Urology Key Laboratory of Guangdong Province, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Department of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.
Front Endocrinol (Lausanne). 2023 Mar 16;14:1148898. doi: 10.3389/fendo.2023.1148898. eCollection 2023.
Enzalutamide, as a second-generation endocrine therapy drug for prostate cancer (PCa), is prominent representative among the synthetic androgen receptor antagonists. Currently, there is lack of enzalutamide-induced signature (ENZ-sig) for predicting progression and relapse-free survival (RFS) in PCa.
Enzalutamide-induced candidate markers were derived from single-cell RNA sequencing analysis integrating three enzalutamide-stimulated models (0-, 48-, and 168-h enzalutamide stimulation). ENZ-sig was constructed on the basis of candidate genes that were associated with RFS in The Cancer Genome Atlas leveraging least absolute shrinkage and selection operator method. The ENZ-sig was further validated in GSE70768, GSE94767, E-MTAB-6128, DFKZ, GSE21034, and GSE70769 datasets. Biological enrichment analysis was used to discover the underlying mechanism between high ENZ-sig and low ENZ-sig in single-cell RNA sequencing and bulk RNA sequencing.
We identified a heterogenous subgroup that induced by enzalutamide stimulation and found 53 enzalutamide-induced candidate markers that are related to trajectory progression and enzalutamide-stimulated. The candidate genes were further narrowed down into 10 genes that are related to RFS in PCa. A 10-gene prognostic model (ENZ-sig)-IFRD1, COL5A2, TUBA1A, CFAP69, TMEM388, ACPP, MANEA, FOSB, SH3BGRL, and ST7-was constructed for the prediction of RFS in PCa. The effective and robust predictability of ENZ-sig was verified in six independent datasets. Biological enrichment analysis revealed that differentially expressed genes in high ENZ-sig were more activated in cell cycle-related pathway. High-ENZ-sig patients were more sensitive to cell cycle-targeted drugs (MK-1775, AZD7762, and MK-8776) than low-ENZ-sig patients in PCa.
Our results provided evidence and insight on the potential utility of ENZ-sig in PCa prognosis and combination therapy strategy of enzalutamide and cell cycle-targeted compounds in treating PCa.
恩扎卢胺是第二代前列腺癌（PCa）内分泌治疗药物，是合成雄激素受体拮抗剂的杰出代表。目前，缺乏预测 PCa 进展和无复发生存（RFS）的恩扎卢胺诱导特征（ENZ-sig）。
从整合三种恩扎卢胺刺激模型（0、48 和 168 小时恩扎卢胺刺激）的单细胞 RNA 测序分析中得出恩扎卢胺诱导的候选标记。利用最小绝对收缩和选择算子方法，基于与癌症基因组图谱中 RFS 相关的候选基因构建 ENZ-sig。在 GSE70768、GSE94767、E-MTAB-6128、DFKZ、GSE21034 和 GSE70769 数据集进一步验证了 ENZ-sig。使用生物富集分析发现单细胞 RNA 测序和批量 RNA 测序中高 ENZ-sig 和低 ENZ-sig 之间的潜在机制。
我们发现了一种由恩扎卢胺刺激诱导的异质亚群，并发现了 53 个与轨迹进展和恩扎卢胺刺激相关的恩扎卢胺诱导候选标记。候选基因进一步缩小到与 PCa 中 RFS 相关的 10 个基因。构建了一个由 10 个基因组成的预后模型（ENZ-sig）-IFRD1、COL5A2、TUBA1A、CFAP69、TMEM388、ACPP、MANEA、FOSB、SH3BGRL 和 ST7-用于预测 PCa 的 RFS。在六个独立数据集验证了 ENZ-sig 的有效和稳健的预测能力。生物富集分析表明，高 ENZ-sig 中差异表达的基因在细胞周期相关途径中更为活跃。与低 ENZ-sig 患者相比，高 ENZ-sig 患者对细胞周期靶向药物（MK-1775、AZD7762 和 MK-8776）更敏感。
我们的研究结果为 ENZ-sig 在 PCa 预后中的潜在应用以及恩扎卢胺与细胞周期靶向化合物联合治疗 PCa 的提供了证据和思路。
