Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jun 19;25(1):131.
doi: 10.1007/s10142-025-01631-z.

WISP2/CCN5 revealed as a potential diagnostic biomarker for endometriosis based on machine learning and single-cell transcriptomic analysis

Sheng Dou  1   2   3   4   5 , Shaohua Ling  3   6 , Weihua Nong  1   2   3   4   5 , Bixiao Wei  3   6   4   5 , Yuehua Huang  2   3   7 , Guangjing Li  7 , Rong Wang  8   9   10   11   12 , Haimei Qin  13   14   15   16   17
Affiliations

WISP2/CCN5 revealed as a potential diagnostic biomarker for endometriosis based on machine learning and single-cell transcriptomic analysis

Sheng Dou et al. Funct Integr Genomics. .

Abstract

Objective: Endometriosis is a prevalent gynecological disease characterized by the ectopic growth of functional endometrial tissue outside the uterine cavity, affecting millions of women worldwide. Currently, the definitive diagnosis relies on invasive laparoscopy (the gold standard), with an average diagnostic delay of 7-10 years from symptom onset. Non-invasive biomarkers from blood or endometrial samples could enable early screening and reduce diagnostic time. Emerging technologies like single-cell sequencing and transcriptomics offer promising approaches for identifying highly specific biomarkers, advancing endometriosis research into the precision medicine era.

Materials and methods: Using three machine learning algorithms, we selected four hub genes, among which WISP2/CCN5 was validated as a potential diagnostic biomarker. We discovered higher-than-normal gene expression of WISP2/CCN5 in the eutopic endometrium, and substantially higher expression in the ectopic endometrium compared with that in the eutopic endometrium.

Results: Finally, through cell communication analysis, we found that elevated WISP2/CCN5 expression in stem cells within ectopic lesions may be mediated by the mitogen-activated protein kinase and Wnt signaling pathways, acting downstream of the fibroblast growth factor pathway.

Conclusions: The transition of endometrial tissue from normal to eutopic, and ultimately to ectopic, was found to coincide with progressively increased expression of WISP2/CCN5, which may serve as a biomarker of endometriosis.

Keywords: WISP2/CCN5; Ectopic; Endometriosis; Eutopic; Manchine learning; Single cell sequence stem cells.

PubMed Disclaimer

Conflict of interest statement

Declarations. Ethical approval and consent to participate: All procedures were approved by the ethics committees of the Affiliated Hospital of Youjiang Medical College for Nationalities and Baise People’s Hospital. All studies were conducted in accordance with the relevant guidelines and regulations of the ethics committees of the two hospitals, and informed consent was obtained from all study subjects and/or their legal guardians.Ethical approval number: 2024042302. Consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Similar articles

See all similar articles

References

    1. Ahn SH, Singh V, Tayade C (2017) Biomarkers in endometriosis: challenges and opportunities. Fertil Steril 107(3):523–532. https://doi.org/10.1016/j.fertnstert.2017.01.009 - DOI - PubMed
    1. Akhmetshina A, Palumbo K, Dees C, Bergmann C, Venalis P, Zerr P, Horn A, Kireva T, Beyer C, Zwerina J, Schneider H, Sadowski A, Riener MO, MacDougald OA, Distler O, Schett G, Distler JH (2012) Activation of canonical Wnt signalling is required for TGF-β-mediated fibrosis. Nat Commun 3(735). https://doi.org/10.1038/ncomms1734
    1. Anastasiu CV, Moga MA, Elena Neculau A, Bălan A, Scârneciu I, Dragomir RM, Dull AM, Chicea LM (2020) Biomarkers for the noninvasive diagnosis of endometriosis: state of the Art and future perspectives. Int J Mol Sci 21(5). https://doi.org/10.3390/ijms21051750
    1. Bae SJ, Jo Y, Cho MK, Jin JS, Kim JY, Shim J, Kim YH, Park JK, Ryu D, Lee HJ, Joo J, Ha KT (2022) Identification and analysis of novel endometriosis biomarkers via integrative bioinformatics. Front Endocrinol 13(942368). https://doi.org/10.3389/fendo.2022.942368
    1. Brewer JR, Mazot P, Soriano P (2016) Genetic insights into the mechanisms of Fgf signaling. Genes Dev 30(7):751–771. https://doi.org/10.1101/gad.277137.115 - DOI - PubMed - PMC

LinkOut - more resources