Prognostic implication of heterogeneity and trajectory progression induced by enzalutamide in prostate cancer

Yuanfa Feng; Yulin Deng; Zhenfeng Tang; Shanghua Cai; Jinchuang Li; Ren Liu; Jiaming Wan; Huichan He; Guohua Zeng; Jianheng Ye; Zhaodong Han; Weide Zhong

doi:10.3389/fendo.2023.1148898

Prognostic implication of heterogeneity and trajectory progression induced by enzalutamide in prostate cancer

Front Endocrinol (Lausanne). 2023 Mar 16:14:1148898. doi: 10.3389/fendo.2023.1148898. eCollection 2023.

Authors

Yuanfa Feng^{1

2}, Yulin Deng¹, Zhenfeng Tang¹, Shanghua Cai^{1

3}, Jinchuang Li², Ren Liu⁴, Jiaming Wan², Huichan He¹, Guohua Zeng¹, Jianheng Ye², Zhaodong Han², Weide Zhong^{1

2

3

4

5}

Affiliations

¹ Urology Key Laboratory of Guangdong Province, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
² 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.
³ Guangzhou Medical University, Guangzhou Laboratory, Guangzhou, Guangdong, China.
⁴ Guangdong Provincial Institute of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
⁵ Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China.

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Keywords: endocrine therapy; enzalutamide; prostate cancer; relapse-free survival; signature.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Antineoplastic Agents* / therapeutic use
Drug Resistance, Neoplasm
Humans
Male
Neoplasm Recurrence, Local / drug therapy
Prognosis
Prostatic Neoplasms, Castration-Resistant* / drug therapy
Prostatic Neoplasms, Castration-Resistant* / genetics
Prostatic Neoplasms, Castration-Resistant* / metabolism
Proteins

Substances

Antineoplastic Agents
enzalutamide
SH3BGRL protein, human
Proteins

Grants and funding

This work was supported by grants from the National Natural Science Foundation of China 82072813 (WZ), Science and Technology Projects in Guangzhou 202201010726 (ZH), Science and Technology Development Fund of Macau SAR 0031/2021/A (WZ), Emergency Key Program of Guangzhou Laboratory EKPG21-04 (WZ), Guangdong Basic and Applied Basic Research Foundation 2020A1515110792, 2022A1515010342 (JY), and Guangdong Basic and Applied Basic Research Foundation 2022A1515110245 (YD).