Evidence map›Paper›PMID 40990020›Full record

ArticleFrontiers in immunology2025

Prognostic model of ubiquitination-related genes in ovarian cancer based on transcriptomic analysis and experimental validation.

Xiaojing Lin, Shu Zhao, Licheng Li, Yuying Huang, Qiang Zhong, Huali Luo, Qizhu Zhang, Shuxiong Xu, Qinshan Li, Mengxing Li

Abstract read
In one paragraph

Article in Frontiers in immunology, 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

10 authors.

Xiaojing Lin *Department of Obstetrics and Gynecology, Institute of Precision Medicine of Guizhou Province, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Shu Zhao *Department of Obstetrics and Gynecology, Institute of Precision Medicine of Guizhou Province, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Licheng LiDepartment of Hematology, Guizhou Province Institute of Hematology, Guizhou Province Laboratory of Hematopoietic Stem Cell Transplantation Centre, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Yuying HuangDepartment of Clinical Biochemistry, School of Medical Laboratory Science, Guizhou Medical University, Guiyang, Guizhou, China.
Qiang ZhongDepartment of Gynecology, Guizhou Hospital of The First Affiliated Hospital, Sun Yat-sen University, Guiyang, Guizhou, China.
Huali LuoDepartment of Clinical Biochemistry, School of Medical Laboratory Science, Guizhou Medical University, Guiyang, Guizhou, China.
Qizhu ZhangDepartment of Obstetrics and Gynecology, Institute of Precision Medicine of Guizhou Province, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Shuxiong XuDepartment of Urology, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Qinshan LiDepartment of Obstetrics and Gynecology, Institute of Precision Medicine of Guizhou Province, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Mengxing LiDepartment of Hematology, Guizhou Province Institute of Hematology, Guizhou Province Laboratory of Hematopoietic Stem Cell Transplantation Centre, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Ubiquitination plays a crucial role in the malignant progression of ovarian cancer. With the advent of proteolysis-targeting chimeras (PROTACs) targeting ubiquitin enzymes, precision therapies are now possible. Therefore, it is imperative to ascertain the prognostic significance of ubiquitination-related genes in ovarian cancer. Methods: A prognostic model based on ubiquitination-related genes was developed using data from TCGA and GTEx databases. Performance was assessed via Kaplan-Meier, ROC curves, and Cox regression; a nomogram was created. The model's stability was checked using training and test sets. FBXO45 was also experimentally validated in ovarian cancer. Results: The model, based on 17 genes related to ubiquitination, showed high performance (1-year AUC = 0.703, 3-year AUC = 0.704, 5-year AUC = 0.705). The high-risk group had significantly lower overall survival (P < 0.05). Immune analysis showed higher levels of CD8+ T (P < 0.05), M1 (P < 0.01) and follicular (P < 0.05) cells in the low-risk group. High-risk patients had more mutations in MUC17 and LRRK2, while low-risk patients had more RYR2 mutations. FBXO45 is a key E3 ubiquitin ligase in ovarian cancer, promoting growth, spread and migration via the Wnt/β-catenin pathway. Conclusion: Ubiquitination-related markers provide reliable prognostic insights and reflect the immune microenvironment in ovarian cancer, offering a basis for clinical targeting strategies.

Indexed as

Biomarkers, TumorOvarian NeoplasmsTranscriptomeUbiquitinationF-Box ProteinsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMiddle AgedNomogramsPrognosisBiomarkers, TumorF-Box ProteinsFBXO45immunotherapyovarian cancerprognostic modelubiquitinationWnt/β-catenin signaling pathway

Identifiers

PMID40990020
PMCPMC12450667

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.