Evidence map›Paper›PMID 39463992›Full record

ArticlebioRxiv : the preprint server for biology2024

Rigor and Reproducibility of Digital Spatial Profiling on Clinically Sourced Human Tissues.

Kelly D Smith, James W MacDonald, Xianwu Li, Emily Beirne, Galen Stewart, Theo K Bammler, Shreeram Akilesh

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

7 authors.

Kelly D SmithDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195.
James W MacDonaldDepartment of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98105.
Xianwu LiDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195.
Emily BeirneDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195.
Galen StewartDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195.
Theo K BammlerDepartment of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98105.
Shreeram AkileshDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195.ORCID 0000-0003-3152-7991

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Eric Collisson · 1985 to 2026
$296.4M
XENOBIOTIC BIOTRANSFORMATION AND DISPOSITIONP30ES007033 · NIEHS · UNIVERSITY OF WASHINGTON · PI Nicole Ann Errett · 1995 to 2026
$42.5M
Mechanisms of Kidney Injury in COVID-19R01DK130386 · NIDDK · UNIVERSITY OF WASHINGTON · PI AKILESH, SHREERAM, FREEDMAN, BENJAMIN SOLOMON · 2021 to 2023
$1.2M
NCI NIH HHS P30 CA015704NIDDK NIH HHS R01 DK130386NIEHS NIH HHS P30 ES007033
6 · The paper itself

Abstract

Spatial transcriptomic profiling enables precise quantification of gene expression with simultaneous localization of expression profiles onto tissue structures. This new technology promises to improve our understanding of the disease mechanisms. Therefore, there is intense interest in applying these methods in clinical trials or as laboratory developed tests to aid in diagnosis of disease. Before these technologies can be more broadly deployed in clinical research and diagnostics, it is necessary to thoroughly understand their performance in real world conditions. In this study, we vet technical reproducibility, data normalization methods and assay sensitivity focusing predominantly on one widely used spatial transcriptomic methodology, digital spatial profiling. Using clinically sourced human tissue specimens, we find that digital spatial profiling exhibits high rigor and reproducibility. Our approach lays the foundation for incorporation of digital spatial profiling methods into clinical workflows.

Indexed as

CosMx SMIdigital spatial profilingGeoMx DSPhuman biopsy tissuerigor and reproducibilitysingle molecular imagingSpatial transcriptomics

Identifiers

PMID39463992
PMCPMC11507912

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.