Evidence map›Paper›PMID 42147786›Full record

ArticleBioinformatics and biology insights2026

Integrated Analysis of lncRNA-miRNA-mRNA ceRNA Network and Identification of Hub lncRNAs in Molecular Subtypes of Gastric Cancer as Potential Prognostic Indicators.

Seyed Navid Goftari, Ahmad Reza Bahrami, Maryam M Matin

Abstract read
In one paragraph

Article in Bioinformatics and biology insights, 2026. 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
–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

0 citing papers in PubMed.

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

3 authors.

Seyed Navid GoftariDepartment of Biology, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran.
Ahmad Reza BahramiDepartment of Biology, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran.
Maryam M MatinDepartment of Biology, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran.ORCID https://orcid.org/0000-0002-7949-7712

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gastric cancer (GC) is the fourth most common cause of death among cancers in the world, and the most prevalent type of GC is adenocarcinoma. The Cancer Genome Atlas (TCGA) project introduced 4 molecular subtypes of GC adenocarcinomas: Epstein-Barr virus (EBV), microsatellite instability (MSI), genomically stable (GS), and chromosomal instability (CIN). However, the function of long noncoding RNAs (lncRNAs) in these subtypes still remains unknown. Here, we aimed to construct a competing endogenous RNA (ceRNA) network to clarify the role of lncRNAs in each GC subtype and predict patients' overall relapse-free survival (RFS) time. Methods: The RNA-seq data of miRNAs, lncRNAs, and mRNAs related to different GC subtypes and their corresponding normal samples from TCGA were analyzed, and a combination of signed and unsigned weighted gene co-expression network analysis (WGCNA) (csuWGCNA) was recruited to determine co-expressing gene modules. Then, lncRNA-miRNA and miRNA-mRNA interactions were predicted, and the ceRNA regulatory network was established, followed by the identification of hub lncRNAs for any GC subtype. Gene set enrichment analyses were applied to protein-coding genes of each module to investigate their functions. Finally, survival analysis was performed for identified hub lncRNAs. Results: Differentially expressed lncRNAs, miRNAs, and mRNAs related to each GC subtype were identified, ceRNA networks were constructed, and in each subtype, the top 5 lncRNAs with the most MCC scores were chosen as hub lncRNAs. Survival analysis revealed that AC138356.1, LINC01270, and AL118506.1 lncRNAs were associated with the RFS of CIN subtype, LINC02099, AL157871.2, AC068580.3, and AC004264.1 lncRNAs with EBV subtype, AL117335.1 and AC011416.3 lncRNAs with MSI subtype, and MIR210HG and LINC00565 lncRNAs with GS subtype patients. Conclusion: The identified hub lncRNAs provide insights for understanding molecular mechanisms underlying GC subtype transformation and may be useful to predict the RFS of corresponding patients; more research is required to confirm the results.

Indexed as

ceRNAcsuWGCNAGastric cancer molecular subtypeshub lncRNAprognosis factor

Identifiers

PMID42147786
PMCPMC13176561

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.