BACKGROUND: Ovarian cancer (OC) remains one of the most lethal gynecological malignancies, characterized by late-stage diagnosis and high recurrence rates. Despite advances in treatment, the overall survival rate for OC patients remains low due to the lack of reliable biomarkers for early detection and prognosis. Thus, there is an urgent need for novel diagnostic and prognostic biomarkers to improve patient outcomes. In this study, we explored the potential role of the KCTD (Potassium Channel Tetramerization Domain-containing) family genes in OC. METHODS: This study utilized comprehensive in silico and in vitro experiments. RESULTS: Firstly, we analyzed the expression patterns of KCTD genes across 12 OC cell lines and 6 normal control cell lines using RT-qPCR, identifying significant upregulation of KCTD5, KCTD9, KCTD12, and KCTD16, while KCTD2, KCTD10, KCTD15, and KCTD21 were downregulated. ROC analysis revealed high diagnostic accuracy for KCTD2, KCTD5, KCTD9, and KCTD12. Further stage-specific analysis indicated that KCTD2, KCTD5, KCTD15, and KCTD21 are associated with OC progression. Functional assays in SKOV3 and A2780 cells demonstrated that overexpression of KCTD2 and KCTD10 significantly inhibited cell proliferation, migration, and colony formation, suggesting their tumor-suppressive roles. Immune and drug sensitivity analyses revealed that KCTD genes may influence immune evasion and chemoresistance in OC. Additionally, miRNA analysis identified potential regulatory mechanisms of KCTD expression. CONCLUSION: Collectively, our findings indicate that KCTD family members serve as promising biomarkers, offering new insights into therapeutic strategies for OC management. Further validation in clinical settings is essential to establish their potential as therapeutic targets.
Mechanistic Insights Into the Tumor-Driving and Diagnostic Roles of KCTD Family Genes in Ovarian Cancer: An Integrated In Silico and In Vitro Analysis.
KCTD家族基因在卵巢癌中的肿瘤驱动和诊断作用的机制性见解:计算机模拟和体外分析的整合
阅读:20
作者:Zhang Ling, Cheng Chong, Tang Bin
| 期刊: | Cancer Medicine | 影响因子: | 3.100 |
| 时间: | 2025 | 起止号: | 2025 Aug;14(16):e71147 |
| doi: | 10.1002/cam4.71147 | 研究方向: | 肿瘤 |
| 疾病类型: | 卵巢癌 | ||
特别声明
1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。
2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。
3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。
4、投稿及合作请联系:info@biocloudy.com。
