Evidence map›Paper›PMID 40372570›Full record

ArticleDiscover oncology2025

Exploring non-coding RNA expression profiles of AKR1B10P1, RP11-465B22.3, WASH8P, and NPM1P25 as a predictive model for hepatocellular carcinoma patient survival.

Khatereh Firouzi-Farsani, Mina Dehghani-Samani, Razieh Gerami, Reihaneh Sadat Moosavi, Marzieh Gerami, Mohammad Mahdevar

Abstract read
In one paragraph

Article in Discover oncology, 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

6 authors.

Khatereh Firouzi-Farsani *Department of Genetics, Faculty of Basic Sciences, Shahrekord University, Shahrekord, Iran.
Mina Dehghani-Samani *Department of Bioinformatics, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
Razieh GeramiIndependent Researcher, Graduated of PhD Pharmacology from Department of Basic Sciences, School of Veterinary Medicine, Shiraz University, Shiraz, Iran.
Reihaneh Sadat MoosaviDepartment of Genetics, Faculty of Basic Sciences, Shahrekord University, Shahrekord, Iran.
Marzieh GeramiDepartment of Computer Engineering, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran. m.gerami@iaushk.ac.ir.
Mohammad MahdevarDepartment of Genetics and Molecular Biology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The primary aim of the study was to analyze novel long non-coding RNAs (lncRNAs) in hepatocellular carcinoma (HCC) to assess their roles as potential oncogenes and tumor suppressors and to develop a survival prediction model based on their expression levels. Data from The Cancer Genome Atlas, GSE135631, and GSE214846, were utilized to evaluate changes in lncRNA expression in HCC and their associations with patient prognosis. A risk model was created based on lncRNA expression to predict patient mortality. The co-expression network was employed to identify associated pathways, and the results were subsequently validated using the RT-qPCR method. The findings indicated that 14 lncRNAs were down-regulated in HCC, and their increased expression was associated with a favorable prognosis. Additionally, eight lncRNAs were overexpressed and correlated with poorer patient outcomes. The multivariate Cox regression analysis demonstrated that overexpression of AKR1B10P1, RP11-465B22.3, WASH8P, and the downregulation of NPM1P25 could independently predict patient survival, irrespective of clinical variables. The risk score model based on these lncRNAs effectively stratified patients by their mortality risk. Furthermore, the co-expression network analysis revealed that the identified lncRNAs might be involved in various pathways, including fatty acid metabolism, mTOR signaling, glycolysis, angiogenesis, Wnt-β-catenin pathway, and DNA repair. RT-qPCR results validated the significant increase in the expression level of WASH8P in cancer specimens compared to normal tissues. Our results unveiled that changes in the expression levels of AKR1B10P1, RP11-465B22.3, WASH8P, and NPM1P25 were significantly and independently associated with prognosis. Moreover, the patient mortality risk model constructed using these four lncRNAs exhibited a robust capacity to accurately predict patients' survival rates.

Indexed as

Gene expressionLiver cancerNon-coding RNAsPrognosisRT-qPCR

Identifiers

PMID40372570
PMCPMC12081793

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.