ArticleGenome biology2025
Comparison of spatial transcriptomics technologies using tumor cryosections.
Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- RNA-aware tissue preservation workflows for high-quality spatial transcriptomics.bioRxiv : the preprint server for biology · 2026Article
- Standardized metrics for assessment and reproducibility of imaging-based spatial transcriptomics datasets.Nature biotechnology · 2026Article
- Tumor microenvironment-specific nanomedicine: from biology-driven to multi-omics-guided precision engineering.Journal of hematology & oncology · 2026Review
- Spatial Multiomics Reveal Insights Into ADC Efficacy.European journal of immunology · 2026Review
- autoFISH: a modular toolbox for sequential single-molecule RNA FISH experiments.Communications biology · 2026Article
- Translating spatial transcriptomic signatures in adenosquamous carcinoma into bulk prognostic biomarkers in lung adenocarcinoma: a bottom-up approach.NPJ precision oncology · 2026Article
- Spatial AI in cancer: mapping immune evasion topology through multi-modal omics and deep learning.Frontiers in oncology · 2026Review
- Systematic benchmarking of high-throughput subcellular spatial transcriptomics platforms across human tumors.Nature communications · 2025Article
- Harnessing the potential of spatial statistics for spatial omics data with pasta.Nucleic acids research · 2025Article
- Comparison of spatial transcriptomics technologies using tumor cryosections.Genome biology · 2025Article
- An integrated approach for analyzing spatially resolved multi-omics datasets from the same tissue section.Frontiers in molecular biosciences · 2025Article
- scTrends: A living review of commercial single-cell and spatial 'omic technologies.Cell genomics · 2024Review
- Next-generation spatial transcriptomics: unleashing the power to gear up translational oncology.MedComm · 2024Review
- Gene count normalization in single-cell imaging-based spatially resolved transcriptomics.Genome biology · 2024Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
backgroundSpatial transcriptomics technologies are revolutionizing our understanding of intra-tumor heterogeneity and the tumor microenvironment by revealing single-cell molecular profiles within their spatial tissue context. The rapid development of spatial transcriptomics methods, each with unique characteristics, makes it challenging to select the most suitable technology for specific research objectives. Here, we compare four imaging-based approaches-RNAscope HiPlex, Molecular Cartography, Merscope, and Xenium-alongside Visium, a sequencing-based method. These technologies were employed to study cryosections of medulloblastoma with extensive nodularity (MBEN), a tumor chosen for its distinct microanatomical features.
resultsOur analysis reveals that automated imaging-based spatial transcriptomics methods are well-suited to delineate the intricate MBEN microanatomy and capture cell-type-specific transcriptome profiles. We devise approaches to compare the sensitivity and specificity of different methods, along with their unique attributes, to guide method selection based on the research objective. Furthermore, we demonstrate how reimaging slides after the spatial transcriptomics analysis can significantly improve cell segmentation accuracy and integrate additional transcript and protein readouts, expanding the analytical possibilities and depth of insight.
conclusionsThis study underscores important distinctions between spatial transcriptomics technologies and offers a framework for evaluating their performance. Our findings support informed decisions regarding methods and outline strategies to improve the resolution and scope of spatial transcriptomic analyses, ultimately advancing spatial transcriptomics applications in solid tumor research.
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