Evidence map›Paper›PMID 40282264›Full record

ArticleBiology2025

Three Circulating miRNAs Related to Non-Small-Cell Lung Cancer Progression: An Integrative Analysis of Their Biological Roles.

Yanqin Niu, Gaohui Fu, Sijian Xia, Menglong Li, Lin Qiu, Jun Wang, Kang Kang, Deming Gou

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Yanqin NiuShenzhen Key Laboratory of Microbial Genetic Engineering, Vascular Disease Research Center, College of Life Sciences and Oceanography, Guangdong Provincial Key Laboratory of Regional Immunity and Disease, Carson International Cancer Center, School of Medicine, Shenzhen University, Shenzhen 518060, China.
Gaohui FuShenzhen Key Laboratory of Microbial Genetic Engineering, Vascular Disease Research Center, College of Life Sciences and Oceanography, Guangdong Provincial Key Laboratory of Regional Immunity and Disease, Carson International Cancer Center, School of Medicine, Shenzhen University, Shenzhen 518060, China.
Sijian XiaShenzhen Key Laboratory of Microbial Genetic Engineering, Vascular Disease Research Center, College of Life Sciences and Oceanography, Guangdong Provincial Key Laboratory of Regional Immunity and Disease, Carson International Cancer Center, School of Medicine, Shenzhen University, Shenzhen 518060, China.
Menglong LiShenzhen Key Laboratory of Microbial Genetic Engineering, Vascular Disease Research Center, College of Life Sciences and Oceanography, Guangdong Provincial Key Laboratory of Regional Immunity and Disease, Carson International Cancer Center, School of Medicine, Shenzhen University, Shenzhen 518060, China.
Lin QiuShenzhen Key Laboratory of Microbial Genetic Engineering, Vascular Disease Research Center, College of Life Sciences and Oceanography, Guangdong Provincial Key Laboratory of Regional Immunity and Disease, Carson International Cancer Center, School of Medicine, Shenzhen University, Shenzhen 518060, China.
Jun WangShenzhen Key Laboratory of Microbial Genetic Engineering, Vascular Disease Research Center, College of Life Sciences and Oceanography, Guangdong Provincial Key Laboratory of Regional Immunity and Disease, Carson International Cancer Center, School of Medicine, Shenzhen University, Shenzhen 518060, China.
Kang KangDepartment of Biochemistry and Molecular Biology, Shenzhen University Medical School, Shenzhen 518060, China.ORCID 0000-0002-2080-2153
Deming GouShenzhen Key Laboratory of Microbial Genetic Engineering, Vascular Disease Research Center, College of Life Sciences and Oceanography, Guangdong Provincial Key Laboratory of Regional Immunity and Disease, Carson International Cancer Center, School of Medicine, Shenzhen University, Shenzhen 518060, China.ORCID 0000-0002-3312-841X

Funding

National Natural Science Foundation of China 82370065, 82170070, 81970053, and 81600039Shenzhen Municipal Basic Research Program JCYJ20190808123219295 and JCYJ20190808115815137
6 · The paper itself

Abstract

MicroRNAs (miRNAs) are crucial in physiological and pathological processes and serve as biomarkers for various diseases. We previously validated seven miRNA biomarkers and nine in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). In this study, we observed distinct clustering patterns of LUAD or LUSC tissues compared to paired normal tissues based on miRNA expression levels, suggesting the potential involvement of circulating miRNAs in non-small-cell lung cancer (NSCLC) progression. To elucidate their biological function, we identified the most significant differentially expressed miRNAs (DE-miRNAs)-hsa-miR-451a, hsa-miR-139-5p and hsa-miR-126-5p-using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. We then performed protein-protein interaction (PPI) analysis and constructed a miRNA-hub gene regulatory network based on targets predicted by several miRNA-target prediction tools. Additionally, we evaluated the biological functions of these miRNA biomarkers through EdU and wound healing assays in A549 cells. Our study identifies three miRNAs that may contribute to lung cancer progression by modulating cancer-related targets and highlights their potential as biomarkers. Future mechanistic investigations may provide novel insights into NSCLC pathogenesis and open new therapeutic avenues.

Indexed as

bioinformatics analysisbiomarker discoverymicroRNANSCLC (non-small-cell lung cancer)

Identifiers

PMID40282264
PMCPMC12024873

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.