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Meta-Analysis of Interleukin Polymorphisms and NSAID Usage Indicates Correlations to the Risk of Developing Cancer

Nagao M, Sato Y* and Yamauchi A

Department of Pharmaceutical Information Science, Institute of Health Biosciences, The University of Tokushima Graduate School, Tokushima, Japan

*Corresponding Author:
Sato Y
Department of Pharmaceutical Information Science
Institute of Health Biosciences
The University of Tokushima Graduate School
1-78-1 Sho-machi, Tokushima City 770-8505, Japan
Tel: +81-88-633-7253
Fax: +81-88-633-7253
E-mail: [email protected]

Received Date: December 04, 2013; Accepted Date: February 22, 2014; Published Date: February 28, 2014

Citation: Nagao M, Sato Y, Yamauchi A (2014) Meta-Analysis of Interleukin Polymorphisms and NSAID Usage Indicates Correlations to the Risk of Developing Cancer. Int J Genomic Med 2:113. doi: 10.4172/2332-0672.1000113

Copyright: © 2014 Nagao M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

Use of Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) is correlated to reduced risk of developing cancer through reduction of inflammation, which is an important risk factor for cancer. Several studies have investigated the possible association between polymorphisms in the gene encoding inflammatory cytokines and use of NSAIDs with cancer risk; however, these studies have obtained mixed results. Therefore, we performed a meta-analysis to evaluate the association between genetic polymorphisms of Interleukin (IL) 1B, IL6, IL8, and IL10, and NSAID usage with respect to cancer risk. We conducted a comprehensive search in PubMed through May 2013. Odds Ratios (ORs) with corresponding 95% Confidence Intervals (CIs) were calculated using the fixed-effect or the random-effect model. Comprehensive search of databases revealed eight studies fulfilling the inclusion criteria. For IL6 rs1800795, the minor allele carriers demonstrated a significantly decreased cancer risk compared to those homozygous for the major allele (GG) among NSAID users (OR=0.80, 95% CI=0.68-0.95). For IL8 rs4073, NSAID users had a significantly decreased cancer risk compared to the non-NSAID users (OR=0.71, 95% CI=0.53-0.96) among those homozygous for the major allele (TT). For the IL1B rs1143627 and IL10 rs1800872 SNPs, we did not observe any significant difference. We identified a correlation between the polymorphisms IL6 rs1800795 and IL8 rs4073 and NSAID usage in decreased cancer risk.

Keywords

Meta-analysis; Cancer; NSAIDs; Polymorphism; Interleukin

Abbreviations

IL: Interleukin; NF-ΚB: Nuclear Factor-Kappa-B; INOS: Inducible Nitric Oxide Synthase; COX: Cyclooxygenase; NSAID: Non-Steroidal Anti-Inflammatory Drugs; PG: Prostaglandin; OR: Odds Ratio; CI: Confidence Interval

Introduction

Based on clinical and epidemiological studies, chronic inflammation has been shown to be a predisposing factor to several types of cancers, including colon, prostate, and pancreatic cancers, and promotes the proliferation of malignant cells [1,2]. Cancer is caused by several mechanisms, including genetic and epigenetic alterations of genes encoding pro-inflammatory cytokines [3,4]. Further to this, polymorphisms of the genes encoding the inflammatory cytokine are related to cancer susceptibility [1]. Cytokines are multifaceted, endogenous, inflammatory, and immune regulatory mediators, demonstrating both positive and negative regulatory activities on various target cells [5]. Interleukin (IL) 1B, IL6, IL8, etc., are chiefly known as pro-inflammatory cytokines [6]. IL1B is an important pro-inflammatory cytokine that can regulate the expression of some molecules related to inflammation [7]. The rs1143627 (-31T>C) SNP is located in the promoter region of the IL1B gene. The C variant allele of the rs1143627 locus results in a higher transcription of IL1B than of the T allele [8]. IL6 is an important multifaceted inflammatory cytokine mediating immune responses, cell survival, proliferation, and apoptosis. The rs1800795 (-174G>C) SNP is located in the promoter region of the IL6 gene. Therefore, this SNP affects gene transcription, so that the G allele results in a higher transcription level than the C allele [9]. High expression of IL6 is associated with tumor development during the initiation, promotion, malignant conversion, invasion, and metastasis stages [1]. IL8 is known for its leukocyte chemotactic properties and its tumorigenic and proangiogenic activities, and is related to neovascularization-dependent tumor growth, tumor invasion and metastasis [10]. Therefore, it is considered that high expression levels of IL8 constitutes a risk factor to the development and progression of tumors [10,11]. The rs4073 (-251T>A) SNP is located in the promoter region of the IL8 gene and the A allele of rs4073 is associated with increased IL8 production in vitro [12]. IL10, known as the antiinflammatory cytokine is a multifunctional cytokine participating in the development and progression of various malignant tumors. The rs1800872 (-592C>A) SNP is located in the promoter region of the IL10 gene [13]. A haplotype with two other SNPs, rs1800896 (-1082G>A) and rs1800871 (-819C>T) is associated with IL10 production. [14]. IL10 down-regulates the expression of macrophage costimulatory molecules [15,16]. IL10 has anti-inflammatory and immunosuppressive activities, and aids the tumors escape immune surveillance. Therefore, it has been suggested that IL10 has a complex influence on tumor development. IL10 has anti-tumor activity, yet promotes tumor genesis [16]. Therefore, it is suggested that IL1B, IL6, IL8, and IL10 may be associated with the risk of development of cancer.

These inflammatory cytokines are regulated by nuclear factor kappa-B (NF-κB), which is a key molecule of inflammation-mediated carcinogenesis [4]. NF-κB is emerging as one of the targets in the chemoprevention of diseases involving reactive species overload, because many of the genes targeted by NF-κB are related to the inflammatory cascade (inducible nitric oxide synthase [iNOS], cyclooxygenase [COX]-2, cytokines, and matrix metalloproteinase), anti-apoptotic events, and cell cycle events [17].

Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) reduce inflammation through a decrease in the synthesis of Prostaglandin (PG) as well as the inhibition of NF-κB [18]. NSAIDs are one of the most widely used medicines for the prevention and/or treatment of various diseases. Several epidemiological studies have investigated whether NSAID usage is correlated to a reduced risk of cancer; however, this remains controversial. Information regarding whether polymorphisms in inflammatory cytokine genes influence cancer risk is important with respect to using NSAIDs for the prevention and treatment of cancer.

To date, several studies have investigated whether polymorphisms in the genes encoding the inflammatory cytokine are associated with cancer risk in conjunction with NSAID usage; however, they have obtained mixed results. Therefore, we performed a meta-analysis to determine the association between polymorphisms in the gene encoding IL and the risk of developing cancer in conjunction with NSAID usage.

Materials and Methods

Literature search

We searched for publications in MEDLINE, Science Direct, and the Cochrane Library by using the keywords and strategy terms “interleukin” or “IL”, “NSAID”, “genotype” or “polymorphism”, and “cancer” or “carcinoma” (last search was performed in May 2013). Noncontrolled trials were excluded. Randomized controlled trials with three or more groups were retained if at least two groups addressed an eligible comparison.

Inclusion criteria

Studies fulfilling the following criteria were chosen: (1) fulltext articles written in English; (2) controlled trials comparing IL polymorphisms and risk of cancer, including NSAID usage status; (3) sufficient published data for estimating odds ratio (OR) or relative risk with 95% confidence interval (CI); and (4) the number of cases, controls, NSAID users, and non-NSAID-users correlated to IL genotypes was clarified. The following details were not considered for selection: (1) blinded nature of the trial, (2) type of cancer, (3) type of NSAID, and (4) NSAID dosage method.

Data extraction

Data extraction was performed independently by two authors (Nagao and Sato) by using a standard protocol according to the inclusion criteria. The following data were extracted: the name of the first author, year of publication, country of research institution, type of cancer, study design, age, gender, and the number of cases and controls with NSAID users or non-users by genotype.

Statistical analysis

All statistical analyses were performed using the rmeta package for R, version 2.14.2 (The R Foundation for Statistical Computing, Tsukuba, Japan; http://www.R-project.org). Two-sided probability (P) values of <0.05 were considered statistically significant. ORs with 95% CIs were calculated to assess the strength of the following associations: (1) between IL genotype with NSAID users and the risk of developing cancer, (2) between NSAID users homozygous for the major allele and the risk of developing cancer, (3) between IL genotype with non- NSAID users and the risk of developing cancer, and (4) between NSAID users with the minor allele and the risk of developing cancer. Hardy- Weinberg Equilibrium (HWE) was assessed by using the Pearson’s χ2 test for genotypes in the control group for each study.

All meta-analyses were appraised for inter-study heterogeneity by using χ2-based Q statistics for statistical significance of heterogeneity. If there was no heterogeneity based on a Q-test P value of >0.05, a fixed-effect model using the Mantel-Haenszel (M-H) method was used. Otherwise, the random-effects model using the DerSimonian and Laird method was employed. Sensitivity analyses and evaluations of possible publication bias were not performed because of the limited distraction sample sizes in the publications included in the meta-analysis.

Results

Characteristics of eligible studies

Figure 1 shows a flow diagram of the selection process of relevant studies. Sixteen relevant reports were initially identified. Eight of these were initially excluded because they did not perform the analysis for recurring SNPs. Two more studies were excluded because they did not provide the number of subjects used for the calculation of OR. Therefore, only six of the 16 studies were included in the meta-analysis. The baseline characteristics and methodological quality of all included studies are summarized in Table 1 and Supplementary Table 1. The reported studies in each article included the following polymorphisms: IL6 rs1800795 (n=5), IL8 rs4073 (n=4), IL1B rs1143627 (n=4), and IL10 rs1800872 (n=4) [19-24].

clinical-medical-genomics-literature-search

Figure 1: Flow diagram of the literature search and study selection.

Study Country Outcome Study design Age Gender case control Genotyping method Genotype distribution P value
for HWE
Males/Females No Yes No Yes
IL-6rs1800795 GC+CC/GG GC+CC/GG GC+CC/GG GC+CC/GG   GG CG CC  
Vogel et al.[19] Denmark LC Nested case-cohort 50-64 631/516 203/73 92/31 368/140 168/61 TaqMan PCR 204 361 179 0.44
Slattery et al. [20] USA CC Case-control 30-79 Without details 664/417 278/214 715/442 529/286 two-step PCR process and mass spectrometry 728 897 347 0.015
Vogel et al. [21] Denmark BCC Nested case-cohort 50-64 293/326 175/48 62/16 153/64 71/24 TaqMan PCR 89 157 69 0.99
Vogel et al. [22] Denmark CRC Nested case-cohort 50-64 618/490 178/62 83/27 383/129 181/53 TaqMan PCR 204 364 185 0.37
Vogel et al. [23] Denmark BC Nested case-cohort 50-64 0/712
(females only)
112/32 147/53 112/34 172/50 TaqMan PCR 98 177 86 0.73
IL-8rs4073 TA+AA/TT TA+AA/TT TA+AA/TT TA+AA/TT   TT AT AA  
Vogel et al.[19] Denmark LC Nested case-cohort 50-64 631/516 210/66 100/23 406/102 170/59 TaqMan PCR 161 364 219 0.67
Vogel et al. [21] Denmark BCC Nested case-cohort 50-64 293/326 168/55 63/15 163/54 73/22 TaqMan PCR 76 170 69 0.16
Vogel et al.[22] Denmark CRC Nested case-cohort 50-64 618/490 180/60 87/23 411/101 175/59 TaqMan PCR 160 367 226 0.63
Vogel et al.[23] Denmark BC Nested case-cohort 50-64 0/712
(females only)
114/42 131/69 93/41 148/74 TaqMan PCR 78 167 78 0.54
IL-1Brs1143627 TC+CC/ TT TC+CC/ TT TC+CC/ TT TC+CC/ TT   TT CT CC  
Vogel et al. [19] Denmark LC Nested case-cohort 50-64 631/516 172/104 71/52 268/240 125/104 TaqMan PCR 350 310 84 0.22
Vogel et al.[21] Denmark BCC Nested case-cohort 50-64 293/326 121/102 42/36 120/97 59/36 TaqMan PCR 135 142 38 0.94
Vogel et al.[22] Denmark CRC Nested case-cohort 50-64 618/490 131/109 67/43 269/243 130/104 TaqMan PCR 353 312 88 0.14
Macarthur et al.[24] UK CRC Cohort Without details 360/312 121/71 24/27 188/118 44/41 TaqMan PCR 165 179 59 0.36
IL-10rs1800872 CA+AA/CC CA+AA/CC CA+AA/CC CA+AA/CC   CC AC AA  
Vogel et al.[19] Denmark LC Nested case-cohort 50-64 631/516 117/159 43/80 196/312 94/135 TaqMan PCR 452 250 42 0.34
Vogel et al.[21] Denmark BCC Nested case-cohort 50-64 293/326 88/135 31/47 90/127 30/65 TaqMan PCR 194 106 15 0.92
Vogel et al.[22] Denmark CRC Nested case-cohort 50-64 618/490 85/155 42/68 198/314 98/136 TaqMan PCR 455 256 42 0.45
Macarthur et al.[24] UK CRC Case-control Without details 360/312 84/108 16/35 114/192 35/50 TaqMan PCR 248 133 22 0.46

Table 1: Summary of the studies included in the meta-analysis.

The genotypes of four SNPs were in HWE in control group of each studies, except for one study on IL6 rs1800795 (Table 1) (P=0.015) [20].

IL6 rs1800795 polymorphism

Five studies reported an association between the IL6 rs1800795 polymorphism and the risk of developing cancer in conjunction with NSAID usage. In our meta-analysis, there were no significant differences among those homozygous for the major allele (GG) (Figure 2A; OR=0.87, 95% CI=0.73-1.04, Pheterogeneity=0.73), or the minor allele carriers (GC+CC) (Figure 2B; OR=0.80, 95% CI=0.62-1.05, Pheterogeneity=0.003). The minor allele carriers demonstrated a significantly decreased cancer risk compared to those homozygous for the major allele among NSAID users (Figure 2C; OR=0.80, 95% CI=0.68-0.95, Pheterogeneity=0.33); however, we did not note any significant difference among non-NSAID users (Figure 2D; OR=1.04, 95% CI=0.91-1.18, Pheterogeneity=0.46).

clinical-medical-genomics-polymorphism-cancer

Figure 2: Forest plot of the association between the IL6 rs1800795 polymorphism and NSAID usage on cancer risk. The difference in the risk of development of cancer between NSAID users and non-NSAID users homozygous for the major allele (A), between NSAID users and non-NSAID users from individuals who are minor allele carriers (B), between non-NSAID users homozygous for the major allele and the minor allele carriers (C), and between NSAID users homozygous for the major allele and the minor allele carriers (D). Squares represent study-specific ORs; horizontal lines represent 95% CIs; the size of the square reflects study-specific statistical weight (inverse of the variance); diamonds represent summary OR and 95% CI.

IL8 rs4073 polymorphism

Four studies reported an association between the IL8 rs4073 polymorphism and the risk of developing cancer in conjunction with NSAID usage. According to our meta-analysis, use of NSAIDs was significantly correlated with decreased cancer risk among subjects homozygous for the major allele (TT) (Figure 3A; OR=0.71, 95% CI=0.53-0.96, Pheterogeneity=0.75); however, there were no significant differences among the minor allele carriers (TA+AA) (Figure 3B; OR=0.98, 95% CI=0.82-1.15, Pheterogeneity=0.16). No significant difference was noted between IL8 rs4073 polymorphism (TT vs. TA+AA) and the risk of developing cancer, among non-NSAID users (Figure 3C; OR=0.88, 95% CI=0.72-1.07, Pheterogeneity=0.39) or NSAID users (Figure 3D; OR=1.17, 95% CI=0.91-1.52, Pheterogeneity=0.57).

clinical-medical-genomics-diamonds-lines

Figure 3: Forest plot of the association between the IL8 rs4073 polymorphism and NSAID usage on cancer risk. The difference in the risk of development of cancer between NSAID users and non-NSAID users homozygous for the major allele (A), between NSAID users and non-NSAID users who are minor allele carriers (B), between non-NSAID users homozygous for the major allele and the minor allele carriers (C), and between NSAID users homozygous for the major allele and the minor allele carriers (D). Squares represent study-specific ORs; horizontal lines represent 95% CIs; the size of the square reflects study-specific statistical weight (inverse of the variance); diamonds represent summary OR and 95% CI.

IL1B rs1143627 polymorphism

Four studies reported an association between the IL1B rs1143627 polymorphism and the risk of developing cancer in conjunction with NSAID usage. No significant differences were noted between NSAID usage and the risk of developing cancer among those homozygous for the major allele (TT) (Figure 4A; OR=1.03, 95% CI=0.81-1.30, Pheterogeneity=0.87), or the minor allele carriers (TC+CC) (Figure 4B; OR=0.89, 95% CI=0.73-1.09, Pheterogeneity=0.60), and between the IL1B rs1143627 polymorphism (TT vs. TC+CC) and the risk of developing cancer among non-NSAID users (Figure 4C; OR=1.16, 95% CI=0.99- 1.37, Pheterogeneity=0.27) or NSAID users (Figure 4D; OR=1.03, 95% CI=0.79-1.33, Pheterogeneity=0.45).

clinical-medical-genomics-homozygous-square

Figure 4: Forest plot of the association between the IL1B rs1143627 polymorphism and NSAID usage on cancer risk. The difference in the risk of development of cancer between NSAID users and non-NSAID users homozygous for the major allele (A), between NSAID users and non-NSAID users who are minor allele carriers (B), between non-NSAID users homozygous for the major allele and the minor allele carriers (C), and between NSAID users homozygous for the major allele and the minor allele carriers (D). Squares represent study-specific ORs; horizontal lines represent 95% CIs; the size of the square reflects study-specific statistical weight (inverse of the variance); diamonds represent summary OR and 95% CI.

IL10 rs1800872 polymorphism

Four studies reported an association between the IL10 rs1800872 polymorphism and the risk of developing cancer in conjunction with NSAID usage. We found no significant differences between NSAID usage and the risk of developing cancer among those homozygous for the major allele (CC) (Figure 5A; OR=1.01, 95% CI=0.83-1.23, Pheterogeneity=0.22), or the minor allele carriers (CA+AA) (Figure 5B; OR=0.86, 95% CI=0.67-1.10, Pheterogeneity=0.54), and between the IL10 rs1800872 polymorphism (CC vs. CA+AA) and the risk of developing cancer among non-NSAID users (Figure 5C; OR=1.05, 95% CI=0.89- 1.24, Pheterogeneity=0.29) or NSAID users (Figure 5D; OR=0.87, 95% CI=0.67-1.14, Pheterogeneity=0.35).

clinical-medical-genomics-study-specific

Figure 5: Forest plot of the association between the IL10 rs1800872 polymorphism and NSAID usage on cancer risk. The difference in the risk of development of cancer between NSAID users and non-NSAID users homozygous for the major allele (A), between NSAID users and non-NSAID users who are minor allele carriers (B), between the non-NSAID users homozygous for the major allele and the minor allele carriers (C), and between the NSAID users homozygous for the major allele and the minor allele carriers (D). Squares represent study-specific ORs; horizontal lines represent 95% CIs; the size of the square reflects studyspecific statistical weight (inverse of the variance); diamonds represent summary OR and 95% CI.

Discussion

One study on IL6 rs1800795 was statistically deviated from HWE. In the study conducted by Slattery et al., n=897 (46%) had the heterozygote genotype IL6 rs1800795 when we expected n=949 (48%) based on allele frequencies [20]. There was a similar shift of observed and expected genotypes for the homozygote wild-type (37% observed, 36% expected) and the homozygote variant genotype (17% observed, 16% expected). We do not attribute this result to deviation from HWE because the overall concordance rate for blinded quality controls was >92%, although the deviation from HWE could be explained as not only the result of laboratory or genotyping error but from population migration and gene mutations.

In the current study, we searched the literature to determine the association between IL polymorphisms and NSAID usage with respect to the risk of developing cancer. The IL6 rs1800795 SNP is located in the promoter region of the IL6 gene. Therefore, this SNP affects gene transcription, where the G allele has a higher transcription level than the C allele [9]. Elevated serum levels of IL6 have been shown to be associated with an increased incidence of several cancers, including prostate, bladder, colon, and breast cancers [20]. To date, several studies have investigated associations of the IL6 rs1800795 SNP and risk of cancer; however, these studies have produced mixed results. Slattery et al. reported that the C allele of rs1800795 is associated with lower risk of breast cancer [25]. Theodoropoulos et al. observed that the C allele of the rs1800795 SNP reduced the risk of colorectal cancer, while Landi et al. indicated that individuals with the C allele had an increased risk of colorectal cancer [26,27]. Our meta-analysis showed that the minor allele carriers (GC+CC) were associated with a significantly decreased risk of cancer compared to carriers homozygous for the major allele (GG) among NSAID users. This result shows that the C allele of rs1800795 is associated with lower risk of cancer in conjunction with NSAID usage. It is suggested that because C allele carriers have lower transcription levels of IL6 than those homozygous for the G allele, NSAID consumption reduces the expression of IL6, and decreases the risk of developing cancer.

The IL8 rs4073 SNP is located in the promoter region of the IL8 gene and the A allele of rs4073 is associated with increased IL8 production in vitro [12]. There is a significant correlation between IL8 mRNA expression in bladder cancer and in invasive and high-grade tumors [28]. We found that NSAID users demonstrated a significantly decreased risk of developing cancer compared with non-NSAID users among those homozygous for the major allele (TT) of the rs4073 SNP, although no significant association was noted between the IL8 rs4073 polymorphism and the risk of developing cancer among non-NSAID users or NSAID users. This suggests that because homozygosity of the T allele leads to lower production levels of IL8 than that found in A allele carriers, NSAID usage reduces the expression of IL8, and thereby decreases the risk of developing cancer. On the one hand, it is reasonable to assume that the level of IL8 in minor allele carriers (TA+AA) could also be down regulated through NSAID usage so as to cause a reduced cancer risk as well, but the results did not confirm this hypothesis. Lee et al. reported that variants of the COX-1 gene resulted in significantly lower indomethacin-mediated inhibition of COX-1 activity compared to the wild type [29]. We suggest that the difference in sensitivity to NSAIDs is caused by the variant of the IL8 gene.

The IL1B rs1143627 SNP is also located in the promoter region of the IL1B gene. The C variant allele of the rs1143627 SNP has a higher transcription level of IL1B than the T allele [8]. IL1B is implicated in tumor progression and is up-regulated in many types of tumor. Reducing endogenous IL1 activity reduces both metastasis and tumor burden [30]. Our meta-analysis did not indicate any significant differences between these two genotypes.

There was no association between the risk of developing cancer, NSAID usage, and the IL10 rs1800872 polymorphism. The IL10 rs1800872 SNP is located in the promoter region of the IL10 gene. Macarthur et al. reported that the A variant allele carriers of rs1800872, who produce less IL10 had a significantly reduced risk of colorectal cancer when taking aspirin [24]. Therefore, the influence of the IL10 rs1800872 polymorphism on the risk of developing cancer with NSAID usage may differ by the type of cancer or population investigated. Consequently, in the present study, we have not performed a stratified analysis with respect to the cancer type or population because of the limited number of studies available.

The types of NSAIDs considered (e.g., aspirin, ibuprofen, and other NSAIDs), dose methods (e.g., dosage and duration), study design (e.g., case control study or cohort study), population (e.g., age, gender, type of cancer, and ethnicity), study power, HWE in the controls for each study, and distraction sample size differed among the studies included in this meta-analysis. In addition, there was a lack of specificity for cancer type and topography in our analysis because few studies have investigated the effect of associations between polymorphisms in IL genes and NSAID use on cancer risk. Most outcomes show poor correlation between SNPs or NSAID usage and cancer risk, which are mainly due to the dual role that these ILs play in the balance between the promotion and inhibition of cancer development. Nonetheless, our results provide limited evidence for these associations. Future emerging studies are expected to resolve the contradictions in the results of the limited evidence available to date.

In conclusion, we found an association between the IL6 rs1800795 and IL8 rs4073 polymorphisms and NSAID usage with respect to cancer risk. Thus, the polymorphisms of inflammatory cytokine genes may influence the risk of developing cancer with NSAID usage. Thus, these polymorphisms may be clinically useful for deciding whether NSAIDs should be used for the prevention and treatment of cancer.

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