Evidence map›Paper›PMID 39022675›Full record

ReviewNon-coding RNA research2024

Exosomal LncRNAs and CircRNAs in lung cancer: Emerging regulators and potential therapeutic targets.

Xia Li, Yunbing Wu, Yue Jin

Abstract readReview
In one paragraph

Review in Non-coding RNA research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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.

Xia LiCenter of Molecular Diagnostic, Northern Jiangsu People's Hospital of Jiangsu Province, Yangzhou, 225001, China.
Yunbing WuDepartment of Medicine Laboratory, Northern Jiangsu People's Hospital of Jiangsu Province, Yangzhou, 225001, China.
Yue JinCenter of Molecular Diagnostic, Northern Jiangsu People's Hospital of Jiangsu Province, Yangzhou, 225001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer remains one of the most prevalent and lethal malignancies globally, characterized by high incidence and mortality rates among all cancers. The delayed diagnosis of lung cancer at intermediate to advanced stages frequently leads to suboptimal treatment outcomes. To improve the management of this disease, it is imperative to identify new, highly sensitive prognostic and diagnostic biomarkers. Exosomes, extracellular vesicles with a lipid-bilayer structure and a size range of 30-150 nm, are pivotal in intercellular communication and play significant roles in lung cancer progression. Non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), are highly prevalent within exosomes and play a crucial role in various pathophysiological processes mediated by these extracellular vesicles. Beyond their established functions in miRNA and protein sequestration, these ncRNAs are involved in regulating translation and interactions within exosomes. Numerous studies have highlighted the importance of exosomal lncRNAs and circRNAs in influencing epithelial-mesenchymal transition (EMT), angiogenesis, proliferation, invasion, migration, and metastasis in lung cancer. Due to their unique functional characteristics, these molecules are promising therapeutic targets and biomarkers for diagnosis and prognosis. This review provides a succinct summary of the formation of exosomal lncRNAs and circRNAs, clarifies their biological roles, and thoroughly explains the mechanisms by which they participate in the progression of lung cancer. Finally, we discuss the potential clinical applications and challenges associated with exosomal lncRNAs and circRNAs in lung cancer.

Indexed as

BiomarkersCircRNAsExosomesLncRNAsLung cancer

Identifiers

PMID39022675
PMCPMC11254510

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.