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

Authors :
Ke ZB
You Q
Chen JY
Sun JB
Xue YT
Zhuang RB
Zheng QS
Chen YH
Wei Y
Sun XL
Xue XY
Xu N
Source :
Computers in biology and medicine [Comput Biol Med] 2022 Jul; Vol. 146, pp. 105711. Date of Electronic Publication: 2022 Jun 07.
Publication Year :
2022

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.<br />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.<br />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.<br />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.<br /> (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1879-0534
Volume :
146
Database :
MEDLINE
Journal :
Computers in biology and medicine
Publication Type :
Academic Journal
Accession number :
35701253
Full Text :
https://doi.org/10.1016/j.compbiomed.2022.105711