Oral Diseases (2015) 21, 195–206 doi:10.1111/odi.12241 © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd All rights reserved www.wiley.com

ORIGINAL ARTICLE

The association between miR-499a polymorphism and oral squamous cell carcinoma progression Y-Y Hou1,2, J-H Lee3, H-C Chen4,5, C-M Yang4,5, S-J Huang6, H-H Liou6, C-C Chi1, K-W Tsai6, L-P Ger6,7 1

Department of Otorhinolaryngology, Kaohsiung Veterans General Hospital, Kaohsiung; 2Department of Nursing, Yuh-Ing Junior College of Health Care and Management, Kaohsiung; 3Department of Pathology and Laboratory Medicine, Kaohsiung Veterans General Hospital, Kaohsiung; 4Department of Stomatology, Kaohsiung Veterans General Hospital, Kaohsiung; 5Department of Dental Technology, Shu-Zen Junior College of Medicine and Management, Kaohsiung; 6Department of Medical Education and Research, Kaohsiung Veterans General Hospital, Kaohsiung; 7Institute of Biomedical Sciences, National Sun Yat-Sen University, Kaohsiung, Taiwan

OBJECTIVE: To investigate the association of miR-499a genetic polymorphism with the risk of oral leukoplakia, oral submucous fibrosis (OSF), oral squamous cell carcinoma (OSCC), and clinicopathological outcomes of OSCC. METHODS: The genotyping of miR-499a T>C (rs3746444) using TagMan assay was conducted in two case-control studies of 1549 subjects. miR-499a-5p and miR-499a-3p were assayed using stem-loop RT-PCR for 63 paired OSCC and adjacent normal tissues. RESULTS: T/C+C/C genotypes [adjusted odds ratio (AOR) 1.84, P = 0.032] and C allelic type (AOR 1.91, P = 0.007) at miR-499a T>C were associated with an increased risk of BQ-related OSF as compared to those with T/T genotype or T allelic type, respectively. Conversely, T/C+C/C genotypes and C allelic type decreased the risk of OSCC, especially for non-BQ-related OSCC (for genotype: AOR 0.49, P = 0.010; for allelic type: AOR 0.50, P = 0.007). Additionally, downregulation of miR-499a-5p was found in OSCC tissues (P = 0.001) and correlated with the TT genotype (P = 0.001). CONCLUSION: The T/C+C/C genotypes of MiR-499a may contribute to an increased risk of BQ-related OSF, but a decreased risk of OSCC. miR-499a T>C influences the expression levels of miR-499a-5p during the tumorigenesis of OSCC. Oral Diseases (2015) 21, 195–206 Correspondence: Luo-Ping Ger, Department of Medical Education and Research, Kaohsiung Veterans General Hospital, Kaohsiung 813, Taiwan. Tel: 011-886-7-346-8356, Fax: 011-886-7-346-8056, E-mail: [email protected] vghks.gov.tw and Kuo-Wang Tsai, Department of Medical Education and Research, Kaohsiung Veterans General Hospital, Kaohsiung 813, Taiwan. Tel: 011886-7-342-2121 ext. 1510, Fax: 011-886-7-346-8056, E-mail: [email protected] vghks.gov.tw Received 8 January 2014; revised 26 February 2014; accepted 25 March 2014

Keywords: microRNA; miR-499a; polymorphism; progression; oral cancer; oral submucous fibrosis

Introduction In Taiwan, oral cancer is the fourth leading cancer in men and the top cancer in young male adults (25– 44 years old) (PROMOTION BOH, 2011). Although oral cancer can arise de novo, it is widely accepted that oral precancerous lesions (OPLs) have a potential to progress into malignant tumors (Pindborg et al, 1997; Warnakulasuriya et al, 2011). OPLs are defined as a morphologically altered tissue, including oral submucous fibrosis (OSF), oral leukoplakia (OL), oral erythroplakia, oral lichen planus, and others (Kramer et al, 1978; Mithani et al, 2007). OL and OSF are the most common forms of OPLs, and OSF has been reported almost exclusively among Asians (Humayun and Prasad, 2011). The malignant transformation rate of OL and OSF was found to be in the range of 7–42% (Tilakaratne et al, 2006; Yen et al, 2008). Oral squamous cell carcinoma (OSCC) is the most common oral malignancy, accounting for more than 90% of all oral cancers (Sharma et al, 2010). Metastasis is a major problem of treatment failure, leading to a poor prognosis for patients with OSCC. Therefore, monitoring the progression from OPLs to possible malignancy or diagnosis at an early stage of disease is vital in the prevention and treatment of OSCC. MicroRNAs (miRNAs) are small non-protein-coding RNAs of 21–23 nucleotides, and their function in cellular physiology, development, and disease is to negatively regulate the expression of protein-coding genes (Pan et al, 2013). Depending on their respective target genes, miRNAs can act as tumor-suppressive or oncogenesis agents in carcinogenesis. Therefore, aberrant expression of miRNAs is frequently associated with

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many diseases, including heart disease, neurological disorders, and cancer (Croce and Calin, 2005; Yang et al, 2009; Esteller, 2011). To date, several dysregulated miRNAs have been reported involving oral cancer progression, including let-7 family, miR-1, miR-9, miR10b, miR-21, miR-31, miR-133a, miR-137, miR-138 miR-143, miR-146a, miR-193a, miR-221, miR-222, miR-342, miR-346, miR-373, and miR-375 (Gorenchtein et al, 2012; Perez-Sayans et al, 2012; Gomes et al, 2013; Yoshizawa and Wong, 2013). Substance use, such as betel quid (BQ) chewing, cigarette smoking, and alcohol drinking have been identified as major risk factors for OPLs and oral cancer (Ko et al, 1995; Chen et al, 2008; Lian Ie et al, 2013). However, only a small portion of BQ chewers, smokers, and drinkers develop OPLs and oral cancer. Genetic predisposition may explain such an individual variability. A variant in the pre-miRNA sequence may influence susceptibility to oral cancer, affecting the transcriptional activity of the primary transcript and disturbing the processing of mature miRNAs, or altering their target genes (Jazdzewski et al, 2008, 2009; Xu et al, 2010; Kogo et al, 2011; Alshatwi et al, 2012; Vinci et al, 2013). The miR-499a T>C singlenucleotide polymorphism (SNP) was shown to be associated with human cancer, such as lung cancer, breast cancer, gastric cancer, prostate cancer, head-and-neck cancer, cervical squamous cell carcinoma, and gallbladder cancer (Hu et al, 2009; Liu et al, 2010; Zhou et al, 2011, 2012; Alshatwi et al, 2012; Chu et al, 2012; Xiang et al, 2012; Guan et al, 2013; Hong et al, 2013; Vinci et al, 2013). Although the association between miR-499a SNP and susceptibility to oral cancer has been investigated, the conclusions were controversial (Liu et al, 2010; Chu et al, 2012). It remains unclear whether miR-499a T>C SNP is associated with oral cancer progression, and little is known about why miR-499a T>C SNP correlates with the oral cancer risk. Evaluation of the relationship between SNPs and miRNA expression might improve our understanding of miRNA biogenesis or the potential contribution of the SNP to disease etiology and progression. In this study, we investigated the association between miR499a T>C (rs3746444) SNP and susceptibility to OL, OSF, and OSCC. The effect of interactions between miR499a T>C SNP and substance use on the risk of OSCC was also evaluated. By examining the expression levels of miR-499a in the paired OSCC and adjacent normal tissues, we evaluated the association of miR-499a expression with the various genotypes and clinicopathological development of OSCC.

Materials and methods Ethics statement This study protocol was independently reviewed and approved by the Institutional Review Board of the Kaohsiung Veterans General Hospital (Kaohsiung, Taiwan; IRB number: VGHKS13-CT3-08). The requirements for written informed consent from subjects were waived by the Institutional Review Board of the Kaohsiung Veterans General Hospital because all the data and specimens were previously collected and analyzed anonymously. Oral Diseases

Study subjects Two frequency-matched case-control studies were carried out in this study. In the two case-control studies, all case patients with newly diagnosed, previously untreated, and pathologically confirmed primary OSCC were recruited between January 2004 and November 2012 from the Departments of Otolaryngology and Dentistry, at Kaohsiung Veterans General Hospital (KSVGH). In the first case-control study, a total of 598 male subjects who habitually chewed BQ were recruited, including 204 healthy controls, 169 OL cases, 80 OSF cases (10 cases with OSF and OL in the same time), and 155 OSCC cases, to evaluate whether the SNP in miR-499a (T>C) sequence was associated with the occurrence of BQ-related OL, BQrelated OSF, and BQ-related OSCC. The healthy controls, OL cases, and OSF cases were recruited from the oral health screen clinic at the Department of Otolaryngology, KSVGH, and from the oral health screen campaigns for vehicle drivers, hardware workers, and cleaners held by the Kaohsiung city government or Department of Otolaryngology, KSVGH, between 2004 and 2012. The selection criteria for healthy controls included the absence of history of cancer and OPLs, and negative finding for OPLs and oral cancer screening. Healthy controls and three case groups (OL, OSF, and OSCC) were frequencymatched on age ( 5 years) and years of BQ chewing. In the second case-control study, a total of 512 newly pathologically confirmed primary OSCC case patients and 668 cancer-free controls were recruited to evaluate whether the SNP in miR-499a (T>C) sequence was associated with the occurrence of OSCC, even stratified by the status of BQ chewing, cigarette smoking, and alcohol drinking. There were 668 non-cancer controls recruited from the inpatients or outpatients at the Departments of Orthopedics, Ophthalmology, CV, GU, GS, Otolaryngology, or Dentistry, KSVGH. The selection criteria for controls included no individual history of cancer and OPLs, which were confirmed by the screening physicians. Control subjects were frequency-matched to the cases on gender and age ( 5 years). A BQ chewer was defined as a person who had chewed at least one BQ per day for at least 1 year or more. Packyears of BQ consumption were calculated using the following: pack-years = (mean number of BQs chewed per day/20 BQs) 9 number of years chewed. Light and heavy BQ chewers were categorized by using the median values of BQ consumption (pack-years) in controls as the cutoff. A smoker was defined as a person who had smoked at least a cigarette per day for at least 1 year or more. Packyears of cigarette consumption were calculated using the following: pack-years = (mean number of cigarettes smoked per day/20 cigarettes) 9 number of years smoked. Light and heavy smokers were categorized by using the median value of cigarette consumption (pack-years) in controls as the cutoff. A drinker was defined as a person who had drunk at least once a week for more than 1 year. Gram-years were calculated using the following: gram-years = mean gram of alcohol drank per day 9 number of years drank. Light and heavy drinkers were also categorized by using the median value of alcohol consumption (gram-years) in controls as the cutoff. In

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addition, pathological TNM classification was determined at the time of the initial resection of the tumor in accordance with the guidelines of the 2002 American Joint Committee on Cancer (AJCC) system. Polymorphism genotyping The QIAamp DNA midi kit (Qiagen Sciences, Germantown, MD, USA) was used to extract and purify the genomic DNA from the whole-blood samples. The genotypes of miR-499a T>C (rs3746444) were identified using the TaqMan real-time polymerase chain reaction (PCR) method and then analyzed using the ABI PRISM 7500 Sequence Detection System (Applied Biosystems, Foster City, CA, USA) in a 96-well format. Each PCR amplification was performed in 10 ll of reaction mixture containing 20 ng DNA, 5 ll 29 TaqMan Universal PCR Master Mix (Applied Biosystems), 0.25 ll 409 Primer/Probe mixture, and ddH2O. The PCR program was the following: 95°C for 10 min, and 40 cycles of 15 s at 95°C, and 1 min at 60°C. A single no-DNA-template control in each 96-well plate was used for quality control. The allelic-specific fluorescence data from each plate were analyzed using the SDS v1.3.1 software (Applied Biosystems, 2005) to determine the genotype of each sample. The quality control procedures were implemented to ensure genotyping accuracy in our laboratory. Initially, 100% of the samples of the less prevalent genotypes and 5% of the samples of the more prevalent genotype were randomly selected and run in duplicate to verify the genotyping. The results were 100% concordant with the initial results. Then, a senior researcher independently reviewed all of the absolute quantification curves obtained with the fluorescence data from the TaqMan assays. If the genotyping is different from the previous one, the samples were run in duplicate to ensure the accuracy of the genotyping. Clinical samples for RNA extraction Sixty-three paired tumor and adjacent normal tissue samples were obtained from patients with OSCC who underwent surgical resection at the Department of Dentistry or Otorhinolaryngology, Kaohsiung Veterans General Hospital. In addition, all subjects had not received radiotherapy or chemotherapy or any other treatment before the operation. Tumor and adjacent normal tissue samples, which were at least 2 cm distal to tumor margins, were obtained after tumor resection and snap-frozen in liquid nitrogen within minutes in the operation room. Frozen tissue was screened by the attending pathologist for the presence of tumor cells and homogenized before DNA and RNA extraction. The total RNA and DNA of the 63 paired tissues were extracted using a TRIzol reagent (Invitrogen, Carlsbad, CA, USA). Briefly, tissue samples were homogenized in 1 ml of TRIzol reagent and mixed with 0.2 ml chloroform to extract protein. Then, RNA was precipitated using 0.5 ml isopropanol. DNA was extracted with back extraction buffer (4M guanidine thiocyanate, 50 mM sodium citrate, and 1M Tris). Finally, DNA was precipitated using EtOH. The concentration, purity, and amount of total RNA and DNA were determined using a Nanodrop 1000

spectrophotometer (Nanodrop Technologies Inc., Wilmington, DE, USA).

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Stem-loop RT-PCR One microgram of total RNA was reverse-transcribed using a stem-loop RT reaction with miR-499a RT primers and SuperScript III Reverse Transcriptase (Invitrogen). The reaction was performed for 30 min at 16°C, followed by (20°C/30 s, 42°C/30 s, 50°C/1 s), for 50 cycles. Finally, the enzyme was inactivated with incubation at 85°C for 5 min. Gene expression was detected using a SYBR Green I assay (Applied Biosystems), and the expression levels of miR-499a were normalized to that of U6 (DCt = target microRNA Ct-U6 Ct). The individual primers used in this study were as follows: miR-499a-5p-RT: 50 -CTCAACTGGTGTCGTGGAGTCGGCAATTCAGT TGAGAAACATCA-30 miR-499a-5p-GSF: 50 -CGGCGGTTAAGACTTGCAGTG-30 miR-499a-3p-RT: 50 -CTCAACTGGTGTCGTGGAGTCGGCAATTCAGT TGAGAGCACAGA-30 miR-499a-3p-GSF(A): 50 -CGGCGGAACATCACAGCAAGT-30 miR-499a-3p-GSF(G): 50 -CGGCGGAACGTCACAGCAAGT-30 Statistical analysis For the tested polymorphism, departure from the HardyWeinberg equilibrium in the control subjects was evaluated by a chi-square test with one degree of freedom. Univariate analysis was first performed to calculate the crude odds ratios (CORs) and their 95% confidence intervals (CIs) of selected demographic and substance use’s factors, as well as genetic polymorphisms among case and control subjects by logistic regression analysis. Multiple logistic regression analysis was used to evaluate the association between genotypic and allelic type in the miR-499a T>C with OSCC risk, by adjusting various confounders, such as age, sex, ethnicity, the pack-years of BQ chewing and cigarette smoking, as well as the gram-years of alcohol drinking. In addition, the Wilcoxon matched-pairs signedranks test was used to evaluate the expression levels of miR-499a between the paired normal and tumor tissues. The Mann-Whitney U test was used for comparison of miR-499a levels between two different genotypes in the same tissue type. The chi-square test was used to compare the frequency distribution of miR-499a genotype between two different clinicopathological outcomes. The t-test or Mann-Whitney U test was used to compare the expression levels of miR-499a between two different clinicopathological outcomes. In addition, the log-rank test and Cox proportional hazards model were used to evaluate the impact of different genotype of miR-499a or miR-499a expression (high vs low) on OSCC patient’s disease-specific survival and disease-free survival. All statistical analyses were performed using the SPSS software package (version 12.0, SPSS Inc., Chicago, IL, USA). Results of P < 0.05 were considered statistically significant.

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Results Association between miRNA-499a (T>C) rs3746444 SNP and susceptibility to BQ-related OL, BQ-related OSF, and BQ-related OSCC In this study, we recruited 169 OL, 80 OSF, 155 OSCC patients, and 204 healthy control subjects with BQ chewing habits. The demographic characteristics and frequencies of substance use for the subjects are shown in Table 1. All case patients and control subjects were well matched on age, sex, and substance use, and no significant difference was observed for case patients and control subjects (P > 0.05). The genotyping of the SNP in miR-499a T>C was successfully performed in all case and control subjects. The genotypic and allelic frequencies of miR499a T>C SNP for the control and three case groups (OL, OSF, and OSCC) are shown in Table 2. The genotype distribution of miR-499a T>C SNP in the control subjects agreed with the Hardy-Weinberg equilibrium (P = 0.130). A significantly increased risk of BQ-related OSF was associated with T/C+C/C of miR-499a T>C SNP, compared with the wild genotype T/T [adjusted odds ratio (AOR) = 1.84, 95% confidence interval (CI) = 1.05–3.20, P = 0.032]. The C allele at miR-499a T>C SNP was significantly correlated with an increased risk of BQ-related OSF (AOR = 1.91, 95% CI = 1.19–3.07, P = 0.007) (Table 2). However, the genotypic and allelic frequencies of miR-499a SNP did not differ significantly between BQrelated OL and BQ-related OSCC. Association between miRNA-499a (T>C) rs3746444 SNP and susceptibility to OSCC Betel quid chewing has been reported as a critical causal factor of oral cancer, which may result in a non-significant result between miR-499a T>C SNP and risk of OSCC (Table 2). Considering that BQ chewing may modify genetic susceptibility to OSCC, we included all control subjects and patients with OSCC who had ever or never chewed BQ for stratification analysis. As shown in Table 3, the subjects of the case-control study consisted of 512 pathologically proved OSCC case patients and 668 sex- and age-matched cancer-free control patients. As expected, BQ chewing, cigarette smoking, and alcohol drinking were associated with an increased risk of OSCC (P < 0.001) (Table 3). Specifically, a far greater proportion of heavy BQ chewing subjects and light BQ chewing subjects was observed in case patients than those in control patients, as shown in Table 3 (heavy BQ chewing: COR = 14.28, 95% CI: 10.42–19.56, P < 0.001; light BQ chewing: COR = 5.69, 95% CI: 4.03–8.04, P < 0.001). This result indicated that BQ chewing is a highly influential factor, resulting in an increased risk of OSCC in a dose-dependent manner (P for linear trend C SNP in the control patients was in agreement with the Hardy-Weinberg equilibrium (P = 0.119). Notably, the variant T/C and T/C+C/C genotypes at miR-499a SNP were associated with a significantly decreased risk of OSCC (T/C genotype: AOR = 0.69, 95% CI = 0.5–0.96, P = 0.028; and T/C+C/ Oral Diseases

C genotypes: AOR = 0.71, 95% CI = 0.51–0.97, P = 0.033). The C allele at miR-499a SNP was correlated with a decreased risk of OSCC (AOR = 0.75, 95% CI = 0.57–0.99, P = 0.045) (Table 4). The interactions between BQ chewing, cigarette smoking, or alcohol drinking and miR-499a T>C SNP on the risk of OSCC were analyzed in both genotypic and allelic type models (Table 5). No interactions were found between status of cigarette smoking and genotype on risk of OSCC. A borderline significant interactions were found between BQ chewing (P for interaction = 0.068) or alcohol drinking (P for interaction = 0.098) and genotype of miR-499a SNP. Nevertheless, significant interactions were found between status of BQ chewing and allelic type of miR-499a SNP on the risk of OSCC (P for interaction = 0.026). The influence of C allele on risk of OSCC appeared to be greater in non-BQ chewers (with a 50% reduction of risk, P = 0.007) than that in BQ chewers (with a 3% reduction of risk, P = 0.86). These results suggest that the status of BQ chewing might modulate the impact of miR-499a allelic type (P = 0.026) or genotype (P = 0.068) on the risk of OSCC. To further explore the impacts of the miR-499a T>C SNP on the prognosis of OSCC, we classified OSCC patients into two groups: one subgroup with T/T genotype (394 of 512 patients with OSCC) and the other group with the T/C+C/C genotype (118 of 512 patients with OSCC). We found no significant difference between miR-499a SNP genotypes and clinicopathological features (Table S1), disease-specific survival (P = 0.171), or disease-free survival (P = 0.325, Figure S1). Association of miR-499a expression with the genotype of miRNA-499a T>C (rs3746444) SNP in the paired OSCC and adjacent normal tissues As shown in Figure 1a, miRNA-499a T>C SNP was located at the 3p arm of miR-499a. We further examined the relative expression levels of miR-499a-5p and -3p using a real-time PCR approach in 63 paired OSCC and adjacent normal tissues and showed that expression levels of miR-499a-3p were not detected in most of the oral cancer samples (Figure S2). Consistent with miRBase data, we found that 5p arm usage of miR-499a is dominant during maturation. As compared to the corresponding adjacent normal tissues, more patients (44/63, 69.8%) had a decreased expression of miR-499a-5p in OSCC tissues by the use of McNemar test (P = 0.002, Figure 1b). In addition, a significant decrease (P = 0.001) of miR-499a-5p in 63 OSCC tissues was also found by the use of t-test (Figure 1c). We further analyzed the relationship between the expression level of miR-499a-5p and the clinicopathological features and survival. As shown in Table 6, low expression of miR-499a-5p was associated with the larger tumor size (Z = 2.007, P = 0.045) and the advanced stage of disease (t = 1.768, P = 0.082, a borderline significance). In addition, the expression levels (with cutoff set at the 50th percentile, low vs high) were not correlated with the disease-specific survival and disease-free survival (data not shown).

90 (53.3) 79 (46.7) 47 (27.8) 63 (37.3) 59 (34.9)

99 (48.5)

55 (27.0) 74 (36.3) 75 (36.8)

(28.4) (32.0) (25.4) (14.2)

105 (51.5)

48 54 43 24 88 (52.1) 81 (47.9)

(27.0) (29.9) (29.4) (13.7)

46.3  11.1

100 (49.0) 104 (51.0)

55 61 60 28

47.0  11.2

OLa,b (n = 169) Number (%)

(26.3) (30.0) (33.8) (10.0)

25 (31.3) 26 (32.5) 29 (36.3)

37 (46.3)

43 (53.8)

36 (45.0) 44 (55.0)

21 24 27 8

46.6  10.6

OSFa,c (n = 80) Number (%)

b

(25.8) (29.7) (33.5) (11.0)

33 (21.3) 51 (32.9) 71 (45.8)

66 (42.6)

89 (57.4)

77 (49.7) 78 (50.3)

40 46 52 17

46.5  9.1

OSCCa,d (n = 155) Number (%)

All subjects are males. OL, oral leukoplakia. c OSF, oral submucous fibrosis. There are 10 cases with OL and OSF in the same time. d OSCC, oral squamous cell carcinoma. e COR, crude odds ratio; p-value is estimated by logistic regression analysis. f P-value is estimated by t-test. g P-value is estimated by Mann-Whitney U test. h Twenty betel quids per pack. i Twenty cigarettes per pack.

a

Age mean  s.d. (years) < 40 40–49 50–59 ≧60 BQ chewing (packh-years) Light (≦ 24.50) Heavy (>24.50) Smoking (packi-years) Never smoker Light (≦29.75) Heavy (>29.75) Drinking (gram-years) Never drinker Light (≦1071.43) Heavy (>1071.43)

Factor/category

BQ controlsa (n = 204) Number (%)

1.00 1.00 (0.60–1.67) 0.92 (0.55–1.55)

0.93 (0.62–1.40)

1.00

1.00 0.89 (0.59–1.33)

1.00 1.01 (0.60–1.73) 0.82 (0.47–1.42) 0.98 (0.50–1.92)

CORe (95% CI)

0.989 0.754

0.731

0.557

0.958 0.483 0.958

0.537f

P-valuee

OL vs BQ controls

1.00 0.77 (0.40–1.48) 0.85 (0.45–1.61)

0.91 (0.54–1.53)

1.00

1.00 1.18 (0.70–1.98)

1.00 1.03 (0.52–2.05) 1.18 (0.60–2.32) 0.75 (0.29–1.90)

CORe (95% CI)

0.438 0.619

0.729

0.542

0.932 0.635 0.542

0.784f

P-valuee

OSF vs BQ controls

Table 1 Crude odds ratios for BQ controls and BQ-related OL, OSF, and OSCC cases according to selected demographic and lifestyle risk factors

1.00 1.15 (0.66–2.01) 1.58 (0.92–2.71)

0.79 (0.52–1.20)

1.00

1.00 1.03 (0.68–1.56)

1.00 1.04 (0.59–1.81) 1.19 (0.69–2.07) 0.84 (0.40–1.73)

CORe (95% CI)

0.628 0.098

0.263

0.905

0.899 0.533 0.627

0.527g

P-valuee

OSCC vs BQ controls

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Oral Diseases

Number (%)

152 51 1 355 53

Genotype

T/T T/C C/C T allele C allele

121 47 1 289 49

(71.6) (27.8) (0.6) (85.5) (14.5)

(61.3) (32.5) (6.3) (77.5) (22.5)

49 26 5 124 36

(61.3) (32.5) (6.3) (77.5) (22.5)

Number (%)

49 26 5 124 36

Number (%)

111 (71.6) 39 (25.2) 5 (3.2) 261 (84.2) 49 (15.8)

Number (%)

111 (71.6) 39 (25.2) 5 (3.2) 261 (84.2) 49 (15.8)

Number (%)

OSCCa,d (n = 155)

0.547

1.00 1.14 (0.75–1.73)

P-valuef

AORf (95% CI)

0.532

0.551

1.00 1.14 (0.75–1.73)

1.00 1.16 (0.73–1.84)

0.528

e

1.00 1.16 (0.73–1.84)

P-value

OL vs BQ controls COR (95% CI)

e

1.00 1.91 (1.19–3.07)

1.00 1.84 (1.05–3.20)

AORf (95% CI)

1.00 1.95 (1.22–3.11)

1.00 1.85 (1.07–3.20)

COR (95% CI)

e

0.007

0.032

P-valuef

0.006

0.028

P-value

OSF vs BQ controls e

1.00 1.26 (0.82–1.93)

1.00 1.16 (0.72–1.87)

AORf (95% CI)

1.00 1.26 (0.83–1.91)

1.00 1.16 (0.72–1.85)

CORe (95% CI)

0.285

0.536

P-valuef

0.285

0.539

P-valuee

OSCC vs BQ controls

Bold values denotes statistically significant. a All subjects are males. b OL, oral leukoplakia. c OSF, oral submucous fibrosis. There are 10 cases with OL and OSF in the same time. d OSCC, oral squamous cell carcinoma. e COR, crude odds ratio; p-value is estimated by logistic regression analysis. f AOR, adjusted odds ratio, adjusted for age (40–49, 50–59, ≧60 vs 24.50 vs ≦24.50), the pack-years of smoking (>29.75 vs ≦29.75 and never smoker), and the gram-years of drinking (1–1071.43, >1071.43 vs never drinker); p-value is estimated by multiple logistic regression analysis.

(74.5) (25.0) (0.5) (87.0) (13.0)

Number (%)

(71.6) (27.8) (0.6) (85.5) (14.5)

152 51 1 355 53

T/T T/C C/C T allele C allele

121 47 1 289 49

Number (%)

Number (%)

miR-499a (T>C) Genotype

OSFa,c (n = 80)

200

(74.5) (25.0) (0.5) (87.0) (13.0)

OLa,b (n = 169)

BQ controlsa (n = 204)

Table 2 Crude and adjusted odds ratios for BQ-related OL, OSF, and OSCC according to various genotypes and allelic types of miR-499a (T>C) rs3746444

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Table 3 Crude odds ratios for cancer-free controls and OSCC cases according to selected demographic and lifestyle risk factors Controls (n = 668)

OSCCa (n = 512)

Factor/category

Number (%)

Number (%)

CORb (95% CI)

Age mean  s.d. (years) < 40 40–49 50–59 ≧60 Sex Female Male BQ chewing (pack d-years) Never chewing Light (0.21–13.71) Heavy (>13.71)

52.8  11.5 67 (10.0) 191 (28.6) 250 (37.4) 160 (24.0)

52.8  10.9 51 (10.0) 148 (28.9) 186 (36.3) 127 (24.8)

1.00 1.02 (0.67–1.55) 0.98 (0.65–1.47) 1.04 (0.68–1.61)

40 (6.0) 628 (94.0)

37 (7.2) 475 (92.8)

1.00 0.82 (0.52–1.30)

492 (73.7) 88 (13.2) 88 (13.2)

112 (21.9) 114 (22.3) 286 (55.9)

1.00 5.69 (4.03–8.04) 14.28 (10.42–19.56) P for linear trend

< 0.001 < 0.001 < 0.001

Smoking (pack e-years) Never smoker Light (0.15–24.0) Heavy (>24.0)

259 (38.8) 204 (30.5) 205 (30.7)

90 (17.6) 142 (27.7) 280 (54.7)

1.00 2.00 (1.45–2.76) 3.93 (2.91–5.31) P for linear trend

< 0.001 < 0.001 < 0.001

Drinking (gram-years) Never drinker Light (0.53–740.57) Heavy (>740.57)

423 (63.3) 122 (18.3) 123 (18.4)

168 (32.8) 117 (22.9) 227 (44.3)

1.00 2.36 (1.73–3.21) 4.76 (3.58–6.33) P for linear trend

< 0.001 < 0.001 < 0.001

P-valueb 0.972c 0.934 0.913 0.849 0.394

Bold values denotes statistically significant. a OSCC, oral squamous cell carcinoma of the oral cavity. b COR, crude odds ratio; p-value is estimated by logistic regression analysis. c P-value is estimated by t-test. d Twenty betel quids per pack. e Twenty cigarettes per pack.

We further investigated whether the expression levels of miR-499a-5p were altered by various genotypes of miR-499a SNP. According to the genotyping results, 49 patients were T/T genotype, 12 were T/C genotype, and two were C/C genotype. In addition, the genotypes of genomic DNA, normal tissue DNA, and cancer tissue DNA were completely identical. The expression levels of miR-499a-5p for patients of T/T genotype were significantly higher than those of the T/C+C/C genotype in adjacent normal tissues, but above differences were not observed in the 63 corresponding OSCC tissues (Figure 2). In addition, the miR-499a-5p expression levels for T/T genotype in OSCC tissues were significantly decreased as compared to those with T/T genotype in corresponding adjacent normal tissues (P = 0.001), but above expression differences were not observed for the T/C+C/C genotypes between 63 paired tissues (Figure 2). Therefore, downregulation of miR-499a-5p was observed correlated with the TT genotype (P = 0.001) and tumor progression (n = 63, P = 0.001), especially for those with the advanced stage of disease (P = 0.016) and large tumor size (P = 0.004).

Discussion In the present study, we found that the T/C + C/C genotypes and C allele (especially the C allele) of miRNA499a SNP increased the risk of BQ-related OSF, but not for BQ-related OL and BQ-related OSCC. Conversely, the T/C +C/C genotypes and C allele (especially C allele)

decreased the susceptibility to OSCC, particularly the non-BQ-related OSCC. The T/T genotype of miR-499a SNP decreased the miR-499-a-5p expression when the normal tissues progressed to OSCC tissues (Figure 2). Therefore, miR-499a-5p was significantly downregulated in oral cancer tissue (n = 63, P = 0.001), especially for those with the advanced stage of disease (P = 0.016) and large tumor size (P = 0.004). The expression levels of miR-499a-5p in T/T genotype were significantly higher than those in T/C+C/C genotypes for normal tissues (n = 63). However, no evidence for any correlation between genotype and miR-499a-5p expression was observed in tumor tissues. To the best of our knowledge, the T/C+C/C genotypes or C allele correlated with the increased risk of BQ-related OSF but correlated with the decreased risk of non-BQ-related OSCC has not been previously reported. Genetic variants occurring in the pre-miRNA sequence may influence the miRNA maturation process or alter the miRNA-target interaction. Numerous studies have revealed that miRNA polymorphism contributes to the development of precancer or cancer, whereas few explained why polymorphism of miRNA is correlated with cancer susceptibility. The rs3746444 occurring at the seed region of the miR-499a-3p may directly alter the target selection of miRNA or arm selection of miR-499a. The miRBase showed that the expression level of miR-499a-3p was lower than that of miR-499a-5p. Our previous studies indicated that the 5p or 3p arm usage of some miRNAs is Oral Diseases

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Table 4 Crude and adjusted odds ratios for OSCC according to various genotypes and allelic types of miR-499a (T>C) rs3746444 Controls (n = 668)

OSCCa (n = 512)

miRNA-499a (T>C)

Number (%)

Number (%)

T/T T/C C/C T/T T/C+C/C T allele C allele

464 192 12 464 204 1120 216

394 109 9 394 118 897 127

(69.5) (28.7) (1.8) (69.5) (30.5) (83.8) (16.2)

CORb (95% CI)

(77.0) (21.3) (1.8) (77.0) (23.1) (87.6) (12.4)

1.00 0.67 0.88 1.00 0.68 1.00 0.73

P-valueb

(0.51–0.88) (0.37–2.12)

0.004 0.781

(0.52–0.89)

0.004

(0.58–0.93)

AORc (95% CI) 1.00 0.69 0.93 1.00 0.71 1.00 0.75

0.010

P-valuec

(0.50–0.96) (0.32–2.69)

0.028 0.893

(0.51–0.97)

0.033

d

0.045

(0.57–0.99)

Bold values denotes statistically significant. a OSCC, oral squamous cell carcinoma of the oral cavity. b COR, crude odds ratio; p-value is estimated by logistic regression analysis. c AOR, adjusted odds ratio, adjusted for sex (male vs female), age (40–49, 50–59, ≧60 vs 13.71 vs never chewing), cigarette smoking (0.15–24.0, >24.0 vs never smoking), and alcohol drinking (0.53–740.57, >740.57 vs never drinker); p-value is estimated by multiple logistic regression analysis. d Because allelic type of miRNA-499a was correlated with volume of alcohol drinking, we did not put alcohol drinking into the multiple logistic regression model to prevent the occurrence of overadjustment. Table 5 Crude and adjusted odds ratios for OSCC according to genotypes and allelic types of miR-499a (T>C) rs3746444 and substance use 512 OSCC cases vs 668 Controls Cases/controls Factor/category Genotypic model

T/T

Crude OR (95% CI)

Adjusted OR (95% CI)

P-valuea

T/T

T/C, C/C

0.46 (0.28–0.78) 0.89 (0.59–1.33)

0.004 0.575

1.00 1.00

T/C, C/C

T/T

T/C, C/C

92/335 302/129

20/157 98/47

1.00 1.00

P-valueb

P for interaction

0.49 (0.28–0.85) 0.88 (0.58–1.32)

0.010 0.525

0.068

BQ chewing Non-BQ chewing BQ chewing Cigarette smoking Never smoking Smoking Alcohol drinking Never drinking Drinking

68/178 326/286

23/83 95/121

1.00 1.00

0.73 (0.42–1.24) 0.69 (0.50–0.94)

0.244 0.019

1.00 1.00

0.69 (0.36–1.31) 0.69 (0.48–1.00)

0.254 0.052

0.999

133/283 261/181

35/140 83/64

1.00 1.00

0.53 (0.35–0.81) 0.90 (0.62–1.31)

0.004 0.582

1.00 1.00

0.52 (0.32–0.86) 0.90 (0.58–1.38)

0.010 0.622

0.098

Allelic model

T allele

C allele

T allele

C allele

P-valuea

T allele

P-valueb

P for interaction

204/816 693/304

20/168 107/48

1.00 1.00

0.48 (0.29–0.78) 0.98 (0.68–1.41)

0.003 0.905

1.00 1.00

0.50 (0.30–0.83) 0.97 (0.67–1.41)

0.007 0.867

0.026

158/431 739/689

24/91 103/125

1.00 1.00

0.85 (0.67–1.08) 0.88 (0.76–1.01)

0.184 0.066

1.00 1.00

0.67 (0.37–1.19) 0.77 (0.55–1.08)

0.166 0.129

0.777

299/698 598/422

37/148 90/68

1.00 1.00

0.58 (0.40–0.86) 0.93 (0.67–1.31)

0.006 0.693

1.00 1.00

0.59 (0.38–0.92) 0.93 (0.64–1.37)

0.020 0.727

0.122

BQ chewing Non-BQ chewing BQ chewing Cigarette smoking Never smoking Smoking Alcohol drinking Never drinking Drinking

C allele

Bold values denotes statistically significant. a P-value is estimated by logistic regression analysis. b P-value is adjusted for sex (male vs female), age (40–49, 50–59, ≧60 vs 13.71 vs never chewing), cigarette smoking (0.15–24.0, >24.0 vs never smoking), and alcohol drinking (0.53–740.57, >740.57 vs never drinker); p-value is estimated by multiple logistic regression analysis.

significantly altered during the progression of cancers such as breast cancer and gastric cancer (Chang et al, 2012; Li et al, 2012). Furthermore, Landgraf et al reported that miR-499a-3p was expressed in an invasive breast cancer cell line (Landgraf et al, 2007). Therefore, we examined both miR-499a-3p and miR-499a-5p expression in oral cancer tissues and the corresponding adjacent normal tissues in this study. Our data indicated that the 5p arm rather than 3p arm of miR-499a is selected to load into RISC during maturation and rs3746444 did not influence Oral Diseases

arm selection of miR-499a in oral cancer (Figure S2). Because miR-499a-3p is rare in most OSCC tissues, the target selection of miR-499a-3p did not contribute to rs3746444 and lead to a risk of OSCC. In the adjacent normal tissues, we found that the expression levels of miR-499a-5p in T/T genotype were significantly higher than those in T/C+C/C genotypes for normal tissues (n = 63). Conversely, no significant difference in miR499a-5p between T/T and T/C+C/C genotypes was observed in oral cancer tissues. Therefore, we found that

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(a)

(b)

Figure 1 Expression levels of miR-499a-5p in OSCC tissues. (a) Schema of hairpin loop structure of pre-miR-499a sequence. An arrowhead indicates the location of rs3746444 (T>C) polymorphism within the seed region of miR-499a. Mature sequences of miR-499a-5p and miR-499a-3p are underlined. (b) The changes in expression levels of miR-499a-5p between OSCC and the corresponding adjacent normal tissues from 63 patients. U6 was used as an internal control to normalize the expression levels of miR-499a-5p (△Ct = Ct miR-499a-5p — Ct U6). All samples were examined in triplicate and analyzed using the McNemar test. (c) The expression levels of miR-499a-5p in the OSCC tissues from 63 patients were compared to those of the corresponding adjacent normal tissues. U6 was used as an internal control to normalize the expression levels of miR-499a-5p (△Ct = Ct miR-499a-5p — Ct U6). All samples were analyzed using a Student’s t-test

(c)

genotype had impact on risk of OSCC, but had not any impact on OSCC patients’ clinicopathological features, recurrence, and survival. Oral submucous fibrosis is a chronic inflammatory disease characterized by epithelial atrophy and fibrosis in the submucosa of oral tissues (Le et al, 1996; Khan et al, 2012). Epidemiological data and intervention studies suggest that areca nut (main part of BQ) is the main etiological factor for OSF (Sinor et al, 1990; Sumeth Perera et al, 2007; Khan et al, 2012). We found that a lower miR-499a-5p production genotype (T/C+C/C) was associated with an increased risk of BQ-related OSF. miR-499a has been reported to repress EST1 expression (Wei et al, 2012). Recently, a role for EST1 in fibrosis has been revealed in promoting profibrotic gene expression, such as connective tissue growth factor (CCN2) and collagen type I (Trojanowska, 2000; Nakerakanti et al, 2006; Van Beek et al, 2006; Hahne et al, 2011). ETS-1 regulates the CCN2 promoter and mediates the ability of TGF-b to induce CCN2 (Nakerakanti et al, 2006; Van Beek et al, 2006). In addition, genetic polymorphisms of

a couple genes of collagen type I, such as collagen 1A1 and collagen 1A2, have been reported to predispose to OSF (Chiu et al, 2002). For BQ chewers, the profibrotic gene expression might be more increased for carriers of T/C+C/C genotypes than for those of T/T genotype. Therefore, T/C+T/T genotype correlated with the increased risk of BQ-related OSF in this study. Additionally, CCN2 plays a positive role in tumorigenesis, where it may contribute to the formation of reactive stroma by promoting excessive matrix remodeling and tumor angiogenesis (Planque and Perbal, 2003; Nakerakanti et al, 2006). However, the association between T/C+T/T genotype and risk of BQ-related OSCC was not found in this study, except for the protection from the development of non-BQ-related OSCC, whose results were quite confusing. Therefore, potentially distinct mechanisms underlie progression of BQ-related OSCC or non-BQ-related OSCC, such as a distinct gene expression background between various OPLs and OSCC by different substance use, which need to be further evaluated in the near future. Oral Diseases

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Table 6 The relationship between expression levels of miR-499a-5p and clinicopathological data of patients with OSCC miR-499a-5p (n = 63) Variables Cell differentiation Well Moderate, poor AJCC pathological I, II III, IV T classification T1, T2 T3, T4 N classification N0 N1, N2

No (%)

Mean  s.d.

Statistic

P-valuea

9 (14.3) 54 (85.7) stage 27 (42.9) 36 (57.1)

8.77  2.74 9.59  2.59

t = 0.873

0.386

8.82  3.13 9.97  2.04

t = 1.768

0.082

31 (49.2) 32 (50.8)

8.68  3.18 10.25  1.59

Z = 2.007

0.045b

44 (69.8) 19 (30.2)

9.46  2.71 9.51  2.40

t = 0.059

0.953

Bold values denotes statistically significant. a P-value is estimated by Student’s t-test. b P-value is estimated by Mann-Whitney U test.

Figure 2 Expression of miR-499a-5p in OSCC and corresponding adjacent normal tissues according to the genotype. Relative expression levels of miR-499a-5p were examined in 63 OSCC tissues and corresponding adjacent normal tissues using real-time PCR. U6 was used as an internal control to normalize the expression levels of miR-499a-5p (△Ct = Ct miR-499a-5p — Ct U6). All samples were examined in triplicate and analyzed using a Student’s t-test. P < 0.05 was considered significant

Several genetic epidemiological studies have found the associations of common SNP rs3746444 in miR-499a with risk of various cancers (Hu et al, 2009; Liu et al, 2010; Zhou et al, 2011, 2012; Alshatwi et al, 2012; Chu et al, 2012; Xiang et al, 2012; Guan et al, 2013; Hong et al, 2013; Vinci et al, 2013). Unfortunately, the results in these studies are controversial and inconclusive, including oral, head-and-neck cancers. Chu et al carried out a casecontrol study in middle Taiwan and found that the T/C (AOR = 1.79, 95% CI: 1.16–2.75, P < 0.05) and C/C (AOR = 4.52, 95% CI: 1.24–16.48, P < 0.05) genotypes or C allele (AOR = 1.81, 95% CI: 1.23–2.65, P < 0.05) of miR-499a (T>C) was correlated with the increased risk of oral cancer (Chu et al, 2012). However, Liu et al’s study in USA demonstrated that the T/C + C/C genotypes (AOR = 0.83, 95% CI: 0.69–0.99, P < 0.05) of miR-499a Oral Diseases

(T>C) were correlated with the reduced risk of head-andneck cancers (Liu et al, 2010). Our association data of miR-499a (T>C) and OSCC are comparable with those of Liu et al’s study but completely contrary to those of Chu et al’s findings (Chu et al, 2012). Wang et al’s metaanalysis (Wang et al, 2012) revealed that the miR-499a SNP (rs3746444) C allele frequency in Caucasian controls (0.218) was higher than that in Asian controls (0.179). Among controls, the C allele frequency in our study (0.162) was comparable to Asians (Wang et al, 2012) in Wang et al’s study (0.179) and those Asians (Chinese + Japanese) in HapMap (0.167) [http://www.ncbi.nlm.nih. gov/projects/SNP/snp_ref.cgi?rs=3746444]. Two reasons may account for the opposite finding between our and Chu et al’s investigations. First, the C allele frequency in 470 controls of Chu et al’s study was significantly lower than those in our 668 controls (0.085 vs 0.162, v2 = 26.91, P < 0.001). Second, the frequency of C allele in 425 OSCC cases for Chu et al’ study was higher than those in our 512 OSCC cases (0.152 vs 0.124, v2 = 3.26, P = 0.071), although only marginal significance was found (Chu et al, 2012). miRNAs have been reported to be involved in prognosis of cancer through modulating cell proliferation, cell cycle, and cancer cell migration and invasion (Pan et al, 2013). Liu et al reported that miR-499a-5p was highly expressed in lymph node-metastasis CRC patients and promotes colon cancer migration and invasion via regulating the expression of forkhead box O4 (FOXO4) and programmed cell death 4 (PDCD4) (Liu et al, 2011). Conversely, miR-499a could repress EST1 expression and block the invasion and migration of HepG2 cells. EST1 plays a fundamental role in the extracellular matrix degradation, a process required for tumor cell invasion and migration. This implies that miR-499 may have a tumorsuppressive function in the pathogenesis of HCC, by targeting ETS1 (Wei et al, 2012). ETS1 was previously reported as an oncogene and contributed to migration and invasion of OSCC (Pande et al, 1999, 2001; Vairaktaris et al, 2007). Therefore, miR-499a may have dual and opposing functions, either as tumor-suppressor miR or as onco-miRs, in various cancer types. Our data showed that miR-499a-5p was downregulated in OSCC, and its low expression correlated with the large size of tumor (P = 0.045) and the advanced stage of disease (P = 0.082, only a borderline significance). We suggest that miR-499a might play a tumor-suppressive role in prognosis, by targeting ETS1 expression in OSCC progression. However, the detailed mechanism of miR-499a participation in oral cancer progression needs further investigation. There are several limitations in this study. Firstly, we did not recruit the OPLs (OL + OSF) case patients who were non-BQ chewers. Therefore, stratified analysis by BQ chewing status was not carried out to identify potent interaction between miR-499a T>C and status of BQ chewing on risk of OPLs, which had been carried out for interaction of SNP and BQ chewing on risk of OSCC in this study. Secondly, we did not collect the OL and OSF tissues and the corresponding adjacent normal tissues to evaluate the expression levels of miR-499a-5p; therefore, the assay results of the tumor adjacent normal tissues cannot represent the OSF

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tissues. Thirdly, the real function of miR-499a-5p in OSCC has not been carried out in this study. In conclusion, a lower miR-499a-5p production genotypes T/C+C/C were correlated with an increased risk of BQ-related OSF but a decreased risk of OSCC, especially for non-BQ-related OSCC. miR-499a T>C influences the expression levels of miR-499a-5p during the tumorigenesis of OSCC, but not in the prognoses of OSCC. The downregulation of miR-499a-5p was observed in tumorigenesis, especially for advanced stage of disease and large tumor size. In the future, detailed biological characterization is necessary to validate these findings. Acknowledgements This work was supported by grants from Kaohsiung Veterans General Hospital (VGHKS 103-091, VGHKS 102-005, VGHKS 102-037, VGHKS101-033, and VGHKS101-115).

Conflict of interest The authors declare no conflict of interest.

Author contributions Kuo-Wang Tsai and Yu-Yi Hou contributed to the conception and design, data acquisition, drafting and revising the article. Sin-Jhih Huang performed the experiments and data interpretation. Jang-Hwa Lee, Hung-Chih Chen, Cheng-Mei Yang, and Chao-Chuan Chi performed clinical examination, recruitment of patients, and revising the article. Huei-Han Liou contributed in analysis of data and revising the article. Luo-Ping Ger contributed to the conception and design, analysis and interpretation, revising the article, and final approval of the manuscript.

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Supporting Information Additional Supporting Information may be found in the online version of this article: Figure S1 Kaplan-Meier estimates of the cumulative survival curves. Figure S2 Expression levels of miR-499a-5p and miR499a-3p in 63 paired adjacent normal and OSCC tissues by various genotypes. Table S1 The relationship between genotype of miR499a T>C and clinicopathological data of OSCC patients.

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The association between miR-499a polymorphism and oral squamous cell carcinoma progression.

To investigate the association of miR-499a genetic polymorphism with the risk of oral leukoplakia, oral submucous fibrosis (OSF), oral squamous cell c...
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