Evidence map›Paper›PMID 29510677›Full record

ArticleBMC genomics2018

Summarizing performance for genome scale measurement of miRNA: reference samples and metrics.

P Scott Pine, Steven P Lund, Jerod R Parsons, Lindsay K Vang, Ashish A Mahabal, Luca Cinquini, Sean C Kelly, Heather Kincaid, Daniel J Crichton, Avrum Spira and 15 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. 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

25 authors.

P Scott PineJoint Initiative for Metrology in Biology, National Institute of Standards and Technology, 443 Via Ortega, Stanford, CA, 94305, USA. p.scott.pine@nist.gov.
Steven P LundStatistical Engineering Division, National Institute of Standards and Technology, Gaithersburg, MD, USA.
Jerod R ParsonsJoint Initiative for Metrology in Biology, National Institute of Standards and Technology, 443 Via Ortega, Stanford, CA, 94305, USA.
Lindsay K VangJoint Initiative for Metrology in Biology, National Institute of Standards and Technology, 443 Via Ortega, Stanford, CA, 94305, USA.
Ashish A MahabalCenter for Data Driven Discovery, California Institute of Technology, Pasadena, CA, USA.
Luca CinquiniJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.
Sean C KellyJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.
Heather KincaidJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.
Daniel J CrichtonJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.
Avrum SpiraSection of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
Gang LiuSection of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
Adam C GowerSection of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
Harvey I PassDepartment of Cardiothoracic Surgery, NYU Langone Medical Center, New York, NY, USA.
Chandra GoparajuDepartment of Cardiothoracic Surgery, NYU Langone Medical Center, New York, NY, USA.
Steven M DubinettDepartment of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Kostyantyn KrysanDepartment of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Sanford A StassDepartment of Pathology, University of Maryland School of Medicine, Baltimore, MD, USA.
Debra KukurugaDepartment of Pathology, University of Maryland School of Medicine, Baltimore, MD, USA.
Kendall Van Keuren-JensenTranslational Genomics Research Institute, Phoenix, AZ, USA.
Amanda Courtright-LimTranslational Genomics Research Institute, Phoenix, AZ, USA.
Karol L ThompsonCenter for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Barry A RosenzweigCenter for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Lynn SorbaraDivision of Cancer Prevention, National Cancer Institute, Rockville, MD, USA.
Sudhir SrivastavaDivision of Cancer Prevention, National Cancer Institute, Rockville, MD, USA.
Marc L SalitJoint Initiative for Metrology in Biology, National Institute of Standards and Technology, 443 Via Ortega, Stanford, CA, 94305, USA.

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Samuel Wheeler French · 1985 to 2026
$134.5M
BIOLOGY OF THE LUNG--MULTIDISCIPLINARY PROGRAMT32HL007035 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Darrell N. Kotton, JOSEPH P MIZGERD · 1985 to 2026
$24.3M
University of Maryland Biomarker Reference LaboratoryU24CA115091 · NCI · UNIVERSITY OF MARYLAND BALTIMORE · PI STASS, SANFORD A · 2005 to 2021
$7.1M
The UCLA - Boston University Lung Cancer Biomarker Development LaboratoryU01CA152751 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUBINETT, STEVEN M., ELASHOFF, DAVID · 2010 to 2015
$5.0M
The EDRN Mesothelioma Biomarker Discovery LaboratoryU01CA214195 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI PASS, HARVEY IRA, YANG, HAINING · 2016 to 2021
$3.5M
The Boston University-UCLA Lung Cancer Biomarker Development LabU01CA214182 · NCI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI ABERLE, DENISE R., DUBINETT, STEVEN M. · 2016 to 2021
$3.1M
Division of Cancer Prevention, National Cancer Institute U01CA214182Division of Cancer Prevention, National Cancer Institute U01CA214195Division of Cancer Prevention, National Cancer Institute U24CA115091NCI NIH HHS P30 CA016042NCI NIH HHS U01 CA152751NCI NIH HHS U01 CA214182NHLBI NIH HHS T32 HL007035
6 · The paper itself

Abstract

backgroundThe potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls.

resultsThree pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes.

conclusionsThe set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process.

Indexed as

Genome, HumanBrainFemaleGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansLiverMicroRNAsPlacentaPregnancyReference StandardsMicroRNAsDashboardmicroRNAmiRNAProcess controlsReference samples

Identifiers

PMID29510677
PMCPMC5838960

What OpenQuestion holds

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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.