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Genome biologyGenomicsPeer-reviewed journal article

Comparison of spatial transcriptomics technologies used for tumor cryosections

Anne RademacheriD, Alik HuseynoviD, Michele BortolomeazziiD, Sina Jasmin WilleiD, Sabrina SchumacheriD, Pooja SantiD, Denise Keitel, Konstantin OkonechnikoviD, David R. GhasemiiD, Kristian W. PajtleriD, Jan‐Philipp MallmiD, Karsten RippeiD

PDFDOIPreprint

Abstract

BackgroundSpatial transcriptomics (ST) 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 evolution of ST methods, each with unique features, presents a challenge in selecting the most appropriate technology for specific research objectives. Here, we compare four imaging-based ST methods - RNAscope HiPlex, Molecular Cartography, MERFISH/Merscope, and Xenium - together with sequencing-based ST (Visium). These technologies were used to study cryosections of medulloblastoma with extensive nodularity (MBEN), a tumor chosen for its distinct microanatomical features. ResultsOur analysis reveals that automated imaging-based ST methods are well suited to delineating the intricate MBEN microanatomy, capturing cell-type-specific transcriptome profiles. We devise approaches to compare the sensitivity and specificity of the different methods together with their unique attributes to guide method selection based on the research aim. Furthermore, we demonstrate how reimaging of slides after the ST analysis can markedly improve cell segmentation accuracy and integrate additional transcript and protein readouts to expand the analytical possibilities and depth of insights. ConclusionsThis study highlights key distinctions between various ST technologies and provides a set of parameters for evaluating their performance. Our findings aid in the informed choice of ST methods and delineate approaches for enhancing the resolution and breadth of spatial transcriptomic analyses, thereby contributing to advancing ST applications in solid tumor research.

Citations
36
FWCI
8.07
Field percentile
top 1%

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