Plasma Messenger RNAs Identified Through Bioinformatics Analysis are Novel, Non-Invasive Prostate Cancer Biomarkers

Rui Wang; Yingzi Wu; Jin Yu; Guizhu Yang; Hao Yi; Bin Xu

doi:10.2147/OTT.S221276

Plasma Messenger RNAs Identified Through Bioinformatics Analysis are Novel, Non-Invasive Prostate Cancer Biomarkers

Onco Targets Ther. 2020 Jan 17:13:541-548. doi: 10.2147/OTT.S221276. eCollection 2020.

Authors

Rui Wang^#^{1

2

3}, Yingzi Wu^#^{4

5}, Jin Yu^#⁶, Guizhu Yang^{1

2}, Hao Yi⁷, Bin Xu⁸

Affiliations

¹ Department of Oral and Maxillofacial-Head Neck Oncology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, People's Republic of China.
² National Clinical Research Center for Oral Diseases, Shanghai, People's Republic of China.
³ Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, People's Republic of China.
⁴ TCM Department,The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, People's Republic of China.
⁵ The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, People's Republic of China.
⁶ Department of Gynecology of Traditional Chinese Medicine, Changhai Hospital, Naval Medical University, Shanghai 200433, People's Republic of China.
⁷ Department of Prosthodontics, College of Stomatology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
⁸ Department of Urology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China.

^# Contributed equally.

Abstract

Aim: To identify new biomarkers of prostate cancer (PCa) for the diagnosis and prediction of clinical outcomes.

Materials and methods: Existing microarray data of PCa tissues in the Oncomine database were analyzed and candidate differentially expressed genes (DEGs) that may be novel and noninvasive biomarkers were obtained. On this basis, plasma mRNA was extracted from PCa patients and healthy donors. Furthermore, plasma mRNA expression of DEGs was evaluated by qRT-PCR. Finally, the diagnostic power of the biomarkers was evaluated in comparison to the clinical characteristics of the patients.

Results: In this study, the top five significantly overexpressed mRNA (AMACR, PPP1R14b, PCA3, DLX1, and RPL22L1) and the top five significantly underexpressed mRNA (DUOX1, EFS, GSTP1, S100A16, and NCRNA00087) were selected for further validation in PCa patients and healthy donors by qRT-PCR. The results showed that AMACR, DLX1, PCA3, DUOX1, and GSTP1 mRNA were stably amplified in plasma. Additionally, DLX1, PCA3, DUOX1, and GSTP1 mRNA expression was significantly different between PCa circulating free mRNA samples and healthy donors. These mRNAs may be useful biomarkers for PCa diagnosis.

Conclusion: Analysis of the expression of genes in the Oncomine database showed that DLX1, PCA3, and DUOX1 expressions have a cancer specific pattern in PCa. Collectively, DLX1, PCA3, and DUOX1 may be useful candidate biomarkers for PCa diagnosis.

Keywords: DLX1; DUOX1; GSTP1; PCA3; prostate cancer.