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. 2015 May 12;9:89–101. doi: 10.4137/BBI.S21742

Computational and in vitro Investigation of miRNA-Gene Regulations in Retinoblastoma Pathogenesis: miRNA Mimics Strategy

Nalini Venkatesan 1,2, Perinkulam Ravi Deepa 2, Vikas Khetan 3, Subramanian Krishnakumar 1,✉
PMCID: PMC4429751  PMID: 25983556

Abstract

PURPOSE

Retinoblastoma (RB), a primary pediatric intraocular tumor, arises from primitive retinal layers. Several novel molecular strategies are being developed for the clinical management of RB. miRNAs are known to regulate cancer-relevant biological processes. Here, the role of selected miRNAs, namely, miR-532-5p and miR-486-3p, has been analyzed for potential therapeutic targeting in RB.

METHODS

A comprehensive bioinformatic analysis was performed to predict the posttranscriptional regulators (miRNAs) of the select panel of genes [Group 1: oncogenes (HMGA2, MYCN, SYK, FASN); Group 2: cancer stem cell markers (TACSTD, ABCG2, CD133, CD44, CD24) and Group 3: cell cycle regulatory proteins (p53, MDM2)] using Microcosm, DIANALAB, miRBase v 18, and REFSEQ database, and RNA hybrid. The expressions of five miRNAs, namely, miR-146b-5p, miR-532-5p, miR-142-5p, miR-328, and miR-486-3p, were analyzed by qRT–PCR on primary RB tumor samples (n = 30; including 17 invasive RB tumors and 13 noninvasive RB tumors). Detailed complementary alignment between 5’ seed sequence of differentially expressed miRNAs and the sequence of target genes was determined. Based on minimum energy level and piCTAR scores, the gene targets were selected. Functional roles of these miRNA clusters were studied by using mimics in cultured RB (Y79, Weri Rb-1) cells in vitro. The gene targets (SYK and FASN) of the studied miRNAs were confirmed by qRT-PCR and western blot analysis. Cell proliferation and apoptotic studies were performed.

RESULTS

Nearly 1948 miRNAs were identified in the in silico analysis, From this list, only 9 upregulated miRNAs (miR-146b-5p, miR-305, miR-663b, miR-299, miR-532-5p, miR-892b, miR-501, miR-142-5p, and miR-513b) and 10 downregulated miRNAs (miR-1254, miR-328, miR-133a, miR-1287, miR-1299, miR-375, miR-486-3p, miR-720, miR-98, and miR-122*) were found to be common with the RB serum miRNA profile. Downregulation of five miRNAs (miR-146b-5p, miR-532-5p, miR-142-5p, miR-328, and miR-486-3p) was confirmed experimentally. Predicted common oncogene targets (SYK and FASN) of miR-486-3p and miR-532-5p were evaluated for their mRNA and protein expression in these miRNA mimic-treated RB cells. Experimental overexpression of these miRNAs mediated apoptotic cell death without significantly altering the cell cycle in RB cells.

CONCLUSION

Key miRNAs in RB pathogenesis were identified by an in silico approach. Downregulation of miR-486-3p and miR-532-5p in primary retinoblastoma tissues implicates their role in tumorigenesis. Prognostic and therapeutic potential of these miRNA was established by the miRNA mimic strategy.

Keywords: bio-informatics analysis, miRNA-mRNA, mimics, retinoblastoma

Introduction

MicroRNAs (miRNAs), being small (∼18–22 nucleotides), endogenous, noncoding RNAs, are involved in various biological roles by negatively regulating mRNA expression at both the posttranscriptional and posttranslational levels.1–3 Further, the gene expressions are suppressed by the interaction with their target messenger RNAs (mRNAs), either by blocking the translation process or by initiating the cleavage. Thus, these small regulators have vital roles in numerous biological processes, such as cell differentiation and apoptosis4 and also in pathological processes including some of the cancers.5–7 The abnormal expression of miRNAs may contribute to either tumor progression (oncomirs) or tumor regression (tumor suppressor) through miRNA–mRNA interactions (MMIs).8 So determining the expression and the function of miRNAs in cancers would help to understand their pathogenesis and disease management.

In addition to the transcription factors (coexpressed genes), the dysregulated miRNA–mRNA pairs play a crucial role in cancer formation. To this end, a number of predictive tools, namely, TargetScan,9,10 PicTar,11 miRanda,12,13 and PITA,14 are used to identify the MMIs based on the seed complementarity between miRNAs and the 3′UTRs of specific mRNAs. In addition, these tools also indicate the details of sequence conservation of adjacent bases together with thermodynamic properties of MMIs.15 However, there exists a high false discovery rate in determining the miRNA/target mRNA with these tools. This, in turn, underscores the requirement of experimental validation tools including quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blot analyses to indicate the functional miRNA and MMIs.16

In the present study, using a simple bioinformatics approach, we have demonstrated two key miRNAs (miR-486-3p and miR-532-5p) regulating a panel of genes reported earlier in RB tumorigenesis.17–25 In this approach, we have considered three groups of genes, namely, Group 1: oncogenes that include high-mobility group-A2 (HMGA2),24 N-myc proto-oncogene protein (MYCN),19 spleen tyrosine kinase (SYK),25 fatty acid synthase (FASN)23; Group 2: genes involved in cancer cell stemness, which include epithelial cell adhesion molecule (TACSTD1),21 ATP-binding cassette sub-family G member 2 (ABCCG2),22 cluster of differentiation 24 (CD24),20 CD133, and CD4417; and Group 3: cell cycle regulatory genes, which includes TP53 and MDM2 (mouse double minute 2 homolog).18 An in silico approach using the predictive tools including Microcosm, DIANALAB, miRBase v18, REFSEQ database, and RNA Hybrid was used to determine MMIs. Further, the identified miRNAs’ role in RB tumorigenesis has been addressed by in vitro experimental validations using RB cell lines (Y79 and Weri Rb1).

Material and Methods

In silico analysis to predict miRNAs regulating a panel of genes reported in RB

A comprehensive bioinformatic analysis was carried out to find the list of miRNAs that could target and are likely to be involved in posttranslational regulation of widely reported genes in RB progression. The select panel of genes were divided into three groups based on the functions, namely, Group 1: oncogenes (HMGA2, MYCN, SYK, FASN); Group 2: cancer stem cell markers (TACSTD1, ABCG2, CD133, CD44, CD24); and Group 3: cell cycle regulatory proteins (p53 and MDM2). The known, predicted, and validated miRNAs that could target any of these groups of genes in Groups 1, 2, and 3 were obtained from the following databases:

  1. Microcosm (http://www.ebi.ac.uk/enright-srv/microcosm/htdocs/targets/v5/)

  2. DIANALAB (http://diana.cslab.ece.ntua.gr/DianaTools New/index.php?r=tarbase)

  3. miRBase v18 (http://www.mirbase.org/)

  4. REFSEQ database (www.ncbi.nlm.nih.gov/RefSeq/)

  5. RNA Hybrid.

miRNAs targeting the selected genes were considered based on their MFE (minimal free energy of ≤−30 and a P-value of ≤0.05). Further, using the miRanda algorithm, the detailed complementary alignment between 5′ seed sequence of differentially expressed miRNAs and the sequence of target genes were determined.

Some of the other genes regulated by these two miRNAs (miR-486-3p and miR-532-5p) were predicted using the online tools Target scan (http://www.targetscan.org version 5.2), pic-TAR (http://pictar.mdc-berlin.de), and microcosm (http://www.ebi.ac.uk/enright-srv/microcosm/htdocs/targets/v5/).

Primary RB tumor tissues

This study was reviewed and approved by the institutional ethics committee of Vision Research Foundation, Sankara Nethralaya (Ethics number: 249b-2011-P). The study was conducted in accordance with the principles of the Declaration of Helsinki.

RB primary tumor samples were collected from 30 enucleated eyeballs of RB patients as part of RB management during 2011–2012. The study included 15 male and 15 female patients with a median age of 2.5 years. Grading of the tumors was performed from the microscopic observations of hematoxylin and eosin (H&E)-stained RB sections by an ocular pathologist. Histopathological information, namely, tumor invasion of the choroid, optic nerve, or orbit (Table 4), was obtained from surgical pathology reports. Among the tumors analyzed, there were 17 invasive tumors and 13 noninvasive tumors, which included 8 differentiated and 22 undifferentiated tumors with high-risk histopathological features. Based on the clinical presentation of the patients, the tumors were classified as per the International Intraocular Retinoblastoma Classification (IIRC): there were 9 tumors in group E, 15 tumors in group D, and 6 tumors in group B.26 There were 8 invasive and 1 noninvasive tumors in group E, 5 invasive and 10 noninvasive in group D, and 4 invasive and 2 noninvasive in group B. Normal adult retinas collected from five cadaveric eyeballs (received at the C.U. Shah eye bank, Sankara Nethralaya, http://www.sankaranethralaya.org/eye-bank.html) during the year 2012 were included in the study.

Table 4.

miRNA expression to normal cadaveric donor retina of RB primary tumor tissues with the clinicopathological description.

RB TUMOR NUMBERS AGE (YRS)/SEX RB GROUP (IIRC) CLASSIFICATION CLINICO-PATHOLOGICAL DESCRIPTIONS miR-142 miR-146b miR-328 miR-486-3p miR-582-5p
RB1 3Y/F B OS:WD, NI −14.59 −8.11 −8.36 −14.85 −8.24
RB2 2Y/F D OS:PD, NI −14.03 −8.52 −6.38 −14.75 −5.65
RB3 8 mon/F D OD:PD, NI 4.51 7.51 5.39 3.16 −3.77
RB4 1Y/M D OD:WD, No CI, Post-lam inv 5.01 5.44 4.80 2.67 −5.18
RB5 8 mon/M B OS: WD, NI −5.56 −4.00 −5.31 −8.86 −0.96
RB6 2Y/F D OD: PD, NI −15.27 −13.14 −13.17 −14.18 −9.46
RB7 3Y/F D OD: WD focal RPE Inv, CI <3 mm 0.30 0.14 0.12 −0.24 0.09
RB8 3Y/M D OD: MD, focal RPE, minimal post-lam inv −0.17 −0.35 −0.39 −0.90 −0.58
RB9 7Y/F D OS: MD, NI 0.53 1.19 −0.42 0.17 0.22
RB10 2Y/F D OD: WD, RPE, CI <3 mm −1.19 −1.23 −1.21 −2.14 −0.83
RB11 2Y/M B OD: WD, NI −0.11 −0.19 −0.48 −0.83 −0.50
RB12 2Y/F D OS: PD, NI −0.64 −0.93 −1.34 −1.53 −1.38
RB13 2Y/M D OS: PD, NI −1.44 −1.46 −2.14 −1.93 −2.01
RB14 2Y/F E OS: MD, CI >3 mm, pre-lam inv −12.69 −8.82 −8.30 −13.41 −4.90
RB15 6Y/F E OD:WD, focal CI <3 mm, pre-lam inv −11.83 −8.17 −7.91 −10.97 −8.01
RB16 4Y/M E OS:PD, CI >3 mm, pre-lam, scleral inv −13.47 −7.36 −13.23 −13.10 −6.54
RB17 4Y/M E OD:PD, CI >3 mm, post-lam ON 2.69 5.51 2.61 0.21 −8.22
RB18 11Y/F D OS: PD, CI <3mm, −15.70 −13.32 −9.10 −15.81 −11.18
RB19 3Y/M D OS: PD, No CI post-lam ON −0.18 −0.34 −0.53 −1.00 −0.69
RB20 1Y/M E OS: MD, CI >3 mm, pre-lam 0.23 0.04 0.01 −0.51 −0.14
RB21 3Y/M E OS: PD, CI >3 mm, pre-lam and post-lam ON inv 0.02 −0.20 −0.30 −0.89 −0.51
RB22 9 mon/M E OS: MD, CI <3 mm, pre-lam −0.16 −0.86 −0.38 −1.40 −0.57
RB23 2Y/F E OD: MD, CI >3 mm 0.29 0.11 0.08 −0.44 −0.12
RB24 4Y/M E OS: PD, CI >3 mm, pre-lam and post-lam inv −0.49 −0.67 −0.71 −1.22 −0.90
RB25 4Y/F D OS: WD,CI <3 mm −0.57 −0.74 −0.90 −1.26 −0.69
RB26 4Y/F D OD: UD, CI >3 mm, pre-lam inv 0.06 −0.12 −0.85 −2.12 −0.53
RB27 1Y/F B OD: MD, CI <3 mm −1.78 −1.75 −1.96 −2.65 −1.97
RB28 2Y/M B OS: MD, No CI, pre-lam and post-lam inv −0.55 −0.53 −0.86 −1.43 −0.66
RB29 3Y/M B OS: MD,CI <3 mm, pre-lam inv 2.21 −0.83 1.47 0.02 −0.24
RB30 4Y/M D OD: MD, CI <3 mm, pre-lam inv 0.79 −1.21 0.62 −0.77 −1.05
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Abbreviations: M, Male; F, Female; OD, Right eye; OS, Left eye; RPE, Retinal Pigment epithelium; CI, Choroidal invasion; pre-lam, Pre-laminar; post-lam, Post-laminar; inv, Invasion; ON, optic nerve.

Cell lines

Human RB Cancer cell lines (Y79 and Weri Rb1; Riken cell bank, Japan) were used in this study. The RB cell lines were cultured with supplementation of 10% heat-inactivated fetal calf serum (Gibco-BRL), 0.1% ciprofloxacin, 2 mM L-glutamine, 1 mM sodium pyruvate, and 4.5% dextrose (Sigma Aldrich) in Roswell Park Memorial Institute 1640 medium (Gibco-BRL).

Treatment of miRNA mimics in RB cells

The description of miRNA mimics used in the study is given in Table 1. About 1 × 50,000 cells were plated per well (12-well plates) and allowed to grow for 24–36 hours (until they were 40%–60% confluent). They were transfected with 0.5 mL antibiotic-free media containing 50 pmol of specific miRNAs mimics plus the corresponding concentration of transfection reagent (Lipofectamine™ 2000) for 24, 48, and 72 hours. After incubation, the cells were harvested and processed for further analysis. The same protocol was applied using nontarget scrambled miRNA as transfected control.

Table 1.

Details of miRIDIAN microRNA mimics with the mature sequence and accession number.

S.NO miRIDIAN microRNA MIMICS, CAT. NO (DHARMACON, THERMO FISHER SCIENTIFIC-INDIA) MATURE SEQUENCE AND ACCESSION NUMBER
1. Mimic Negative control (Based on cel-miR-67, as they have minimal identity with miRNAs in humans. CN-001000-01-20 UCACAACCUCCUAGAAAGAGUAGA (MIMAT0000039)
2. Human hsa-miR-486-3p–Mimic, C-301211-01-0010 CGGGGCAGCUCAGUACAGGAU (MIMAT0004762)
3. Human hsa-miR-532-5p–Mimic, C-300867-01-0010 CAUGCCUUGAGUGUAGGACCGU (MIMAT0002888)
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miRNA/gene expression analysis by qRT-PCR in RB primary tumors and miRNA mimic-treated RB cells

Total RNA isolation from the RB primary tumor tissues (n = 30) was carried out as per manufacturer’s instructions by using the miRCURY RNA Isolation Kit (cat. number 300111, Exiqon). Polyadenalation and complementary strand synthesis of 100 ng of total RNA was carried out as per manufacturer’s instruction using the cDNA synthesis kit (cat. no. 203450, Exiqon). The presence of miRNAs in 5 ng of cDNA was determined using miRNA-specific primers and SYBR Green master mix in the primary RB tumors and in cell lines as per manufacture’s protocol. The LNA primers used in this study are tabulated in Table 2. Complementary strand synthesis for the gene expression studies was carried out using oligo dT as random primers and 1 μg of total RNA (Sensiscript II; cat. no. 205211, Qiagen). Gene expression levels of SYK and FASN in the transcribed cDNA was determined using syber green master mix (cat. no. 330500, Qiagen). The primers of SYK: FP: 5′GGAAGTGAAGTCACCGCTATG3′; RP: 3′GGGAGCGGTTAGTTCACCAC5′, and FASN: FP: 5′CG ACAGCACCAGCTTCGCCA3’; RP: 5′CACGCT-GGCCTGCAGCTTCT3′. The commercial software SDS ver.1.3; ABI was used to calculate ∆∆Ct.27 Relative expression values for genes/miRNA were normalized to GAPDH/RNU6B as endogenous control. The unit of fold change was expressed in log2 transformed ratios.

Table 2.

Details of miRIDIAN miRNA primers (LNA, Exiqon, USA).

S.NO PRODUCT NUMBER PRODUCT NAME, microRNA PRIMER SET. TARGET SEQUENCE TARGET SEQUENCE ACCESSION NUMBER
1. 202353 hsa-miR-486-3p CGGGGCAGCUCAGUACAGGAU MIMAT0004762
2. 202435 hsa-miR-532-5p CAUGCCUUGAGUGUAGGACCGU MIMAT0002888
3. 202074 hsa-miR-328 CUGGCCCUCUCUGCCCUUCCGU MIMAT0000752
4. 202274 hsa-miR-146b-5p UGAGAACUGAAUUCCAUAGGCU MIMAT0002809
5. 204722 hsa-miR-142-5p CAUAAAGUAGAAAGCACUACU MIMAT0000433
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Western blot analysis of SYK and FASN proteins in miRNA mimic-treated RB cells

The total protein cell lysate of miRNA mimics in RB cells was extracted using RIPA lysis buffer [50 mM Tris-HCl (pH 7.6), 5 mM EDTA, 150 mM sodium chloride, 0.1% phenylmethanesulfonyl fluoride (PMSF), and 250 μL of 1 mg/mL protease inhibitor cocktail] on ice. A total of 25 μg protein was resolved by using 10% SDS-PAGE (sodium dodecyl sulfate-polyacrylamide gel electrophoresis) for SYK protein and 8% SDS-PAGE for FASN protein expression. Following protein electrophoresis, the separated proteins were transferred onto nitrocellulose membranes at 100 V for one hour. After blocking the membrane with 5% skimmed milk for one hour, the blots were incubated with the specific primary antibody [SYK (cat. no. ab 57465, Abcam:) 1:1000; FASN (cat. no. 610962, BD Biosciences): 1:250] overnight at 4 °C followed by the corresponding horseradish peroxidase-conjugated secondary antibody (1:4000) and incubated for two hours. After intermittent washes with Tween Tris-buffered saline, the membranes were subjected to chemiluminescence detection (SuperSignal West Femto Maximum Sensitivity Substrate). Intensity of the bands was measured densitometrically (Quantity One, version 4.7 software using GS-800 calibrated densitometer, Bio-Rad) and normalized with the respective β-actin expression to derive the protein concentration in the individual samples. This relative band intensity quantification was done using Image J software.

Measurement of cell viability using MTT assay in miRNA mimic-treated RB cells

The cell viability in the mimic-transfected RB cells was analyzed by using 3-(4,5-dimethylthiazolyl) 2,5diphenyltetrazolium bromide (MTT) assay. About 5,000 cells/96 wells were transfected with 50 pmol of miRNA mimics and scramble mimics. Following 24, 48, and 72 hours of transfection, serum-free RPMI medium containing 10 μL of 5 mg/mL MTT was added and incubated at 37 °C in a CO2 incubator for four hours. The formed formazan crystals were dissolved in 100 μL dimethylsulfoxide (DMSO), and the absorbance was measured spectrophotometrically at 570 nm (Beckman Coulter); the background was subtracted at 650 nm. Assay was performed in triplicates with and without scramble miRNA as controls.

Measurement of apoptosis using annexin-V-FLUOS stain in miRNA mimic-treated RB cells

About 2 × 105 cells/12-well plate were transfected with 50 pmol miRNA mimics and scramble mimics and incubated at 37°C in a CO2 incubator for 48 hours. At the end of incubation, the cells were collected, washed, and processed for the apoptosis assay using the annexin-V-FLUOS apoptosis detection kit (cat. no. 556547, BD Pharminogen) as per the manufacturer’s instructions. The percentage of apoptotic cells in the experimental groups was determined by using a flow cytometer (FACS Calibur, Becton-Dickinson).

Measurement of change in cell cycle using propidium iodide stain in miRNA mimic-treated RB cells

In order to determine the effect of mimic treatment in RB cells, 50 pmol miRNA mimics and scramble mimics were transfected in 2 × 105 cells/12-well plate and incubated at 37 °C in a CO2 incubator for 48 hours. At the end of incubation, the cells were collected, washed twice with ice-cold 1 × PBS, fixed for 30 minutes with 70% cold ethanol twice, and then incubated at 37 °C for 2 hours in 1 × PBS buffer containing 100 μg/mL RNase A and 5 μg/mL propidium iodide. Following staining, the cells were washed and the percentage of cells at various cell cycle phases was determined using the flow cytometer.

Statistical analysis

One-way ANOVA, post hoc Dunnet T-test, independent t-test, and Mann–Whitney U-test were performed to compare the variables of in vitro experiments and of RB primary tumors. Paired Student’s t-test was used to compare the miRNA expressions in control and experimental groups of in vitro studies.

Results

Identification of miRNAs regulating the most candidate genes involved in RB tumorigenesis

From the comprehensive bioinformatics analysis, the number of miRNAs that are likely to be involved in posttranslational regulation of Group I genes (HMGA2, MYCN, SYK, FASN) were identified as 5004, Group II genes (TACSTD1, ABCG2, CD133, CD44, CD24) as 4804 miRNAs, and Group III genes (p53 and MDM2) as 7261 miRNAs. In order to remove redundancy, filtration of all the identified miRNAs was carried out, after which 1948 miRNAs were obtained. Further, in order to determine the miRNAs relevant to RB tumoriogenesis, the identified 1948 miRNAs were intersected with the miRNAs involved in RB tumoriogenesis reported earlier in serum samples.28 From this intersection, we observed only nine upregulated miRNAs, which include miR-146b-5p, miR-305, miR-663b, miR-299, miR-532-5p, miR-892b, miR-501, miR-142-5p, and miR-513b. In addition, we again observed only 10 downregulated miRNAs, which include miR-1254, miR-328, miR-133a, miR-1287, miR-1299, miR-375, miR-486-3p, miR-720, miR-98, and miR-122*.

Further, from this list of miRNAs, the highly regulated miRNAs are filtered based on their MFE (≤−30, P-value ≤0.05) and those reported in the Microcosm and DIANA LAB databases (Table 3). Based on these results, three miRNAs were selected, namely, miR-146b-5p, miR-532-5p, and miR-142-5p, from the upregulated miRNAs panel and two miRNAs, namely, miR-328 and miR-486-3p, from the down-regulated list for validation in RB primary tumor tissues.

Table 3.

miR-SVR scores and the position on the mRNA sequence for the selected five miRNAs and their posttranslational regulatory genes.

S.NO GENE miRNA SHOWING HITS ON THE GENE SVR SCORE POSITION ON mRNA SEQUENCE
1. FASN hsa-miR-532-5p −0.0013 137, 464
hsa-miR-146b-3p −0.0077 538
hsa-miR-328 −0.0004 498
hsa-miR-486-3p −0.0008,−0.046, −0.1287 1, 110, 393
2. HMGA2 Has-miR-142-3p −0.6633, 545, 1228, 1547, 2499
hsa-miR-328 −0.0281, −0.811, −0.5492−0.0130 2093
3. MYCN hsa-miR-532-3p −0.0006 239
4. SYK hsa-miR-532-5p −0.0080 1574
hsa-miR-146b-3p −0.0005 2594
hsa-miR-486-3p −0.0283 2421
5. ABCG2 hsa-miR-532-5p −0.1924, −0.0032 590, 659
hsa-miR-146b-5p −0.7574, −0.5036 910, 1819
hsa-miR-142-5p −0.5511, −0.5931 361, 897
hsa-miR-328 −0.0445 602
hsa-miR-486-5p −0.0083 1533
6. CD24 hsa-miR-532-5p −0.0076 711
hsa-miR-142-5p −0.0202 1677
hsa-miR-146b-5p −0.0027 543
hsa-miR-486-5p −0.0006,−0.0008 953, 1090
7. CD133 hsa-miR-532-3p −0.0024 365
has-miR-142-5p −0.0098 503
has-miR-146b-5p −0.0030,−0.008, −0.0109, −0.0249 −0.0017, 1355, 2166, 2433, 2800
hsa-miR-146b-3p −0.0010 975, 1621
has-miR-328 −0.1154 190
hsa-miR-532-5p −0.0035 1076
hsa-miR-142-3p −0.9794 272
has-miR-142-5p −0.8091 604
hsa-miR-486-5p −0.0224 392
9. P53 hsa-miR-532-3p −0.0687 235
has-miR-146b-5p −0.0017 88
hsa-miR-146b-3p −0.0016 176
10. Mdm2 hsa-miR-532-5p −0.0057, −0.0002, −0.0006 −0.0017, 555, 783, 1122
hsa-miR-142-5p −0.0014, −0.0011, −0.0023, −0.0003, 1707, 2868,
hsa-miR-146b-5p −0.0005 −0.0001,−0.0001, −0.0003, 3158, 4279, 5297, 4557
hsa-miR-486-5p −0.0002, −0.0000 553, 778, 1119, 1510, 5177
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miRNA expression in RB primary tumor tissues and in normal cadaveric adult donor retina

The miRNA expression analysis in RB primary tumor tissues (n = 30) by qRT-PCR revealed a median fold change of miR-486-3p (in the order of invasion = −1.26, no invasion = −1.07), miR-532-5p (in the order of invasion = −0.69, no invasion of = −1.00), miR-142 (in the order of invasion = −0.18, no invasion = −0.17), miR-146b (in the order of invasion = −0.73, no invasion = −0.87), and miR-328 (in the order of invasion = −0.70, no inva sion = −0.59). The miRNA expression of RB tumor tissues relative to normal cadaveric donor retina with the clinicopathological description is given in Table 4. The median fold change of all these five miRNAs in normal cadaveric adult donor retina is in the following order: miR-486-3p, −0.14; miR-532-5p, −0.01; miR-142, 0.24; miR-146b: 0.14, and miR-328, 0.19 (Table 5). Interestingly, we observed a downregulation of all the validated miRNAs relative to the normal donor retina. No significant association of the miRNA expression with that of normal retina was observed.

Table 5.

Fold change of select miRNAs (n = 5) in RB cell lines (Y79 and Weri Rb1), RB primary tumors (invasion/no invasion) and in normal cadaveric donor retinae.

miRNAs MEAN FOLD CHANGE IN log2 RATIO (SD) MEDIAN FOLD CHANGE IN log2 RATIO
Y79 Weri Rb 1 INVASION RB TUMORS
(n = 17)		 NO INVASION RB TUMORS
(n = 13)		 RETINA
(n = 5)
miR-486–3p −1.921 (0.5) −1.868 (0.2) −1.261 −1.079 0.01
miR-532–5p −1.765 (0.5) −1.775 (0.3) −0.694 −1.006 −0.19
miR-142–5p −0.985 (0.4) −0.870 (0.2) −0.182 −0.176 0.35
miR-146–5p −1.395 (0.5) −1.877 (0.2) −0.737 −0.877 0.27
miR-328 −2.090 (0.6) −1.922 (0.2) −0.705 −0.593 0.41
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miRNA expression in RB cell lines (Y79 and Weri Rb1)

The median fold change of all these five miRNAs in Y79 is in the order miR-486-3p, −1.92; miR-532-5p, −1.76; miR-142, −0.98; miR-146b, −1.39; and miR-328, −2.09 while in Weri Rb 1 it is in the order miR-486-3p, −1.86, miR-532-5p, −1.77; miR-142, −0.86, miR-146b, −1.87; and miR-328, −1.92. Taken together, the miRNA expressions in primary RB tumor tissues and in cell lines, the two miRNAs with high fold decrease, namely, miR-486-3p and miR-532-5p, were selected for the in vitro functional analysis using RB cell lines Y79 and Weri Rb1. Based on the miRSVR scores, the gene targets of these two miRNAs, namely, SYK (miR-532-5p: miRSVR score = −0.0080 and miR-486-3p: miRSVR score = −0.0283) and FASN (miR-532-5p: miR-SVR score = −0.0013 and miR-486-3p: miRSVR = −0.0008) were selected for further in vitro validations.

Functional analysis of the select miRNAs in RB cell lines

Since we observed downregulation of miR-486-3p and miR-532-5p, we carried out the addition of miRNA mimics to the RB cells, which would enable us to better understand the MMI. The nontargeting mimic was used as the scramble control in miRNA mimic experiments.

Gene expression in mimic-transfected RB cells

The RB cells were transfected with 50 pmol of mature miRNA sequences (mimics) miR-486-3p and miR-532-5p and the scramble negative control. After 48 hours of transfection, the levels of SYK and FASN mRNAs were analyzed in comparison with the scramble transfected control. The mean expression levels of SYK and FASN mRNA expression in mimic-transfected Y79 and Weri Rb1 cells at the end of 24, 48, and 72 hours of incubation are given in Table 6.

Table 6.

Fold decrease in SYK and FASN mRNA in the miRNA mimic-transfected RB cells.

TREATMENT WITH miRNA MIMICS Y79-SYK (SD) Y79-FASN (SD) Weri Rb1-SYK (SD) Weri Rb1-FASN (SD)
miR-486–3p-24 −2.2 (0.3) −1.8 (1.0) −3.4 (1.7) 0.8 (2.0)
miR-532–5p-24 −0.6 (0.3) −0.6 (0.2) 8.1 (0.1) 4.9 (0.1)
miR-486–3p-48 −2.2 (1.1) −2.6 (0.3) −3.4 (1.0) −0.3 (0.5)
miR-532–5p-48 −4.7 (2.1) −1.2 (0.4) −8.7 (1.0) −1.7 (2.2)
miR-486–3p-72 0.6 (0.1) 1.9 (0.2) 3.9 (0.8) 0.4 (1.6)
miR-532–5p-72 0.1 (0.1) 0.5 (0.2) 3.3 (1.3) −0.7 (1.1)
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These results indicate a significant decrease of SYK and FASN mRNAs by −2.2 and −2.6-fold change in miR-486-3p mimic-transfected Y79 cells at end of 48 hours of incubation. Similarly, a decrease of SYK and FASN mRNAs by −4.7- and −1.2-fold change in miR-532-5p mimic-transfected Y79 cells was seen at the end of 48 hours of incubation. In Weri Rb1, miR-486-3p mimic transfection resulted in the decrease of SYK and FASN mRNAs by −3.4- and −0.3-fold change at the end of 48 hours of incubation, while miR-532-5p mimic transfection resulted in the decrease of SYK and FASN mRNAs by −8.7- and −1.7-fold change at the end of 48 hours of incubation, respectively. In addition, these results indicate the better downregulation of the regulatory mRNAs (SYK and FASN) at the end of 48 hours of incubation compared to the other time points (24 and 72 hours). Thus, 50 pmol concentration of mimics and 48 hours of incubation were selected for the further experiments.

Change of SYK and FASN protein expression in miRNA-mimic transfected RB cells

The decrease in SYK and FASN mRNA in miR-486-3p and miR-532-5p mimic-transfected RB cells was confirmed with the protein expression using western blot analysis. We observed a decrease of ∼30% of SYK and ∼20% FASN proteins in miR-486-3p transfected Y79 cells and 30% of SYK and 20% FASN in miR-532-5p transfected Y79 cells compared to scramble transfected Y79 cells after 48 hours of incubation. Similarly, we observed a decrease of ∼35% of SYK and ∼25% of FASN protein in miR-486-3p transfected Weri Rb1 cells and ∼ 35% of SYK and ∼25% of FASN in miR-532-5p transfected Weri Rb1 cells compared to scramble transfected Weri Rb1 cells after 48 hours of incubation.

Decrease of cell viability in mimic-transfected RB cells

In Y79 cells, the treatment with miR-486-3p mimics resulted in a reduction of cell viability to 86.08%, 58.42%, and 66.86% at the end of 24, 48, and 72 hours of incubation, respectively. The treatment with miR-532-5p of Y79 cells resulted in the decrease of cell viability to ∼88.97%, 71.05%, and 77.8%, while the scramble transfected negative control showed a cell viability of 94.2%, 82.2%, and 80.84% at the end of 24, 48, and 72 hours of incubation, respectively, compared to untransfected cell control.

Similarly, in Weri Rb 1, the treatment of miR-486-3p mimics resulted in a reduction of cell viability to 90.41%, 66.41%, and 51.74% at the end of 24, 48, and 72 hours of incubation, respectively. The treatment with miR-532-5p of Weri Rb1 cells resulted in a decrease of cell viability to ∼87.63%, 72.47%, 56.39%, while the scramble transfected negative control showed a cell viability of 96.51%, 86.51%, and 89.78% at the end of 24, 48, and 72 hours of incubation, respectively, compared to untransfected control cells.

Increase of apoptosis in mimic-transfected RB cells

In Y79 cells, the annexin assay revealed that treatment with miR-486-3p and miR-532-5p mimics resulted in the induction of late apoptotic cells to about 30.9% and 30.6%, while the scramble mimic treatment resulted in 2.62% compared to the untransfected cell control, at the end of 48 hours of incubation. Similarly, treatment with miR-486-3p and miR-532-5p mimics in Weri Rb1 cells resulted in the induction of late apop-totic cells to about 19.6% and 21.8%, while the scramble mimic treatment resulted in 13.5% compared to the untransfected control cells at the end of 48 hours of incubation. A significant change (P-value <0.05) in the percentage of cell viability in miR-486-3p and miR-532-5p-mimic treated Y79 cells was observed.

Alteration of cell cycle phases in the mimic-transfected RB cells

In Y79 cells, treatment with miR-486-3p and miR-532-5p mimics resulted in altered percentage of G2/S phase cells to ∼48.7% and 48.7%, respectively, while treatment with the scramble mimics resulted in 30.5% at the end of 48 hours of incubation. Similarly, treatment with miR-486-3p and miR-532-5p mimics of Weri Rb1 resulted in the alteration of G2/S phase cells to ∼53.1% and 54.9%, respectively, while treatment with the scramble mimics resulted in 47.9% at the end of 48 hours of incubation. Though a significant change of G2 /S phase cell percentage was observed in Y79 cells, no significant change was observed in Weri Rb1 cells.

Discussion

The standard methodology to perform functional analysis of MMIs would require array-based mRNA and miRNA global expressions or RNA sequencing inputs. These approaches would require large investment, including a huge quantity of purified RNA and the economic resources to perform two different arrays, which in turn limits number of paired miRNA–mRNA datasets in the available public repositories.29 Thus data mining from these repositories would provide immediate information about the paired miRNA–mRNA networks and their gene target regulations.

In this study, we used an in silico approach to identify miRNAs regulating the panel of genes [categorized as Group I genes (HMGA2, MYCN, SYK, FASN), Group II genes (TACSTD1, ABCG2, CD133, CD44, CD24), and Group III genes (p53 and MDM2) involved in RB tumoriogenesis; Figure 1]. With the removal of redundancy, 1948 common miRNAs were obtained from this miRNA approach. Further, the comparison of these miRNAs with the reported RB serum miRNA expression profile28 revealed 9 upregulated miRNAs (miR-146b-5p, miR-305, miR-663b, miR-299, miR-532-5p, miR-892b, miR-501, miR-142-5p, and miR-513b) and 10 downregulated miRNAs (miR-1254, miR-328, miR-133a, miR-1287, miR-1299, miR-375, miR-486-3p, miR-720, miR-720, miR-98, and miR-122*). However, in order to rule out the false discovery rate of the current study, five miRNAs (upregulated panel, n = 3: miR-146b-5p, miR-532-5p, and miR-142-5p and downregulated panel, n = 2: miR-328 and miR-486-3p) were selected for in vitro experimental validation using qRT-PCR.

Figure 1.

Figure 1

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Schematic representation of the steps followed in the identification of miRNAs regulating the panel of candidate genes involved in RB progression. (A–C) Classification of a panel of genes regulating the RB tumoriogenesis as Group 1: oncogenes (HMGA2, MYCN, SYK, FASN); Group 2: cancers stem cell markers (TACSTD1, ABCG2, CD133, CD44, CD24), and Group 3: cell cycle regulatory proteins (p53 and MDM2). (D) Identification of the miRNA–mRNA targets using Microcosm, DIANALAB, miRBase v18, REFSEQ database, and RNA Hybrid. (E) Reducing redundancy and filtering of 1948 miRNAs. (F) Intersection with miRNA profiling (serum samples). (G) Derived upregulated (n = 9) and downregulated (n = 10) miRNAs. (H) Filtering based on their MFE (minimal free energy of ≤−30 and P-value of ≤0.05) reported in MICROCOSM and DIANA LAB databases. (I) miRNA expression in RB tissues (n = 30)/normal retina (n = 5) using qRT-PCR. (J) functional evaluation of two miRNAs using mimics (RB cell lines).

However, the miRNA expression analysis using qRT-PCR revealed a higher downregulation of two miRNAs, namely miR-486-3p (median fold change in the order of invasion = −1.26, no invasion = −1.07) and miR-532-5p (median fold change in the order of invasion = −0.69, no invasion = −1.00) compared to the normal cadaveric donor retina. The regulatory genes of these two key miRNAs (miR-486-3p and miR-532-5p) are SYK and FASN. Filtration of gene targets of these miRNAs was based on their MFE of ≤−30 and P-value of ≤0.05 and those reported in Microcosm and DIANA LAB databases (Table 3). Similarly, we observed downregulation of these miRNAs in two of the RB cell lines, namely Y79 and Weri Rb1 (Tables 4 and 5; Fig. 2B). Downregulated miR-486-3p has been known to contribute to aggressive lung cancer with lymphnode metastasis30–32 and also reported to be a biomarker in the primary non-small-cell lung carcinoma (NSCLC) tissues and plasma32 and gastric cancer progression.33 Further, lowered miR-486-3p and miR-532-5p have been reported in renal cell carcinoma.34 These reports in other cancers together corroborate the current results of lowered miR-486-3p and miR-532-5p expression in RB. However, interestingly, higher expression of miR-532-5p is reported in the RB serum samples (n = 14). The small sample size could be one of the factors responsible for the variation among these results.28

Figure 2.

Figure 2

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Graphical representation of select miRNA expression in (A) RB primary tumors (invasion, n = 17 and no invasion n = 13) and in normal cadaveric adult retinae (n = 5) and (B) RB cell lines (Y79 and Weri Rb1), Fold change of the miRNAs is in the order of miR-486-3p (blue bar), miR-532-5p (red bar), miR-142-5p (green bar), miR-146b-5p (purple bar), and miR-328 (yellow bar). Error bars represent the standard deviation of three experiments.

In order to study the functional role of these two miRNAs in RB progression and their regulation of SYK and FASN as gene targets, in vitro experiments using miRNA mimics were performed. Using the classical approach, mRNA and protein levels of the target genes were quantified in RB cells treated with miRNA mimics (miR-486-3p and miR-532-5p) in comparison with scramble mimics.16,35 From these experiments, we observed an inverse correlation of SYK and FASN mRNA expression in RB cells transfected with the mimics, especially at the end of 48 hours of incubation (Table 5, Fig. 3). The reduced SYK and FASN protein expression in mimic-transfected RB cells compared to the scrambled control corroborates the mRNA downregulation of mimic-transfected RB cells (Fig. 4). Earlier reports have shown the significant role of these two genes in other cancers such as breast cancer36 and, especially, RB.23,25,37 Zhang et al have reported the upregulation of the protooncogene SYK with its importance in RB cell survival and indicated SYK as a promising therapeutic target.25 Further, FASN was reported as a potential therapeutic target in RB management with its marked overexpression in invasive tumors.23

Figure 3.

Figure 3

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Graphical representation of SYK and FASN mRNA in mimic-transfected RB cells. The bar graph represents relative expression of SYK (blue) and FASN (red) in 50 pmol of miR-486-3p and miR-532-5p mimics transfection. Fold change in transfected RB cells are derived relative to scramble transfected control at the end of 24, 48, and 72 hours of incubation. Error bars represent the standard deviation of three experiments,

Notes: **P-value <0.01. A: Y79 and B: Weri Rb1.

Figure 4.

Figure 4

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Protein expression in miRNA mimic-transfected RB cells. (A) Western blot analysis of FASN and SYK proteins in miRNA mimic-transfected RB cells. Lanes 1–3: Scramble control, miR-486-3p and miR-532-5p mimic-transfected Y79 cells. Lanes 4–6: Scramble control, miR-486-3p and miR-532-5p mimic-transfected Weri Rb1 cells. (B and C) Bar graph representing the percentage of proteins FASN and SYK in miR-486-3p and miR-532-5p mimic-transfected RB cells (Y79 and Weri Rb 1). Error bars represent the standard deviation of two experiments.

Further, the chemical inhibitors of the FASN enzyme in RB cells have resulted in apoptosis in RB cells.38,39 These earlier studies corroborate our current results of reduced cell proliferation and increased apoptosis due to lowered SYK and FASN expression in miRNA mimic-transfected RB cells relative to scramble treated control cells (Figs. 5 and 6). We also observed mild morphological changes such as a decrease in RB cell size (image not shown) in RB cells treated with miRNA mimics miR-486-3p and miR-532-5p compared to the scramble treated control cells. These morphological changes in cells may be attributed to the metabolic changes, induction of apoptosis, cellular senescence, and cellular degeneration due to increase of cellular miRNAs (miR-486-3p and miR-532-5p). Taken together, the current results of SYK and FASN downregulation in mimic-transfected RB cells indicate the role of these oncogenes in RB cell growth.

Figure 5.

Figure 5

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Graphical representation of cell viability assay using MTT. Percentage of cell viability in 50 pmol of miR-486-3p and miR-532-5p mimic-transfected RB cells (A) Y79 and (B) Weri Rb1 at the end of 24, 48, and 72 hours of incubation. The four lines indicate in the order of untransfected control (blue), scramble control (red), miR-486-3p (green), and miR-532-5p (purple). Error bars represent the standard deviation of three experiments.

Notes: **P-value <0.01; *P-value <0.05.

Figure 6.

Figure 6

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Scatter plot of apoptotic cells in scramble control and mimics transfected RB cells. (A) Y79, (B) Weri Rb1. Overlay graph of scramble control and mimic-transfected RB cells (C) Y79, (D) Weri Rb1. In the overlay graph, black line indicates unstained cells, green line indicates untransfected cells, pink line indicates miR-486-3p-transfected cells, and blue line indicates miR-532-5p-transfected cells.

Using the gene target prediction tools Target scan, picTAR, and Microcosm, the genes involved in cell migratory function contributing to the invasion and metastases were listed.

Some of these genes are as follows: TSPAN9, SOX10, SOX12, ADAM19, and ITGA11 (regulated by miR-486-3p); ADAM22, ITGA11, CDC42, IGF1R, SMAD2, and SMAD5 (regulated by miR-532-5p). Among these genes, the suppression of TSPAN9, SOX10, ITGA11, and CDC42 are reported to inhibit cellular migration in other cancers. Earlier reports have indicated the deregulation of TSPAN9 (CD9) and CDC42 in prostate cancer,40,41 SOX10 in cutaneous melanoma,42 and ITGA11 through the suppression of integrin-mediated signaling pathway in nasopharyngeal carcinoma.43 Thus, these predicted genes implicated by the in silico tools can be validated in future for cell migration function.

Further, the cell cycle analysis in mimic-transfected RB cells pointed to a marked change in the G2/S phase of the Y79 cells (∼48.7% and 48.7%), and the scramble mimic treatment resulted in 30.5% of G2/S phase of cell cycle, while no marked cell cycle phase was observed in mimic-transfected Weri Rb 1 cells (Fig. 7). The difference in aggressive phenotypes that exists between the two cell lines may be responsible for the variation in this cell cycle results among the mimic-transfected RB cell lines.

Figure 7.

Figure 7

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Scatter plot of cell cycle analysis stained by propidium iodide stain in 50 pmol of mimics at the end of 48 hours of incubation. (A) Measurement of various cell cycle stages in mimic-treated Y79 cells. (B) Measurement of various cell cycle stages in mimic-treated Weri Rb 1 cells. The bar graph shows RB cells at various stages of cell cycle in scramble and mimic-treated RB cells. Error bars represent the standard deviation of three experiments.

Conclusion

We have reported the downregulation of miR-486-5p and miR-532-5p in primary RB tumors, implicating their role in RB tumorigenesis and their prognostic potential. The downregulation of the gene targets SYK and FASN at the transcript level and protein level in the presence of miRNA mimics confirmed the miRNA–mRNA regulatory relationship. Mimic-mediated overexpression of miR-486-3p and miR-532-5p resulted in apoptotic cell death of RB cancer cells, suggesting its beneficial role in RB control.

Supplementary Material

Supplementary File. This EXCEL file indicates the list of gene targets determined by comprehensive analysis of miRNA–mRNA networks. The worksheets provide the interaction between the miRNAs and mRNAs as scores ranging from 1 to 4 based on their sequence-based interaction. The databases Microcosm, DIANALAB, miRBase v 18, REFSEQ database, and RNA hybrid were used to predict the posttranscriptional regulators (miRNAs) of the select panel of genes ([Group 1: oncogenes (HMGA2, MYCN, SYK, FASN); Group 2: cancer stem cell markers (TACSTD1, ABCG2, CD133, CD44, CD24) and Group 3: cell cycle regulatory proteins (p53 and MDM2]). Further, the work sheet provides the summary of the predicted miRNAs interception with miRNA profiling of retinoblastoma serum samples reported earlier.

Acknowledgments

We wish to thank Mr. Madavan Vasudevan Bionivid Technology [P] Ltd, Kasturi Nagar, Bangalore, India for technical inputs in the bioinformatics analysis. This work was funded by a research grant from the Department of Biotechnology (DBT), Government of India (No.BT/01/CEIB/11/V/16-Programme support on Retinoblastoma).

Footnotes

ACADEMIC EDITOR: Thomas Dandekar, Associate Editor

FUNDING: Department of Biotechnology (DBT), Government of India (No.BT/01/CEIB/11/V/16-Programme support on Retinoblastoma). The authors confirm that the funder had no influence over the study design, content of the article, or selection of this journal.

COMPETING INTERESTS: Authors disclose no potential conflicts of interest.

Paper subject to independent expert blind peer review by minimum of two reviewers. All editorial decisions made by independent academic editor. Upon submission manuscript was subject to anti-plagiarism scanning. Prior to publication all authors have given signed confirmation of agreement to article publication and compliance with all applicable ethical and legal requirements, including the accuracy of author and contributor information, disclosure of competing interests and funding sources, compliance with ethical requirements relating to human and animal study participants, and compliance with any copyright requirements of third parties. This journal is a member of the Committee on Publication Ethics (COPE).

Author Contributions

Conceived and designed the experiments: NV, SK, PRD. Analyzed the data: NV, SK, PRD. Wrote the first draft of the manuscript: NV, SK, PRD. Contributed to the writing of the manuscript: NV, SK, PRD, VK. Agree with manuscript results and conclusions: NV, SK, PRD, VK. Jointly developed the structure and arguments for the paper: NV, SK, PRD, VK. Made critical revisions and approved final version: NV, SK, PRD, VK. All authors reviewed and approved of the final manuscript.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary File. This EXCEL file indicates the list of gene targets determined by comprehensive analysis of miRNA–mRNA networks. The worksheets provide the interaction between the miRNAs and mRNAs as scores ranging from 1 to 4 based on their sequence-based interaction. The databases Microcosm, DIANALAB, miRBase v 18, REFSEQ database, and RNA hybrid were used to predict the posttranscriptional regulators (miRNAs) of the select panel of genes ([Group 1: oncogenes (HMGA2, MYCN, SYK, FASN); Group 2: cancer stem cell markers (TACSTD1, ABCG2, CD133, CD44, CD24) and Group 3: cell cycle regulatory proteins (p53 and MDM2]). Further, the work sheet provides the summary of the predicted miRNAs interception with miRNA profiling of retinoblastoma serum samples reported earlier.

BBI-9-2015-089-s001.xls (2.6MB, xls)

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