The integration of multidisciplinary approaches revealed PTGES3 as a novel drug target for breast cancer treatment

Qinan Yin; Haodi Ma; Yirui Dong; Shunshun Zhang; Junxiang Wang; Jing Liang; Longfei Mao; Li Zeng; Xin Xiong; Xingang Chen; Jingjing Wang; Xuewei Zheng

doi:10.1186/s12967-024-04899-0

The integration of multidisciplinary approaches revealed PTGES3 as a novel drug target for breast cancer treatment

J Transl Med. 2024 Jan 20;22(1):84. doi: 10.1186/s12967-024-04899-0.

Authors

Qinan Yin¹, Haodi Ma¹, Yirui Dong¹, Shunshun Zhang¹, Junxiang Wang², Jing Liang³, Longfei Mao⁴, Li Zeng¹, Xin Xiong⁵, Xingang Chen¹, Jingjing Wang¹, Xuewei Zheng⁶

Affiliations

¹ Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China.
² School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang, China.
³ The First Affiliated Hospital of Henan University of Science and Technology, Luoyang, China.
⁴ College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, Luoyang, China.
⁵ Department of Pathology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
⁶ Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China. xwzheng0529@163.com.

Abstract

Background: The main challenge in personalized treatment of breast cancer (BC) is how to integrate massive amounts of computing resources and data. This study aimed to identify a novel molecular target that might be effective for BC prognosis and for targeted therapy by using network-based multidisciplinary approaches.

Methods: Differentially expressed genes (DEGs) were first identified based on ESTIMATE analysis. A risk model in the TCGA-BRCA cohort was constructed using the risk score of six DEGs and validated in external and clinical in-house cohorts. Subsequently, independent prognostic factors in the internal and external cohorts were evaluated. Cell viability CCK-8 and wound healing assays were performed after PTGES3 siRNA was transiently transfected into the BC cell lines. Drug prediction and molecular docking between PTGES3 and drugs were further analyzed. Cell viability and PTGES3 expression in two BC cell lines after drug treatment were also investigated.

Results: A novel six-gene signature (including APOOL, BNIP3, F2RL2, HINT3, PTGES3 and RTN3) was used to establish a prognostic risk stratification model. The risk score was an independent prognostic factor that was more accurate than clinicopathological risk factors alone in predicting overall survival (OS) in BC patients. A high risk score favored tumor stage/grade but not OS. PTGES3 had the highest hazard ratio among the six genes in the signature, and its mRNA and protein levels significantly increased in BC cell lines. PTGES3 knockdown significantly inhibited BC cell proliferation and migration. Three drugs (gedunin, genistein and diethylstilbestrol) were confirmed to target PTGES3, and genistein and diethylstilbestrol demonstrated stronger binding affinities than did gedunin. Genistein and diethylstilbestrol significantly inhibited BC cell proliferation and reduced the protein and mRNA levels of PTGES3.

Conclusions: PTGES3 was found to be a novel drug target in a robust six-gene prognostic signature that may serve as a potential therapeutic strategy for BC.

Keywords: Breast cancer; Drug target; PTGES3; Prognostic signature.

MeSH terms

Breast Neoplasms* / drug therapy
Breast Neoplasms* / genetics
Diethylstilbestrol
Female
Genistein
Humans
Limonins*
Molecular Docking Simulation
Prognosis
RNA, Messenger

Substances

Diethylstilbestrol
gedunin
Genistein
Limonins
RNA, Messenger
PTGES3 protein, human