Evidence map›Paper›PMID 42001613›Full record

ArticleEBioMedicine2026

Proteomic profiling and molecular reclassification of high-grade serous ovarian cancer identifies prognostic subtypes and immunotherapy biomarkers.

Mengyan Tu, Sangsang Tang, Qiao Zhang, Tianchen Guo, Yixuan Cen, Xiaomeng Xu, Shenglong Wu, Xin Chen, Weiguo Lu, Chen Ding and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in EBioMedicine, 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

11 authors.

Mengyan TuDepartment of Gynaecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, Zhejiang, China; Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynaecological Diseases, Hangzhou, 310006, Zhejiang, China.
Sangsang TangDepartment of Gynaecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, Zhejiang, China; Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynaecological Diseases, Hangzhou, 310006, Zhejiang, China.
Qiao ZhangState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, 200433, China.
Tianchen GuoDepartment of Gynaecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, Zhejiang, China; Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynaecological Diseases, Hangzhou, 310006, Zhejiang, China.
Yixuan CenDepartment of Gynaecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, Zhejiang, China; Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynaecological Diseases, Hangzhou, 310006, Zhejiang, China.
Xiaomeng XuState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, 200433, China.
Shenglong WuDepartment of Gynaecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, Zhejiang, China; Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynaecological Diseases, Hangzhou, 310006, Zhejiang, China.
Xin ChenDepartment of Gynaecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, Zhejiang, China; Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynaecological Diseases, Hangzhou, 310006, Zhejiang, China.
Weiguo LuDepartment of Gynaecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, Zhejiang, China; Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynaecological Diseases, Hangzhou, 310006, Zhejiang, China; Zhejiang Provincial Clinical Research Centre for Obstetrics and Gynaecology, Hangzhou, 310058, Zhejiang, China. Electronic address: lbwg@zju.edu.cn.
Chen DingState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, 200433, China. Electronic address: chend@fudan.edu.cn.
Junfen XuDepartment of Gynaecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, Zhejiang, China; Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynaecological Diseases, Hangzhou, 310006, Zhejiang, China; Zhejiang Provincial Clinical Research Centre for Obstetrics and Gynaecology, Hangzhou, 310058, Zhejiang, China. Electronic address: xjfzu@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigh-grade serous ovarian cancer (HGSOC) is the most lethal histological subtype of ovarian cancer, exhibiting significant heterogeneity and limited therapeutic options. A comprehensive characterisation of proteomic landscape across disease stages is needed to identify actionable biomarkers and therapeutic targets.

methodsWe performed proteomic profiling of 116 primary HGSOC tumours, followed by integrative bioinformatics analyses incorporating clinical annotation. Key findings were validated using multiplex immunohistochemistry, in vitro and in vivo functional assays, and external datasets.

findingsWe identified FIGO stage IIA as a crucial turning point distinguishing early-from advanced-stage disease, marked by a transition from oxidative stress to cell cycle-driven programmes. Trajectory analysis of tumour progression revealed GOSR2 as a key regulator of stage transition. Mechanistically, GOSR2 interacted with SEC24D to inhibit the secretion of CXCL9 and CXCL12, resulting in reduced CD8+ T cell infiltration. Unsupervised clustering defined three reproducible proteomic subtypes (S-I to S-III), which were validated in TCGA and single-cell transcriptomic datasets and associated with distinct clinical outcomes. The S-III subtype was characterised by ECM-receptor interaction, immune evasion, and poor prognosis. Transcription factors network analysis identified regulators potentially driving these phenotypes. In parallel, three immune-contexture subtypes (IC1-IC3) were delineated, reflecting differential tumour immune microenvironment states with prognostic relevance. Advanced-stage HGSOC was further stratified using ISG15, ITGB2, and RELA expression, idenfifying a subgroup with potential susceptibility to immunotherapy.

interpretationOur findings provide a framework for biomarker-guided stratification and the development of precision therapeutic strategies in HGSOC.

fundingKey R&D Program of Zhejiang, NSFC, and 4+X CRP of WHZJU.

Indexed as

Biomarkers, TumorCystadenocarcinoma, SerousOvarian NeoplasmsProteomicsAnimalsChemokine CXCL12Chemokine CXCL9Computational BiologyFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansImmunotherapyNeoplasm GradingNeoplasm StagingPrognosisBiomarkers, TumorChemokine CXCL12Chemokine CXCL9CXCL9 protein, humanHigh-grade serous ovarian cancerMolecular subtypingPrecision therapyProteomics

Identifiers

PMID42001613
PMCPMC13101710

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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 OpenQuestion graph.