Bonhan Koo1 | Yunlim Kim2 | Yoon Ok Jang1 | Huifang Liu1 | Myoung Gyu Kim1 | Hyo Joo Lee1 | Myung Kyun Woo3 | Choung-Soo Kim2,4 | Yong Shin1

1Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seodaemun-gu, Seoul, Republic of Korea
2Department of Urology, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, Republic of Korea
3Department of Biomedical Engineering, School of Electrical Engineering, University of Ulsan, Nam-gu, Ulsan, Republic of Korea
4Department of Urology, Ewha Womans University Mokdong Hospital, Yangcheon-gu, Seoul, Republic of Korea

Correspondence Choung-Soo Kim, Yong Shin

Changes in specific circulating RNA (circRNA) expressions can serve as diagnostic noninvasive biomarkers for prostate cancer (PCa). However, there are still unmet needs, such as unclear types and roles of circRNAs, PCa detection in benign prostatic hyperplasia (BPH) by unstandardized methods, and limitations of sample volume capacity and low circRNA concentrations. This study reports a simple and rapid circRNA enrichment and isolation technique named “HAZIS-CirR” for the analysis of urinary circRNAs. The method utilizes homobifunctional hydrazides with amine-modified zeolite and polyvinylidene fluoride (PVDF) syringe filtration for combining electrostatic and covalent coupling and size-based filtration, and it offers instrument-free isolation of circRNAs in 20 min without volume limitation, thermoregulation, and lysis. HAZIS-CirR has high capture efficiency (82.03%–92.38%) and a 10-fold more sensitive detection limit (20 fM) than before enrichment (200 fM). The clinical utility of HAZIS-CirR is confirmed by analyzing circulating mRNAs and circulating miRNAs in 89 urine samples. Furthermore, three miRNA panels that differentiate PCa from BPH and control, PCa from control, and BPH from control, respectively, are established by comparing miRNA levels. HAZIS-CirR will be used as an optimal and established method for the enrichment and isolation of circRNAs as diagnostic, prognostic, and predictive biomarkers in human cancers.