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Year : 2021  |  Volume : 17  |  Issue : 5  |  Page : 1209-1218

Association of miR-155 and MIR155HG polymorphisms with cancer risk: A meta-analysis

1 Guanghua School of Stomatology, Hospital of Stomatology, Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-Sen University, Guangzhou, China
2 Department of Pediatrics, The University of Hong Kong-Shenzhen Hospital, Shenzhen; Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China

Date of Submission06-Jun-2021
Date of Acceptance07-Oct-2021
Date of Web Publication27-Nov-2021

Correspondence Address:
Binghui Zeng
Guanghua School of Stomatology, Hospital of Stomatology, Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-Sen University, Guangzhou, 510055
Dongsheng Yu
Guanghua School of Stomatology, Hospital of Stomatology, Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, 510055
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jcrt.jcrt_913_21

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 > Abstract 

Background: Analysis of emerging data shows that miRNAs, including miR-155, play important roles in tumorigenesis. Several studies have indicated that miR-155 and MIR155HG polymorphisms may be related to cancer risk, but the association was controversial. Therefore, we conducted this first-reported comprehensive meta-analysis of the association of miR-155 and MIR155HG polymorphisms with cancer risk.
Materials and Methods: We searched several databases, including PubMed, Embase, and Web of Science, to identify the eligible studies reporting the association of miR-155 and MIR155HG polymorphisms with cancer risk. We calculated the pooled odds ratios (ORs) and 95% confidence intervals (CIs) to analyze the association. Stata software (version 16.0) was used to analyze the data we collected.
Results: After being carefully and strictly screened, eight articles reporting on six common single-nucleotide polymorphisms consisting of 6184 cases and 6896 controls were included in this meta-analysis. The six polymorphisms included were rs767649 (T>A), rs928883 (A>G), rs2829803 (G>A), rs1893650 (T>C), rs4143370 (G>C), and rs12482371 (T>C). Our results showed that, in the overall analysis, heterozygotes increased cancer risk, with a marginal P value, compared with wild-type (OR = 1.06, 95% CI = 1.00–1.12, P = 0.062). Subsequent analyses showed that only rs767649 was associated with an increased risk of non-small-cell lung cancer (NSCLC) in an allele model (T vs. A: OR = 1.15, 95% CI = 1.04–1.26, P = 0.007), a homozygote model (TT vs. AA: OR = 1.31, 95% CI = 1.06–1.60, P = 0.011), and a recessive model (TT vs. AT + AA: OR = 1.30, 95% CI = 1.08–1.55, P = 0.005).
Conclusion: The present meta-analysis indicates that the rs767649 polymorphism might be a potential factor for NSCLC risk; however, more studies should be conducted to confirm these findings.

Keywords: Cancer, meta-analysis, miR-155, non-small-cell lung cancer, polymorphism

How to cite this article:
Zou Z, Lu H, Zhang W, Li Y, He Y, Lin H, Zhao W, Yu D, Zeng B. Association of miR-155 and MIR155HG polymorphisms with cancer risk: A meta-analysis. J Can Res Ther 2021;17:1209-18

How to cite this URL:
Zou Z, Lu H, Zhang W, Li Y, He Y, Lin H, Zhao W, Yu D, Zeng B. Association of miR-155 and MIR155HG polymorphisms with cancer risk: A meta-analysis. J Can Res Ther [serial online] 2021 [cited 2022 May 20];17:1209-18. Available from: https://www.cancerjournal.net/text.asp?2021/17/5/1209/331315

 > Introduction Top

Cancer is caused by the accumulation of mutations in the genome, leading to the uncontrolled growth of cells in the body. It is a serious threat to human health. Cancer is the second leading cause of death in North America[1] and the leading cause of death in China.[2] Therefore, great effort must be exerted to prevent as well as treat cancer, and early detection and diagnosis are of great significance. Recently, some studies have proposed new ideas whereby the detection of micro-RNA polymorphisms can indicate cancer risk as well as prognosis.

miRNAs, a class of small noncoding regulatory RNAs with sizes of 17–25 nucleotides, play a significant role in cancer formation. According to some research, miRNAs posttranscriptionally suppress target mRNA expression, which is mainly and normally through interaction with the target sites in the 3′UTR of target mRNAs. Moreover, miRNAs can play vital roles in cell fate determination, proliferation, and death.[3] Among all miRNAs, miR-155 has a strong relationship with cancer. miR-155 is supposed to be an inflammation-associated oncogenic miRNA, frequently overexpressed in hematological malignancies and solid tumors. In a series of well-designed experiments, Witten et al. have found that miR-155 promotes tumor formation not only through causing a mutator phenotype that results in a high mutation rate, but also through creating a gene expression environment that is particularly susceptible to malignant transformation, in which c-Kit, an oncogene, is highly expressed.[4] Furthermore, miR-155 can mediate downregulation of UBQLN1/2, which can induce invasion and migration of cancer cells and regulate the expression of epithelial and mesenchymal markers to induce an EMT-like phenotype.[5] In addition, many studies have shown that circulating plasma levels of miR-155 can act as a biomarker to predict cancer risk. For example, miR-155 is upregulated in rectal cancer, colonic cancer, B-cell malignancies, cervical cancer, and so on, while it is downregulated in esophageal cancer.[6],[7],[8],[9] Single-nucleotide polymorphisms (SNPs) are a kind of genetic variant found to have an important effect on gene expression. Numerous studies have proved that SNPs are valuable and effective gene markers for early cancer diagnosis, leading to the earliest possible cancer treatment.[10],[11] Growing numbers of studies have indicated that miR-155 polymorphisms are associated with both cancer susceptibility and prognosis.[12],[13] The results remain controversial, however, and there is no clear consensus.

Several studies have reported the association between miR-155 expression and cancer risk.[4],[14],[15],[16] However, the association between the miR-155 polymorphisms and overall human cancer risk has not been analyzed comprehensively. Therefore, we conducted this meta-analysis to determine the association. miR-155 is processed from MIR155HG (miR155 host gene), and the genetic variation of MIR155HG can also affect miR-155 expression.[17] In this analysis, we analyzed the association between MIR155HG polymorphisms and cancer risk.

 > Materials and Methods Top

Literature search

The literature retrieval was carried out systematically as well as comprehensively by the investigators. The databases include PubMed, Web of Science, and Embase. The relevant studies were found by means of the following key words: ([SNPs] OR [polymorphisms] OR [variant] OR [variation] OR [susceptibility]) AND ([cancer] OR [carcinoma] OR [neoplasm] OR [tumor] OR [malignancy]) AND ((miR-155) OR (MIR155HG)). The year of the search ranged from November 25, 2019 to November 25, 2020.

Inclusion and exclusion criteria

Eligible studies had to meet the following inclusion criteria: (i) a case-control study; (ii) association between miR-155 or MIR155HG polymorphisms and cancer risk; and (iii) ample data available for the calculation of odds ratios (OR) and 95% confidence intervals (CIs). Two or more case-control cohorts were considered as two or more independent studies. If the articles met the following criteria, they were excluded: (i) were reviews or conference abstracts; (ii) duplicated existing records; (iii) were unrelated to cancer risk; (iv) were unrelated to SNPs; and (v) had insufficient data for extraction.

Assessment for study quality

The quality of each study was assessed based on the Newcastle-Ottawa Scale for case-control studies.[18] The scoring index of study quality includes: (1) adequacy of case definition; (2) the number of cases; (3) representativeness of the cases; (4) ascertainment of relevant cancers; (5) ascertainment of genotyping method; (6) Hardy-Weinberg equilibrium (HWE); (7) assessment of outcome; and (8) adequate follow-up. If the study met a scoring index, it received a point. The quality scores of each study ranged from 0 to 8. If the study not only scored 7 or more, but also received a HWE P exceeding 0.05, it could also be incorporated into this meta-analysis. Details of the evaluation methods and the specific scores of each study can be seen in [Table 1]. After strict rating, all the included studies were deemed to be eligible.
Table 1: Detailed characteristics of included articles

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Data extraction

The authors extracted all the useful data from the literature comprehensively and carefully. In this meta-analysis, the extracted items included: First author, year, ethnicity, cancer type, genotyping method, source of control groups, total numbers of both cases and controls, as well as genotype distribution in cases and controls.

Statistical analysis

All statistical analyses presented in this article were performed by means of Stata/MP version 16.0 Corp (College Station, Texas, USA) for Windows (64-bit × 86-64). The HWE was used to assess the genotype frequencies of miR-155 and MIR155HG polymorphisms, and the HWE of each article was calculated by the Fisher exact test. PHWE < 0.05 was considered as significant disequilibrium. The association between miR-155 and MIR155HG polymorphism and the risk of cancer was estimated by calculation of the pooled ORs and their corresponding 95% CIs. Cochran's Q test and I2 tests were used to measure the heterogeneity between the studies. For the Q test, P < 0.10 showed significant heterogeneity; otherwise, the heterogeneity was not statistically significant. Regarding I2 tests, I2 between 0% and 25% was considered as lacking heterogeneity; I2 between 25% and 50% was considered as showing modest heterogeneity; and I2 more than 50% was considered as showing high heterogeneity.[26] Therefore, if P < 0.10 and I2 ≥ 50%, heterogeneity existed, and a fixed-effect model was applied; otherwise, a random-effect model was used. In total, five models were carried out to assess the relationship between miR-155 and MIR155HG polymorphisms and cancer risk: an allele model (mutation allele vs. ancestral allele); a dominant model ([mutant homozygote + heterozygote] vs. wild homozygote); a recessive model (mutant homozygote vs. wild homozygote + heterozygote); a homozygote model (mutant homozygote vs. wild homozygote); and a heterozygote model (heterozygote vs. wild homozygote). Publication bias was assessed by Begg's rank correlation and Egger's linear regression, in which P < 0.10 is considered statistically significant.

 > Results Top

Study identification

In total, eight articles were finally selected for this meta-analysis based strictly on the inclusion criteria. Initially, we found 234 articles that were relevant to the key words after eliminating the duplicate records from PubMed, Embase, and Web of Science. We excluded 192 articles through screening the titles and the abstracts (among them, 64 were conference abstracts, 22 were functional studies, 26 were reviews, and 80 were irrelevant to the association between miR-155 or MIR155HG and cancer risk). Subsequently, after reading the full texts carefully, we excluded 34 articles (17 were not casecontrol studies, 10 were not relevant to cancer risk, and 7 were not relevant to miR-155 or MIR155HG SNPs). Ultimately, eight articles that met the inclusion criteria and reached high scores in our methodology quality were included in our meta-analysis, which contained 6184 total cases and 6896 total controls. The flow chart of literature selection is shown in [Figure 1].
Figure 1: The flow diagram shows the selection of the included studies and inclusion process

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In summary, there were eight articles that consisted of 24 studies regarding the association between miR-155 and MIR155HG polymorphisms and cancer risk. Three articles addressed MIR155HG, and the remaining five articles miR-155. To sum up, the analyzed SNPs were rs928883 (n = 4); rs2829803 (n = 2); rs767649 (n = 6); rs12482371 (n = 2); rs1893650 (n = 3); rs4143370 (n = 2); rs11911469 (n = 1); rs2829803 (n = 1); rs34904192 (n = 1); rs77218221 (n = 1); and rs77699734 (n = 1). The relevant cancers included diffuse large B-Cell Lymphoma, follicular lymphoma, marginal zone lymphoma/mucosa-associated lymphoma, tissue lymphoma, mantle cell lymphoma, non-small-cell lung cancer (NSCLC), hepatocellular carcinoma, cervical cancer, colorectal cancer, liver cancer, and gastric cancer. Only one article reported on a study population whose ethnicity was European, while the others were Asian. The controls in five articles were population-based (PB), and three were from a hospital-based healthy population matched for age and gender. The distribution of genotypes of all the studies agreed with HWE (P>0.05). Moreover, all of the included studies scored 8 points according to our methodology quality evaluation. The detailed characteristics of each study are shown in [Table 1].

Quantitative data synthesis

All included articles were summarized to assess the association strength of the pooled miR-155 and MIR155HG polymorphisms with the risk of overall cancer. Six SNPs - rs767649 (A>T), rs928883 (A>G), rs2829803 (G>A), rs1893650 (T>C), rs4143370 (G>C), and rs12482371 (T>C) - with data from two or more cohorts available, were analyzed in the present study [Table 2]. We then calculated the pooled ORs and 95% CIs of each study. In the overall analysis, the heterozygote increased cancer risk with a marginal P value compared with wild-type [OR = 1.06, 95% CI = 1.00–1.12, P = 0.062; [Figure 2]]. There were no significant associations with cancer risk in overall SNPs in other genetic models [Supplementary Figure S1], [Supplementary Figure S2], [Supplementary Figure S3], [Supplementary Figure S4]. The fixed-effect and random-effect models were used according to their respective heterogeneity [Table 3].
Table 2: Detailed data for the miR-155 and MIR155HG meta-analysis

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Figure 2: Forest plot shows the association between polymorphisms of miR-155 and MIR155HG and various cancer in the heterozygote model (heterozygote vs. wild homozygote)

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Table 3: Meta-analysis of the association between miR-155 and MIR155HG polymorphisms and cancer risk

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In the subgroup analyses, the association of each SNP with a certain cancer risk was studied. However, individual SNPs did not show significant association with cancer risk in any genetic model. We also conducted stratification analysis based on different cancer type, ethnicity of the study population, and source of the controls. In the comparison between rs767649 and NSCLC risk, significant and meaningful associations were found. A significant association was found in the allele model (T vs. A: OR = 1.15, 95% CI = 1.04–1.26, P = 0.007), the recessive model (TT vs. AT + AA: OR = 1.30, 95% CI = 1.08–1.55, P = 0.005), and the homozygote model (TT vs. AA: OR = 1.31, 95% CI = 1.06–1.60, P = 0.011), but not in the heterozygote model (AT vs. AA: OR = 1.07, CI = 0.92–1.25, P = 0.353) and the dominant model (AT + TT vs. AA, OR = 1.13, CI = 0.98–1.30, P = 0.089) [Figure 3].
Figure 3: Forest plot shows the association between rs767649 polymorphism in the miR-155 and non-small cell lung cancer risk. (a) allele model (T vs. A) (b) dominant model (AT + TT vs. AA) (c) recessive model (TT vs. AT + AA) (d) heterozygote model (AT vs. AA) (e) homozygote model (TT vs. AA)

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Furthermore, we found significant associations between rs767649 and hepatocellular carcinoma or cervical cancer, but because the included cohorts were from the same articles, more studies are needed to confirm the associations. In addition, we found a significant association between rs928883 and cancer risk in European-ethnicity and PB controls, but also because the included cohorts were from the same article, more studies are needed to confirm the association. No other significant associations were found in any other comparisons.

Test of heterogeneity

Interstudy heterogeneity (slight, moderate, or severe) was found in the overall comparison and subgroup analyses [Table 3]. For example, high heterogeneity was found in the overall analyses. However, since there were only eight included articles, we were unable to conduct meta-regression analyses to identify the source of heterogeneity. However, we can speculate that the source of heterogeneity consists of few articles, different ethnicities, insufficient subjects of study, and so on, all of which require further analyses with more articles included.

Publication bias

Publication bias was assessed by Begg's rank correlation and Egger's linear regression. There was no statistically significant publication bias found in Begg's test. However, statistically significant publication bias was found in Egger's test, with P < 0.05. Publication bias was revealed in the recessive model of rs928883 in Egger's test and the recessive model of rs1893650 in Egger's test [Table 4]. This may be attributable to language bias, the lack of publications with opposing results, and/or the inflated estimates resulting from flawed methodological designs for smaller studies. Further, we found the data collected in the study by Schuetz et al. to be incomplete and limited, lacking publications with opposing results.
Table 4: Results of Begg's and Egger's tests for publication bias

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 > Discussion Top

Regarding the SNPs in miR-155 and MIR155HG, Sethupathy et al. first published an article which marked the beginning of the study of miR-155 polymorphisms.[27] From that time on, with more and more research, numerous functional SNPs were identified. Until now, however, there has been no comprehensive analysis about the association of miR-155 SNPs with cancer susceptibility. Therefore, we conducted this meta-analysis, in which 6 SNPs (rs767649, rs928883, rs2829803, rs1893650, rs4143370, and rs12482371) in miR-155 and MIR155HG were comprehensively analyzed for their association between miR-155 and MIR155HG polymorphisms and cancer risk. Our results show that the polymorphisms of miR-155 and MIR155HG may have a potential relationship with cancer risk, but more studies are needed to confirm.

Rs767649 is the 'hottest' as well as the most-studied so far among all the SNPs in miR-155. Rs767649 is located in the upstream flanking region of the pre-miR-155 gene in a potential enhancer element.[28] Furthermore, studies have shown that it is able to affect the binding affinity of NF-κB, which is involved in tumor microenvironment, angiogenesis, and other aspects of tumor formation.[29] Xie et al. found that the variant allele in rs767649 could up-regulate miR-155 expression in the way of increasing transcriptional activity.[20] Overexpression of miR-155 can inhibit the expression of redox-rich genes, which are associated with mtDNA damage, ROS, and autophagy, thereby promoting cancer cell growth and development. Hence, those authors conjectured that rs767649 variants may contribute to lung cancer risk through binding with NF-κB and activate miR-155 expression.[20] Later, Dezfuli[25] pointed out that rs767649 is a risk factor for NSCLC, which is in agreement with the findings of Xie et al.[20] Moreover, the study by Ji et al. reported that rs767649 contributes to the susceptibility of hepatocellular carcinoma, also verifying this proposition.[21] Interestingly, however, Wang et al. reported that the rs767649 polymorphisms are associated with a decreased risk of cervical cancer.[22] Furthermore, in our analysis, we also found that rs767649 has an increased cancer risk in NSCLC. Further analysis showed that the TT genotype was significantly associated with NSCLC in both recessive and homozygous models. As we went further, we found that the rs767649 T allele could promote the expression of miR-155 in both lung cancer and hepatocellular cancer, but not in cervical cancer. In contrast, in cervical cancer, the T allele could downregulate the expression of miR-155. Moreover, another study proposed that miR-155 could promote the formation of cervical cancer through suppressing LKB1.[30] Therefore, a more complex mechanism could be undetected, and further studies about the association between rs767649 and various cancer risks as well as the influence of the mechanism of rs767649 on miR-155 expression are needed to confirm the relationship between rs767649 and miR-155 expression.

Rs928883 is located 2.3 kb upstream of miR155, in the second intron of MIR155HG, the host gene of this 64-bp microRNA.[19] In our analysis, we found no significant and meaningful association between rs928883 and cancer risk.

Rs2829803, rs1893650, rs4143370, and rs12482371 were all located in the intron region of MIR155HG. At one time, intron sequences were supposed to be nonfunctional. However, with the continuous development of research, introns were found to have specific functions and can lead to disease or even cancer if mutated.[31] No association was found between rs2829803 and cancer risk. In addition, Wu et al. hypothesized that rs12482371, rs1893650, and rs928883 may enhance the translation of the MIR155HG gene to affect the risk of colorectal cancer.[23] We might hypothesize that all the SNPs located in the intron region of MIR155HG can affect tumor formation in the same way. Interestingly enough, the effects of the same SNPs are quite different in cancer regardless of pathological type. For example, Chao et al.[24] found that rs12482371 and rs1893650 in MIR155HG were associated with a decreased risk in liver cancer, while rs928883 was associated with an increased risk. In contrast, Wu et al. found that rs12482371 and rs1893650 were related to an increased colorectal cancer risk, while rs928883 decreased that risk.[23] From these completely opposing examples, it is not hard for us to see that even the same SNPs may function differently in different types of cancer. However, the mechanisms are still not well understood.

 > Conclusion Top

One common finding in so many studies is that miR-155/MIR155HG polymorphisms, mainly through affecting the expression of miR-155, proceed to influence cancer formation, metastasis, and development. Furthermore, it must be noted that even the same SNPs can increase or decrease the risk of cancer in different cancer types. Expression of miR-155 may play a different role in different types of cancer. Although generally considered an oncogenic miRNA, the overexpression of miR-155 is able to promote tumor growth, metastasis, and inhibit cancer cell apoptosis. However, to our surprise, we found some studies reporting that miR-155 can act as a tumor suppressor, whose overexpression can lead to cancer cell apoptosis and suppress its proliferation in colorectal cancer.[32] Moreover Li et al. have reported that miR-155 plays a role in tumor suppression in the development and progression of gastric cancer. Furthermore, in a series of experiments, they have proved that miR-155 can suppress gastric cancer cell growth.[33] Therefore, we can ask another question: Why can miR-155 exert different functions in different types of cancer? Until now, there has been no unified conclusion. But some mechanisms have been proposed to explain their interaction. For example, it can drive oncogenesis as a way of promoting and cooperating with mutations in the c-Kit oncogene, while it can also play the role of cancer suppressor by regulating the expression level of MAP3K10.[4],[33]

Financial support and sponsorship

The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.

This work was supported by the Fundamental Research Funds of the Central Universities, Sun Yat-Sen University (19ykpy86), and China Postdoctoral Science Foundation (2020M673023) to Binghui Zeng; the National Natural Science Foundation of China (81873711, 82073378) to Dongsheng Yu

Conflicts of interest

There are no conflicts of interest.

 > References Top

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  [Figure 1], [Figure 2], [Figure 3]

  [Table 1], [Table 2], [Table 3], [Table 4]


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