Evidence map›Paper›PMID 40155942›Full record

ArticleJournal of ovarian research2025

Identification of exosome-related SERPINB1 as a novel predictor for tumor immune microenvironment and clinical outcomes in ovarian cancer.

Rui Gu, Liping Jiang, Shuqin Dai, Yajie Yue, Shangjin Li, Shudan Zheng, Liwei Wu, Shaojie Zhao

Abstract read
In one paragraph

Article in Journal of ovarian research, 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. Review
  2. 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

8 authors.

Rui Gu *Department of Obstetrics and Gynecology, Wuxi School of Medicine, Wuxi Maternity and Child Health Care Hospital, Jiangnan University, Jiangsu, 214002, China.
Liping Jiang *Department of Obstetrics and Gynecology, Wuxi School of Medicine, Wuxi Maternity and Child Health Care Hospital, Jiangnan University, Jiangsu, 214002, China.
Shuqin DaiDepartment of Obstetrics and Gynecology, Wuxi School of Medicine, Wuxi Maternity and Child Health Care Hospital, Jiangnan University, Jiangsu, 214002, China.
Yajie YueDepartment of Obstetrics and Gynecology, Wuxi School of Medicine, Wuxi Maternity and Child Health Care Hospital, Jiangnan University, Jiangsu, 214002, China.
Shangjin LiDepartment of Obstetrics and Gynecology, Wuxi School of Medicine, Wuxi Maternity and Child Health Care Hospital, Jiangnan University, Jiangsu, 214002, China.
Shudan ZhengDepartment of Obstetrics and Gynecology, Wuxi School of Medicine, Wuxi Maternity and Child Health Care Hospital, Jiangnan University, Jiangsu, 214002, China.
Liwei WuDepartment of Obstetrics and Gynecology, Wuxi School of Medicine, Wuxi Maternity and Child Health Care Hospital, Jiangnan University, Jiangsu, 214002, China. fox2062@126.com.
Shaojie ZhaoDepartment of Obstetrics and Gynecology, Wuxi School of Medicine, Wuxi Maternity and Child Health Care Hospital, Jiangnan University, Jiangsu, 214002, China. zsjie2005@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith a high global incidence of over three million new cases in 2020 and a high mortality of over two million fatalities, ovarian cancer is one of the most common malignant tumors in gynecology. Exosomes can control the immunological condition of the tumor microenvironment (TME) by participating in intercellular interactions. Therefore, we aimed to construct an exosome-related prognostic model to predict the clinical outcomes of ovarian cancer patients.

methodsIn this research, expression patterns of exosome-related genes were examined in multiple single-cell RNA-sequencing and bulk RNA-sequencing datasets. In addition, a novel exosome-related prognostic model was established by the least absolute shrinkage and selection operator (LASSO) regression method. Then, the correlations between risk score and immunological characteristics of the TME were explored. Moreover, SERPINB1, a gene in the prognostic signature, was further analyzed to reveal its value as a novel biomarker.

resultsIn the current study, combined with single-cell and bulk omics datasets, we constructed an exosome-related prognostic model of four genes (LGALS3BP, SAT1, SERPINB1, and SH3BGRL3). Moreover, the risk score was associated with worse overall survival (OS) in ovarian cancer patients. Further analysis found that patients with high-risk score tended to shape a desert TME with hardly infiltration of immune cells. Then, SERPINB1, positively correlated with the favorable OS and negatively with the risk score, was chosen as the representative biomarker of the model. Moreover, SERPINB1 was positively correlated with the infiltration of immune subpopulations in both public and in-house cohort. In addition, the high-resolution analysis found that SERPINB1

conclusionTo sum up, we established a novel exosome-related prognostic model (LGALS3BP, SAT1, SERPINB1, and SH3BGRL3) to predict the prognosis of patients with ovarian cancer and identify the immunological characteristics of the TME. In addition, SERPINB1 was identified as a promising biomarker for prognostic prediction in ovarian cancer.

Indexed as

ExosomesOvarian NeoplasmsSerpinsTumor MicroenvironmentBiomarkers, TumorFemaleHumansPrognosisBiomarkers, TumorSERPINB1 protein, humanSerpinsExosomeGene signatureImmune infiltrationOvarian cancerSERPINB1

Identifiers

PMID40155942
PMCPMC11954311

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.