PO.CL01.16 · 临床研究

RHO GTP酶通路特征作为膀胱癌潜在预后生物标志物和治疗靶点

A RHO GTPase pathway signature as a potential prognostic biomarker and therapeutic target in bladder cancer

编号 3941 展板 16 时间 4/20 02:00–05:00 区域 Section 48 主讲 Weiyi Gong, MS

分会场 Prognostic Biomarkers 2

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作者与单位 Authors & Affiliations

Weiyi Gong¹, Chongwen Cao², Peng Wang³, Shang-Jui Wang⁴, Akshay Sood⁵, Lingbin Meng³, Qingqing Wu⁶, Cheryl Lee⁵, Anil Vasdev Parwani⁶, Jenny Li⁶, Xuefeng Liu⁷

¹Comprehensive Cancer Center, Biomedical Sciences Graduate Program, The Ohio State University, Columbus, OH,²Comprehensive Cancer Center, The Ohio State University, Columbus, OH,³Department of Medicine, Wexner Medical Center, The Ohio State University, Columbus, OH,⁴Department of Radiation Oncology, Wexner Medical Center, The Ohio State University, Columbus, OH,⁵Department of Urology, Wexner Medical Center, The Ohio State University, Columbus, OH,⁶Department of Pathology, College of Medicine, The Ohio State University, Columbus, OH,⁷Department of Pathology, Urology and Radiation Oncology, Wexner Medical Center, The Ohio State University, Columbus, OH

摘要 Abstract

中文摘要

背景：RHO GTP酶循环调控包括增殖、分化、衰老和程序性细胞死亡在内的重要细胞过程。然而，该通路的许多预测下游效应因子仍缺乏充分表征，其在膀胱癌（BLCA）中的预后相关性也不甚明确。本研究旨在基于RHO GTP酶循环效应因子基因表达开发BLCA的预后模型，并鉴定功能上参与BLCA进展的关键效应因子。方法：分析了来自癌症基因组图谱（TCGA）和我们James机构队列的RNA-seq数据及临床信息。采用LASSO和Cox回归分析构建与RHO GTP酶循环相关的预后基因特征。基于该特征将患者分层为高风险组和低风险组。开展通路富集分析和治疗反应预测，以比较风险组之间的生物学特征。使用shRNA介导的敲低对候选效应因子基因在BLCA细胞系中进行功能验证，随后进行增殖和集落形成实验。结果：所得基因特征可靠地将患者分层为高风险组和低风险组，Kaplan-Meier曲线显示高风险组生存期显著缩短。这些发现在我们的独立数据集中得到验证。在特征基因中，UACA、CLTC和SNAP23成为关键候选因子。通路富集分析表明高风险患者中存在YAP和EMT信号的激活。生物信息学药物预测分析鉴定出PI-103和PLX-4720可作为高风险组的潜在治疗化合物。功能实验表明，敲低每个特征基因均显著降低BLCA细胞系的增殖和集落形成，并一致诱导衰老样形态。结论：本研究建立了一个基于RHO GTP酶循环效应因子基因的稳健BLCA预后模型，并突出UACA、CLTC和SNAP23作为潜在的预后生物标志物和有前景的治疗靶点。我们的发现为进一步研究RHO GTP酶通路效应因子及其在改善BLCA诊断和治疗中的潜在作用奠定了基础。

查看英文原文 English abstract

Background: The RHO GTPase cycle regulates essential cellular processes, including proliferation, differentiation, senescence, and programmed cell death. However, many predicted downstream effectors of this pathway remain poorly characterized, and their prognostic relevance in bladder cancer (BLCA) is not well understood. This study aimed to develop a prognostic model for BLCA based on RHO GTPase cycle effector gene expression and to identify key effectors functionally involved in BLCA progression. Methods: RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) and our James institutional cohort were analyzed. LASSO and Cox regression analyses were used to construct a prognostic gene signature associated with the RHO GTPase cycle. Patients were stratified into high- and low-risk groups based on this signature. Pathway enrichment analyses and therapy-response predictions were performed to compare biological features between risk groups. Candidate effector genes were functionally validated in BLCA cell lines using shRNA-mediated knockdown, followed by proliferation and colony-formation assays. Results: The resulting gene signature reliably stratified patients into high- and low-risk groups, with Kaplan-Meier curves showing significantly reduced survival in the high-risk group. These findings were validated in our independent dataset. Among the signature genes, UACA, CLTC, and SNAP23 emerged as key candidates. Pathway enrichment indicated activation of YAP and EMT signaling in high-risk patients. Bioinformatic drug-prediction analysis identified PI-103 and PLX-4720 as potential therapeutic compounds for the high-risk group. Functional experiments demonstrated that knockdown of each signature gene significantly reduced proliferation and colony formation in BLCA cell lines and consistently induced a senescence-like morphology. Conclusions: This study establishes a robust prognostic model for BLCA based on RHO GTPase cycle effector genes and highlights UACA, CLTC, and SNAP23 as potential prognostic biomarkers and promising therapeutic targets. Our findings provide a foundation for further investigation into RHO GTPase pathway effectors and their potential role in improving BLCA diagnosis and treatment.

利益披露 Disclosure

W. Gong, None.. C. Cao, None.. P. Wang, None.. S. Wang, None.. A. Sood, None.. L. Meng, None.. Q. Wu, None.. C. Lee, None.. A. V. Parwani, None.. J. Li, None.. X. Liu, None.

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