转化为简体中文并保持原句结构：前列腺癌转移性去势抵抗（mCRPC）患者的生存率较低，主要由于对可用治疗，如阿比特龙（Abi）缺乏反应或获得性抗药性。需要更好地了解其潜在分子机制，以确定克服抗药性的有效靶点。鉴于细胞内转录动力学的复杂性，批量转录组数据的差异基因表达分析不能提供足够详细的抗药机制洞察。将网络结构纳入其中可以克服这种限制，提供Abi-resistance在mCRPC中的全局和功能视角。在这里，我们开发了TraRe，一种使用稀疏贝叶斯模型的计算方法，以检查三个不同水平的表型驱动转录机制的差异：转录网络，特定调控元件和单独的转录因子。TraRe被应用于拥有Abi-response临床数据的46名mCRPC患者的转录组数据，并揭示在Abi-responsive患者和Abi-resistant患者中表现出明显差异的被放弃的免疫应答转录模块。这些模块在独立的mCRPC研究中得到复制。此外，重要的重接预测及其相关转录因子在两个前列腺癌细胞系中进行了实验验证，这些细胞系具有不同的阿比抗性特点。其中ELK3，MXD1和MYB在Abi-sensitive和Abi-resistant细胞的细胞存活方面发挥不同的作用。此外，ELK3调节细胞迁移能力，这可能对mCRPC产生直接影响。总的来说，这些发现揭示了驱动阿比特龙反应的潜在转录机制，证明了TraRe是一种基于识别的转录网络紊乱生成新假设的有前途的工具。

Survival rates of patients with metastatic castration-resistant prostate cancer (mCRPC) are low due to lack of response or acquired resistance to available therapies, such as abiraterone (Abi). A better understanding of the underlying molecular mechanisms is needed to identify effective targets to overcome resistance. Given the complexity of the transcriptional dynamics in cells, differential gene expression analysis of bulk transcriptomics data cannot provide sufficient detailed insights into resistance mechanisms. Incorporating network structures could overcome this limitation to provide a global and functional perspective of Abi-resistance in mCRPC. Here, we developed TraRe, a computational method using sparse Bayesian models to examine phenotypically-driven transcriptional mechanistic differences at three distinct levels: transcriptional networks, specific regulons, and individual transcription factors. TraRe was applied to transcriptomic data from 46 mCRPC patients with Abi-response clinical data and uncovered abrogated immune response transcriptional modules that showed strong differential regulation in Abi-responsive compared to Abi-resistant patients. These modules were replicated in an independent mCRPC study. Further, key rewiring predictions and their associated transcription factors were experimentally validated in two prostate cancer cell lines with different Abi resistance features. Among them, ELK3, MXD1, and MYB played a differential role in cell survival in Abi-sensitive and Abi-resistant cells. Moreover, ELK3 regulated cell migration capacity, which could have a direct impact on mCRPC. Collectively, these findings shed light on the underlying transcriptional mechanisms driving abiraterone response, demonstrating that TraRe is a promising tool for generating novel hypotheses based on identified transcriptional network disruptions.