Evidence map›Paper›PMID 41079114›Full record

ArticleFrontiers in oncology2025

Establishment and validation of a prognostic model based on vasculogenic mimicry-related gene clustering in ovarian cancer.

Xueyuan Zhao, Yan Jia, Weijia Wen, Caixia Shao, Qiaojian Zou, Linna Chen, Hongye Jiang, Guofen Yang, Wei Wang, Chunyu Zhang and 1 more

Abstract read
In one paragraph

Article in Frontiers in 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

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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

11 authors.

Xueyuan Zhao *Department of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Yan Jia *Department of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Weijia Wen *Department of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Caixia ShaoDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Qiaojian ZouDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Linna ChenDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Hongye JiangDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Guofen YangDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Wei WangDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Chunyu ZhangDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Shuzhong YaoDepartment of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As a critical prognostic factor in ovarian cancer which is the most lethal gynecologic malignancy, vasculogenic mimicry (VM) has not been systematically incorporated into prognostic evaluation frameworks in ovarian cancer (OC). This underscores the necessity to develop and validate a gene subtyping-based prognostic model through comprehensive analysis of VM-related biomarkers. Methods: This study integrated multi-omics data from TCGA, GEO and GTEx, forming a primary set and an external validation cohort. Through literature mining, 28 VM-related genes were identified. Univariate Cox and LASSO regression distilled 9 genes as vasculogenic mimicry-related prognostic index (VMRPI), establishing a risk model validated by ROC and constructing a nomogram with clinical prognostic factors. Consensus clustering stratified patients into VM-high/-low subgroups. Multi-angle assessments connected risk scores with tumor mutational burden, immune infiltration, and chemotherapy sensitivity. Clinical validation encompassed IHC-PAS detection of VM structures in 36 HGSOC paraffin specimens and qRT-PCR confirmation of gene expression in matched frozen tissues. Results: vasculogenic mimicry-related genes (VMGs) exhibited differential expressions in HGSOC versus normal tissues, with consensus clustering stratifying 474 patients into prognostically distinct VM-high/low subgroups. Prognosis-associated DEGs (n=758) enriched in ECM-receptor and PI3K-AKT pathways. A 9-gene prognostic model demonstrated robust predictive accuracy. Risk scores correlated with immune infiltration and drug sensitivity. Multivariate-validated nomogram integrating clinical factors and risk scores achieved precise survival prediction. IHC-PAS confirmed VM structures, with VM-positive cases showing upregulated VMGs and VMRPIs. Conclusions: VMG-based stratification revealed distinct prognostic ovarian cancer subgroups and a 9-VMRPI demonstrated robust prognostic power with validated immune-microenvironment, drug-response associations, IHC-PAS staining, and qRT-PCR confirmation.

Indexed as

immune microenvironmentovarian cancer (OC)prognostic modeltherapeutic responsevasculogenic mimicry (VM)

Identifiers

PMID41079114
PMCPMC12507593

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