An anoikis-related gene signature for prediction of the prognosis in prostate cancer

Xiaodong Zhao; Zuheng Wang; Zilu Tang; Jun Hu; Yulin Zhou; Jingping Ge; Jie Dong; Song Xu

doi:10.3389/fonc.2023.1169425

An anoikis-related gene signature for prediction of the prognosis in prostate cancer

Front Oncol. 2023 Aug 17:13:1169425. doi: 10.3389/fonc.2023.1169425. eCollection 2023.

Authors

Xiaodong Zhao^{1

2}, Zuheng Wang^{1

2}, Zilu Tang^{1

2}, Jun Hu^{1

2}, Yulin Zhou², Jingping Ge², Jie Dong², Song Xu^{1

2}

Affiliations

¹ Jinling School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.
² Department of Urology, Eastern Theater General Hospital of Medical School Of Nan Jing University, Nanjing, Jiangsu, China.

Abstract

Purpose: This study presents a novel approach to predict postoperative biochemical recurrence (BCR) in prostate cancer (PCa) patients which involves constructing a signature based on anoikis-related genes (ARGs).

Methods: In this study, we utilised data from TCGA-PARD and GEO databases to identify specific ARGs in prostate cancer. We established a signature of these ARGs using Cox regression analysis and evaluated their clinical predictive efficacy and immune-related status through various methods such as Kaplan-Meier survival analysis, subject work characteristics analysis, and CIBERSORT method. Our findings suggest that these ARGs may have potential as biomarkers for prostate cancer prognosis and treatment. To investigate the biological pathways of genes associated with anoikis, we utilised GSVA, GO, and KEGG. The expression of ARGs was confirmed by the HPA database. Furthermore, we conducted PPI analysis to identify the core network of ARGs in PCa.

Results: Based on analysis of the TCGA database, a set of eight ARGs were identified as prognostic signature genes for prostate cancer. The reliability and validity of this signature were well verified in both the TCGA and GEO codifications. Using this signature, patients were classified into two groups based on their risk for developing BCR. There was a significant difference in BCR-free time between the high and low risk groups (P < 0.05).This signature serves as a dependable and unbiased prognostic factor for predicting biochemical recurrence (BCR) in prostate cancer (PCa) patients. It outperforms clinicopathological characteristics in terms of accuracy and reliability. PLK1 may play a potential regulatory role as a core gene in the development of prostate cancer.

Conclusion: This signature suggests the potential role of ARGs in the development and progression of PCa and can effectively predict the risk of BCR in PCa patients after surgery. It also provides a basis for further research into the mechanism of ARGs in PCa and for the clinical management of patients with PCa.

Keywords: anoikis-related gene; biochemical recurrence; prediction; prostate cancer; signature.