Evidence map›Paper›PMID 41523581›Full record

ArticleInternational journal of genomics2026

Single-Cell RNA-seq Reveals Deubiquitination Genes as Prognostic Markers in Hepatocellular Carcinoma.

Xuening Lv, Chaozhou Chen, Shuxian Zhang, Feng Liang, Qing Zhang, Irfan Ahmad

Abstract read
In one paragraph

Article in International journal of genomics, 2026. 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. Article
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.

Xuening LvDepartment of Gastroenterology, The First People's Hospital of Lianyungang, Lianyungang, China, lygyy.com.cn.
Chaozhou ChenDepartment of Interventional Radiology, Renji Hospital, School of Medicine, Chongqing University, Chongqing, China, cqu.edu.cn.
Shuxian ZhangDepartment of Gastroenterology, The First People's Hospital of Lianyungang, Lianyungang, China, lygyy.com.cn.ORCID https://orcid.org/0000-0002-4317-441X
Feng LiangDepartment of Gastroenterology, Huai'an Second People's Hospital, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, China, xzmc.edu.cn.ORCID https://orcid.org/0009-0008-7704-3435
Qing ZhangDepartment of Hepatology, Huai'an No. 4 People's Hospital, Huai'an, China.ORCID https://orcid.org/0009-0008-9628-2722
Irfan AhmadDepartment of Gastroenterology, The First People's Hospital of Lianyungang, Lianyungang, China, lygyy.com.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatocellular carcinoma (HCC) carries a dismal prognosis, yet the contribution of deubiquitination-an essential posttranslational regulator-to its progression remains poorly defined. Methods: Single-cell RNA-seq profiles of 13 treatment-naïve HCC tumors were integrated with 374 TCGA and 243 ICGC bulk RNA-seq cohorts. Deubiquitinase (DUB) activity was quantified per cell with AUCell; pathway enrichment was performed with clusterProfiler. A LASSO-Cox machine learning pipeline was used to build a DUB-based risk signature, which was cross-validated internally and externally by time-dependent ROC analysis. Results: Malignant cells exhibited divergent DUB transcription relative to immune compartments (myeloid, B). DUB-high neoplastic subsets displayed heightened inflammatory and IFN- Conclusions: This study highlights the role of deubiquitination in HCC progression and its potential as a prognostic biomarker. The developed model could serve as a valuable tool for patient stratification and personalized treatment strategies, although further experimental validation is needed to confirm these findings.

Indexed as

AIdeubiquitinationHCCmachine learningprognosis

Identifiers

PMID41523581
PMCPMC12779930

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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.