A radiation resistance related index for biochemical recurrence and tumor immune environment in prostate cancer patients. (July 2022)

• Record Type: Journal Article
• Authors: Ke, Zhi-Bin; You, Qi; Chen, Jia-Yin; Sun, Jiang-Bo; Xue, Yu-Ting; Zhuang, Rui-Bin; Zheng, Qing-Shui; Chen, Ye-Hui; Wei, Yong; Sun, Xiong-Lin; Xue, Xue-Yi; Xu, Ning
• Is Part Of: Computers in biology and medicine. Volume 146(2022)
• Publication Date: 2022-07
• Subjects: Prostate cancer -- Radiation resistance -- Tumor immune microenvironment -- Biochemical recurrence; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2022.105711
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Purpose: To establish and verify a novel radiation resistance related index for predicting biochemical recurrence and tumor immune environment in prostate cancer (PCa) patients. Materials and methods: The transcriptome information of PCa were obtained from GEO and TCGA portal. We identified radiation resistance related genes (RRGs) between radioresistant and radiosensitive PCa cells. We conducted multivariate Cox analysis to construct a novel radiation resistance related index for predicting biochemical recurrence (BCR)-free survival (BCRFS). Internal and external validations were conducted. Preliminary experimental verifications were performed. Results: We identified 194 differentially expressed RRGs and three radiation resistance related molecular clusters for PCa. Moreover, we established a novel radiation resistance related index and succeeded in conducting internal and external validations. High-risk populations meant significantly worse BCRFS in training, testing and validating cohort. The area under receiver operating characteristic curve were 0.809, 0.698, and 0.712 in training, testing, and validating cohort. The immune microenvironment was significantly different between high and low-risk score patients. Preliminary experiment identified and validated three potential biomarkers related to radiation resistance (ZNF695, TM4SF19, CCDC3) of PCa. Conclusions: This study successfully established and verified a novel radiation resistance related index, which had an excellent performance in predicting BCR and tumor immune microenvironment in patients with PCa. Highlights: A total of 194 differentially expressed RRGs and three radiation resistance related clusters for PCa were identified. A novel radiation resistance related index for predicting BCR and immune microenvironment in PCa patients were established. CCDC3 inhibited the migration and invasion of PCa cells while TM4SF19 and ZNF695 showed the opposite trend.