Genome Biology (Jun 2025)

Comparison of spatial transcriptomics technologies using tumor cryosections

  • Anne Rademacher,
  • Alik Huseynov,
  • Michele Bortolomeazzi,
  • Sina Jasmin Wille,
  • Sabrina Schumacher,
  • Pooja Sant,
  • Denise Keitel,
  • Konstantin Okonechnikov,
  • David R. Ghasemi,
  • Kristian W. Pajtler,
  • Jan-Philipp Mallm,
  • Karsten Rippe

DOI
https://doi.org/10.1186/s13059-025-03624-4
Journal volume & issue
Vol. 26, no. 1
pp. 1 – 32

Abstract

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Abstract Background Spatial 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. Results Our 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. Conclusions This 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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