Evidence map›Paper›PMID 38106230›Full record

ArticlebioRxiv : the preprint server for biology2023

Systematic benchmarking of imaging spatial transcriptomics platforms in FFPE tissues.

Huan Wang, Ruixu Huang, Jack Nelson, Ce Gao, Miles Tran, Anna Yeaton, Kristen Felt, Kathleen L Pfaff, Teri Bowman, Scott J Rodig and 3 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Huan WangSpatial Technology Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA.ORCID 0000-0001-6773-8382
Ruixu HuangThayer School of Engineering, Molecular and Systems Biology, and Program in Quantitative Biomedical Sciences at Dartmouth College, Hanover, NH 03755, USA.
Jack NelsonSpatial Technology Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA.
Ce GaoDivision of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02215, USA.
Miles TranDivision of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02215, USA.
Anna YeatonPresent affiliation: Immunai, New York, NY 10016, USA.
Kristen FeltImmunoProfile, Brigham & Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Kathleen L PfaffCenter for Immuno-Oncology, Tissue Biomarker Laboratory, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Teri BowmanDepartment of Pathology, Brigham and Women's Hospital, Boston, MA 02215, USA.
Scott J RodigCenter for Immuno-Oncology, Tissue Biomarker Laboratory, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Kevin WeiDivision of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02215, USA.
Brittany A GoodsThayer School of Engineering, Molecular and Systems Biology, and Program in Quantitative Biomedical Sciences at Dartmouth College, Hanover, NH 03755, USA.
Samouil L FarhiSpatial Technology Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA.ORCID 0000-0003-1359-4568

Funding

Zhao - Proj 2P20GM130454 · NIGMS · DARTMOUTH COLLEGE · PI MICHAEL L WHITFIELD · 2019 to 2026
$27.2M
The Cellular Geography of Therapeutic Resistance in CancerU2CCA233195 · NCI · DANA-FARBER CANCER INST · PI VAN ALLEN, ELIEZER M · 2018 to 2023
$13.7M
Pathogenic fibroblast differentiation in rheumatoid arthritisK08AR077037 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI WEI, KEVIN S · 2020 to 2024
$799k
NCI NIH HHS U2C CA233195NIAMS NIH HHS K08 AR077037NIGMS NIH HHS P20 GM130454
6 · The paper itself

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 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.

Identifiers

PMID38106230
PMCPMC10723440

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.