Evidence map›Paper›PMID 37373422›Full record

ArticleInternational journal of molecular sciences2023

Utilizing MiSeq Sequencing to Detect Circulating microRNAs in Plasma for Improved Lung Cancer Diagnosis.

Xinyan Geng, Jen-Hui Tsou, Sanford A Stass, Feng Jiang

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2023. 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
1.9field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
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  4. Article
  5. Review
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

4 authors at 1 institution in 1 country.

Xinyan GengDepartment of Pathology, University of Maryland School of Medicine, 10 South Pine Street, MSTF 7th Floor, Baltimore, MD 21201-1192, USA.ORCID 0009-0000-1420-5435
Jen-Hui TsouDepartment of Pathology, University of Maryland School of Medicine, 10 South Pine Street, MSTF 7th Floor, Baltimore, MD 21201-1192, USA.ORCID 0000-0003-3873-1266
Sanford A StassDepartment of Pathology, University of Maryland School of Medicine, 10 South Pine Street, MSTF 7th Floor, Baltimore, MD 21201-1192, USA.
Feng JiangDepartment of Pathology, University of Maryland School of Medicine, 10 South Pine Street, MSTF 7th Floor, Baltimore, MD 21201-1192, USA.ORCID 0000-0001-8510-3049
University of Maryland, Baltimore · US

Funding

Optimizing Ultrasensitive DNA methylation detection for lung cancer and other malignanciesU2CCA271885 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ROBERT H. CHRISTENSON, JAMES G. HERMAN · 2022 to 2026
$4.2M
NCI NIH HHS U2C CA271885
6 · The paper itself

Abstract

Non-small cell lung cancer (NSCLC) is a major contributor to cancer-related deaths, but early detection can reduce mortality. NSCLC comprises mainly adenocarcinoma (AC) and squamous cell carcinoma (SCC). Circulating microRNAs (miRNAs) in plasma have emerged as promising biomarkers for NSCLC. However, existing techniques for analyzing miRNAs have limitations, such as restricted target detection and time-consuming procedures. The MiSeqDx System has been shown to overcome these limitations, making it a promising tool for routine clinical settings. We investigated whether the MiSeqDx could profile cell-free circulating miRNAs in plasma and diagnose NSCLC. We sequenced RNA from the plasma of patients with AC and SCC and from cancer-free smokers using the MiSeqDx to profile and compare miRNA expressions. The MiSeqDx exhibits high speed and accuracy when globally analyzing plasma miRNAs. The entire workflow, encompassing RNA to data analysis, was completed in under three days. We also identified panels of plasma miRNA biomarkers that can diagnose NSCLC with 67% sensitivity and 68% specificity, and detect SCC with 90% sensitivity and 94% specificity, respectively. This study is the first to demonstrate that rapid profiling of plasma miRNAs using the MiSeqDx has the potential to offer a straightforward and effective method for the early detection and classification of NSCLC.

Indexed as

AdenocarcinomaCarcinoma, Non-Small-Cell LungCarcinoma, Squamous CellCirculating MicroRNALung NeoplasmsMicroRNAsBiomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticHumansBiomarkers, TumorCirculating MicroRNAMicroRNAscirculating cell-freediagnosislung cancermiRNAsNGS

Identifiers

PMID37373422
PMCPMC10299334
OpenAlexW4381252382

What OpenQuestion holds

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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.