Evidence map›Paper›PMID 41048998›Full record

ArticleJournal of Cancer2025

Pseudouridylation-Related Genes Predict Prognosis and Therapeutic Response in Hepatocellular Carcinoma Patients.

Chenlu Lan, Donghua Gao, Yongguang Wei, Huasheng Huang, Xianwei Lv, Xin Zhou, Wei Qin, Xiwen Liao, Guangzhi Zhu, Tao Peng

Abstract read
In one paragraph

Article in Journal of Cancer, 2025. 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

10 authors.

Chenlu LanDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
Donghua GaoDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
Yongguang WeiDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
Huasheng HuangDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
Xianwei LvDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
Xin ZhouDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
Wei QinDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
Xiwen LiaoDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
Guangzhi ZhuDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
Tao PengDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emerging evidence has demonstrated that pseudouridylation regulates mRNA translation and gene expression, yet its molecular characteristics in hepatocellular carcinoma (HCC) remain unknown. Using public databases, we developed pseudouridylation-related molecular subtype and risk score model to assess HCC patient prognosis and disclose their clinical feature, molecular mechanism and immune landscape. Furthermore, quantitative polymerase chain reaction (qPCR) was performed to verify the expression of RDM1, CDCA3 and FLVCR1. Specifically, functional enrichment analysis revealed pseudouridylation-related genes (PRGs) predominantly regulate transcriptional and translational regulation. Prognostic PRGs stratified HCC into two distinct subtypes, the cluster 1 had a poor prognosis and was characterized by high alpha fetoprotein level, poor differentiation, advanced tumor stage, large tumor size, frequent TP53 mutation, up-regulation of cell cycle- and mitosis-associated genes, which was similar to the aggressive proliferation subtype of HCC. In contrast, the cluster 2 exhibited good prognosis and increased infiltration of immune cells, resembling the non-proliferation subtype of HCC, and suggesting its potential responsiveness to immunotherapy. Survival analysis discovered that the risk score model served as an independent prognostic factor, with high-risk group exhibiting significantly shorter overall survival and recurrence-free survival than low-risk group. Notably, receiver operating characteristic analysis revealed that the risk model had a powerful predictive performance for 1- and 3- year survival (AUC=0.806). In addition, functional enrichment analysis suggested that upregulated genes of high-risk group displayed an enrichment of cell cycle progression, mitotic division, and some oncogenic signaling pathways (PLK1, FOXM1, and p53 signaling pathways). qPCR experiment confirmed the significant overexpression of RDM1, CDCA3, and FLVCR1 in HCC tissues, being consistent with public database analysis. In conclusion, pseudouridylation related-molecular subtype and risk model may effectively predict the prognosis and therapeutic response of HCC.

Indexed as

hepatocellular carcinomamolecular subtypeprognostic risk modelpseudouridinepseudouridylationRNA modification

Identifiers

PMID41048998
PMCPMC12491015

What Socratic holds

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LicenceCC BY
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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 Socratic graph.