Aim: To develop novel prognostic markers for early detection and prognosis of ovarian cancer (OC). Materials & methods: We utilized bioinformatics analysis to identify and construct a prognostic model consisting of lncRNAs centered around JARID2 and explored the potential ceRNA network in OC. Cell functional experiments were conducted to validate the reliability of the ceRNA network and investigate the functional role of JARID2 in OC. Results: We constructed a nomogram composed of ten lncRNAs and identified the PKD1P6/miR-424-5p/JARID2 axis. Furthermore, our findings indicated that JARID2 promotes the proliferation of SKOV3 cells, suggesting its oncogenic role in OC. Conclusion: JARID2, potentially regulated by the PKD1P6/miR-424-5p/JARID2 axis, represents a potential novel biomarker for OC.
Keywords: JARID2; TCGA; ceRNA; ovarian cancer.
In this study, we aimed to find new markers that can help detect and diagnose ovarian cancer (OC) at an early stage. To achieve this, we used advanced computer analysis to identify a specific gene called JARID2 and its associated lncRNAs. We also explored how these molecules interact with each other in OC cells. Through our experiments, we developed a model called a nomogram that includes ten lncRNAs. We discovered a specific pathway involving the PKD1P6 gene, a molecule called miR-424-5p and the JARID2 gene. This pathway appears to play a role in promoting the growth of OC cells. Based on our findings, JARID2, possibly regulated by the PKD1P6/miR-424-5p/JARID2 pathway, shows promise as a new biomarker for OC. This research may contribute to early detection and prognosis of the disease.