Evidence map›Paper›PMID 31744596›Full record

ArticleCellular immunology2020

Multi-gene technical assessment of qPCR and NanoString n-Counter analysis platforms in cynomolgus monkey cardiac allograft recipients.

Emily A S Bergbower, Richard N Pierson, Agnes M Azimzadeh

Abstract readComparative Study
In one paragraph

Article in Cellular immunology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Challenges and opportunities in processing NanoString nCounter data.Computational and structural biotechnology journal · 2024
    Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Emily A S BergbowerDepartment of Anesthesiology, University of Maryland Medical Center, Baltimore, MD, United States; Department of Internal Medicine, Greater Baltimore Medical Center, Baltimore, MD, United States.
Richard N PiersonDepartment of Surgery, University of Maryland Medical Center, Baltimore, MD, United States; Department of Surgery and Center for Transplantation Sciences, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
Agnes M AzimzadehDepartment of Surgery, University of Maryland Medical Center, Baltimore, MD, United States; Department of Surgery and Center for Transplantation Sciences, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States. Electronic address: aazimzadeh@mgh.harvard.edu.

Funding

Immunomodulation for Heart Allograft ToleranceU01AI066719 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI PIERSON, RICHARD N · 2005 to 2016
$8.5M
NIAID NIH HHS U01 AI066719
6 · The paper itself

Abstract

Quantitative gene expression profiling of cardiac allografts characterizes the phenotype of the alloimmune response, yields information regarding differential effects that may be associated with various anti-rejection drug regimens, and generates testable hypotheses regarding the pathogenesis of the chronic rejection lesions typically observed in non-human primate heart transplant models. The goal of this study was to assess interplatform performance and variability between the relatively novel NanoString nCounter Analysis System, ΔΔCT (relative) RT-qPCR, and standard curve (absolute) RT-qPCR utilizing cynomolgus monkey cardiac allografts. Methods for RNA isolation and preamplification were also systematically evaluated and effective methods are proposed. In this study, we demonstrate strong correlation between the two RT-qPCR methods, but variable and, at times, weak correlation between RT-qPCR and NanoString. NanoString fold change results demonstrate less sensitivity to small changes in gene expression than RT-qPCR. These findings appear to be driven by technical aspects of each platform that influence the conditions under which each technique is ideal. Collectively, our data contribute to the general effort to optimally utilize gene expression profiling techniques, not only for transplanted tissues, but for many other applications where accurate rank-order of gene expression versus precise quantification of absolute gene transcript number may be relatively valuable.

Indexed as

AllograftsAnimalsEndocardiumGene ExpressionGene Expression ProfilingGenes, EssentialGraft RejectionHeart TransplantationHeart VentriclesImmunosuppression TherapyMacaca fascicularisNucleic Acid Amplification TechniquesReal-Time Polymerase Chain ReactionRNA, MessengerTransplant RecipientsRNA, Messenger

Identifiers

PMID31744596
PMCPMC7060784

What OpenQuestion holds

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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.