cell biochemistry and function Cell Biochem Funct 2016; 34: 142–148. Published online 24 February 2016 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/cbf.3171
Circulating microRNAs, miR-92a, miR-100 and miR-143, as noninvasive biomarkers for bladder cancer diagnosis Tarek Kamal Motawi1, Sherine Maher Rizk1*, Taghreed Mahmoud Ibrahim2 and Ihab Abdel-Rahman Ibrahim3 1
Biochemistry, Faculty of Pharmacy, Cairo University, Cairo, Egypt National Sohag Hospital, Sohag, Egypt 3 Internal Medicine, Faculty of Medicine, Cairo University, Cairo, Egypt 2
The application of microRNAs (miRNAs) as potential biomarkers and therapy targets has been widely investigated in many kinds of cancers. Recent advantages of serum miRNAs open a new realm of possibilities for non-invasive diagnosis and prognosis of bladder cancer (BC). The aim of our study was to identify plasma miR-92a, miR-100 and miR-143 expression signatures in patients with BC to introduce new markers for establishing BC diagnosis and prognosis. Blood samples were collected from 70 BC patients and 62 controls. An expression of three target miRNAs (miR-92a, miR-100 and miR-143) was measured using quantitative real-time PCR method. Results were correlated with clinicopathological data and analysed. Plasma levels of miR-92a, miR-100 and miR-143 were significantly lower in BC patients than in control group. Receiver operator characteristic analysis revealed that the sensitivity and specificity values of miR-92a were 97·1% and 76·7%, respectively, with a cut-off value of 0·573. The sensitivity and specificity values of miR-100 were 90% and 66·7%, respectively, with a cut-off value of 0·644. The sensitivity and specificity values of miR143 were 78·6% and 93·3%, respectively, with a cut-off value of 0·164. This study explores the existence of specific plasma miRNAs as early diagnostic biomarkers for BC in Egyptian patients; and these findings suggest that plasma miR-92a, miR-100 and miR-143 could be promising novel circulating biomarkers in clinical detection of BC. Copyright © 2016 John Wiley & Sons, Ltd. key words—bladder cancer; microRNA; molecular marker; diagnosis; prognostic factor; RT-PCR
INTRODUCTION Bladder cancer (BC) is the fifth most common cancer in the general population and the second most common cause of death in patients with genitourinary tract malignancies.1 Approximately 90% of tumours are urothelial transitional cell carcinoma. This disease presents two different forms: non-muscle-invasive BC (NMIBCs) (stage Ta and T1), which are frequently recurrent and can sometimes become invasive, and muscle-invasive BC (MIBCs) (stage T2 to T4), about 7% of which are metastatic at diagnosis.2 The challenges that clinicians face with BC are the difficulties of early diagnosis, disease recurrence and progression. Current prognostic strategies, such as tumour grade, stage, size and number of foci, have restricted utility for clinicians because they do not specifically exhibit the clinical outcomes.3 Diagnosis and monitoring strategies for BC have been based on the integration of cystoscopy and urinary cytology data.4 As a consequence,
*Correspondence to: Sherine Maher Rizk, Biochemistry, Faculty of Pharmacy, Cairo University, Cairo, Egypt. E-mail: [email protected]
Copyright © 2016 John Wiley & Sons, Ltd.
researchers have been searching for novel biomarkers, and an important research approach was focusing on the role of microRNAs (miRNAs) in the development and diagnosis of BC.5 miRNAs are endogenous noncoding 19–23 nucleotide RNAs involved in post-transcriptional regulation of gene expression,6 and play significant roles in a variety of biological processes, including proliferation, migration, differentiation and apoptosis.7 Mutated or abnormally expressed miRNAs have been implicated in cancer development and progression,8 acting as tumour suppressors or oncogenes.9 The stability against degradation by RNases and external influences (pH-alteration, storage and freeze/thawing) qualifies miRNAs in many biofluids (such as urine and plasma) as non-invasive biomarkers, and their expression levels may reflect those found in target tissue.10 Their profile may be used to identify altered tumourigenic pathways,11 or help in understanding clinical outcome.12,13 Interestingly, previous studies have documented a link between miRNA expression and cancer pathogenesis for several types of cancer.14,15 However, there are limited reports on the expression profile of miRNAs and their diagnostic potential in BC Received 17 October 2015 Revised 25 January 2016 Accepted 25 January 2016
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circulating micrornas as biomarkers for bc diagnosis compared with the abundant literature addressing other cancer types.16 In the present study, we examined alterations in the expression of miR-92a, miR-100 and miR-143 in plasma samples from patients with BC and healthy volunteers and analysed the correlation between the expression of these miRNAs and the clinicopathological features of this malignancy.
SUBJECTS AND METHODS Patients and samples The present study was conducted on 70 plasma samples provided by BC patients, who were clinically diagnosed with BC and confirmed by surgical biopsies at General Surgery Department, Faculty of Medicine, Cairo University, during the period from August 2013 to June 2014. The BC patients were divided into NMIBC (median age: 56 years; range: 49–65 years) and MIBC (median age: 55 years; range: 35–82 years) groups. In addition, 62 healthy volunteers, recruited by the Blood Transfusion Unit, Faculty of Medicine, Cairo University, were enrolled (median age: 56·5 years; range 47–65 years) and served as the control group. Subjects with chronic or recurrent urinary tract infections, unevaluated gross haematuria or malignancy were excluded from the control group. Patients with metastasis or any other type of malignancy were excluded from the BC group. Neither chemotherapy nor radiotherapy was administered prior to participation in the study. All participants were recruited and enrolled in the study after providing written informed consent for use of their blood samples for research purposes and all study protocols were approved by the Ethics Committee of Faculty of Pharmacy, Cairo University. All clinicopathological data was collected from medical records for the analysis of differences among groups. The clinical and pathological characteristics of the BC patients are shown in Table 1. Clinical staging of BC was performed using cystoscopy. All tumour biopsies were analysed by a single genitourinary pathologist according to a standardized protocol. Pathological staging and classification were performed according to Witjes et al.17 and Babjuk et al.18 Tumours were thus classified as Tx (primary tumour cannot be assessed), T0 (no evidence of primary tumour), Ta (non-invasive papillary carcinoma), Tis (carcinoma in situ: ‘flat tumour’), T1 (invasive up to the subepithelial connective tissue), T2 (invading the muscle), T3 (invading the perivesical fat) and T4 (invading an adjacent organ). Tumours were also graded based on the likelihood of recurrence and progression into grade I (tumours may recur but have only a low risk of progression), grade II (tumours are more likely to recur and progress compared with grade I) and grade III (tumours are very likely to recur and progress). Blood (10 ml) was drawn on ethylenediaminetetraacetic acid from an antecubital vein in BC patients or healthy control subjects using standard percutaneous venipuncture. Copyright © 2016 John Wiley & Sons, Ltd.
Table 1.
Clinical-pathological parameters of the study cohorts Healthy group
BC
Sex (no., %) Male Female Age Mean ± SD Median Range Subgroups (no., %) 70 Bilharziasis (no., %) Present Absent Histology (no., %) Urothelial Squamous Mixed TNM-stage (no., %) Ta T1 T2a T2b T3a T3b T4a Grade GII GIII
NMIBC n = 11 (%)
MIBC n = 59 (%)
n = 62 (%)
7 (63·6%) 4 (36·4%)
45 (76·3%) 14 (23·7%)
42 (67·7%) 20 (32·3%)
57·18 ± 5·42 56 49–65
56·07 ± 9·79 55 35–82
57·20 ± 4·65 56·50 47–65
1 (9·1%) 10 (90·9%) 0 (0%)
12 (20·3%) 43 (72·9%) 4 (6·8%)
2 (3·2%) 60 (96·8%) 0 (0%)
6 (54·5%) 5 (45·5%)
45 (76·3%) 14 (23·7%)
0 (0%) 62 (100%) NA
11 (100%) 0 (0%) 0 (0%)
32 (54·2%) 16 (27·1%) 11 (18·6%)
1 (9·1%) 8 (72·7%) 2 (18·2%) 0 (0·0%) 0 (0·0%) 0 (0·0%) 0 (0·0%)
0 (0·0%) 0 (0·0%) 4 (6·8%) 31 (52·5%) 14 (23·7%) 7 (11·9%) 3 (5·1%)
9 (81·8%) 2 (18·2%)
29 (49·2%) 30 (50·8%)
NA
NA
BC, bladder cancer; NMIBC, non-muscle-invasive bladder cancer; MIBC, muscle-invasive bladder cancer; NA, non-applicable. Pathological staging and classification were performed according to Witjes et al.17 and Babjuk et al.18
Plasma was separated by centrifugation at 3000 rpm for 10 min at 4 °C, and then re-centrifuged at 5000 rpm for 5 min to obtain cell-free plasma, which was stored at 80 °C until use. Only non-haemolysed plasma samples were used in our study, as haemolysis affects miRNA levels. Haemolysis was detected by spectral analysis at 541 nm. 19 Plasma miRNA assay Purification of miRNAs. Total RNA with preserved miRNAs was extracted from 200 μl plasma with the miRNeasy extraction kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s instructions for isolation of total RNA, and eluted with 50 μl of RNase-free water. The isolated RNA was quantified using NanoDrop ND-1000 spectrophotometer (Thermo Fisher scientific, Waltham, USA). Reverse transcription of miRNA. Total RNA was reverse transcribed using the miRNeasy serum/plasma Reverse Transcription Kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s instructions with 5 μl of total RNA per reaction. Cell Biochem Funct 2016; 34: 142–148.
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Real-time PCR detection of miRNA. The expression of miR92a, miR-100 and miR-143 was evaluated by qRT-polymerase chain reaction (PCR) analysis according to the manufacturer’s protocol. U6 snRNA was used as the endogenous control. For real-time PCR, the cDNA template was mixed with SYBER Green Master Mix (Qiagen, Valencia, CA, USA) in a final volume of 25 μl and added to a custom 96-well miScript miRNA PCR array plate enriched with forward and reverse miRNAspecific primers for miR-92a, miR-100 and miR-143. The plate was sealed with optical thin-wall 8-cap strips. Real-time PCR reactions were performed using an Applied Biosystems 7500 Real Time PCR System (Foster city, CA, USA) with the following conditions: 95 °C for 15 min, followed by 40 cycles at 94 °C for 15 s, 55 °C for 30 s and 70 °C for 34 s. The cycle threshold (CT) is defined as the number of cycles required for the fluorescent signal to cross the threshold in real-time PCR. The expression of miRNAs was reported as the ΔCt value, which was calculated by subtracting the CT values of miRNA U6 snRNA from the CT values of the target miRNAs. Because there is an inverse correlation between ΔCt and miRNA expression levels, lower ΔCt values are associated with increased miRNA expression. The 2-ΔΔ (Ct) method was used to determine the relative quantitative levels of individual miRNAs. Statistical analysis Comparisons of quantitative variables were performed using the nonparametric Kruskal–Wallis test when comparing more than two groups and the nonparametric Mann–Whitney U test when comparing two groups. Multiple linear regression analysis was performed including different miRNAs as dependent variables and other clinical and pathological parameters as independent variables. The p values less than 0·05 were considered statistically significant. Correlation was performed to test for linear relations between quantitative variables by Spearman correlation coefficient. Receiver operator characteristic (ROC) curves were derived and area-under-the curve (AUC) analysis was performed to obtain the best cut-off value of miRNA value for detecting cancer patients.
RESULTS Expression levels of miRNAs The data presented in Figure 1 demonstrate that there was a highly significant decrease in the quantitative expression levels of miR-92a, miR-100 and miR-143 in BC patients compared with the control group (p < 0·001). However, only miR-143 expression level differed significantly in the NMIBC and the MIBC groups. No significant correlations were found between expression levels of any of the three miRNAs and age, bilharziasis, grade or tumour, lymph node and metastasis (TNM)-stage in BC patients (Table 2). As shown in Table 3, the multiple regression analyses revealed sex (B = 0·302, p = 0·036) as a significant independent predictor for decreased plasma Copyright © 2016 John Wiley & Sons, Ltd.
Figure 1. Box plot of plasma levels of (A) miR-92a, (B) miR-100 and (C) miR-143, in healthy normal subjects, non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) patients. Expression levels of the miRNA are normalized to U6 snRNA. The line inside the boxes denotes the medians. The boxes mark the interval between the 25th and 75th percentiles. The whiskers denote the intervals between the 10th and 90th percentiles. Filled circles indicate data points outside the 10th and 90th percentiles. Statistically significant differences were determined by Kruskal–Wallis test
miR-100. Age, bilharziasis, TNM stage and grade were not independent predictors for decreased plasma miRNAs in our study. Among subjects with BC, plasma miR-92a was positively correlated with plasma miR-100 (r = 0·511, p = 0·0001) and plasma miR-143 (r = 0·411, p = 0·0002), Cell Biochem Funct 2016; 34: 142–148.
circulating micrornas as biomarkers for bc diagnosis
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Table 2. Correlation of plasma levels of microRNAs with clinicpathological parameters in patients with BC miR-92a
Age Sex Bilharziasis TNM stage Grade
miR-100
miR-143
r
p
r
p
r
p
0·130 -0·056 0·113 0·099 0·067
0·285 0·644 0·355 0·417 0·583
-0·123 -0·259 -0·129 0·149 -0·027
0·311 0·031 0·290 0·218 0·821
0·008 -0·153 -0·022 0·187 0·031
0·946 0·209 0·858 0·121 0·798
Table 3. Multiple linear regression model including different microRNAs as dependent variables and other clinical and pathological parameters as independent variables miR-92a
Sex Age Bilharziasis TNM stage Grade
miR-100
miR-143
B
p
B
p
B
p
0·046 0·002 -0·010 -0·004 0·027
0·387 0·318 0·834 0·858 0·336
-0·302 -0·006 -0·196 0·027 0·083
0·036 0·354 0·141 0·663 0·273
-0·156 -0·006 -0·023 0·027 0·034
0·160 0·260 0·825 0·564 0·564
while plasma miR-100 was positively correlated with plasma miR-143 (r = 0·414, p = 0·0004) as shown in Figure 2. Diagnostic performance of miR-92a, miR-100 and miR-143 for BC The diagnostic performance of miR-92a, miR-100 and miR143 (and a combination of these markers) in differentiating BC patients from healthy volunteers was evaluated by ROC curve analysis. Cut-off points were determined such that they maximized the sum of sensitivity and specificity. The cut-off points for miR-92a, miR-100 and miR-143 were 0·573, 0·644 and 0·164, respectively. The sensitivity and specificity of miR-92a calculated in this study were 97·1% and 76·7%, respectively, with an AUC value of 0·940 (Figure 3A). The sensitivity and specificity of miR-100 were 90% and 66·7%, respectively, with an AUC value of 0·823 (Figure 3B). Finally, the sensitivity and specificity of miR143 quantitative expression calculated in this study were 78·6% and 93·3%, respectively, with AUC value of 0·915 (Figure 3C). The AUC for the combined miR-92a and miR100 was 0·898 [95% confidence interval (CI), 0·830 to 0·966], with a sensitivity of 94·3% and a specificity of 73·3% (Figure 3D). Meanwhile, the AUC for the combined miR92a and miR-143 was 0·953 (95% CI, 0·913 to 0·994), with a sensitivity of 94·3% and a specificity of 86·6% (Figure 3E), which showed the highest sensitivity and specificity among all combinations. The AUC for the combined miR-100 and miR-143 was 0·892 (95% CI, 0·823 to 0·961), with a sensitivity of 88·6% and a specificity of 83·3% (Figure 3F). Finally, the sensitivity and specificity of combined miR-92a, miR-100 and miR-143 quantitative expression calculated in this study were 94·3% and 83·3%, respectively, whereas the AUC was 0·926. Copyright © 2016 John Wiley & Sons, Ltd.
Figure 2. Correlation between miR-92a, miR-100 and miR-143 among bladder cancer patients
DISCUSSION BC is the most expensive cancer to treat.20 About 80% of patients had bladder tumours that had not invaded the detrusor, termed non-muscle-invasive tumours, and in general, the prognosis is good. The vast majority of BC patients have a 30–70% recurrence rate, and NMIBCs has Cell Biochem Funct 2016; 34: 142–148.
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Figure 3. Receiver operating characteristic (ROC) curve analysis. The ROC plots for miR-92a (A), miR-100 (B), miR-143 (C), miR-92a + miR-100 (D), miR-92a + miR-143 (E), miR-100 + miR-143 (F) and combination of three miRNAs (G) were used to differentiate bladder cancer patients from normal subjects. AUC, area-under-the receiver operating characteristic curve; CI, confidence interval
progression to muscle invasion in up to 30% patients.21 Early detection and timely intervention can increase patient survival. Therefore, to develop improved and more effective prevention and treatment protocols, there is a need to find new biomarkers of tumourigenesis and prognosis of BC. miRNA expression profiling has been shown to classify tissue and tumour type accurately.22 While analysis of miRNA expression in biopsy samples may be associated Copyright © 2016 John Wiley & Sons, Ltd.
with sampling errors and invasiveness, the quantification of plasma miRNA levels is less invasive, simpler and can monitor tumour dynamics. Several reports have demonstrated that miRNA is consistently detectable in plasma. Therefore, it may be considered that the circulating miRNA level in the plasma may reflect tumour tissue miRNA expression.14 miRNAs represent promising biomarkers with potential not only for detecting BC but also informing on Cell Biochem Funct 2016; 34: 142–148.
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circulating micrornas as biomarkers for bc diagnosis prognosis and monitoring treatment response.23 In the current study, we focused on plasma miRNA expression levels to determine their utility as markers for predicting the clinical characteristics in patients with BC. We based our selection of the three miRNAs (miR-92a, miR-100 and miR-143) on our interpretation of the published literature that reports their downregulation in BC cells. The study of the expression profile of these miRNAs in plasma may represent a gold mine of non-invasive biomarkers for this type of cancer. In our study, we showed downregulated expression of plasma miR-92a, miR-100 and miR-143 in BC patients compared with healthy controls, suggesting a major role of these tumour suppressor miRNAs in bladder carcinogenesis. Although BC represents a heterogeneous entity with significant malignant potential, one of the major findings of the present study was that the altered miR-92a and miR-100 were downregulated in the same way in the two forms of bladder tumour, irrespective of the pathological stage, suggesting that these deregulations could be relatively early events of bladder carcinogenesis. These results corroborate those reported by Catto et al.24 who found that altered miRNA expression occurred early in bladder tumourigenesis, before the onset of muscle invasion. The downregulation of plasma miR-92a has been recognized in patients with hematologic neoplasia, including acute leukaemia,25,26 non-Hodgkin’s lymphoma27 and hepatocellular carcinoma28 as well as in patients with cardiovascular diseases.29 In a study carried out by Pignot and his colleagues30 on bladder tumour cells, miR-92a was underexpressed in NMIBC tissue, but normally expressed or overexpressed in MIBC tissue. It was reported that miR-92 were inversely correlated with advanced clinical stage,31 and it has been predicted that miR-92a affects genes that are involved in the regulation of the actin cytoskeleton and mitogen-activated protein kinases signalling pathway.32 Both processes are well known to be associated with cancer. Downregulation of miR-100 in BC tumour tissue was previously demonstrated in many studies.33–35 On the contrary, there are no reports on its plasma or serum level in BC patients. The observed downregulation of plasma miR100 in BC patients in our study suggests that miR-100 may act as a potential tumour suppressor in BC. miR-100 could pleiotropically inhibit cell growth and colony formation, suppress cell migration and invasion, induce G1 arrest in BC cells and suppress tumourigenesis in nude mice models of BC.35 Previously, it was reported that miR-143 is downregulated in human BC cells.36,37 To the best of our knowledge, we are the first to report a suppressed level of miR-143 in the plasma of BC patients. miR-143 has well documented antiproliferative and proapoptotic effects because of its ability to downregulate a host of target genes, including plasminogen activator inhibitor-1.38 This miRNA has also been reported to be implicated in Kras regulation and apoptosis avoidance.36,39 Lin et al.36 showed that the oncogene RAS is a possible target gene of miR-143 in BC. In addition, it was found that miR-143 inhibits tumour formation by Copyright © 2016 John Wiley & Sons, Ltd.
targeting Bcl-2 in cervical cancer.40 Several studies have also demonstrated that miR-143 suppresses tumour growth by inhibition of multiple tumour survival effectors, thereby suggesting a potential value of this miRNA in cancer therapy.41 We employed the ROC curve to analyse the diagnostic value of plasma miR-92a, miR-100 and miR-143 levels in BC patients. As a result, ROC demonstrated that miR-92a and miR-143 had a high diagnostic value for BC with the AUC of 0·940 and 0·915, respectively. MiR-100 showed a moderate diagnostic value for BC with the AUC of 0·823. More powerful diagnostic values were observed when combining miR-92a with miR-143, resulting in an AUC of 0·953 with 94·3% sensitivity and 86·6% specificity. Although our results are promising, this study has several limitations. Firstly, as the sample size is still small, further validations in large cohorts or in different ethnic groups are recommended. Secondly, it is uncertain whether this plasma miRNA elevation is specific for certain subtypes of BC. Thus, additional studies are necessary to compare their plasma levels in different subtypes.
CONCLUSIONS In conclusion, the present study demonstrates a reduction in miR-92a, miR-100 and miR-143 levels in plasma of BC patients. The best combination of the plasma markers miR92a and miR-143, revealed in our plasma quantitative assay, makes a very promising and specific BC screening test possible. Although the testing with these markers reached a sensitivity of 94·3% for BC prediction, the specificity was about 87%. There is, therefore, a need to compare the results with other types of cancer to clarify whether these miRNAs are useful as specific markers for BC.
CONFLICT OF INTEREST The authors have declared that there is no conflict of interest.
AUTHOR CONTRIBUTIONS TKM and SMR conceived and designed the experiments. TKM, SMR and TMI performed the experiments, analysed the data and wrote the paper. TKM, SMR, TMI and IAI contributed reagents/materials/analysis tools.
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5. Braicu C, Cojocneanu-Petric R, Chira S, et al. Clinical and pathological implications of miRNA in bladder cancer. Int J Nanomedicine 2015; 10: 791–800. 6. Yang XW, Zhang LJ, Huang XH, et al. miR-145 suppresses cell invasion in hepatocellular carcinoma cells: miR-145 targets ADAM17. Hepatol Res 2014; 44: 551–559. 7. Ha TY. MicroRNAs in human diseases: from cancer to cardiovascular disease. Immune Netw 2011; 11: 135–154. 8. Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004; 116: 281–297. 9. Calin GA, Croce CM. MicroRNA signatures in human cancers. Nat Rev Cancer 2006; 6: 857–866. 10. Chen X, Ba Y, Ma L, et al. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res 2008; 18: 997–1006. 11. Zhang B, Pan X, Cobb GP, Anderson TA. MicroRNAs as oncogenes and tumour suppressors. Dev Biol 2007; 302: 1–12. 12. Volinia S, Calin GA, Liu CG, et al. Proc Natl Acad Sci U S A 2006; 103: 2257–2261. 13. Schetter AJ, Leung SY, Sohn JJ, Zanetti KA, Bowman ED. MicroRNA expression profiles associated with prognosis and therapeutic outcome in colon adenocarcinoma. JAMA 2008; 299: 425–436. 14. Iorio MV, Ferracin M, Liu CG, et al. MicroRNA gene expression deregulation in human breast cancer. Cancer Res 2005; 65: 7065–7070. 15. Yu SL, Chen HY, Chang GC, et al. MicroRNA signature predicts survival and relapse in lung cancer. Cancer Cell 2008; 13: 48–57. 16. Feng Y, Kang Y, He Y, et al. microRNA-99a acts as a tumour suppressor and is down-regulated in bladder cancer. BMC Urol 2014; 14: 50. 17. Witjes JA, Compérat E, Cowan NC, et al. European Association of Urology. EAU guidelines on muscle-invasive and metastatic bladder cancer: summary of the 2013 guidelines. Eur Urol 2014; 65(4): 778–792. 18. Babjuk M, Burger M, Zigeuner R. European Association of Urology. EAU guidelines on non-muscle-invasive urothelial carcinoma of the bladder update 2013. Eur Urol 2013; 64(4): 639–653. 19. Kirschner MB, Kao SC, Edelman JJ, et al. Haemolysis during sample preparation alters microRNA content of plasma PLoS One 2011; 6(9): e24145. 20. Botteman MF, Pashos CL, Redaelli A, Laskin B, Hauser R. The health economics of bladder cancer: a comprehensive review of the published literature. Pharmacoeconomics 2003; 21: 1315–1330. 21. Jokisch JF, Karl A, Stief C. Intravesical immunotherapy in nonmuscle invasive bladder cancer. Indian J Urol 2015; 31(4): 304–311. 22. Markou A, Sourvinou I, Vorkas PA, Yousef GM, Lianidou E. Clinical evaluation of microRNA expression profiling in non small cell lung cancer. Lung Cancer 2013; 81(3): 388–396. 23. Matullo G, Naccarati A, Pardini B. MicroRNA expression profiling in bladder cancer: the challenge of next generation sequencing in tissues and biofluids. Int J Cancer. 2015. doi: 10.1002/ijc.29895. [Epub ahead of print]. 24. Catto JW, Miah S, Owen HC, at al.. Distinct microRNA alterations characterize high- and lowgrade bladder cancer. Cancer Res 2009; 69: 8472–8481.
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Cell Biochem Funct 2016; 34: 142–148.
Circulating microRNAs, miR-92a, miR-100 and miR-143, as noninvasive biomarkers for bladder cancer diagnosis Tarek Kamal Motawi1, Sherine Maher Rizk1*, Taghreed Mahmoud Ibrahim2 and Ihab Abdel-Rahman Ibrahim3 1
Biochemistry, Faculty of Pharmacy, Cairo University, Cairo, Egypt National Sohag Hospital, Sohag, Egypt 3 Internal Medicine, Faculty of Medicine, Cairo University, Cairo, Egypt 2
The application of microRNAs (miRNAs) as potential biomarkers and therapy targets has been widely investigated in many kinds of cancers. Recent advantages of serum miRNAs open a new realm of possibilities for non-invasive diagnosis and prognosis of bladder cancer (BC). The aim of our study was to identify plasma miR-92a, miR-100 and miR-143 expression signatures in patients with BC to introduce new markers for establishing BC diagnosis and prognosis. Blood samples were collected from 70 BC patients and 62 controls. An expression of three target miRNAs (miR-92a, miR-100 and miR-143) was measured using quantitative real-time PCR method. Results were correlated with clinicopathological data and analysed. Plasma levels of miR-92a, miR-100 and miR-143 were significantly lower in BC patients than in control group. Receiver operator characteristic analysis revealed that the sensitivity and specificity values of miR-92a were 97·1% and 76·7%, respectively, with a cut-off value of 0·573. The sensitivity and specificity values of miR-100 were 90% and 66·7%, respectively, with a cut-off value of 0·644. The sensitivity and specificity values of miR143 were 78·6% and 93·3%, respectively, with a cut-off value of 0·164. This study explores the existence of specific plasma miRNAs as early diagnostic biomarkers for BC in Egyptian patients; and these findings suggest that plasma miR-92a, miR-100 and miR-143 could be promising novel circulating biomarkers in clinical detection of BC. Copyright © 2016 John Wiley & Sons, Ltd. key words—bladder cancer; microRNA; molecular marker; diagnosis; prognostic factor; RT-PCR
INTRODUCTION Bladder cancer (BC) is the fifth most common cancer in the general population and the second most common cause of death in patients with genitourinary tract malignancies.1 Approximately 90% of tumours are urothelial transitional cell carcinoma. This disease presents two different forms: non-muscle-invasive BC (NMIBCs) (stage Ta and T1), which are frequently recurrent and can sometimes become invasive, and muscle-invasive BC (MIBCs) (stage T2 to T4), about 7% of which are metastatic at diagnosis.2 The challenges that clinicians face with BC are the difficulties of early diagnosis, disease recurrence and progression. Current prognostic strategies, such as tumour grade, stage, size and number of foci, have restricted utility for clinicians because they do not specifically exhibit the clinical outcomes.3 Diagnosis and monitoring strategies for BC have been based on the integration of cystoscopy and urinary cytology data.4 As a consequence,
*Correspondence to: Sherine Maher Rizk, Biochemistry, Faculty of Pharmacy, Cairo University, Cairo, Egypt. E-mail: [email protected]
Copyright © 2016 John Wiley & Sons, Ltd.
researchers have been searching for novel biomarkers, and an important research approach was focusing on the role of microRNAs (miRNAs) in the development and diagnosis of BC.5 miRNAs are endogenous noncoding 19–23 nucleotide RNAs involved in post-transcriptional regulation of gene expression,6 and play significant roles in a variety of biological processes, including proliferation, migration, differentiation and apoptosis.7 Mutated or abnormally expressed miRNAs have been implicated in cancer development and progression,8 acting as tumour suppressors or oncogenes.9 The stability against degradation by RNases and external influences (pH-alteration, storage and freeze/thawing) qualifies miRNAs in many biofluids (such as urine and plasma) as non-invasive biomarkers, and their expression levels may reflect those found in target tissue.10 Their profile may be used to identify altered tumourigenic pathways,11 or help in understanding clinical outcome.12,13 Interestingly, previous studies have documented a link between miRNA expression and cancer pathogenesis for several types of cancer.14,15 However, there are limited reports on the expression profile of miRNAs and their diagnostic potential in BC Received 17 October 2015 Revised 25 January 2016 Accepted 25 January 2016
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circulating micrornas as biomarkers for bc diagnosis compared with the abundant literature addressing other cancer types.16 In the present study, we examined alterations in the expression of miR-92a, miR-100 and miR-143 in plasma samples from patients with BC and healthy volunteers and analysed the correlation between the expression of these miRNAs and the clinicopathological features of this malignancy.
SUBJECTS AND METHODS Patients and samples The present study was conducted on 70 plasma samples provided by BC patients, who were clinically diagnosed with BC and confirmed by surgical biopsies at General Surgery Department, Faculty of Medicine, Cairo University, during the period from August 2013 to June 2014. The BC patients were divided into NMIBC (median age: 56 years; range: 49–65 years) and MIBC (median age: 55 years; range: 35–82 years) groups. In addition, 62 healthy volunteers, recruited by the Blood Transfusion Unit, Faculty of Medicine, Cairo University, were enrolled (median age: 56·5 years; range 47–65 years) and served as the control group. Subjects with chronic or recurrent urinary tract infections, unevaluated gross haematuria or malignancy were excluded from the control group. Patients with metastasis or any other type of malignancy were excluded from the BC group. Neither chemotherapy nor radiotherapy was administered prior to participation in the study. All participants were recruited and enrolled in the study after providing written informed consent for use of their blood samples for research purposes and all study protocols were approved by the Ethics Committee of Faculty of Pharmacy, Cairo University. All clinicopathological data was collected from medical records for the analysis of differences among groups. The clinical and pathological characteristics of the BC patients are shown in Table 1. Clinical staging of BC was performed using cystoscopy. All tumour biopsies were analysed by a single genitourinary pathologist according to a standardized protocol. Pathological staging and classification were performed according to Witjes et al.17 and Babjuk et al.18 Tumours were thus classified as Tx (primary tumour cannot be assessed), T0 (no evidence of primary tumour), Ta (non-invasive papillary carcinoma), Tis (carcinoma in situ: ‘flat tumour’), T1 (invasive up to the subepithelial connective tissue), T2 (invading the muscle), T3 (invading the perivesical fat) and T4 (invading an adjacent organ). Tumours were also graded based on the likelihood of recurrence and progression into grade I (tumours may recur but have only a low risk of progression), grade II (tumours are more likely to recur and progress compared with grade I) and grade III (tumours are very likely to recur and progress). Blood (10 ml) was drawn on ethylenediaminetetraacetic acid from an antecubital vein in BC patients or healthy control subjects using standard percutaneous venipuncture. Copyright © 2016 John Wiley & Sons, Ltd.
Table 1.
Clinical-pathological parameters of the study cohorts Healthy group
BC
Sex (no., %) Male Female Age Mean ± SD Median Range Subgroups (no., %) 70 Bilharziasis (no., %) Present Absent Histology (no., %) Urothelial Squamous Mixed TNM-stage (no., %) Ta T1 T2a T2b T3a T3b T4a Grade GII GIII
NMIBC n = 11 (%)
MIBC n = 59 (%)
n = 62 (%)
7 (63·6%) 4 (36·4%)
45 (76·3%) 14 (23·7%)
42 (67·7%) 20 (32·3%)
57·18 ± 5·42 56 49–65
56·07 ± 9·79 55 35–82
57·20 ± 4·65 56·50 47–65
1 (9·1%) 10 (90·9%) 0 (0%)
12 (20·3%) 43 (72·9%) 4 (6·8%)
2 (3·2%) 60 (96·8%) 0 (0%)
6 (54·5%) 5 (45·5%)
45 (76·3%) 14 (23·7%)
0 (0%) 62 (100%) NA
11 (100%) 0 (0%) 0 (0%)
32 (54·2%) 16 (27·1%) 11 (18·6%)
1 (9·1%) 8 (72·7%) 2 (18·2%) 0 (0·0%) 0 (0·0%) 0 (0·0%) 0 (0·0%)
0 (0·0%) 0 (0·0%) 4 (6·8%) 31 (52·5%) 14 (23·7%) 7 (11·9%) 3 (5·1%)
9 (81·8%) 2 (18·2%)
29 (49·2%) 30 (50·8%)
NA
NA
BC, bladder cancer; NMIBC, non-muscle-invasive bladder cancer; MIBC, muscle-invasive bladder cancer; NA, non-applicable. Pathological staging and classification were performed according to Witjes et al.17 and Babjuk et al.18
Plasma was separated by centrifugation at 3000 rpm for 10 min at 4 °C, and then re-centrifuged at 5000 rpm for 5 min to obtain cell-free plasma, which was stored at 80 °C until use. Only non-haemolysed plasma samples were used in our study, as haemolysis affects miRNA levels. Haemolysis was detected by spectral analysis at 541 nm. 19 Plasma miRNA assay Purification of miRNAs. Total RNA with preserved miRNAs was extracted from 200 μl plasma with the miRNeasy extraction kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s instructions for isolation of total RNA, and eluted with 50 μl of RNase-free water. The isolated RNA was quantified using NanoDrop ND-1000 spectrophotometer (Thermo Fisher scientific, Waltham, USA). Reverse transcription of miRNA. Total RNA was reverse transcribed using the miRNeasy serum/plasma Reverse Transcription Kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s instructions with 5 μl of total RNA per reaction. Cell Biochem Funct 2016; 34: 142–148.
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Real-time PCR detection of miRNA. The expression of miR92a, miR-100 and miR-143 was evaluated by qRT-polymerase chain reaction (PCR) analysis according to the manufacturer’s protocol. U6 snRNA was used as the endogenous control. For real-time PCR, the cDNA template was mixed with SYBER Green Master Mix (Qiagen, Valencia, CA, USA) in a final volume of 25 μl and added to a custom 96-well miScript miRNA PCR array plate enriched with forward and reverse miRNAspecific primers for miR-92a, miR-100 and miR-143. The plate was sealed with optical thin-wall 8-cap strips. Real-time PCR reactions were performed using an Applied Biosystems 7500 Real Time PCR System (Foster city, CA, USA) with the following conditions: 95 °C for 15 min, followed by 40 cycles at 94 °C for 15 s, 55 °C for 30 s and 70 °C for 34 s. The cycle threshold (CT) is defined as the number of cycles required for the fluorescent signal to cross the threshold in real-time PCR. The expression of miRNAs was reported as the ΔCt value, which was calculated by subtracting the CT values of miRNA U6 snRNA from the CT values of the target miRNAs. Because there is an inverse correlation between ΔCt and miRNA expression levels, lower ΔCt values are associated with increased miRNA expression. The 2-ΔΔ (Ct) method was used to determine the relative quantitative levels of individual miRNAs. Statistical analysis Comparisons of quantitative variables were performed using the nonparametric Kruskal–Wallis test when comparing more than two groups and the nonparametric Mann–Whitney U test when comparing two groups. Multiple linear regression analysis was performed including different miRNAs as dependent variables and other clinical and pathological parameters as independent variables. The p values less than 0·05 were considered statistically significant. Correlation was performed to test for linear relations between quantitative variables by Spearman correlation coefficient. Receiver operator characteristic (ROC) curves were derived and area-under-the curve (AUC) analysis was performed to obtain the best cut-off value of miRNA value for detecting cancer patients.
RESULTS Expression levels of miRNAs The data presented in Figure 1 demonstrate that there was a highly significant decrease in the quantitative expression levels of miR-92a, miR-100 and miR-143 in BC patients compared with the control group (p < 0·001). However, only miR-143 expression level differed significantly in the NMIBC and the MIBC groups. No significant correlations were found between expression levels of any of the three miRNAs and age, bilharziasis, grade or tumour, lymph node and metastasis (TNM)-stage in BC patients (Table 2). As shown in Table 3, the multiple regression analyses revealed sex (B = 0·302, p = 0·036) as a significant independent predictor for decreased plasma Copyright © 2016 John Wiley & Sons, Ltd.
Figure 1. Box plot of plasma levels of (A) miR-92a, (B) miR-100 and (C) miR-143, in healthy normal subjects, non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) patients. Expression levels of the miRNA are normalized to U6 snRNA. The line inside the boxes denotes the medians. The boxes mark the interval between the 25th and 75th percentiles. The whiskers denote the intervals between the 10th and 90th percentiles. Filled circles indicate data points outside the 10th and 90th percentiles. Statistically significant differences were determined by Kruskal–Wallis test
miR-100. Age, bilharziasis, TNM stage and grade were not independent predictors for decreased plasma miRNAs in our study. Among subjects with BC, plasma miR-92a was positively correlated with plasma miR-100 (r = 0·511, p = 0·0001) and plasma miR-143 (r = 0·411, p = 0·0002), Cell Biochem Funct 2016; 34: 142–148.
circulating micrornas as biomarkers for bc diagnosis
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Table 2. Correlation of plasma levels of microRNAs with clinicpathological parameters in patients with BC miR-92a
Age Sex Bilharziasis TNM stage Grade
miR-100
miR-143
r
p
r
p
r
p
0·130 -0·056 0·113 0·099 0·067
0·285 0·644 0·355 0·417 0·583
-0·123 -0·259 -0·129 0·149 -0·027
0·311 0·031 0·290 0·218 0·821
0·008 -0·153 -0·022 0·187 0·031
0·946 0·209 0·858 0·121 0·798
Table 3. Multiple linear regression model including different microRNAs as dependent variables and other clinical and pathological parameters as independent variables miR-92a
Sex Age Bilharziasis TNM stage Grade
miR-100
miR-143
B
p
B
p
B
p
0·046 0·002 -0·010 -0·004 0·027
0·387 0·318 0·834 0·858 0·336
-0·302 -0·006 -0·196 0·027 0·083
0·036 0·354 0·141 0·663 0·273
-0·156 -0·006 -0·023 0·027 0·034
0·160 0·260 0·825 0·564 0·564
while plasma miR-100 was positively correlated with plasma miR-143 (r = 0·414, p = 0·0004) as shown in Figure 2. Diagnostic performance of miR-92a, miR-100 and miR-143 for BC The diagnostic performance of miR-92a, miR-100 and miR143 (and a combination of these markers) in differentiating BC patients from healthy volunteers was evaluated by ROC curve analysis. Cut-off points were determined such that they maximized the sum of sensitivity and specificity. The cut-off points for miR-92a, miR-100 and miR-143 were 0·573, 0·644 and 0·164, respectively. The sensitivity and specificity of miR-92a calculated in this study were 97·1% and 76·7%, respectively, with an AUC value of 0·940 (Figure 3A). The sensitivity and specificity of miR-100 were 90% and 66·7%, respectively, with an AUC value of 0·823 (Figure 3B). Finally, the sensitivity and specificity of miR143 quantitative expression calculated in this study were 78·6% and 93·3%, respectively, with AUC value of 0·915 (Figure 3C). The AUC for the combined miR-92a and miR100 was 0·898 [95% confidence interval (CI), 0·830 to 0·966], with a sensitivity of 94·3% and a specificity of 73·3% (Figure 3D). Meanwhile, the AUC for the combined miR92a and miR-143 was 0·953 (95% CI, 0·913 to 0·994), with a sensitivity of 94·3% and a specificity of 86·6% (Figure 3E), which showed the highest sensitivity and specificity among all combinations. The AUC for the combined miR-100 and miR-143 was 0·892 (95% CI, 0·823 to 0·961), with a sensitivity of 88·6% and a specificity of 83·3% (Figure 3F). Finally, the sensitivity and specificity of combined miR-92a, miR-100 and miR-143 quantitative expression calculated in this study were 94·3% and 83·3%, respectively, whereas the AUC was 0·926. Copyright © 2016 John Wiley & Sons, Ltd.
Figure 2. Correlation between miR-92a, miR-100 and miR-143 among bladder cancer patients
DISCUSSION BC is the most expensive cancer to treat.20 About 80% of patients had bladder tumours that had not invaded the detrusor, termed non-muscle-invasive tumours, and in general, the prognosis is good. The vast majority of BC patients have a 30–70% recurrence rate, and NMIBCs has Cell Biochem Funct 2016; 34: 142–148.
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Figure 3. Receiver operating characteristic (ROC) curve analysis. The ROC plots for miR-92a (A), miR-100 (B), miR-143 (C), miR-92a + miR-100 (D), miR-92a + miR-143 (E), miR-100 + miR-143 (F) and combination of three miRNAs (G) were used to differentiate bladder cancer patients from normal subjects. AUC, area-under-the receiver operating characteristic curve; CI, confidence interval
progression to muscle invasion in up to 30% patients.21 Early detection and timely intervention can increase patient survival. Therefore, to develop improved and more effective prevention and treatment protocols, there is a need to find new biomarkers of tumourigenesis and prognosis of BC. miRNA expression profiling has been shown to classify tissue and tumour type accurately.22 While analysis of miRNA expression in biopsy samples may be associated Copyright © 2016 John Wiley & Sons, Ltd.
with sampling errors and invasiveness, the quantification of plasma miRNA levels is less invasive, simpler and can monitor tumour dynamics. Several reports have demonstrated that miRNA is consistently detectable in plasma. Therefore, it may be considered that the circulating miRNA level in the plasma may reflect tumour tissue miRNA expression.14 miRNAs represent promising biomarkers with potential not only for detecting BC but also informing on Cell Biochem Funct 2016; 34: 142–148.
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circulating micrornas as biomarkers for bc diagnosis prognosis and monitoring treatment response.23 In the current study, we focused on plasma miRNA expression levels to determine their utility as markers for predicting the clinical characteristics in patients with BC. We based our selection of the three miRNAs (miR-92a, miR-100 and miR-143) on our interpretation of the published literature that reports their downregulation in BC cells. The study of the expression profile of these miRNAs in plasma may represent a gold mine of non-invasive biomarkers for this type of cancer. In our study, we showed downregulated expression of plasma miR-92a, miR-100 and miR-143 in BC patients compared with healthy controls, suggesting a major role of these tumour suppressor miRNAs in bladder carcinogenesis. Although BC represents a heterogeneous entity with significant malignant potential, one of the major findings of the present study was that the altered miR-92a and miR-100 were downregulated in the same way in the two forms of bladder tumour, irrespective of the pathological stage, suggesting that these deregulations could be relatively early events of bladder carcinogenesis. These results corroborate those reported by Catto et al.24 who found that altered miRNA expression occurred early in bladder tumourigenesis, before the onset of muscle invasion. The downregulation of plasma miR-92a has been recognized in patients with hematologic neoplasia, including acute leukaemia,25,26 non-Hodgkin’s lymphoma27 and hepatocellular carcinoma28 as well as in patients with cardiovascular diseases.29 In a study carried out by Pignot and his colleagues30 on bladder tumour cells, miR-92a was underexpressed in NMIBC tissue, but normally expressed or overexpressed in MIBC tissue. It was reported that miR-92 were inversely correlated with advanced clinical stage,31 and it has been predicted that miR-92a affects genes that are involved in the regulation of the actin cytoskeleton and mitogen-activated protein kinases signalling pathway.32 Both processes are well known to be associated with cancer. Downregulation of miR-100 in BC tumour tissue was previously demonstrated in many studies.33–35 On the contrary, there are no reports on its plasma or serum level in BC patients. The observed downregulation of plasma miR100 in BC patients in our study suggests that miR-100 may act as a potential tumour suppressor in BC. miR-100 could pleiotropically inhibit cell growth and colony formation, suppress cell migration and invasion, induce G1 arrest in BC cells and suppress tumourigenesis in nude mice models of BC.35 Previously, it was reported that miR-143 is downregulated in human BC cells.36,37 To the best of our knowledge, we are the first to report a suppressed level of miR-143 in the plasma of BC patients. miR-143 has well documented antiproliferative and proapoptotic effects because of its ability to downregulate a host of target genes, including plasminogen activator inhibitor-1.38 This miRNA has also been reported to be implicated in Kras regulation and apoptosis avoidance.36,39 Lin et al.36 showed that the oncogene RAS is a possible target gene of miR-143 in BC. In addition, it was found that miR-143 inhibits tumour formation by Copyright © 2016 John Wiley & Sons, Ltd.
targeting Bcl-2 in cervical cancer.40 Several studies have also demonstrated that miR-143 suppresses tumour growth by inhibition of multiple tumour survival effectors, thereby suggesting a potential value of this miRNA in cancer therapy.41 We employed the ROC curve to analyse the diagnostic value of plasma miR-92a, miR-100 and miR-143 levels in BC patients. As a result, ROC demonstrated that miR-92a and miR-143 had a high diagnostic value for BC with the AUC of 0·940 and 0·915, respectively. MiR-100 showed a moderate diagnostic value for BC with the AUC of 0·823. More powerful diagnostic values were observed when combining miR-92a with miR-143, resulting in an AUC of 0·953 with 94·3% sensitivity and 86·6% specificity. Although our results are promising, this study has several limitations. Firstly, as the sample size is still small, further validations in large cohorts or in different ethnic groups are recommended. Secondly, it is uncertain whether this plasma miRNA elevation is specific for certain subtypes of BC. Thus, additional studies are necessary to compare their plasma levels in different subtypes.
CONCLUSIONS In conclusion, the present study demonstrates a reduction in miR-92a, miR-100 and miR-143 levels in plasma of BC patients. The best combination of the plasma markers miR92a and miR-143, revealed in our plasma quantitative assay, makes a very promising and specific BC screening test possible. Although the testing with these markers reached a sensitivity of 94·3% for BC prediction, the specificity was about 87%. There is, therefore, a need to compare the results with other types of cancer to clarify whether these miRNAs are useful as specific markers for BC.
CONFLICT OF INTEREST The authors have declared that there is no conflict of interest.
AUTHOR CONTRIBUTIONS TKM and SMR conceived and designed the experiments. TKM, SMR and TMI performed the experiments, analysed the data and wrote the paper. TKM, SMR, TMI and IAI contributed reagents/materials/analysis tools.
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