UROLOGICAL ONCOLOGY The Association of miR-let 7b and miR-548 with PTEN in Prostate Cancer Mojtaba Saffari1, 2, Sayyed Mohammad Hossein Ghaderian3*, Mir Davood Omrani4, Mandana Afsharpad5, Kimia Shankaie6, Niusha Samadaian7 Purpose: This study aims to investigate the expression level of mir-let7b-3p and mir-548, which are involved in PTEN expression in tissue samples of prostate cancer patients versus benign prostate hyperplasia (BPH) and normal adjacent tissue. Materials and Methods: Prostate cancer tissues were obtained from patients after receiving informed consent. Total RNA extraction and cDNA synthesis were performed for determining gene expression. Results: Ten patients were determined to have high Gleason scores (> 7), 36 and seven samples had intermediate Gleason scores (7≥) and BPH, respectively, and 40 samples were derived from normal adjacent tissue. Downreg- ulation of mir-let7b and upregulation of mir-548 expression significantly correlated with high-risk Gleason scores. Conclusion: The present study showed that miR-let7b and/or mir-548 can be considered as potential targets in prostate cancer therapy. Keywords: Prostate cancer; mir-let7b; mir-548; PTEN INTRODUCTION One of the most frequently diagnosed malignancies in men is prostate. Various factors including envi- ronmental elements such as lifestyle, race and genetics alterations and epigenetic mechanisms influence pros- tate cancer and its progression toward advanced malig- nancy1,2. The discovery of genetic or epigenetic as- sociations with prostate cancer in the post-genome era has improved diagnosis and management of therapy 3. PTEN tumor suppressor gene plays a key role in PI3k/ AKT pathway regulation, which is the most prominent signaling pathway that regulates some cellular pro- cesses such as cell cycle, survival, metabolism, motil- ity, genomic instability and angiogenesis, and frequent changes in prostate cancer. It was shown that the PTEN expression level decreased in 4% of primary prostate cancer and more than 40% in metastatic prostate cancer 4 . For this reason, the inhibition of PTEN suppressor can be used as a potential target therapy for metastat- ic prostate cancer. The early determination of prostate cancer is necessary for an effective treatment and to in- crease survival time. At present, the most common tools for the diagnosis of prostate cancer is serum prostate specific antigen (PSA) level 5. Sensitivity and specific- ity of a PSA cutoff of 4 ng/ml are about 50% and 90%, respectively. This limitation leads to low detection rate 1Department of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 2Cancer Biology Research Center, Cancer Institute of Iran, Tehran University of Medical Sciences, Tehran, Iran. 3Chronic Kidney Disease Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 4Urogenital Stem Cell Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 5Cancer Control Research Center, Cancer Control Fundation, Iran, Iran University of Medical Sciences, Tehran, Iran. 6Department of Biology, Science and research branch, Islamic Azad University, Tehran, Iran. 7Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. *Correspondence: Urology & Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran Pasdaran, 9th Boostan Ave. Tehran, Iran. Tel: +982122770954 Fax: +982122567282.E-mail: sghaderian@sbmu.ac.ir. Received May 2018 & Accepted September 2018 of prostate cancer in range of 4–10 ng/ml PSA level (called gray zone), and therefore, it is a disadvantage of PSA screening as a biomarker. Although PSA has decreased the mortality rate of prostate cancer, it can lead to over-diagnosis or overtreatment 6,7. MicroRNAs (miRNAs), on average 22 nucleotides long, are a class of small noncoding RNAs and play key roles in the gene regulatory processes 8. First, they are transcribed in the nucleus by RNA polymerase II called pri-miRNA, and then they are processed into pre-miRNA by Drosha and transported to the cytoplasm to be converted to 19-25 nucleotides double strand mi- croRNA by Dicer. MicroRNAs are transported into the RNA-induced silencing complex (RISC) that bind to 3ÚTR of the target genes and negatively regulate trans- lation 9. The alteration of miRNA expression leads to changes in many fundamental cellular and biological processes such as differentiation, proliferation, migra- tion, cell cycle and apoptosis that cause disease and cancer. Chromosomal rearrangement such as deletion, amplification, mutation, and methylation of promoter alter miRNA expression levels 10. Increasing miRNA expression profiling improves diagnosis, staging, pro- gression, prognosis, and response to treatment in hu- man cancers. Therefore, miRNAs can be used as a new oncomir or tumor suppressor mir, and new biomarkers for the diagnosis, prognosis and prediction of treatment Urological Oncology 267 Vol 16 No 03 May-June 2019 268 response. It has been demonstrated that miRNAs are very stable against heat, pH alteration, freeze-thaw and ribonuclease5. For this reason, miRNA levels are stud- ied in different types of patient samples. Based on information from databases/literature, which show the potential miRNAs that influence the PTEN target gene, we selected mir-let7b-3p and mir-548 for quantification by real-time polymerase chain reactions (RT-PCRs) and determined the PTEN expression levels between tumor tissues and normal tissues. In the pres- ent study, we showed dysregulation of mir-let7b and mir-548 expression levels in prostate cancer tissues. MATERIALS & METHODS Target prediction for microRNA Two online computational algorithms, TargetScan (www.targetscan.org) and Diana Tools (diana.imis. athena-innovation.gr), were used for the bioinformatics prediction of miRNA binding sites. Ethics Statement All tests were carried out in conformity with relevant guidelines. Written informed consent was obtained from each contributor prior to tumor sample collec- tion. All the clinical samples were obtained from Imam Khomeini Hospital of Tehran University of Medical Sciences. This study was approved by the Ethical Re- view Committee of Shahid Beheshti University of Med- ical Sciences. Sample collection In this study, all the samples of newly diagnosed pros- tate cancer cases were collected from Imam Khomeini Hospital between 2015and 2016. After informed con- sent, the patients for the study were selected as per the inclusion criteria: age above 40 years, high PSA, his- topathological findings of the needle biopsy specimens confirmed prostate cancer or BPH, and no chemother- apy treatments were given before surgery. The exclu- sion criteria were: age 40 years or below, normal PSA, and frequent urination without prostate cancer symp- tom. Then a pathologist distinguished tumor tissue from adjacent healthy tissue as normal sample according to the pathology results of previous needle biopsy. RNA extraction and cDNA synthesis Total RNA extraction from the tissue samples was done with Trizol (Invitrogen Carlsbad, CA) in line with the manufacturer’s protocol. The quantity of RNA samples was assessed spectrophotometrically by using Nano- drop ND-2000 (Thermo Fisher Scientific). The Mir-Q method as described by Sharbati-Tehrani11 was used for miR-let7b and mir-548 cDNA synthesis according to sequence-specific primers (Table 1). Reference gene validation analysis To validate housekeeping genes (HKGs) and to choose the most stable and reliable ones, nine of the most fre- quently used HKGs as internal control in RT-qPCR including SDHA, TBP, RPS13, UBC, ACTB, HSP- 90AB1, PGM1, HPRT1, GAPDH named as 1, 2, 3, 4, 5, 6, 7, 8, and 9 respectively, were studied by considering their functional characteristics as well. A total number of six prostate tissue samples—three prostate carcino- mas and three BPH—were included in this study. The qPCR of all the samples was carried out in triplicates, in a total volume of 20 µL containing 1X SYBR®Pre- mix Ex Taq™II(TliRNaseH Plus) (TaKaRa), 5рM of each sense and anti-sense primer (Table 2), plus 1µL of cDNA template. PCR reaction was performed on the Rotor-Gene Q 5plex HRM System (Qiagene) under 30 sec enzyme activation at 95ºC, followed by 40 cycles of The association of miR-let 7b and miR-548 with PTEN in prostate cancer-Saffari et al. Table 1. Oligonucleotide sequences were used to cDNA synthesis and amplification of miRNAs. Oligonucleotide name Sequence RT6-miRlet-7b TGTCAGGCAACCGTATTCACCGTGAGTGGTAACCAC RT6-miR-548 TGTCAGGCAACCGTATTCACCGTGAGTGGTGCAAAA short- miRlet-7b-rev CGTCAGATGTCCGAGTAGAGGGGGAACGGCGTGAGGTAGTAGGTTGT short- miR-548-rev CGTCAGATGTCCGAGTAGAGGGGGAACGGCGTCAAAACTGGCAATTAC MP-fw TGTCAGGCAACCGTATTCACC MP-rev CGTCAGATGTCCGAGTAGAGG Gene symbol Primer sequence (5´→3´) Amplicon length (bp) SDHA F:GCAAACAGGAACCCGAGG 202 R: CAGCTTGGTAACACATGC TBP F:TGAATAGTGAGACGAGTTCC 140 R: TAGGGATTCCGGGAGTCAT UBC F: GCGGTGAACGCCGATGATTAT 125 R: GATCTGCATTGTCAAGTGACG HPRT1 F: CCTGGCGTCGTGATTAGTGAT 131 R: AGACGTTCAGTCCTGTCCATTA RPS13 F: AAGTACGTTTTGTGACAGGCA 187 R: CGGTGAATCCGGCTCTCTATTAG HSP90AB1 F: TCTGGGTATCGGAAAGCAAGCC 80 R: GTGCACTTCCTCAGGCATCTTG PGM1 F: AGCATTCCGTATTTCCAGCAG 120 R: GCCAGTTGGGGTCTCATACAAA ACTB F: AGCCTCGCCTTTGCGGA 174 R: CTGGTGCCTGGGACG GAPDH F: GAAGGTGAAGGTCGGAGTCA 109 R: ATTGAAGGGGTCATTGATGG PTEN F: GATGATGTTTGAAACTATTCCAATG 73 R: CTTTAGCTGGCAGACCACAA Table 2. Gene symbol, primer sequence and amplicon length of selected candidate references genes 95ºC for 5 sec, 58ºC for 15 sec, and 72ºC for 20 sec. We used geNorm (Vandesompele et al., 2002), NormFinder (Andersen et al., 2004), and BestKeeper (Pfaffl et al., 2004) statistical algorithms to evaluate the stability of each candidate HKG. The cycle threshold (Ct) average values of each sample’s triplicates were inputted direct- ly into BestKeeper software. For NormFinder, the aver- age Ct of each sample was transformed to the relative quantities linear row data, using the Q = 2-Ct Equation (Livak and Schmittgen, 2001), while the normalized Ct values calculated via the Q = E (minCt-sampleCt) Equation (Q = normalized Ct value for a given gene in the current specimen, E = PCR amplification effi- ciency (ranging from 1 to 2 with 100% = 2), minCt = minimum Ct value for the gene among all specimens and sampleCt = the Ct value of the gene for the current specimen) were used as the input data for the geNorm program. Quantitative Real-Time PCR The quantitative assay of mature miRNAs was per- formed by SYBR Premix Ex Taq II (Tli RNaseH Plus) (Takara, Japan) by using the miR-Q method and done in the Rotor-Gene Q 5plex HRM System (Qiagene). Addi- tionally, the expression level of PTEN was determined by using specific primers, as shown in Table 3. The reaction mixtures were incubated at 95°C for 30 Sec, followed by 40 cycles at 95°C for 5 Sec, and at 60°C for 30 Sec. The expression of miRNA from each sample was normalized by using the 2−ΔΔCT method relative to 5S rRNA. ΔΔCt was then computed by subtracting the ΔCt of normal tissue from the ΔCt of prostate can- cer. The change in gene expression was calculated by using Equation 2−ΔΔCt 12. Statistical analysis Data were presented as means ± SEM and evaluated by the t-test, one way or two way analysis of variance (ANOVA) followed by the Tukey test (SPSS 24 and GraphPad prism 7.0 Software Inc., La Jolla, CA, USA). A P-value <0.05 was considered to be statistically sig- nificant. Each point or column represents the mean ± SEM (n = 4–5) (P < 0.05). RESULTS Sample collection All the samples were divided into four groups: Gleason score >7 (10 samples), Gleason score ≤ 7 (36 samples), BPH (7 samples) and non-cancerous (40 samples). The characteristics of the patients are listed in Table 3. mir-let7b and mir-548 have predictive potential binding sites in the 3’UTR of human PTEN According to bioinformatics tools (such as DIANA tools and TargetScan) and analysis, we found that two putative binding sites of mir-let7b and mir-548 are ex- ited in the 3’UTR of human PTEN target gene (Figure 1). cDNA synthesis for miR-548 and let-7b The mir-Q method as described by Sharbati-Tehrani Table 3. Clinical Characteristics of Patients Group 1 Group 2 Group 3 Group 4 Gleason Score G > 7 G ≤ 7 BPH Non-cancer sample 10 36 7 40 Age(min-max) 56-70 52-81 47-83 62-85 median 64.6 65.4 65.8 71 mean 63 66.5 65 73.5 SD 5.37 6.7 14.8 8.7 Figure 1. PTEN has two predictive banding sites for miR-548 and miR-let7b. A) Sequences of miR-548 and its putative binding sites in 3’ÚTR of PTEN. B) Sequences of miR-let7b and its putative binding sites in 3’ÚTR of PTEN. Figure 2. Schematic picture of mir-Q design. First, cDNA is syn- thesized by a miRNA-specific oligonucleotide that has 5' overhang (RT6-miR-x) and six complementary bases (red). Then, a single strand cDNA is converted to a double strand by a specific oligo- nucleotide with 5' overhang (short-miR-x-rev). Finally, amplifica- tion is performed by using two terminal universal primers (MP-fw &MP-rev) (13). The association of miR-let 7b and miR-548 with PTEN in prostate cancer-Saffari et al. Urological Oncology 269 Vol 16 No 03 May-June 2019 270 was used for miR-let7b and mir-548 cDNA synthesis according to the sequence-specific adaptor and primers (Table 1 and Figure 2). This method is based on the SYBR green assay. Expression stability of candidate HKGs Based on the M-value calculated by geNorm, all the studied HKGs revealed values lower than the cutoff value of 1.5, suggesting that all of them could be relia- bly used as the reference gene in the qPCR analysis of prostate tissues (Figure 3). The stability ranking of the nine studied HKGs from the most stable to the least sta- ble based on geNorm M-value were 5, 6, 8, 1, 2, 9, 4, 3, and 7, respectively (Figure 3). The normalization fac- tor calculated via pairwise variation values between two sequential normalization (V (n/n+1)) by taking 0.15 as a cut-off value, we suggested using two genes data for more reliable qPCR normalization (Figure 4). Accord- ing to NormFinder stability values, the HKGs’ ranking of stability from the most stable expressed to the least stable were 5, 8 4, 3, and 7, respectively (Figure 3). 4 and 9 also exhibited the best combination of two genes across all the samples, with a stability value of 0.003, suggesting more stability. Considering Pearson correla- tions, reported as the BestKeeper correlation coefficient by BestKeeper algorithm, stability ranking order of studied genes were quite in concordance with those re- sulted, using geNorm and NormFinder, by 5 as the most stable followed by 8, 6, 1, 2, 9, 3, 4, and 7 respectively (Figure 3). Finally, the expression of ACTB was used to normalize the qPCR reactions, as it was indicated to be the most stable HKG among the studied candidate HKGs by BestKeeper, geNorm, and NormFinder. Down-regulation of let-7b expression correlated with increasing Gleason scores Following qRT-PCR analyses, it was revealed that miR-let7b was significantly decreased in the Gleason>7 group versus the non-cancerous group. Although the expression of miR-let7b reduced in Gleason ≤7 pa- tients, the data was not statistically significant. (*p < 0.05) (Figure 5). Over-expression of mir-548 in prostate cancer tis- sues correlated with increasing Gleason scores The expression levels of mir-548c in all the four groups were performed quantitatively by qRT-PCR. As shown in Figure 6, the amount of mir-548 expression level in the cancerous sample increased in high grade of pros- tate cancer in comparison with BPH and normal tissues as non-cancerous tissues (*P < 0.05). DISCUSSION The dysregulation of various miRNAs expressions are seen in prostate cancer patients, and therefore, deter- mining the most important miRNAs and their associat- ed pathways is very important. In this study, we decided to evaluate the expression level of mir-548c-3p in can- Figure 3. Candidate housekeeping genes’ stability results. A) The geNorm stability results. The calculated M-value (y-axis) is plotted on the y-axis, with lower M-values corresponding to a more stably expressed gene. B) The NormFinder stability results. The calculat- ed NormFinder stability values are plotted on the y-axis, with low- er stability values corresponding to more stably expressed genes. C) The BestKeeper stability results. The calculated BestKeeper correlation coefficient is plotted on the y-axis, with higher corre- lation coefficient corresponding to a more stably expressed gene. Figure 4. Determination of the optimal number of control genes required for normalization based on the pairwise variation value (Vn/n+1), which is calculated between two sequential normaliza- tion factors. The optimal number of reference genes was calculated as 2. Figure 5. The qRT-PCR analysis of miR-let7b expression in pros- tate cancer tissues and their matched adjacent non-cancerous tis- sues. Data reveal that it is down regulated in both cancerous sam- ples (Gleason scores >7 and 7≤) about more than 45% (> 45% reductions, *p < 0.05). The association of miR-let 7b and miR-548 with PTEN in prostate cancer-Saffari et al. cer tissue samples. Previous studies have demonstrat- ed that miRNAs play several key roles in a number of cellular pathways and biological processes such as dif- ferentiation, apoptosis, cell cycle regulation, migration and metastasis13,14. PI3K/AKT signaling pathway has a lipid kinase fam- ily and according to their substrate and sequence ho- mology, divided into three classes. Class-1 pertains to heterodimers and includes two subunits: catalytic and regulatory. PIP2 is a substrate of class I PI3K and con- verts to PIP3 as a second messenger. Then it activates downstream cascades that lead to cell growth and pro- liferation15. PTEN is an antagonist of the PI3K signaling function that leads to PIP3 accumulation in cells and inhibits the activation of its downstream signals. Furthermore, PTEN is a tumor suppressor that dephosphorylates PIP3and reverses the activity of PI3K/AKT signaling pathway. Therefore, PTEN inhibits cell growth and pro- liferation. PTEN mutation frequencies that affect both alleles and mono allelic loss of PTEN function have been shown in different cancers such as endometrial, glioblastoma, leukemia, prostate, and breast cancers. Epigenetics phenomena including DNA methylation and microRNA decrease PTEN expression 16-18. Tran- scriptional silencing can describe the role of PTEN hap- loinsufficiency, although the loss of heterozygosity of PTEN is more seen in sporadic tumors and the severity is negatively correlated to the tumor phenotype 19. In addition, the alteration of PTEN expression can influ- ence prognosis and response to treatment; PTEN nega- tive tumors have shown poor response to chemotherapy drugs such as trastuzumab or cetoximab20. Inositol polyphosphate 4-phosphatase type II (INPP4B) is another gene that acts either as a tumor suppressor or an oncogene. The negative regulation of PI3K/AKT signaling pathway by INPP4B as a tumor suppressor has been seen in various cancers, although it has been demonstrated that INPP4B expression increases in colon cancer and stimulates cell growth by the down regulation of PTEN21. In addition, overexpression of INPP4B causes the activation of PI3K/AKT pathway by the upregulation of GSK322. As a tumor suppressor, INPP4B, similar to PTEN, converts PIP2 to PIP3, which needs activation of the PI3K/AKT signaling pathway23. In breast or prostate cancer, the loss of INPP4B function is associated with poor prognosis. Accordingly, the overexpression of IN- PP4B may diminish cell proliferation24. Angiogenesis, migration and invasion are inhibited by the overexpres- sion of INPP4B in DU-145 and PC-3 prostate cancer cell lines25,26. Cellular homeostasis needs to be balanced between pro- tein phosphorylation and dephosphorylation. PHLPP, as a tumor suppressor, is a protein phosphatase that leads to loss of function of PHLPP, and it has been shown to be same as that of PTEN in various cancers. Hydrophobic motifs of PKC and AKT are PHLPP tar- gets and are dephosphorylated by it. Evidence suggests that co-deletion of PHLPP and PTEN may cause met- astatic progression27-29. Therefore, according to pre- vious studies, PTEN plays a key role in the regulation of PI3K/AKT signaling pathway and the loss of PTEN function leads to malignancies. Our study used two databases, TargetScan and Diana tools, for determining the miRNAs that have putative binding sites in 3’UTR of PTEN gene, which frequently alter in various cancers such as prostate cancer. Accord- ing to this intent, miR-let7b and miR-548 were found to have two different potential binding sites in the 3’UTR of PTEN. As mentioned earlier, previous studies have shown that PTEN, as an important tumor suppressor gene, is a phosphatase family member that regulates PI3K and AKT. RNA-induced transcriptional silencing by microRNA is one the mechanisms for the down-reg- ulation of PTEN expression. Previous studies have shown that miR-let-7b acts as a tumor suppressor mir and the expression level of miR-let-7b is downregulated in many human cancers such as prostate cancer30,31. Of course, our data showed that the miR-let7b expres- sion level, as a tumor suppressor miRNA, is downreg- ulated in prostate cancer, and therefore, it seems that there is no correlation between the expression levels of PTEN and miR-let7b. Additionally, we investigated the over expression of miR-548 expression level in prostate tumor tissues as compared to normal tissues adjacent. CONCLUSIONS This study showed that there is a difference in the ex- pression of miR-548 in tumor and normal tissues and over expression of miR-548 is seen in prostate tumor tissues. We suggest that when miR-548c-3p increases in prostate cancer, it may repress the level of PTEN expression. Additionally, previous studies have report- ed that the expression levels of PTEN, INPP4B and PHLPP decrease in prostate cancer and this is why they can be used as potential targets for cancer treatment. ACKNOWLEDGMENTS We acknowledge the support of the Urogenital Stem Cell Research Center (UGSCRC), Shahid Beheshti University of Medical Sciences. Assistance by Dr. Ha- mid Ghaedi is gratefully acknowledged. Figure 6. The expression levels of miR-548 in prostate cancer tissues and non-cancerous tissues. The qRT-PCR analysis of miR- 548c expression in prostate cancer tissues (Gleason scores < 7 and Gleason scores ≥7) and their matched adjacent non-cancerous tissues. Data reveal up to more than 2-fold change in high grade prostate cancer samples compare to BPH and non-cancerous sam- ples. The values represent the means and the error bars represent the SEM (*p < 0.05). The association of miR-let 7b and miR-548 with PTEN in prostate cancer-Saffari et al. Urological Oncology 271 Vol 16 No 03 May-June 2019 272 CONFLICT OF INTEREST The authors declare no conflict of interest. REFERENCES 1. Alegria-Torres JA, Baccarelli A, Bollati V. Epigenetics and lifestyle. Epigenomics. 2011;3:267-77. 2. Attard G, Clark J, Ambroisine L, et al. Duplication of the fusion of TMPRSS2 to ERG sequences identifies fatal human prostate cancer. Oncogene. 2008;27:253-63. 3. Koochekpour S. Genetic and epigenetic changes in human prostate cancer. Iran Red Crescent Med J. 2011;13:80-98. 4. Taylor BS, Schultz N, Hieronymus H, et al. Integrative genomic profiling of human prostate cancer. Cancer Cell. 2010;18:11-22. 5. Kim WT, Kim WJ. MicroRNAs in prostate cancer. 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