Identification of Enzalutamide Resistance-Related circRNA-miRNA-mRNA Regulatory Networks in Patients with Prostate Cancer

Abstract

This study aimed to identify enzalutamide resistant-related (EnzR-related) circRNAs and to characterize and validate circRNA-miRNA-mRNA ceRNA regulatory network and corresponding prognostic signature of prostate cancer patients. Methods: We obtained circRNA expression microarray from the Gene Expression Omnibus (GEO) database and performed differential expression analysis to identify EnzR-related circRNAs using the limma package. The miRNA and mRNA expression profiling were downloaded and performed differential expression analysis, then overlapped with predicted candidates. Next, we established circRNA-miRNA-mRNA ceRNA network and PPI network utilized Cytoscape software and STRING database, respectively. In addition, univariate and Lasso Cox regression analyses were applied to generate a prognostic signature. Receiver operating characteristic (ROC) curves and Kaplan-Meier analysis were used to evaluate the reliability and sensitivity of the signature. Ultimately, we chose hsa_circ_0047641 to validate the feasibility of the EnzR-related ceRNA regulatory pathway using qRT-PCR, CCK8 and Transwell assays. Results: We identified 13 EnzR-related circRNAs and constructed a ceRNA regulatory network that contained two downregulated circRNAs (has-circ-00000919 and has-circ -0000036) and two upregulated circRNAs (has-circ-0047641 and has-circ-0068697), and their sponged 6 miRNAs and 167 targeted mRNAs. Subsequently, these targeted mRNAs were performed to implement PPI analysis and to identify 10 Hub genes. Functional enrichment analysis provided new ways to seek potential biological functions. Besides, we established a prognostic signature of PCa patients based on 8 prognostic-associated mRNAs. We confirmed that the survival rates of PCa patients with high-risk subgroup were slightly lower than those with low-risk subgroup in the TCGA dataset (p<0.001), and ROC curves revealed that the AUC value for prognostic signature was 0.816. Finally, the functional analysis suggested that knockdown of hsa_circ_0047641 could inhibit the progression of PCa and could reverse Enz-resistance in vitro. Conclusion:We identified 13 EnzR-related circRNAs, and constructed and confirmed that EnzR-related circRNA-miRNA-mRNA ceRNA network and corresponding prognostic signature could be a useful prognostic biomarker and therapeutic target.

Deregulated microRNAs Involved in Prostate Cancer Aggressiveness and Treatment Resistance Mechanisms

“…The identification of miRNA–mRNA regulatory relationships through a correlation-based approach (i.e., integrating miRNA and mRNA profiling data, finding negative correlations between expression profiles of miRNAs and predicted mRNA targets) has been suggested as a more accurate way to identify critical miRNA–mRNA interactions in PCa [ 214 , 215 , 216 ]. In our previous studies, we combined the correlation-based approach with comprehensive pathway analysis to construct miRNA–mRNA regulatory networks underlying AA PCa disparities.…”

Circular RNAs and Drug Resistance in Genitourinary Cancers: A Literature Review

“…Greene et al screened the circRNA expression of two enzalutamide-resistant LNCaP clones against the control cell line and found 111 commonly altered circRNAs [ 137 ]. Yu et al further analyzedGreene et al’s data and constructed a ceRNA regulatory network [ 138 ]. They chose hsa_circ_0047641 and further validated its effect on the proliferation of enzalutamide-sensitive and resistant PCa cells.…”

“…They could serve as prognostic biomarkers in cancers [ 91 , 108 ]. Some studies, Luo et al [ 108 ] and Yu et al [ 138 ] for example, further illustrated the functions of these circRNAs in cancer invasion and proliferation. However, it should be noted that the effect of these circRNAs on drug resistance was not all experimentally validated, which is mandatory for ascertaining the causal–effect relationship.…”

The Role and Clinical Potentials of Circular RNAs in Prostate Cancer

“…Survival rate analysis in PCa patients by the Kaplan-Meier curve unveiled a positive correlation between higher expression of cognate genes corresponding to anti-carcinogenic circRNAs (hsa_circ_0006410, hsa_circ_AKAP7 and hsa_circ_0005848) and better overall survival (OS) in PCa patients. Also, Yu et al (49) identified 13 circRNAs in association with resistance to enzalutamide as an androgen deprivation therapy (ADP) drug used against PCa. Six miRNAs, 167 mRNAs, and 10 hub genes were identified as targets of the circRNAs.…”