Systematic benchmarking of imaging spatial transcriptomics platforms in FFPE tissues.

Autor:	Wang H; Spatial Technology Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA., Huang R; Thayer School of Engineering, Molecular and Systems Biology, and Program in Quantitative Biomedical Sciences at Dartmouth College, Hanover, NH 03755, USA., Nelson J; Spatial Technology Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA., Gao C; Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02215, USA., Tran M; Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02215, USA., Yeaton A; Present affiliation: Immunai, New York, NY 10016, USA., Felt K; ImmunoProfile, Brigham & Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02215, USA., Pfaff KL; Center for Immuno-Oncology, Tissue Biomarker Laboratory, Dana-Farber Cancer Institute, Boston, MA 02215, USA., Bowman T; Department of Pathology, Brigham and Women's Hospital, Boston, MA 02215, USA., Rodig SJ; Center for Immuno-Oncology, Tissue Biomarker Laboratory, Dana-Farber Cancer Institute, Boston, MA 02215, USA.; Department of Pathology, Brigham and Women's Hospital, Boston, MA 02215, USA., Wei K; Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02215, USA.; Department of Pathology, Brigham and Women's Hospital, Boston, MA 02215, USA., Goods BA; Thayer School of Engineering, Molecular and Systems Biology, and Program in Quantitative Biomedical Sciences at Dartmouth College, Hanover, NH 03755, USA., Farhi SL; Spatial Technology Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA.
Jazyk:	angličtina
Zdroj:	BioRxiv : the preprint server for biology [bioRxiv] 2023 Dec 19. Date of Electronic Publication: 2023 Dec 19.
DOI:	10.1101/2023.12.07.570603
Abstrakt:	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 benchmarked the performance of three commercial iST platforms on serial sections from tissue microarrays (TMAs) containing 23 tumor and normal tissue types for both relative technical and biological performance. On matched genes, we found that 10x Xenium shows higher transcript counts per gene without sacrificing specificity, but that all three platforms concord to orthogonal RNA-seq datasets and can perform spatially resolved cell typing, albeit with different false discovery rates, cell segmentation error frequencies, and with varying degrees of sub-clustering for downstream biological analyses. 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. Competing Interests: Declaration of interests All authors declare that they have no conflicts of interest.
Databáze:	MEDLINE
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