Evidence map›Paper›PMID 34306018›Full record

ArticleFrontiers in genetics2021

Circulating miRNAs in Serum as Biomarkers for Early Diagnosis of Non-small Cell Lung Cancer.

Xiaotong Duan, Simiao Qiao, Dianhe Li, Shangbiao Li, Zhihao Zheng, Qin Wang, Xiaoxia Zhu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  17. MicroRNAs as Biomarkers for Ionizing Radiation Injury.Frontiers in cell and developmental biology · 2022
    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

7 authors.

Xiaotong DuanDepartment of Radiation Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Simiao QiaoDepartment of Radiation Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Dianhe LiDepartment of Radiation Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Shangbiao LiDepartment of Radiation Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Zhihao ZhengDepartment of Radiation Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Qin WangDepartment of Radiation Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Xiaoxia ZhuDepartment of Radiation Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNon-small cell lung cancer (NSCLC) accounts for about 85% of lung cancers. This study aimed to discover the potential miRNA biomarkers for early detection of NSCLC.

methodsTotal circulating miRNAs were extracted from six patients and six volunteers and run on the miRNA chip. The differentially expressed miRNAs acquired by data mining were intersected with chip results, and qRT-PCR were carried out. Then the differentially miRNAs were validated by using a validation cohort (120 participants). ROC curves were established to evaluate the diagnostic efficacy of the differentially circulating miRNAs. The target genes of the differential miRNAs were identified using the miRTarBase database, and follow-up GO and KEGG enrichment analysis were conducted.

resultsWe identified 577 miRNA which screened according to the criteria (fold change > 2 and

conclusionsThe combination of miR-492, miR-590-3p, and miR-631 can be utilized to distinguish healthy individuals and early-stage NSCLC patients. IMPACT: The combination of miR-492, miR-590-3p, and miR-631 might be a promising serum biomarker in patients for the early diagnosis of NSCLC.

Indexed as

biomarkersearly diagnosishealthy controlsmicroRNAnon-small cell lung cancer

Identifiers

PMID34306018
PMCPMC8299278

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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.