Mengxiao He

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 uses single-cell RNA-sequencing and spatial transcriptomics to analyze epithelial and fibroblast states in hormone therapy-naive prostate cancer, identifying novel phenotypes and molecular perturbations.

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 uses spatial transcriptomics and snRNA-seq to analyze host-pathogen interactions in P. berghei-infected mouse liver tissues, revealing changes in lipid metabolism and inflammatory responses.

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 uses spatial transcriptomic data to show that bulk genomic signature scoring in prostate cancer biopsies is confounded by tumour heterogeneity, leading to inaccurate risk assessments.

The paper uses spatial transcriptomics to analyze copy number variations in benign and malignant tissues, revealing clonal patterns and suggesting early cancer evolution mechanisms.