The role of the LncRNA XIST/miR-15a-5p/MN1 signaling axis in gender disparities in bladder cancer prognosis.

LncRNA XIST/miR-15a-5p/MN1 信号轴在膀胱癌预后性别差异中的作用

阅读:5
作者:Cai Fangzhen, Xu Siwei, Li Yinan, He Qingliu, Su Qingfu, Chen Heyi, Liu Weihui, Chen Jiabi, Wang Qingshui, Assaraf Yehuda G, Lin Yao, Zhuang Wei
BACKGROUND: Bladder cancer (BC) exhibits significant gender disparities in incidence and prognosis, with women experiencing worse prognosis despite lower incidence rates. This study aims to elucidate the molecular mechanisms underlying these gender-specific differences, focusing on the role of the long non-coding RNA XIST. METHODS: Comprehensive bioinformatics analysis was performed using TCGA and GSE13507 cohorts to identify gender-differential gene expression. Functional experiments including cell proliferation, migration, and invasion assays were conducted in bladder cancer cell lines. Molecular interactions were investigated through gene knockdown, overexpression, and luciferase reporter assays. A zebrafish model was employed to validate in vivo findings. RESULTS: Our study revealed that XIST expression is significantly higher in female bladder cancer tissues and strongly associated with poor prognosis in female patients. The XIST/miR-15a-5p/MN1/FZD2 signaling axis was found to play a critical role in promoting bladder cancer progression. Specifically, XIST upregulates MN1 by sponging miR-15a-5p, which in turn enhances FZD2 expression. Functional experiments demonstrated that XIST knockdown significantly inhibited bladder cancer cell proliferation, migration, and invasion, effects which could be reversed by FZD2 overexpression. CONCLUSIONS: The XIST/miR-15a-5p/MN1 signaling axis plays a critical role in the gender disparity observed in bladder cancer prognosis, particularly in women. Targeting this pathway may offer new therapeutic strategies for improving outcomes in female BC patients.

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。