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Prognostic Value of MUC2 Expression in Colorectal Cancer: A Systematic Review and Meta-Analysis.

1. Introduction

Colorectal cancer (CRC) is associated with substantial morbidity and is ranked the third leading cause of cancer-related mortality in the world [1, 2]. The 5-year and 10-year survival rates for CRC are 65% and 58%, respectively [3]. Recurrence is very common in CRC [4, 5], and there is a high risk of subsequent primary cancers in the colon, rectum, and other parts of the digestive system [6]. CRC incidence and mortality rates are rising rapidly in many low- and middle-income countries. The incidence is highest in highly developed countries, but the rates are stabilizing or decreasing in these regions. A 60% increase in the global burden of CRC with more than 2.2 million new cases and 1.1 million deaths is predicted by 2030.

The American Joint Committee on Cancer/Union for International Cancer Control tumor-node-metastasis (TNM) system provides the strongest prognostic parameters for CRC and serves as the basis for treatment decisions [7]. However, the TNM system is less able to predict outcomes in patients with intermediate levels of CRC [8], and there are no definitive biomarkers for monitoring the efficacy of CRC therapies [9]. Therefore, it is necessary to identify new molecular markers that have the potential to predict therapeutic outcomes, serve as therapeutic targets, and improve clinical management in CRC.

Mucins are a family of high molecular weight glycosylated proteins [10] that protect epithelial cells and form the ductal surfaces of several organs [11-13]. To date, approximately 20 mucins have been identified, which can be divided into two subfamilies based on their structure and function, the secreted gel-forming mucins and the transmembrane mucins [14]. Among these, MUC2 is a secreted gel-forming mucin that is encoded within a cluster of genes at the chromosomal locus 11p15 and is thought to share a common ancestor with von Willebrand factor (VWF) [15, 16].

Secreted MUC2 mucin constitutes the major structural component of the mucus in the colon. Colonic mucus has a stratified appearance; the inner mucus layer is attached to the epithelium, is compact, and is devoid of bacteria, while the outer mucus layer is not attached to the epithelium and has an expanded volume due to the action of endogenous proteases, which allows it to be colonized by intestinal bacteria [17]. The inner mucus layer is impervious to bacteria and provides a protective barrier for the colon epithelium. The downregulation of MUC2 expression eliminates this protective mucus barrier, creating a microenvironment in which bacteria can contact the epithelial surface and activate an inflammatory response. Chronic inflammation leads to cellular damage and molecular changes that transform the inflamed epithelium to low-grade dysplasia (LGD), high-grade dysplasia (HGD), and finally CRC [18]. Functionally, MUC2 inhibits the intestinal inflammatory response, thus suppressing the development of intestinal tumors [19, 20]. Conversely, decreased MUC2 expression contributes to CRC by promoting interleukin-6-induced epithelial to mesenchymal transition (EMT), thereby influencing the invasiveness of cancer cells [21, 22]. These mechanisms suggest that MUC2 is an attractive biomarker for diagnosis, immunotherapy, and prognosis in CRC.

Evidence suggests that MUC2 expression is associated with invasion and metastasis in various malignant tumors, including pancreatic cancer [23], gastric carcinoma [24], gallbladder carcinoma [25], extrahepatic bile duct carcinoma [26], breast cancer [27], ovarian cancer [28], ampullary cancer [29], prostate cancer [30], laryngeal cancer [31], and lung cancer [32]. However, the association between MUC2 expression and prognosis in CRC remains to be elucidated. Some studies showed that a low level of MUC2 expression in CRC tissues is associated with poor prognosis [33], while other studies report no obvious correlation [34-37]. Therefore, the objective of the current meta-analysis was to determine the prognostic value of MUC2 in CRC by assessing the association between MUC2 expression levels in CRC tissues and survival. The associations between MUC2 expression levels and several CRC clinicopathological characteristics were also investigated.

2. Materials and Methods

2.1. Search Strategy. Two reviewers (Chao Li, Didi Zuo) independently searched the PubMed, Web of Science, Embase, Cochrane Library, China Biology Medicine disc (CBMdisc), Wanfang Database, and China National Knowledge Infrastructure (CNKI) databases from inception through November 9, 2017, using the following MeSH terms and free-text words: "colorectal neoplasms"/"colorectal cancer"/"colon cancer"/"rectal cancer" and "mucin 2"/"MUC2" and "survival"/"outcome"/"prognosis"/"mortality". A manual search of the reference lists of relevant articles was conducted to identify additional relevant studies. The search was limited to articles published in the English or Chinese language.

2.2. Inclusion and Exclusion Criteria. Inclusion criteria were as follows: (1) study design: cohort, (2) population: patients with CRC, (3) parameter: MUC2 expression levels in CRC tissue samples, and (4) outcomes: associations between MUC2 expression levels in CRC tissues and overall survival (OS). Exclusion criteria were as follows: (1) duplicate publications; (2) in vitro or animal studies; (3) conference reports, reviews, books, case reports, or letters; or (4) insufficient data. When articles reported data from the same study, data from the most recent article was included.

2.3. Study Selection and Data Extraction. Two reviewers (Chao Li, Didi Zuo) independently examined titles and abstracts to select eligible studies. The full text of potentially relevant studies was retrieved and examined to determine which studies met the inclusion criteria.

Two reviewers (Chao Li, Didi Zuo) independently extracted data from eligible studies including first author's last name, year of publication, country, number of patients, mean age of patients, time of follow-up, MUC2 detection method, MUC2 antibody, cutoff values used to assess MUC2 expression levels, and clinical outcomes. Disagreements about study selection and data extraction were resolved by discussion with a third reviewer (Libin Yin) until consensus was reached.

2.4. Methodological Quality. Two reviewers (Chao Li, Didi Zuo) independently assessed the methodological quality of the included studies using the modified Newcastle-Ottawa Scale (NOS) [38], which allocates a maximum of 9 points according to the quality of the selection, comparability, and outcomes of the study populations. Study quality was defined as poor (0-3), fair (4-6), or good (7-9). Publication bias was assessed using Begg's rank correlation test and Egger's linear regression [39].

Disagreements about the assessment of methodological quality were resolved by discussion with a third reviewer (Libin Yin) until consensus was reached.

2.5. Statistical Analysis. Statistical analyses were performed using Review Manager, version 5.3 (Cochrane Collaboration, Copenhagen, Denmark), and STATA, version 12.0 (Stata Corporation, College Station, TX, USA). Hazard ratios (HRs) with 95% confidence intervals (CIs) were used to evaluate the association between MUC2 expression levels (low versus high) in CRC tissues and OS. HR data were obtained directly from studies or were calculated from Kaplan-Meier curves using Engauge Digitizer, version 4.1 (http://markummitchell.github.io/engauge-digitizer/) [40]. An HR > 1 suggested a worse prognosis in CRC patients with a low level of MUC2 expression, and an HR < 1 indicated a better prognosis. Risk ratios (RRs) with 95% CIs were used to evaluate the associations between MUC2 expression levels (low versus high) in CRC tissues and CRC clinicopathological characteristics, including TNM stage, lymph node metastasis, lymphatic invasion, tumor site, tumor size, gender, histological grade, depth of invasion, and distant metastasis. An RR > 1 suggested that a clinicopathological characteristic was associated with a low level of MUC2 expression, and an RR < 1 indicated a characteristic was associated with a high level of MUC2 expression. A random-effects model was used to pool studies with significant heterogeneity, as determined by the chi-squared test (P [less than or equal to] 0.10) and the inconsistency index ([I.sup.2] [greater than or equal to] 50%) [41, 42]. Sources of heterogeneity were explored using metaregression. Sensitivity analysis omitting one study at a time was conducted to investigate the robustness of the findings. P < 0.05 was considered statistically significant.

3. Results

3.1. Search Results. The searches identified 301 articles. Titles and abstracts were screened, and 99 duplicates and 172 studies that did not meet the inclusion criteria were excluded. The full text of 30 articles was retrieved for further review. Of these, 5 review articles, 4 studies that did not report an endpoint, and 10 studies with insufficient data were excluded. Finally, 11 studies [37, 43-52] were found eligible for inclusion in our review (Figure 1).

3.2. Characteristics of the Included Studies. The characteristics of the included studies are shown in Table 1. The 11 eligible studies [37, 43-52] were published between 2007 and 2017. Overall, the studies included 2619 patients (range, 35-938 patients). The mean age of patients ranged from 52.9 to 70.5 years, and the median follow-up ranged from 36 to 128 months. Various anti-MUC2 monoclonal antibodies were utilized, including Ccp-58 MRQ-18, NCL-MUC2, and H300. All studies quantified MUC2 expression levels in CRC tissues by immunohistochemistry (IHC). The measurements in all of the included studies were of overall intensity of staining or of percentage cells that were stained. However, each study used a different cutoff point.

3.3. Methodological Quality. The methodological quality of all included studies was good (NOS score > 7) (Table 2). Begg's rank correlation test and Egger's linear regression revealed no publication bias (Begg's test: OS, P = 0.152; DFS/RFS, P = 0806; TNM stage, P = 0711; lymph node metastasis, P = 0536; lymphatic invasion, P = 1000; tumor site, P = 1000; tumor size, P = 1000; gender, P = 0060, histological grade, P = 0707; depth of invasion, P = 0707; and distant metastasis, P = 1000) (Supplementary File 1).

3.4. Outcomes

3.4.1. MUC2 Expression and Overall Survival in CRC. The association between the MUC2 expression level in CRC tissues and OS was investigated in 10 studies. The meta-analysis demonstrated that a low level of MUC2 expression was associated with poor OS in patients with CRC (HR, 1.67; 95% CI, 1.43-1.94; P <000001; Figure 2(a)). There was no evidence of significant heterogeneity between the studies (P = 028,[I.sup.2] = 17%).

3.4.2. MUC2 Expression and Disease-Free Survival/ Recurrence-Free Survival. The association between the MUC2 expression level in CRC tissues and DFS/RFS was investigated in 5 studies. The meta-analysis demonstrated that a low level of MUC2 expression was associated with shorter DFS/RFS in patients with CRC (HR, 1.60; 95% CI, 1.21-2.12; P = 0001; Figure 2(b)). There was no evidence of significant heterogeneity between the studies (P = 098, [I.sup.2] = 0%).

3.4.3. MUC2 Expression and TNM Stage. The association between the MUC2 expression level in CRC tissues and TNM stage was investigated in 8 studies. The meta-analysis demonstrated that a low level of MUC2 expression was associated with CRC in the advanced stages (TNM stage III/IV) compared to the localized stages (TNM stage I/II) (RR, 1.42; 95% CI, 1.26-1.60; P <000001; Figure 3(a)). There was no evidence of significant heterogeneity between the studies (P = 0007, [I.sup.2] = 46%).

3.4.4. MUC2 Expression and Lymph Node Metastasis. The association between the MUC2 expression level in CRC tissues and lymph node metastasis was investigated in 8 studies. The meta-analysis demonstrated that a low level of MUC2 expression was associated with lymph node metastasis in patients with CRC (RR, 1.41; 95% CI, 1.25-1.60; P < 0.00001; Figure 3(b)). There was no evidence of significant heterogeneity between the studies (P < 000001, [I.sup.2] = 49%).

3.4.5. MUC2 Expression and Lymphatic Invasion. The association between the MUC2 expression level in CRC tissues and lymphatic invasion was investigated in 3 studies. The metaanalysis demonstrated that a low level of MUC2 expression was associated with lymphatic invasion in patients with CRC (RR, 1.64; 95% CI, 1.26-2.12; P = 00002; Figure 3(c)). There was no evidence of significant heterogeneity between the studies (P = 019, [I.sup.2] = 40%).

3.4.6. MUC2 Expression and Tumor Site. The association between the MUC2 expression level in CRC tissues and tumor site was investigated in 5 studies. The meta-analysis demonstrated that a low level of MUC2 expression was associated with CRC in the rectum compared to the colon (RR, 1.26; 95% CI, 1.09-1.46; P = 0001; Figure 3(d)). There was no evidence of significant heterogeneity between the studies (P = 011, [I.sup.2] = 47%).

3.4.7. MUC2 Expression and Tumor Size. The association between the MUC2 expression level in CRC tissues and tumor size was investigated in 2 studies. The meta-analysis demonstrated that a low level of MUC2 expression was associated with large tumors compared to small tumors in patients with CRC (RR, 1.32; 95% CI, 1.02-1.70; P = 003; Figure 3(e)). There was no evidence of heterogeneity between the studies (P = 096, [I.sup.2] = 0%).

3.4.8. MUC2 Expression and Other Clinical Features. The associations between the MUC2 expression level in CRC tissues and other clinicopathological characteristics were investigated The meta-analysis demonstrated that a low level of MUC2 expression did not show an association with gender (female versus male: RR, 0.92; 95% CI, 0.82-1.04; P = 020; Figure 3(f)), histological grade (RR 1.19; 95% CI, 0.95-1.50; P = 013; Figure 3(g)), depth of invasion (T3, T4 versus T1, T2: RR, 1.03; 95% CI, 0.66-1.62; P = 089; Figure 3(h)), and distant metastasis (positive versus negative: RR, 1.13;95% CI, 0.92-1.38; P = 024; Figure 3(i)).

3.5. Sensitivity Analysis. Sensitivity analysis omitting one study at a time indicated that the findings of this meta-analysis were robust (Supplementary File 2).

3.6. Metaregression. The metaregression of factors influencing the association of MUC2 expression with OS and DFS/ RFS in CRC was performed. None of the covariates analyzed, including year, country, antibody, or cutoff values, influenced the association (Supplementary File 3).

4. Discussion

Evidence suggests that CRC tissues express low levels of MUC2 and that MUC2 plays a role in the development and progression of CRC. However, the prognostic value of MUC2 in CRC remains to be elucidated. Although a previous meta-analysis [53] investigated the association between MUC2 expression and CRC clinicopathological characteristics, to the authors' knowledge, the current study is the first meta-analysis to evaluate the prognostic value of MUC2 expression in CRC. The results showed that a low level of MUC2 expression in CRC tissues was associated with poor OS and DFS/RFS. These findings suggest that MUC2 has a protective role in CRC, which may be explained by several mechanisms. MUC2 silencing may promote CRC metastasis by interleukin-6-induced EMT, which contributes to the invasiveness of cancer cells [21, 54].

MUC2 downregulation may contribute to chronic inflammation [55], generating a microenvironment that results in genomic instability [56]. In addition, MUC2 downregulation has been associated with increased expression of tumor-associated antigen carcinoembryonic antigen-related cell adhesion molecules 5 and 6 (CEACAM5 and CEACAM6), which are involved in cell adhesion, migration, tumor invasion, and metastasis [57, 58]. Taken together, these data indicate that MUC2 may serve as a therapeutic target with potential to improve clinical management in CRC and suggest that randomized controlled clinical trials investigating the role of MUC2 in CRC therapy are warranted.

In accordance with our findings, previous studies indicated that a low level of MUC2 expression in CRC tissues is an indicator of poor prognosis. Betge et al. [48], showed that loss of MUC2 expression in CRC tissues was a predictor of adverse outcome. Wang et al. [45] reported that low MUC2 expression in CRC tissues was significantly associated with lymph node metastasis, poor cellular differentiation, and an advanced tumor stage in CRC, and patients with high MUC2 expression in CRC tissues had higher 5-year survival than patients with low MUC2 expression. Lugli et al. [59] found that the loss of MUC2 in CRC tissues was an adverse prognostic factor for survival in mismatch-repair- (MMR-) proficient and MLH1-negative CRC. In contrast, other studies showed a lower 3-year survival rate in patients with high MUC2 expression in CRC tissues compared to low MUC2 expression (0% versus 60%, resp.) [60]. Espinoza et al. [34] reported that MUC2 expression levels in CRC tissues did not significantly correlate with DFS among African Americans and Caucasian Americans.

As CRC clinicopathological characteristics are often used in clinical practice to predict prognosis, the current study comprehensively explored the association between MUC2 expression levels in CRC tissues and CRC clinicopathological characteristics. The results showed that a low level of MUC2 expression was associated with advanced TNM stage, lymph node metastasis, lymphatic invasion, tumor in the rectum versus the colon, and large tumor size. However, there were no associations between MUC2 expression level and gender, histological grade, depth of invasion, and distant metastasis. Previous reports have demonstrated that advanced TNM stage, lymph node metastasis, lymphatic invasion, rectal tumor site, and large tumor size are predictors of poor prognosis in CRC [44, 46, 61-63]. These data, together with the findings from the current study, imply that the low levels of MUC2 expression in CRC tissues may be used as a biomarker for poor prognosis.

As MUC2 expression levels in CRC tissues are important for diagnosis and prognosis in CRC, MUC2 levels in CRC tissues may be used to guide clinical decision-making. MUC2 may be detected by immunohistochemistry, which is a relatively simple and cost-effective method that could gain widespread acceptance. However, as MUC2 is determined postoperatively in CRC tissue samples, continuous monitoring of MUC2 expression levels throughout the course of disease and with treatment will be challenging.

This study was associated with some limitations. First, some of the included studies did not directly report HRs; instead, they had to be extracted from Kaplan-Meier curves, which may have affected the robustness of our results. Second, the potential sources of heterogeneity between the studies included publication year, country, MUC2 antibody, and cutoff values for MUC2 expression; however, the metaregression analysis revealed that none of these factors were significant sources of heterogeneity. Last, the sample size in the study was small; therefore, the findings should be considered preliminary.

In conclusion, the current study suggests that a low level of MUC2 expression is an independent factor of poor prognosis in colorectal cancer and also associated with later TNM stage, presence of lymph node metastasis, rectal tumor site, and large tumor size. However, the clinical relevance of MUC2 downregulation in CRC tissues remains to be elucidated. Large well-designed cohort studies are required to validate MUC2 as a biomarker for poor prognosis in CRC.

https://doi.org/10.1155/2018/6986870

Conflicts of Interest

The authors declare no competing financial interests.

Authors' Contributions

Chao Li helped in the data curation, investigation, methodology, resources, validation, and writing of the original draft. Didi Zuo helped in the data curation, formal analysis, and investigation. Libin Yin helped in the analysis, investigation, and validation. Yuyang Lin helped in doing formal analysis and designed a software. Chenguang Li designed a software. Tao Liu also designed a software. Lei Wang helped in the conceptualization, funding acquisition, project administration, supervision, visualization, and writing--review and editing.

Supplementary Materials

Supplementary 1. Supplementary File 1: publication bias. (a) OS, (b) DFS/RFS, (c) TNM stage, (d) lymph node metastasis, (e) lymphatic invasion, (f) tumor site, (g) tumor size, (h) gender, (i) tumor grade, (j) depth of invasion, (k) distant.

Supplementary 2. Supplementary File 2: sensitivity analysis. (a) OS, (b) DFS/RFS, (c) TNM stage, (d) lymph node metastasis, (e) lymphatic invasion, (f) tumor site, (g) tumor size, (h) gender, (i) tumor grade, (j) depth of invasion, (k) distant.

Supplementary 3. Supplementary File 3: results of metaregression analysis exploring the source of heterogeneity with OS and DFS.

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Chao Li (iD), (1) Didi Zuo, (2) Libin Yin, (1) Yuyang Lin, (1) Chenguang Li, (1) Tao Liu, (1) and Lei Wang (iD) (1)

(1) Department of Colorectal and Anal Surgery, The First Hospital of Jilin University, Changchun, China

(2) Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, China

Correspondence should be addressed to Lei Wang; leiwang1967@163.com

Received 20 January 2018; Revised 15 April 2018; Accepted 22 April 2018; Published 5 June 2018

Academic Editor: Riccardo Casadei

Caption: Figure 1: Flowchart of literature search. From: Moher D, Libertati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PloS Med 6(7): e1000097. doi:10.1371/journal.pmed1000097. For more information, visit http://www.prisma-statement.org.
Table 1: Main characteristics of the included publications.

Publication        Year     Country     Patient   Gender    Antibody
                                        number

Adams et al.       2009   Switzerland     938     422/510      NR

Betge et al.       2016     Germany       381     215/166    Ccp-58

Elzagheid et al.   2013      Libya        141      55/86     MRQ-18

Imai et al.        2013      Japan        250     136/114    Ccp-58

Kang et al.        2011      Korea        229       NR         NR

Khanh et al.       2013      Japan        206     114/92     Ccp-58

Lu et al.          2014      China        60       33/27     Ccp-58

Perez et al.       2008     Brazil        35       20/15     Ccp-58

Wang et al.        2017      China        139      76/63    NCL-MUC2

Yu et al.          2007      China        150      95/55     Ccp-58

Zwenger et al.     2014    Argentina      90       52/38      H300

Publication        Cutoff (low/high level)   Method   Outcome

Adams et al.             High (>5%)           IHC       OS

Betge et al.             High (>0%)           IHC     OS/DFS

Elzagheid et al.         High (>0%)           IHC     OS/DFS

Imai et al.        High ([greater than or     IHC     OS/RFS
                       equal to] 25%)

Kang et al.         High (staining score      IHC       OS
                   [greater than or equal
                           to] 6)

Khanh et al.       High ([greater than or     IHC     OS/RFS
                        equal to] 5%)

Lu et al.                High (>5%)           IHC       OS

Perez et al.             High (>10%)          IHC     OS/DFS

Wang et al.              High (>20%)          IHC       OS

Yu et al.           High (staining score      IHC       OS
                   [greater than or equal
                           to] 2)

Zwenger et al.     High (staining score > 0)  IHC       OS

Publication        TNM stage   Mean age    Median      NOS
                               (years)    follow-up   score
                                          (months)

Adams et al.         I-IV        70.5        128        7

Betge et al.         I-IV        68.5        NR         8

Elzagheid et al.     I-IV         NR         77         8

Imai et al.          I-IV         NR         NR         8

Kang et al.         II-III        NR         108        7

Khanh et al.         I-IV         NR         NR         8

Lu et al.            I-IV        52.9        NR         8

Perez et al.         I-IV        62.2        NR         7

Wang et al.          II-IV        NR         NR         8

Yu et al.            I-IV        57.5        NR         8

Zwenger et al.       I-IV         NR         NR         8

IHC: immunohistochemistry; OS: overall survival; DFS: disease-free
survival; RFS: recurrence-free survival; NR: not reported; NOS
score: Newcastle-Ottawa Scale score.

Table 2: Quality assessment of the included studies.

First author, year                          Selection (1)

                         Representativeness    Selection of
                         of exposed cohort *   nonexposed
                                                 cohort *

Adams et al., 2009                *                 *
Betge et al., 2016                *                 *
Elzagheid et al., 2013            *                 *
Imai et al., 2013                 *                 *
Kang et al., 2011                 *                 *
Khanh et al., 2013                *                 *
Lu et al., 2014                   *                 *
Perez et al., 2008                *                 *
Wang et al., 2017                 *                 *
Yu et al., 2007                   *                 *
Zwenger et al., 2014              *                 *

First author, year       Selection (1)      Comparability (2)

                         Ascertainment      No primary outcome
                         of exposure *   was present at the start
                                                of study *

Adams et al., 2009             *
Betge et al., 2016             *                    *
Elzagheid et al., 2013         *
Imai et al., 2013              *
Kang et al., 2011              *                    *
Khanh et al., 2013             *
Lu et al., 2014                *
Perez et al., 2008             *                    *
Wang et al., 2017              *
Yu et al., 2007                *
Zwenger et al., 2014           *

First author, year       Comparability (2)

                         Comparable on      Outcome
                         confounder **    assessment *

Adams et al., 2009            * *              *
Betge et al., 2016             *               *
Elzagheid et al., 2013        * *              *
Imai et al., 2013             * *              *
Kang et al., 2011              *               *
Khanh et al., 2013            * *              *
Lu et al., 2014               * *              *
Perez et al., 2008             *               *
Wang et al., 2017             * *              *
Yu et al., 2007               * *              *
Zwenger et al., 2014          * *              *

First author, year       Outcome (3)                 Total
                                                     score
                          Adequate       Loss to
                         follow-up *   follow-up *

Adams et al., 2009            *                        7
Betge et al., 2016            *             *          8
Elzagheid et al., 2013        *             *          8
Imai et al., 2013             *             *          8
Kang et al., 2011             *                        7
Khanh et al., 2013            *             *          8
Lu et al., 2014               *             *          8
Perez et al., 2008            *                        7
Wang et al., 2017             *             *          8
Yu et al., 2007               *             *          8
Zwenger et al., 2014          *             *          8

(1) "Selection" part includes representativeness of cases, selection
of controls, exposure ascertainment, and no death when investigation
begins. (2)"Comparability" part includes comparable on confounders.
(3) "Outcome" part includes outcome assessment, adequate follow-up, and
loss to follow-up rate. * represents score of 1. ** represents
score of 2.

Figure 2: Associations between the MUC2 expression level and OS (a)
and DFS/RFS (b) in CRC.

Study or subgroup         log        SE     Weight      Hazard ratio
                         (hazard                     IV, fixed, 95% CI
                         ratio)

Adams et al., 2009       0.47      0.1383   31.9%    1.60 (1.22, 2.10)
Betge et al., 2016       0.2578    0.1791   19.0%    1.29 (0.91, 1.84)
Elzagheid et al., 2013   0.2311    0.2647    8.7%    1.26 (0.75, 2.12)
Imai et al., 2013        0.3507    0.3537    4.9%    1.42 (0.71, 2.84)
Kang et al., 2011        1.319     0.505     2.4%    3.74 (1.39, 10.06)
Khanh et al., 2013       0.4121    0.3053    6.6%    1.51 (0.83, 2.75)
Lu et al., 2014          1.0508    0.4969    2.5%    2.86 (1.08, 7.57)
Wang et al., 2017        0.9203    0.2352   11.0%    2.51 (1.58, 3.98)
Yu et al., 2007          0.6678    0.2703    8.4%    1.95 (1.15, 3.31)
Zwenger et al., 2014     0.6931    0.3637    4.6%    2.00 (0.98, 4.08)
Total (95% CI)                              100.0%   1.67 (1.43, 1.94)

Heterogeneity: [chi.sup.2] = 10.87, df = 9 (P = 0.28); [I.sup.2] = 17%

Test for overall effect: Z = 6.53 (P < 0.00001)

(a)
                                            (a)

Study or subgroup         log        SE     Weight     Hazard ratio
                         (hazard                     IV, fixed, 95% CI
                         ratio)

Betge et al., 2016       0.4895    0.2419   35.4%    1.63 (1.02, 2.62)
Elzagheid et al., 2013   0.4187    0.2847   25.5%    1.52 (0.87, 2.66)
Imai et al., 2013        0.3577    0.3158   20.8%    1.43 (0.77, 2.66)
Khanh et al., 2013       0.6523    0.3751   14.7%    1.92 (0.92, 4.00)
Perez et al., 2008       0.5798    0.7592    3.6%    1.79 (0.40, 7.91)
Total (95% CI)                              100.0%   1.60 (1.21, 2.12)

Heterogeneity: [chi.sup.2] = 0.42, df = 4 (P = 0.98); [I.sup.2] = 0%

Test for overall effect: Z = 3.27 (P = 0.001)

(b)

Figure 3: Associations between the MUC2 expression level and CRC
clinicopathological characteristics. (a) TNM stage, (b) lymph node
metastasis, (c) lymphatic invasion, (d) tumor site, (e) tumor size,
(f) gender, (g) histological grade, (h) depth of invasion,
(i) distant metastasis.

Study or subgroup        TNM stage (III, IV)   TNM stage (I, II)

                          Events     Total      Events     Total

Betge et al., 2016          44        178         42        196
Elzagheid et al., 2013      22         42         49         99
Imai et al., 2013           90        146         28         86
Khanh et al., 2013          78        104         61        102
Lu et al., 2014             21         28         11         32
Perez et al., 2008          5          15         7          20
Wang et al., 2017           18         24         54        115
Yu et al., 2007             43         72         28         78
Total (95% CI)                        609                   728
Total events               321                   280

Study or subgroup                     Risk ratio
                                  M-H, fixed, 95% CI

                         Weight

Betge et al., 2016       17.6%     1.15 (0.80, 1.67)
Elzagheid et al., 2013   12.8%     1.06 (0.75, 1.50)
Imai et al., 2013        15.5%     1.89 (1.36, 2.63)
Khanh et al., 2013       27.0%     1.25 (1.03, 1.52)
Lu et al., 2014           4.5%     2.18 (1.29, 3.69)
Perez et al., 2008        2.6%     0.95 (0.37, 2.42)
Wang et al., 2017         8.2%     1.60 (1.18, 2.16)
Yu et al., 2007          11.8%     1.66 (1.17, 2.37)
Total (95% CI)           100.0%    1.42 (1.26, 1.60)
Total events

Heterogeneity: [chi.sup.2] = 13.05, df = 7 (P = 0.07); [I.sup.2] = 46%

Test for overall effect: Z = 5.65 (P < 0.00001)

(a)

Study or subgroup          Lymph node (+)        Lymph node (-)

                          Events     Total      Events     Total

Betge et al., 2016          42        166         44        208
Elzagheid et al., 2013      22         42         49         99
Imai et al., 2013           86        140         30         90
Khanh et al., 2013          71         94         68        112
Lu et al., 2014             16         23         9          37
Perez et al., 2008          5          14         7          21
Wang et al., 2017           38         62         34         77
Yu et al., 2007             43         72         28         78
Total (95% CI)                        613                   722
Total events               323                   269

Study or subgroup                       Risk ratio
                                    M-H, fixed, 95% CI

                          Weight

Betge et al., 2016        16.5%     1.20 (0.83, 1.73)
Elzagheid et al., 2013    12.3%     1.06 (0.75, 1.50)
Imai et al., 2013         15.4%     1.84 (1.34, 2.54)
Khanh et al., 2013        26.5%     1.24 (1.03, 1.50)
Lu et al., 2014            2.9%     2.86 (1.52, 5.37)
Perez et al., 2008         2.4%     1.07 (0.42, 2.71)
Wang et al., 2017         12.8%     1.39 (1.01, 1.91)
Yu et al., 2007           11.4%     1.66 (1.17, 2.37)
Total (95% CI)            100.0%    1.41 (1.25, 1.60)
Total events

Heterogeneity: [chi.sup.2] = 13.82, df =7 (P = 0.05); [I.sup.2] = 49%

Test for overall effect: Z = 5.65 (P < 0.00001)

(b)

Study or subgroup    Lymphatic invasion (+)   Lymphatic invasion (-)

                      Events     Total        Events     Total

Betge et al., 2016      46        156           40        218
Imai et al., 2013       98        169           20         65
Perez et al., 2008      3          12           9          23
Total (95% CI)                    337                     306
Total events           147                      69

Study or subgroup             Risk ratio
                              M-H, fixed, 95% CI

                     Weight

Betge et al., 2016   48.8%    1.61 (1.11, 2.33)
Imai et al., 2013    42.2%    1.88 (1.28, 2.77)
Perez et al., 2008    9.0%    0.64 (0.21, 1.93)
Total (95% CI)       100.0%   1.64 (1.26, 2.12)
Total events

Heterogeneity: [chi.sup.2] = 3.31, df = 2 (P = 0.19); [I.sup.2] = 40%

Test for overall effect: Z = 3.74 (P = 0.0002)

(c)

Study or subgroup           Rectum           Colon

                         Events   Total   Events   Total

Betge et al., 2016         43      160      43      214
Elzagheid et al., 2013     29      46       42      95
Khanh et al., 2013         70      92       69      114
Perez et al., 2008         11      22       1       13
Yu et al., 2007            42      93       29      57
Total (95% CI)                     413              493
Total events              195              184

Study or subgroup                     Risk ratio
                                  M-H, fixed, 95% CI

                         Weight

Betge et al., 2016       22.6%    1.34 (0.92, 1.94)
Elzagheid et al., 2013   16.8%    1.43 (1.04, 1.96)
Khanh et al., 2013       37.8%    1.26 (1.04, 1.52)
Perez et al., 2008        0.8%    6.50 (0.94, 44.73)
Yu et al., 2007          22.1%    0.89 (0.63, 1.25)
Total (95% CI)           100.0%   1.26 (1.09, 1.46)
Total events

Heterogeneity: [chi.sup.2] = 7.58, df = 4 (P = 0.11); [I.sup.2] = 47%

Test for overall effect: Z = 3.18 (P = 0.001)

(d)

Study or subgroup   Tumour size          Tumour size (< 5cm)
                    ([greater than
                    or equal to] 5cm)

                     Events     Total      Events     Total

Wang et al., 2017      38         64         34         75
Yu et al., 2007        52        101         19        149
Total (95% CI)                   165                   124
Total events           90

Study or subgroup                  Risk ratio
                               M-H, fixed, 95% CI

                     Weight

Wang et al., 2017    55.0%     1.31 (0.95, 1.80)
Yu et al., 2007      45.0%     1.33 (0.89, 1.98)
Total (95% CI)       100.0%    1.32 (1.02, 1.70)
Total events

Heterogeneity: [chi.sup.2] = 0.00, df = 1 (P = 0.96); [I.sup.2] = 0%

Test for overall effect: Z = 2.15 (P = 0.03)

(e)

Study or subgroup            Female                 Male

                         Events     Total      Events     Total

Elzagheid et al., 2013   38         86         33         55
Imai et al., 2013        56         105        63         130
Khanh et al., 2013       58         92         81         114
Perez et al., 2008       5          15         7          20
Wang et al., 2017        34         63         38         76
Yu et al., 2007          22         55         49         95
Total (95% CI)                      416                   490
Total events             213                   271

Study or subgroup                       Risk ratio
                                    M-H, fixed, 95% CI

                         Weight

Elzagheid et al., 2013   16.4%      0.74 (0.53, 1.02)
Imai et al., 2013        23.0%      1.10 (0.86, 1.42)
Khanh et al., 2013       29.5%      0.89 (073, 1.08)
Perez et al., 2008       2.4%       0.95 (0.37, 2.42)
Wang et al., 2017        14.0%      1.08 (0.78, 1.49)
Yu et al., 2007          14.6%      0.78 (0.53, 1.13)
Total (95% CI)           100.0%     0.92 (0.82, 1.04)
Total events

Heterogeneity: [chi.sup.2] = 5.67, df = 5 (P = 0.34); [I.sup.2] = 12%

Test for overall effect: Z = 1.28 (P = 0.20)

(f)

Study or subgroup          Tumor grade (3)      Tumor grade (1, 2)

                          Events     Total      Events     Total

Betge et al., 2016          27        119         59        255
Elzagheid et al., 2013      9          18         62        123
Imai et al., 2013           87        172         32         63
Khanh et al., 2013          8          12        131        194
Wang et al., 2017           17         22         55        117
Yu et al., 2007             24         36         47        114
Total (95% CI)                        379                   866
Total events               172                   386

Study or subgroup                      Risk ratio
                                    M-H, random, 95% CI

                          Weight

Betge et al., 2016        15.3%     0.98 (0.66, 1.46)
Elzagheid et al., 2013    12.3%     0.99 (0.61, 1.63)
Imai et al., 2013         19.9%     1.00 (0.75, 1.32)
Khanh et al., 2013        14.9%     0.99 (0.65, 1.49)
Wang et al., 2017         19.3%     1.64 (1.22, 2.21)
Yu et al., 2007           18.4%     1.62 (1.18, 2.22)
Total (95% CI)            100.0%    1.19 (0.95, 1.50)
Total events

Heterogeneity: [tau.sup.2] = 0.05; [chi.sup.2] = 12.34, df = 5
(P = 0.03); [I.sup.2] = 59%

Test for overall effect: Z = 1.53 (P = 0.13)

(g)

Study or subgroup       Dept of invasion      Dept of invasion
                            (T3, T4)              (T1, T2)

                        Events     Total      Events     Total

Betge et al., 2016        68        279         18         95
Khanh et al., 2013       110        158         29         48
Lu et al., 2014           16         26         9          34
Perez et al., 2008        7          29         5          6
Yu et al., 2007           41         67         30         83
Zwenger et al., 2014     4 23        54         20         28
Total (95% CI)                      613                   294
Total events             265                   111

Study or subgroup                     Risk ratio
                                  M-H, random, 95% CI

                        Weight

Betge et al., 2016      16.8%     1.29 (0.81, 2.05)
Khanh et al., 2013      19.3%     1.15 (0.90, 1.48)
Lu et al., 2014         14.5%     2.32 (1.23, 4.40)
Perez et al., 2008      13.2%     0.29 (0.14, 0.61)
Yu et al., 2007         18.3%     1.69 (1.20, 2.39)
Zwenger et al., 2014    17.8%     1.60 (0.40, 0.88)
Total (95% CI)          100.0%    1.03 (0.66, 1.62)
Total events

Heterogeneity: [tau.sup.2] = 0.26; [chi.sup.2] = 34.73,
df = 5 (P < 0.00001); [I.sup.2] = 86%

Test for overall effect: Z = 0.14 (P = 0.89)

(h)

Study or subgroup             Distant               Distant
                           metastasis (+)        metastasis (-)

                          Events     Total      Events     Total

Elzagheid et al., 2013      9          15         62        126
Khanh et al., 2013          27         37        112        169
Total (95% CI)                         52                   295
Total events                36                   174

Study or subgroup                       Risk ratio
                                    M-H, fixed, 95% CI

                          Weight

Elzagheid et al., 2013    24.7%     1.22 (0.78, 1.91)
Khanh et al., 2013        75.3%     1.10 (0.88, 1.38)
Total (95% CI)            100.0%    1.13 (0.92, 1.38)
Total events

Heterogeneity: [chi.sup.2] = 0.16, df = 1 (P = 0.69); [I.sup.2] = 0%

Test for overall effect: Z = 0.19 (P = 0.24)

(i)
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Article Details
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Author:Li, Chao; Zuo, Didi; Yin, Libin; Lin, Yuyang; Li, Chenguang; Liu, Tao; Wang, Lei
Publication:Gastroenterology Research and Practice
Article Type:Clinical report
Date:Jan 1, 2018
Words:8135
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