Evidence map›Paper›PMID 33946992›Full record

ArticleJournal of personalized medicine2021

High-Throughput Detection of Multiple miRNAs and Methylated DNA by Droplet Digital PCR.

Ning Li, Pushpa Dhilipkannah, Feng Jiang

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 47% of its field
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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
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  4. Review
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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 at 1 institution in 1 country.

Ning LiDepartment of Pathology, University of Maryland School of Medicine, 10 S. Pine St., Baltimore, MD 21201, USA.
Pushpa DhilipkannahDepartment of Pathology, University of Maryland School of Medicine, 10 S. Pine St., Baltimore, MD 21201, USA.
Feng JiangDepartment of Pathology, University of Maryland School of Medicine, 10 S. Pine St., Baltimore, MD 21201, USA.ORCID 0000-0001-8510-3049
University of Maryland, Baltimore · US

Funding

A diagnostic model for malignant pulmonary nodulesR21CA240556 · NCI · UNIVERSITY OF MARYLAND BALTIMORE · PI JIANG, FENG · 2019 to 2020
$370k
Plasma biomarkers for lung cancer diagnosisUH2CA251139 · NCI · UNIVERSITY OF MARYLAND BALTIMORE · PI JIANG, FENG · 2020 to 2021
$370k
Early detection of lung cancer in VeteransI01CX000512 · VA · BALTIMORE VA MEDICAL CENTER · PI JIANG, FENG · 2012 to 2020
–
CSRD VA I01 CX000512NCI NIH HHS 1UH2CA251139-01NCI NIH HHS R21 CA240556NCI NIH HHS UH2 CA251139
6 · The paper itself

Abstract

Altered miRNA expression and DNA methylation have highly active and diverse roles in carcinogenesis. Simultaneous detection of the molecular aberrations may have a synergistic effect on the diagnosis of malignancies. Herein, we develop a high-throughput assay for detecting multiple miRNAs and DNA methylation using droplet digital PCR (ddPCR) coupled with a 96-microwell plate. The microplate-based ddPCR could absolutely and reproducibly quantify 15 miRNAs and 14 DNA methylation sites with a high sensitivity (one copy/µL and 0.1%, respectively). Analyzing sputum and plasma of 40 lung cancer patients and 36 cancer-free smokers by this approach identified an integrated biomarker panel consisting of two sputum miRNAs (miRs-31-5p and 210-3p), one sputum DNA methylation (RASSF1A), and two plasma miRNAs (miR-21-5p and 126) for the diagnosis of lung cancer with higher sensitivity and specificity compared with a single type of biomarker. The diagnostic value of the integrated biomarker panel for the early detection of lung cancer was confirmed in a different cohort of 36 lung cancer patients and 39 cancer-free smokers. The high-throughput assay for quantification of multiple molecular aberrations across sputum and plasma could improve the early detection of lung cancer.

Indexed as

lung cancermethylationmiRNAplasmasputum

Identifiers

PMID33946992
PMCPMC8146424
OpenAlexW3158500942

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.