Evidence map›Paper›PMID 42769152›Full record

ArticleFrontiers in endocrinology2026

Ovarian cancer proteomic landscape changes across different pathological stages and biomarker-sets identified with integrative multiomics analysis.

Yan Wang, Zheng Fang, Nuo Xu, Liang Chen, Xianquan Zhan

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2026. 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

5 authors.

Yan WangDepartment of Gynecological Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Zheng FangDepartment of Gynecological Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Nuo XuDepartment of Gynecological Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Liang ChenDepartment of Gynecological Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Xianquan ZhanDepartment of Gynecological Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Ovarian cancer (OV) is a highly lethal gynecological malignant tumor, with a high mortality, low survival rate, and lacking effective biomarkers. The concept of predictive, preventive, and personalized medicine (PPPM) underscores the need for early warning systems and tailored interventions, creating a demand for reliable, stage-specific biomarkers. Methods: A comprehensive proteomic analysis of 60 OV tissues across pathological stages I-IV, and 17 benign ovarian tissues were analyzed with data-independent acquisition (DIA) mass spectrometry. Moreover, these proteomic findings were integrated with TCGA/GTEx data for survival analysis and key molecules, followed by experimental validation with western blot and multiplex immunohistochemistry. Results: Totally, 1,669 differentially abundant proteins (DAPs) were significantly different in each pathological stage (I, II, III, and IV) of OVs compared to controls. DAPs in the early stage (Stage I-II) were mainly enriched in biological processes related to cell proliferation, such as cell cycle process and chromosome segregation, DAPs in advanced stages (Stages III-IV) were mainly enriched in pathways including extracellular matrix (ECM) organization and cell adhesion. Trend cluster analysis of these DAPs identified six types of trend clusters across different stages of OVs (C1-C6). PPI network analysis identified 28 hub proteins with multiple centrality algorithms. Of them, hub protein SMC2 was localized at nuclear and upregulated during early stage (I/II), which was significantly upregulated at its mRNA and protein levels in OV tissues with TCGA/GTEx, western blotting, and multiplex immunofluorescence analyses, and had a significant relationship with reduced overall survival (HR = 1.31, 95% CI: 1.12-1.55, p = 0.0011) with Kaplan-Meier survival analysis. Conclusion: This study provided the large-scale stage-resolved proteomic atlas of OVs, identifies a 28-protein core module governing cell cycle and genome stability, and reveals SMC2 plays crucial roles in OVs.

Indexed as

Biomarkers, TumorOvarian NeoplasmsProteomeProteomicsFemaleHumansMultiomicsNeoplasm StagingBiomarkers, TumorProteomebiomarkerschromosome stabilitydata-independent acquisition (DIA)genomic stabilitymolecular stagingovarian cancerpredictive preventive personalized medicine (PPPM/3PM)proteomic landscape

Identifiers

PMID42769152
PMCPMC13590318

What Socratic holds

Textmetadata
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.