Evidence map›Paper›PMID 32607524›Full record

ArticlemedRxiv : the preprint server for health sciences2020

A Streamlined CyTOF Workflow To Facilitate Standardized Multi-Site Immune Profiling of COVID-19 Patients.

Daniel Geanon, Brian Lee, Geoffrey Kelly, Diana Handler, Bhaskar Upadhyaya, John Leech, Manon Herbinet, Diane Del Valle, Sacha Gnjatic, Seunghee Kim-Schulze and 2 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. 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, 12 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 1 institution in 1 country.

Daniel Geanon
Brian Lee
Geoffrey Kelly
Diana Handler
Bhaskar Upadhyaya
John Leech
Manon Herbinet
Diane Del Valle
Sacha Gnjatic
Seunghee Kim-Schulze
Miriam Merad
Icahn School of Medicine at Mount Sinai · US

Funding

High-Dimensional Immune Monitoring of NCI-Supported Immunotherapy TrialsU24CA224319 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Sacha Gnjatic, Seunghee Kim-Schulze · 2017 to 2026
$21.5M
NCI NIH HHS U24 CA224319
6 · The paper itself

Abstract

Mass cytometry (CyTOF) represents one of the most powerful tools in immune phenotyping, allowing high throughput quantification of over 40 single parameters at single-cell resolution. However, wide deployment of CyTOF-based immune phenotyping studies are limited by complex experimental workflows and the need for specialized CyTOF equipment and technical expertise. Furthermore, differences in cell isolation and enrichment protocols, antibody reagent preparation, sample staining and data acquisition protocols can all introduce technical variation that can potentially confound integrative analyses of large data-sets of samples processed across multiple labs. Here, we present a streamlined whole blood CyTOF workflow which addresses many of these sources of experimental variation and facilitates wider adoption of CyTOF immune monitoring across sites with limited technical expertise or sample-processing resources or equipment. Our workflow utilizes commercially available reagents including the Fluidigm MaxPar Direct Immune Profiling Assay (MDIPA), a dry tube 30-marker immunophenotyping panel, and SmartTube Proteomic Stabilizer, which allows for simple and reliable fixation and cryopreservation of whole blood samples. We validate a workflow that allows for streamlined staining of whole blood samples with minimal processing requirements or expertise at the site of sample collection, followed by shipment to a central CyTOF core facility for batched downstream processing and data acquisition. We further demonstrate the application of this workflow to characterize immune responses in a cohort of hospitalized COVID-19 patients, highlighting key disease-associated changes in immune cell frequency and phenotype.

Identifiers

PMID32607524
PMCPMC7325190
OpenAlexW3037348454

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.