Systematic benchmarking of imaging spatial transcriptomics platforms in FFPE tissues
Huan Wang, Ruixu Huang, Jack Nelson, Ce Gao, Miles Tran, Anna Yeaton, Sachi Krishna, Kristen D. Felt, Kathleen L. Pfaff, Teri Bowman, Scott J. Rodig, Kevin Wei, Brittany A. Goods, Samouil L. Farhi
Abstract
Emerging imaging spatial transcriptomics (iST) platforms and coupled analytical methods can recover cell-to-cell interactions, groups of spatially covarying genes, and gene signatures associated with pathological features, and are thus particularly well-suited for applications in formalin fixed paraffin embedded (FFPE) tissues. Here, we benchmark the performance of three commercial iST platforms—10X Xenium, Vizgen MERSCOPE, and Nanostring CosMx—on serial sections from tissue microarrays (TMAs) containing 17 tumor and 16 normal tissue types for both relative technical and biological performance. On matched genes, we find that Xenium consistently generates higher transcript counts per gene without sacrificing specificity. Xenium and CosMx measure RNA transcripts in concordance with orthogonal single-cell transcriptomics. All three platforms can perform spatially resolved cell typing with varying degrees of sub-clustering capabilities, with Xenium and CosMx finding slightly more clusters than MERSCOPE, albeit with different false discovery rates and cell segmentation error frequencies. Taken together, our analyses provide a comprehensive benchmark to guide the choice of iST method as researchers design studies with precious samples in this rapidly evolving field. Wang, Huang, Nelson, Gao, and colleagues perform a head-to-head comparison of multiple platforms for imaging spatial transcriptomics, determining their relative sensitivity, specificity, and ability to identify major cell types in clinical pathology samples.