Evidence map›Paper›PMID 39775403›Full record

ArticleDiscover oncology2025

Bioinformation study of immune microenvironment characteristics of disulfidptosis-related subtypes in ovarian cancer and prognostic model construction.

Ying Zhou, Yuhong Zhang, Yang Zhou, Yanzheng Gu, Youguo Chen, Juan Wang

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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.

Ying Zhou *Department of Obstetrics and Gynecology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Yuhong Zhang *Department of Obstetrics and Gynecology, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University; Suzhou Municipal Hospital, Suzhou, Jiangsu, China.
Yang Zhou *Department of Obstetrics and Gynecology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Yanzheng GuJiangsu Institute of Clinical Immunology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China. gyz_1982@yeah.net.
Youguo ChenDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China. chenyouguo@suda.edu.cn.
Juan WangDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China. wangjuan@suda.edu.cn.

Funding

Suzhou Minsheng Science and Technology SYS2020094the Project of Jiangsu Health Development Research Center JSHD2022067
6 · The paper itself

Abstract

objectiveOvarian cancer significantly impacts women's reproductive health and remains challenging to diagnose and treat. Despite advancements in understanding DNA repair mechanisms and identifying novel therapeutic targets, additional strategies are still needed. Recently, a novel form of cell death called disulfidptosis, which is triggered by glucose deprivation, has been linked to treatment resistance and changes in the tumor microenvironment (TME). However, its role in ovarian cancer is not well understood.

methodsBioinformatics analysis was performed on RNA-seq data from TCGA and GEO databases to identify disulfidptosis-related genes in ovarian cancer. Differential expression analysis and pathway enrichment were conducted, followed by the development of a prognostic model using LASSO Cox regression, validated with GEO datasets (GSE13876, GSE26712). Clinical samples were analyzed using quantitative polymerase chain reaction (qPCR) and immunohistochemistry (IHC) to validate gene expression.

resultsThis study identified disulfidptosis-related gene subtypes in ovarian cancer and demonstrated their influence on the tumor microenvironment (TME), immunotherapy responses, and patient prognosis. Six genes (IFNB1, IGF2, CD40LG, IL1B, IL21, CD38) associated with disulfidptosis were identified and incorporated into a prognostic model. This model predicted patient outcomes and was validated externally. Clinical validation showed its accuracy in predicting progression-free survival and resistance to platinum-based chemotherapy.

conclusionOur findings highlight the significant impact of disulfidptosis-related genes on the ovarian cancer tumor microenvironment, providing insights that could support the development of clinical evaluations and personalized treatment strategies.

Indexed as

DisulfidptosisOvarian cancerPrognostic modelTumor immune microenvironment

Identifiers

PMID39775403
PMCPMC11711411

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.