Abstract

ObjectiveTo evaluate the predicting value of MUC1 expression in lymph node and distant metastasis of colorectal cancer (CRC).MethodsPubmed/ MEDLINE and EMBASE were searched to identify eligible studies that evaluated the correlation between MUC1 and CRC. A meta-analysis was conducted to evaluate the impact of MUC1 expression on CRC metastasis.ResultsA total of 18 studies (n = 3271) met inclusion criteria and the mean Newcastle-Ottawa Scale (NOS) score was 6.3 with a range from 4 to 8. The pooled OR in the meta-analysis of 15 studies indicated that positive MUC1 expression correlated with more CRC node metastasis (OR = 2.32, 95% CI = 1.63–3.29). The data synthesis of 6 studies suggested that MUC1 expression predicted more possibility of CRC distant metastasis (OR = 2.22, 95% CI = 1.23–4.00). In addition, the combined OR of 7 studies showed that MUC1 expression indicated higher Duke’s stage (OR = 3.02, 95% CI = 2.11–4.33). No publication bias was found in the mate-analysis by Begg’s test or Egger’s test with the exception of the meta-analysis of MUC1 with CRC node metastasis (Begg’s test p = 0.729, Egger’s test p = 0.000).ConclusionsDespite of some modest bias, the pooled evidence suggested that MUC1 expression was significantly correlated with CRC metastasis.

Highlights

  • Mucin 1 (MUC1) is a structural transmembrane protein with a heavily glycosylated extracellular domain, which is known as episialin, CA5-3, DF3, PAS-O, PEM, H23Ag, EMA and MCA [1,2]

  • The pooled odd ratio (OR) in the meta-analysis of 15 studies indicated that positive MUC1 expression correlated with more colorectal cancer (CRC) node metastasis (OR = 2.32, 95% Confidence Interval (CI) = 1.63–3.29)

  • The data synthesis of 6 studies suggested that MUC1 expression predicted more possibility of CRC distant metastasis (OR = 2.22, 95% CI = 1.23–4.00)

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Summary

A Systematic Review and Meta-Analysis of

Yunhui Zeng1☯, Qiongwen Zhang2,3☯*, Yujie Zhang4☯, Minxun Lu1, Yang Liu, Tianying Zheng, Shijian Feng, Meiqin Hao, Huashan Shi2,3¤*.

Objective
Methods
Results
Introduction
Evaluation of Publication Bias
Discussion
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