Evidence map›Paper›PMID 37213476›Full record

ArticleInternational journal of general medicine2023

Identification Invasion-Related Long Non-Coding RNAs in Lung Adenocarcinoma and Analysis of Competitive Endogenous RNA Regulatory Networks.

Yuze Mao, Fangyu Cai, Tengjiao Jiang, Xiaofeng Zhu

Open access · goldAbstract read
In one paragraph

Article in International journal of general medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 28% 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

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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

2 citing papers in PubMed, 2 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Yuze Mao *Department of Cardio-Thoracic Surgery, First Affiliated Hospital of Jiamusi University, Jiamusi, Heilongjiang, 154000, People's Republic of China.ORCID 0009-0005-3455-0646
Fangyu Cai *Department of Thoracic Surgery, Beidahuang Industry Group General Hospital, Harbin, Heilongjiang, 150088, People's Republic of China.
Tengjiao JiangDepartment of Cardio-Thoracic Surgery, First Affiliated Hospital of Jiamusi University, Jiamusi, Heilongjiang, 154000, People's Republic of China.
Xiaofeng ZhuDepartment of Cardio-Thoracic Surgery, First Affiliated Hospital of Jiamusi University, Jiamusi, Heilongjiang, 154000, People's Republic of China.ORCID 0000-0002-1928-7107
First Affiliated Hospital of Jiamusi University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cell invasion plays a vital role in cancer development and progression. Aberrant expression of long non-coding RNAs (lncRNAs) is also critical in carcinogenesis. However, the prognostic value of invasion-related lncRNAs in lung adenocarcinoma (LUAD) remains unknown. Methods: Differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and microRNAs (DEmiRNAs) were between LUAD and control samples. Pearson correlation analyses were performed to screen for invasion-related DElncRNAs (DEIRLs). Univariate and multivariate Cox regression algorithms were applied to identify key genes and construct the risk score model, which was evaluated using receiver operating characteristic (ROC) curves. Gene set enrichment analysis (GSEA) was used to explore the underlying pathways of the risk model. Moreover, an invasion-related competitive endogenous RNA (ceRNA) regulatory network was constructed. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to detect the expression of prognostic lncRNAs in the LUAD and control samples. Results: A total of 45 DElncRNAs were identified as DEIRLs. RP3-525N10.2, LINC00857, EP300-AS1, PDZRN3-AS1, and RP5-1102E8.3 were potential prognostic lncRNAs, the expression of which was verified by RT-qPCR in LUAD samples. Both the risk score model and nomogram used the prognostic lncRNAs. ROC curves showed the risk score model had moderate accuracy and the nomogram had high accuracy in predicting patient prognosis. GSEA results indicated that the risk score model was associated with many biological processes and pathways relevant to cell proliferation. A ceRNA regulatory network was constructed in which PDZRN3-miR-96-5p-CPEB1, EP300-AS1-miR-93-5p-CORO2B, and RP3-525N10.2-miR-130a-5p-GHR may be key invasion-related regulatory pathways in LUAD. Conclusion: Our study identified five novel invasion-related prognostic lncRNAs (RP3-525N10.2, LINC00857, EP300-AS1, PDZRN3-AS1, and RP5-1102E8.3) and established an accurate model for predicting the prognosis of patients with LUAD. These findings enrich our understanding of the relationships between cell invasion, lncRNAs, and LUAD and may provide novel treatment directions.

Indexed as

CeRNAinvasionLncRNAlung adenocarcinomaprognosis

Identifiers

PMID37213476
PMCPMC10198273
OpenAlexW4377220437

What OpenQuestion holds

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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.