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MicroRNA Dysregulation in Prostate Cancer

Abstract Prostate cancer biology is complex, and needs to be deciphered. The latest evidence reveals the significant role of non-coding RNAs, particularly microRNAs (miRNAs), as key regulatory factors in cancer. Therefore, the identification of altered miRNA patterns involved in prostate cancer will allow them to be used for development of novel diagnostic and prognostic biomarkers. Patients and Methods: We performed a miRNAs transcriptomic analysis, using microarray (10 matched pairs tumor tissue versus normal adjacent tissue, selected based on inclusion criteria), followed by overlapping with TCGA data. A total of 292 miRNAs were differentially expressed, with 125 upregulated and 167 downregulated in TCGA patients’ cohort with PRAD (prostate adenocarcinoma), respectively for the microarray experiments; 16 upregulated and 44 downregulated miRNAs were found in our cohort. To confirm our results obtained for tumor tissue, we performed validation with qRT-PCR at the tissue and plasma level of two selected transcripts, and finally, we focused on the identification of altered miRNAs involved in key biological processes. Results: A common signature identified a panel of 12 upregulated and 1 downregulated miRNA, targeting and interconnected in a network with the TP53, AGO2, BIRC5 gene and EGFR as a core element. Among this signature, the overexpressed transcripts (miR-20b-5p, miR-96-5p, miR-183-5p) and the downregulated miR-542-5p were validated by qRT-PCR in an additional patients’ cohort of 34 matched tumor and normal adjacent paired samples. Further, we performed the validation of the expression level for miR-20b-5p, miR-96-5p, miR-183-5p plasma, on the same patients’ cohort versus a healthy control group, confirming the overexpression of these transcripts in the PRAD group, demonstrating the liquid biopsy as a potential investigational tool in prostate cancer. Conclusion: In this pilot study, we provide evidence on miRNA dysregulation and its association with key functional components of the PRAD landscape, where an important role is acted by miR-20b-5p, miR-542-5p, or the oncogenic cluster miR-183-96-182.


Introduction
According to Globocan 2020, prostate cancer is the second most frequent malignancy (after lung cancer) worldwide, with 1,414,259 (14.1%) new cases, and causing 375,304 deaths (3.8% of all deaths caused by cancer in men). 1,2 Around 20% of the new cases will develop invasive disease during their lifetime, most of the cases being diagnosed in advanced stages. 3 Current prostate cancer management is based on a series of tests for non-invasive biomarkers. 4 Till now, the serum markers are not sufficient for both early diagnostic and prognostic of prostate cancer. Patient stratification and identification of high-risk groups of prostate cancer have an important role in therapeutic decision. 5 A better understanding of the prostate cancer molecular landscape will have an important role in the development of novel biomarkers or identification of therapeutic target. 6 In this context, in the last decades, the evaluation of non-coding genes opened new avenues in cancer investigation. [7][8][9][10] MicroRNAs (miRNAs) are small non-coding RNAs with 19-25 nucleotides in length that regulate the mRNA level of expression by canonical and non-canonical mechanisms 9,11 and shown an important impact in cellular processes; [12][13][14] also miRNAs have and important role in intercellular signaling. 15 Dysregulation of miRNAs has been observed in several human malignancies, 7,16,17 including prostate cancer. Increasing evidence indicates that the miRNAs can act as either oncogenes or tumor suppressor genes.
miRNAs are mentioned in literature as a potential application of biomarkers for numerous diseases, 7,9,18 including prostate adenocarcinoma (PRAD). 19 Despite this, there is a current lack of validated studies that evaluated the miRNA expression level and direct connection with clinical variables, particularly from the liquid biopsy. 20,21 Recent literature data emphasizes the important role of liquid biopsy in patient stratification. 20,22 In the present pilot study, using microarray technology, we evaluated the miRNA particularities in PRAD on ten matched paired tumor tissues and normal adjacent tissues samples, followed by overlapping with TCGA data and identification of key pathways involved. The profiling study was followed by validation by qRT-PCR in an additional patient cohort comprising 34 matched PRAD samples, followed by an additional validation step from plasma samples from the same patients' cohort.
Consequently, to these analyses, we performed the exploration of the expression level for the most relevant target genes using UALCAN online tools. miRNA-gene interconnection was analyzed using Ingenuity Pathway Analysis (IPA) software. Our findings contribute to the molecular understanding of the tumorigenesis and for prognostic value in PRAD, and provide a set of miRNAs and their target genes that may be useful for the development of novel diagnostic biomarkers and/or more effective therapeutic strategies, particularly for the identification of high-risk groups of PRAD.

Human Subjects, Ethical Approval, and Clinical Data
We designed and performed a microarray experiment for microRNA evaluation on the matched paired samples of PRAD and their normal adjacent tissues (Table 1), age average of 63±4.9, followed by a validation step by qRT-PCR ( Table 2, age average of 66±4.9). Sample collection was done after the approval of the Ethical Committee of The Oncology Institute "Prof. Dr. Ion Chiricuta" no. 5991 from 26.06.2019, following protocols by national and European regulations concerning the use of biological samples and personal data: personal data were anonymized for all cases; all patients and healthy donors were informed about the study, and each provided signed informed consent.

DovePress
The clinical characteristics for each patient enrolled in the microarray analysis (defined as UMPh patient cohort) are given in Table 1, meanwhile, the clinical data for the validation cohort of PRAD patients used for qRT-PCR from tissue (tumor/normal adjacent) and plasma are given in Table 2. For the qRT-PCR of plasma samples, we used male plasma samples from healthy controls (Table 3), considering the estimated age-specific incidence rates for prostate cancer. 23

Clinical Data of Patients from TCGA Data
The Cancer Genome Atlas (TCGA) is a public database developed to generate complex bioinformatics analysis with important implications in understanding the molecular portraits. 24 Therefore, we downloaded the data from the Firebrowse portal (http://firebrowse.org/), comprising data from 494 samples of PRAD and 52 adjacent normal tissue (Table 4).

MiRNA Analysis Conditions from TCGA
We analyzed the miRNAs using Gene Spring considering FC±1.5 as cut-off value and p-value ≤0.05.

RNA Extraction and Quality Control
The tissue samples (tumor and normal adjacent tissue) was extracted using Trireagent, and for the plasma was used Plasma/Serum Circulating and Exosomal RNA Purification Kit (Slurry Format) (Cat. 42800), followed by the evaluation of RNA concentration by the use of NanodropND2000 for microarray, respectively qRT-PCR validation step.

miRNA Microarray and Array Data Analysis Evaluation
For miRNA patterns, we used 10 tumor tissue and normal adjacent tissue matched paired PRAD samples. Starting from 100 ng of total RNA, the hybridization was done using Agilent microRNA Spike-In kit and the labeling miRNA Complete Labeling and Hyb Kit, followed by a purification step using Micro Bio-Spin 6 (Biorad, Mississauga, ON, Canada) spin columns according to producer recommended protocol. Also, for the hybridization, Agilent SurePrint Human miRNA v21.0 microarray slides (G4872A) have been used. After the 20 hours hybridization period in the oven at 55°C, the slides have been washed and scanned using an Agilent Microarray Scanner.

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The bioinformatics analysis was done for matched paired PRAD samples using the same parameters as those used for TCGA data sets. The data were extracted using Agilent Feature Extraction software (Agilent Technologies); Agilent GeneSpring GX program (Agilent Technologies) was used to obtain differentially expression selected "Filter on Volcano Plot" analysis and moderated t-test, with a fold change of 1.5. Benjamini-Hochberg (false discovery rate-FDR) algorithm was applied to reduce the false-positive rates.

Ingenuity Pathway Analyses of Commonly Deregulated miRNAs in PRAD
The identified differentially expressed miRNAs in both patient cohorts (UMPh and TCGA) were uploaded to the IPA software (https://digitalinsights.qiagen.com/products-overview/discovery-insights-portfolio/analysis-and-visualization /qiagen-ipa, QIAGEN). The "core analysis" function of the software was used to analyze the differentially expressed miRNA data, which incorporated the recognition of biological processes, canonical pathways, upstream transcriptional regulators, and interconnected networks.

Online Evaluation of TCGA Gene and miRNA Expression Level in PRAD
Using the UALCAN database (http://ualcan.path.uab.edu/index.html), the expression levels of common miRNA signature in patients with PRAD have been separated on TP53 mutation status and Gleason score. UALCAN is a user-friendly, interactive web resource for TCGA transcriptome data analysis. 25 The analytical results were displayed on the webpage (UALCAN); p<0.05 was considered to denote a statistically significant result. The evaluation of the target genes was done using the DIANA-miRPath v3.0 interface. 26

miRNA qRT-PCR Evaluation on Tissue and Plasma Samples
Three upregulated transcripts (miR-20b-5p, assay ID:001006; miR-96-5p, assay ID: 000186 and miR-183-5p, assay ID: 002269) and one downregulated transcript (miR-543-5p, assay ID: 002269) were selected from common signature from our microarray data and TCGA in both data analyses (UMPh and TGCA patient cohort). RNA was extracted using the TriReagent based method for qRT-PCR. The validation was performed on 34 matched paired PRAD samples, respectively 34 plasma samples from PRAD and 30 healthy controls using TaqMan MicroRNA Reverse Transcription Kit (Applied Biosystems) protocol as described previously, based on ΔΔCt method, 16 on VIIA7 system (Life Technologies). U6 (assay ID: 001973) and RNU48 (assay ID: 001006) were used as normalizers. All qRT-PCR reagents were provided by Life Technologies.

Statistically Analysis
Data analysis was done using GraphPad Prism v9 software (GraphPad Software, San Diego, CA, USA). Student's t-test was used for the differences among the expression levels of gene and miRNAs, as two-group comparisons (in tumor tissue and normal adjacent PRAD tissue, respective for the expression level in the case of plasma for PRAD patients versus healthy control group); p-value≤0.05 was considered as statistically.

Differential miRNA Expression on PRAD-UMPh Patient Cohort
In the case of our patients' cohort with confirmed histopathological PRAD (10 tumor tissue/ normal adjacent tissue matched paired samples) there has been observed an important number of altered transcripts, only 60 differentially expressed miRNAs (16 upregulated and 44 downregulated), the complete list of the altered miRNAs being displayed in Table S1 and Figure 1. Figure 1A presents the UMPh heatmap, in Figure 1C is displayed scatter plot and in the Figure 1E is represented the Volcano plot for the same patient cohort.

Differential miRNA Expression on PRAD-TCGA Patient Cohort
The analysis performed on TCGA samples for PRAD tumor tissue (n=494) versus normal tissue (n=52) reveals a total of 261 miRNAs differentially expressed (208 upregulated and 53 downregulated), displayed as a heatmap in Figure 1B Table S2. Additional scatter plot and Volcano plot graphical representation is displayed in Figure 1D, respectively 1F for TCGA dataset.
For common miRNA signature using UMPh and TCGA patient cohort an additional Venn diagram was created for the overexpressed (Figure 2A) and downregulated transcripts ( Figure 2B).

Validation of Microarray Data by RT-PCR at Plasma Level
Additional validation at plasma level using samples from 34 PRAD patients and 30 healthy controls was performed for the selected overexpressed transcripts, confirming the overexpression level retrieved ( Figure 4A). AUC values are similar, or even higher than those retrieved in tissue ( Figure 4B).

miRNAs as Key Signaling Molecules in PRAD Evaluated Using IPA
The molecular cellular functions identified as significantly enriched (p≤0.05) within the dataset are summarized in Table 5 based on IPA analysis. The most significant altered network identified was "Cellular Development" in both patients' cohorts. We used the common PRAD signature to generate the miRNA-mRNA interaction network using IPA, displayed in Figure 5, revealing the TP53, AGO2, BIRC5, and EGFR as the core element for this network.

miRNA Expression Pattern Considering TP53 Mutation Status in PRAD Based on TCGA Data
Additional investigation of miRNA signature based on TP53 status was done using UALCAN. TP53 is a frequently mutated gene in many cancers, the mutation frequency in PRAD being over 20% ( Figure 8A). The expression level for miR-20b and miR-183-5p was not affected by the TP53 mutation status ( Figure 8B). In the case of miR-96, the expression level was statistically significant much higher in the case of samples with TP53 mutant versus samples with TP53 wild-type. In the case of miR-542, it was statistically downregulated in the TP53 mutant, while the expression level for the TP53 wild-type group was not modified. Evaluation of the expression levels of microRNAs associated with the Gleason grading system in PRAD based on TCGA data was done using UALCAN ( Figure 9). It was observed an increase of the expression level with the Gleason score (particular for Gleason score 10, n=3), these effects being more pronounced for miR-20b-5p and miR-183-5p, but need to be further validated in higher number of cases considering the only 3 cases in Gleason score 10.

Discussion
In this study, we evaluated the differentially expressed miRNAs between PRAD tumors and their adjacent normal tissue, using microarray, then we overlapped the date with those from the TCGA. The most relevant transcripts among the common signature were validated by qRT-PCR in both tumor tissue and patients' plasma. The value of liquid biopsy as an alternative to the extremely invasive tissue biopsy is highly important due to the information relieved in plasma from the tumor. This is particularly important when this can be combined with already implemented non-invasive markers, for higher accuracy diagnostic by combining with circulating miRNA, 20,27 particularly for high risk group identification. 28 Circulating miRNAs are considered the next-generation clinical biomarker, 28 that promote not only the existence of cancer, but also the dynamics, malignant capacity and drug resistance of tumors. 29 Our analysis provides an initial framework to address the long-standing issue of co-operative or Functionally interrelated nature of miRNA targets in a practical setting. Particularly, when correlated with databases related to the  Altered miRNA pattern can be considered a valuable molecular characteristic and can impact clinical trajectories and predictions for enhanced responses to specific therapeutics. 30 We found that the altered miRNAs are involved in key biological processes (Table 5), with important clinical significance, as was emphasis by IPA analysis.

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Our approach selects only tissue-specific mRNA targets in prostate cancer, particularly for specific miRNA signatures. As the reduction in target mRNA expression may not constantly be obvious (as we have assumed), our Research may have minimized the overall effect of miRNAs in prostate carcinogenesis or should be related to downstream/upstream genes, particularly those predicting overall survival rate, highlighted with blue square in Figure 6 (TP53, BIRC5, AGO2 and EGFR), that should be further identified as biomarkers for the identification of high-risks prostate cancer groups.
The established miRNA-gene signatures and the identification of miRNA target gene-related to survival have an important role in the elucidation of molecular mechanisms, underpinning dissimilar molecular profiles, sharing interchangeable prognostic capabilities, and additionally, can serve for prospective applications in drug development. The regulation of miRNAs was interlinked with key regulators of Argonaut 2 (AGO2), 1 sustained also by present study (Figure 5). miRNA association with AGO2 is regulated by TP53, suggesting a new mechanism of miRNA regulation in carcinogenesis through TP53-mediated regulation of AGO2-miRNA interaction. 31,32 A recent study reveals that AGO2 and miR-96 are incorporated into the cytoplasm. 33 Also, miR-542-5p targeted AGO2, being considered a possible therapeutic target. 34 The additional investigation presents important data related to miR-542-5p that targeted AGO2 and EGFR. [35][36][37] Three of the identified transcripts, miR-182-5p, miR-183-5p, and miR-96-5p, are members of the miR-183-96-182 oncogenic cluster. 38,39 MiR-183-5p is proposed as a specific diagnostic biomarker in prostate cancer. 40 The well-known prostate tumor suppressor PTEN was demonstrated to be regulated by miR-183-5p and miR-96-5p. 38 MiR-96 in prostate cancers is much higher expressed in mutant cases than wild-type p53, as shown UALCAN database. This correlation with TP53 mutation status was observed in the head and neck squamous cell carcinoma. 41 MiR-96 is a key regulator of cell-cell adhesion, having the capacity to overexpress E-Cadherin and EpCAM. 42 Other studies reveal that this transcript governs androgen signaling and prostate cancer progression, 43 and regulation of cell proliferation by targeting FOXO1 and FOXO3a. 44 miR-20b was identified as overexpressed in prostate cancer tissues, promoting the regulation of key mechanisms like cellular proliferation, EMT, and migration. 45,46 miR-542 is involved in the regulation of EMT and metastasis, 47 in our case was downregulated, particularly in TP53 mutated samples. TP53 is positively regulated by these transcripts. 48 Also, inhibition of the expression level for miR-542 was related to hypoxic condition 49 or regulated DNA repair/Notch pathway. 50 Mutations in TP53 are among the most common abnormalities in many cancers, 30,51-53 observed in Figure 3 as a core element. miRNAs are altered in tumors, underlining the fact that a possible connection between miRNAs and TP53 could be critical in tumorigenesis, considering that TP53 is a frequently overexpressed and mutated gene in the prostate cancer. [54][55][56] Additional investigation of miRNA interplay should be investigated, particularly for therapeutic application of miRNAs targeting TP53 pathway, 57,58 especially for PRAD.
The limitation of the present study is related to the reduced number of cases, this being minimized by the overlapping of TCGA miRNA signature and validation of part of the common signature in an additional patient cohort by qRT-PCR at tissue and plasma level. At the same time, this pilot profiling study provides valuable data related to the complex pathophysiological mechanism that will serve as a basis for further detailed investigations.

Conclusions
Overlapping of two miRNA independent patient cohorts can identify a common signature, that can be further explored for biomarker discovery. Additionally, this common miRNA signature targets key genes related (TP53, BIRC5, EGFR, and AGO2 correlated with overall survival in PRAD) to the key mechanism involved in prostate cancer, where an important element is associated with TP53 signaling and its related miRNAs. Additional investigations in larger sample size is also required to validate the outcomes of this pilot study, and to be able to identify the high risks groups of prostate cancer based on altered miRNA patterns.