Evidence map›Paper›PMID 42251619›Full record

ArticleJournal of cancer research and clinical oncology2026

Prognostic influence of small leucine-rich proteoglycans on serous ovarian cancer.

H Surmann, A Bartha, B Győrffy, L Kiesel, L Hanker, M Götte

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Article in Journal of cancer research and clinical oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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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

6 authors.

H SurmannDepartment of Gynecology and Obstetrics, Münster University Hospital, Albert-Schweitzer-Campus 1, 48149, Münster, Germany.
A BarthaDepartment of Bioinformatics, Semmelweis University, Budapest, Hungary.
B GyőrffyDepartment of Bioinformatics, Semmelweis University, Budapest, Hungary.
L KieselDepartment of Gynecology and Obstetrics, Münster University Hospital, Albert-Schweitzer-Campus 1, 48149, Münster, Germany.
L HankerDepartment of Gynecology and Obstetrics, Münster University Hospital, Albert-Schweitzer-Campus 1, 48149, Münster, Germany.
M GötteDepartment of Gynecology and Obstetrics, Münster University Hospital, Albert-Schweitzer-Campus 1, 48149, Münster, Germany. mgotte@uni-muenster.de.ORCID http://orcid.org/0000-0003-2360-2496

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeOvarian cancer is one of the most lethal cancers in women worldwide. To be able to offer successful treatment and improve the prognosis, knowledge of factors influencing the tumor microenvironment is indispensable. In this context, the influence of the extracellular matrix on tumor progression is increasingly recognized. Of note, preclinical data in cell line and animal models have suggested that several members of the small leucine-rich proteoglycan (SLRP) family are mechanistically involved in the regulation of tumor progression. We hypothesized that dysregulation of SLRP expression may have a prognostic value in ovarian cancer.

methodsTo distinguish whether this expression is altered in the cells themselves or in the extracellular matrix, quantitative Real-Time PCR was performed on ovarian cancer cell lines and complemented by analysis of CCLE datasets. We used Kaplan-Meier survival curves to investigate whether a high or low mRNA expression influences the survival of ovarian cancer patients. Finally, the interactions of the SLRPs were investigated using a STRING analysis.

resultsWe demonstrated the potential beneficial effect of a low mRNA expression of most SLRPs on the prognosis of serous ovarian cancer. STRING analysis revealed interactions with other proteins already known to influence tumor behavior and metastasis of various carcinomas.

conclusionThese findings suggest that SLRPs may be involved in ovarian cancer biology and could represent candidates for further mechanistic investigation. However, their potential relevance for therapeutic strategies, including treatment response, requires additional functional validation.

Indexed as

Cystadenocarcinoma, SerousOvarian NeoplasmsProteoglycansSmall Leucine-Rich ProteoglycansBiomarkers, TumorCell Line, TumorFemaleGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimatePrognosisRNA, MessengerBiomarkers, TumorProteoglycansRNA, MessengerSmall Leucine-Rich ProteoglycansChemotherapyOvarian cancerPrognosisProteoglycans

Identifiers

PMID42251619
PMCPMC13249986

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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.