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This is a In Vitro Study study (also classified as: Observational).

August 26, 2025Open Access

ADAMTS2 mediates epithelial‒mesenchymal transition and inflammation in high-grade serous ovarian cancer: a study based on bioinformatic analyses and experiments

YTYunjie TianHebei Medical University JLJikuan LiHebei General Hospital RDRuoyu DongSir Run Run Shaw Hospital

Key Points

ADAMTS2 expression levels are crucial for understanding epithelial-mesenchymal transition and its impact on cancer progression.
Machine learning identified key EMT-related signatures, including ADAMTS2, MMP2, and FN1 in high-grade serous ovarian cancer.
Transcriptomic data from 366 patients was analyzed to investigate the relationship between EMT hallmarks and the tumor microenvironment.
This research could lead to new immunotherapeutic strategies targeting EMT in high-grade serous ovarian cancer patients.

Abstract

The importance of epithelial‒mesenchymal transition (EMT) in tumour invasion and metastasis in high-grade serous ovarian cancer (HGSOC) has been highlighted in numerous studies, but genetic biomarkers for predicting EMT in HGSOC are still lacking. The role of EMT hallmarks and the relationship between EMT and the tumour microenvironment in HGSOC were examined based on transcriptomic data from 366 HGSOC patients in the TCGA dataset via the GSVA algorithm, the ESTIMATE method and Pearson correlation analyses. Furthermore, machine learning was applied to determine key EMT signatures and classify EMT subtypes. Moreover, the role of the key EMT signature ADAMTS2 in the behaviour and EMT process of HGSOC cells was detected via western blot, CCK8, transwell, wound healing and immunofluorescence assays. The expression of EMT hallmarks (EMT score) was significantly associated with the progression, immune microenvironment and prognosis of HGSOC patients. Different machine learning algorithms identified MMP2, ADAMTS2, FN1, THBS2, C3ORF80, FAP and POSTN as key EMT-related signatures in HGSOC. Finally, qPCR, western blotting and IHC staining consistently revealed elevated expression of ADAMTS2 in five ovarian cancer tissues from HGSOC patients and five normal ovarian epithelial tissues from five uterine prolapse patients. Further in vitro experiments revealed that ADAMTS2 knockdown inhibited cell proliferation, migration, and invasion as well as the expression of TNF-α, IL-1β and EMT markers (E-cadherin, N-cadherin, SLUG, and TWIST1), whereas ADAMTS2 overexpression promoted the above cellular behaviours and increased the expression of TNF-α, IL-1β and EMT markers. Our study presents a new classifier to predict EMT and the immune microenvironment in HGSOC and identifies ADAMTS2 as a novel regulator of the EMT process. These findings might promote the development of EMT-related immunotherapeutic strategies for HGSOC patients.

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