Evidence map›Paper›PMID 37324105›Full record

ArticleJournal of thoracic disease2023

Extracellular RNA profiles in non-small cell lung cancer plasma.

Yaojun Ni, Wenhao Zhang, Guang Mu, Yan Gu, Hongchang Wang, Ke Wei, Yang Xia, Xueying Xie, Qinyu Ge, Tan Tan and 1 more

Open access · diamondAbstract read
In one paragraph

Article in Journal of thoracic disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

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

11 authors at 4 institutions in 1 country.

Yaojun Ni *Department of Thoracic Surgery, Jiangsu Province People's Hospital and the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Wenhao Zhang *Department of Thoracic Surgery, Jiangsu Province People's Hospital and the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Guang Mu *Department of Thoracic Surgery, Jiangsu Province People's Hospital and the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Yan GuDepartment of Thoracic Surgery, Jiangsu Province People's Hospital and the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Hongchang WangDepartment of Thoracic Surgery, Jiangsu Province People's Hospital and the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Ke WeiDepartment of Thoracic Surgery, Jiangsu Province People's Hospital and the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Yang XiaDepartment of Thoracic Surgery, Jiangsu Province People's Hospital and the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Xueying XieState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
Qinyu GeState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
Tan TanDepartment of Thoracic Surgery, Geriatric Hospital of Nanjing Medical University, Nanjing, China.
Jun WangDepartment of Thoracic Surgery, Jiangsu Province People's Hospital and the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Nanjing Medical University · CNJiangsu Province Hospital · CNSoutheast University · CNState Key Laboratory of Digital Medical Engineering

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Non-small cell lung cancer (NSCLC) has a high mortality rate and poor prognosis. The early detection of high-risk patients is essential to improve patient prognosis. Thus, the identification of a non-invasive, non-radiative, convenient, and fast diagnostic approach should be a top priority in NSCLC research. Circulating extracellular RNAs (exRNAs) in the plasma are potential biomarkers for NSCLC. Methods: We used RNA-sequencing (RNA-seq) technology to explore the NSCLC-related RNAs, especially the circular RNAs (circRNAs). The circRNA-targeted micro RNAs (miRNAs) were predicted using 3 circRNA databases [i.e., the Cancer-Specific CircRNA Database (CSCD), circBank, and Circular RNA Interactome]. The circRNA-miRNA-messenger RNA (mRNA) network was constructed using Cytoscape V3.8.0 (Cytoscape Consortium, San Diego, CA, USA). The expression levels of some differentially expressed genes were validated by a quantitative real-time polymerase chain reaction (qRT-PCR) analysis. Results: The results showed that the RNA biotypes of the mitochondrial ribosomal RNAs (mt-rRNAs) and mitochondrial transfer RNAs (mt-tRNAs) were upregulated in the NSCLC plasma. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms of the differentially expressed transcripts of NSCLC included oxidative phosphorylation, proton transmembrane transport, and the response to oxidative stress. Additionally, the qRT-PCR validation indicated that hsa_circ_0000722 had significantly higher expression in the NSCLC plasma than the control plasma, but hsa_circ_0006156 did not differ between the NSCLC plasma and the control plasma. The expression levels of miR-324-5p and miR-326 were higher in the NSCLC plasma than the control plasma. Conclusions: In this study, an exRNA-sequencing strategy was used to identify the expression of NSCLC-specific transcription factors in clinical plasma samples, and hsa_circ_0000722 and hsa-miR-324-5p were identified as potential biomarkers in NSCLC.

Indexed as

expressionhsa_circ_0000722hsa-miR-324-5pNon-small cell lung cancer (NSCLC)

Identifiers

PMID37324105
PMCPMC10267934
OpenAlexW4379932674

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.