová

SIMPlex generates matched spatial and single-nucleus transcriptomic profiles from the same tissue section to resolve cell states with spatial signatures in mouse and human cancer tissues.

This study characterizes gene expression in human growth plates, identifying novel markers and sub-populations of resting zone chondrocytes with features of quiescent stem cells.

This study uses single-cell and spatial profiling to show that inflammatory signals from macrophages and fibroblasts drive CD8 T cell exhaustion and resistance to immune checkpoint blockade in prostate cancer.

This study shows that disrupting microglial TGF-β signaling causes region-specific demyelination in the spinal cord, with severity varying by age and sex.

This study maps spatial dynamics in early human heart development using single-cell and spatial transcriptomics, identifying cell states and novel features like cardiac fibroblasts and chromaffin cells.

This study maps the spatial organization of the developing human lung using high-parametric protein imaging, revealing cell type composition and temporal changes across five developmental timepoints.

This study creates a comprehensive cell atlas of the first-trimester human brain using single-cell RNA sequencing and spatial transcriptomics, identifying over 600 distinct cell states and their spatial organization.

This paper introduces Expansion Spatial Transcriptomics to improve spatial resolution and capture efficiency in spatial transcriptomics by expanding tissue before transcriptome capture, demonstrated on mouse brain samples.

The paper creates a developmental cell atlas of the human spinal cord using single-cell and spatial transcriptomics, revealing spatiotemporal gene regulation and novel insights into ependymoma cancer stem cells.

The paper introduces RRST, a spatial transcriptomics workflow that improves mRNA recovery from low-quality fresh frozen samples, demonstrating its effectiveness across multiple tissue types.

The paper creates a comprehensive topographic atlas of early human lung development, identifying cell states, trajectories, and interactions to understand cell heterogeneity origins.

The paper introduces a method to align spatial transcriptomics data into a common coordinate framework and demonstrates its application on real and synthetic datasets.

Analysis of the ALS spinal cord using Spatial Transcriptomics reveals spatiotemporal dynamics of disease driven gene regulation.