AUTHOR=Wang Shuo , Su Wei , Zhong Chuanfan , Yang Taowei , Chen Wenbin , Chen Guo , Liu Zezhen , Wu Kaihui , Zhong Weibo , Li Bingkun , Mao Xiangming , Lu Jianming 

TITLE=An Eight-CircRNA Assessment Model for Predicting Biochemical Recurrence in Prostate Cancer

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 8 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2020.599494

DOI=10.3389/fcell.2020.599494

ISSN=2296-634X

ABSTRACT=Prostate cancer（PCa）is a high morbidity malignancy in male, and biochemical recurrence (BCR) may appear after the surgery. Our study is designed to build up a risk score model by circular RNA sequencing data for PCa. The dataset is from GEO database, a cohort of 144 patients in Canada. We removed the low abundance circRNAs (RPKM < 1) and obtained 546 circRNAs for next step. BCR related circRNAs were selected by the Logistic regression using ‘survival’ and ‘survminer’ R package. Least absolute shrinkage and selector operation (LASSO) regression with ten-fold cross-validation and penalty was used to construct a risk score model by ‘glmnet’ R software package. In total, 8 circRNAs(including circ_30029, circ_117300, circ_176436, circ_112897, circ_112897, circ_178252, circ_115617, circ_14736, circ_17720 ) were involved in our risk score model. Further, we employed differentially expressed mRNAs between high and low risk score group. The following Gene Ontology (GO) analysis were visualized by Omicshare Online tools. As the GO analysis results, tumor immune microenvironment related pathways are significant enriched. ‘CIBERSORT’ and ‘ESTIMATE’ R package were used to detect tumor-infiltrating immune cells and compare the level of microenvironment score between high and low risk score group. What’s more, we verified 2 of 8 circRNA’s (circ_14736 and circ_17720) circular characteristic and tested their biological function with qPCR and CCK8 in vitro. circ_14736 and circ_17720 were detected in exosomes of PCa patients’ plasma. This is the first bioinformatics study to establish a prognosis model for prostate cancer using circRNA. These circRNAs were associated with CD8+ T cell activities and may serve as of circRNA-based liquid biopsy panel for the disease prognosis.