Potential Candidate Gene and Underlying Molecular Mechanism Involving in Tumorigenesis of Endometriosis-Associated Ovarian Cancer (EAOC) in Asian Populations

Rut Christine Inggriani, Che‐Chang Chang, Wei-Chung Vivian Yang, Wei‐Chung Vivian Yang
In: IECC 2023 · 2023 · pp. 7 · doi:10.3390/iecc2023-14214 · W4382491956
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⚙ AI-generated summary by claude@2026-06, 2026-06-07 ⓘ

This study identified MYH11, KRT5, and PDGFRA as candidate genes potentially involved in endometriosis-associated ovarian cancer tumorigenesis, particularly related to actin cytoskeleton function.

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Abstract

Molecular aberrations in endometriosis were known to be associated with an increased risk of epithelial ovarian cancer (EOCs), especially endometrioid ovarian cancer (EnOC) and ovarian clear cell carcinoma (OCCC). Causal genetic evidence currently remains elusive. An integrated study of related prognostic markers will help to identify the tumorigenesis pathways in endometriosis-associated ovarian cancer (EAOC). The objective of this study was to gain a better understanding of the tumorigenesis mechanisms that occur in the endometriosis-associated genetic variation-progressed ovarian cancer risk. We found 104 overlapping genes from the KEGG and GO results using WGCNA analysis. To determine whether the same genes were found in one or two types of the histotypes in the EAOC, we overlapped data from the WES and WGCNA results and found three genes, MYH11 (found in all histotypes), KRT5 (found in endometriosis and OCCC), and PDGFRA (found in endometriosis and EnOC). Interestingly, the MYH11 and PDGFRA are involved in the role of the actin cytoskeleton. Several proteins influence the migratory and metastatic phenotype of tumor cells, directly or indirectly, as well as myosin protein and the protein platelet-derived growth factor, suggesting an explanation for the tumorigenesis progression from endometriosis to ovarian cancer. This analysis has provided the fortification of variants for further investigation in this research. With the limitation of the computational study, it can still prove to be an asset for the identification and treatment of endometriosis-associated ovarian cancer diseases associated with the target gene.

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endometriosis

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