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Meta-Analysis of EMT Datasets Reveals Different Types of EMT.

ABSTRACT: As a critical process during embryonic development, cancer progression and cell fate conversions, epithelial-mesenchymal transition (EMT) has been extensively studied over the last several decades. To further understand the nature of EMT, we performed meta-analysis of multiple microarray datasets to identify the related generic signature. In this study, 24 human and 17 mouse microarray datasets were integrated to identify conserved gene expression changes in different types of EMT. Our integrative analysis revealed that there is low agreement among the list of the identified signature genes and three other lists in previous studies. Since removing the datasets with weakly-induced EMT from the analysis did not significantly improve the overlapping in the signature-gene lists, we hypothesized the existence of different types of EMT. This hypothesis was further supported by the grouping of 74 human EMT-induction samples into five distinct clusters, and the identification of distinct pathways in these different clusters of EMT samples. The five clusters of EMT-induction samples also improves the understanding of the characteristics of different EMT types. Therefore, we concluded the existence of different types of EMT was the possible reason for its complex role in multiple biological processes.

SUBMITTER: Liang L

PROVIDER: S-EPMC4892621 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Recent studies have investigated the relationships between PLCE1 polymorphisms and cancer susceptibility. However, some findings lack consistency. Objectives: In the current study, we conducted a meta-analysis to more accurately evaluate the relationships between PLCE1 (rs2274223, rs3765524, rs753724, rs11187842, and rs7922612) single nucleotide polymorphisms (SNPs) and risk for different types of cancer. Methods: We performed a comprehensive search strategy in PubMed, Web of Science, Medline, EMbase, and Scopus for articles available until 19 March 2018. A total of 54 case-control studies comprising 17,955 cases and 20,400 controls were included in the current meta-analysis, which together comprised a total of 32 publications. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) were used to evaluate relationships between the PLCE1 polymorphisms and cancer susceptibility. All statistical analyses were performed using Stata 11 software. Results: Results of the meta-analysis demonstrated that the rs2274223 polymorphism showed a significant correlation with increased overall cancer susceptibility (AG vs. AA: OR 1.168, 95% CI 1.084-1.259; GG vs. AA: OR 1.351, 95% CI 1.163-1.570; AG+GG vs. AA: OR 1.193, 95% CI 1.103-1.290; GG vs. AA+AG: OR 1.262, 95% CI 1.102-1.446; G vs. A: OR 1.163, 95% CI 1.089-1.242). Results of subgroup analysis showed that the rs2274223 polymorphism was associated with higher risk for esophageal cancer and gastric cancer relative to colorectal cancer and head and neck cancer. In addition, the rs2274223 polymorphism was found to be associated with increased cancer risk, especially among the subgroups comprising Asians, studies with population-based controls, studies employing the TaqMan genotyping method, and studies consistent with Hardy-Weinberg equilibrium (HWE). The association between the rs3765524 polymorphism and reduced overall cancer risk was detected in one specific genetic model (CT vs. CC: OR 0.681, 95% CI 0.523-0.886). Results of subgroup analysis showed that the rs3765524 polymorphism was associated with cancer risk in a specific genetic model among the subgroups of colorectal cancer, esophageal cancer, Asians, studies with population-based controls, and studies consistent with HWE. However, relationships among the PLCE1 rs753724, rs11187842, and rs7922612 polymorphisms and tumor risk were not identified. Conclusions: Results of the current meta-analysis suggested that PLCE1 (rs2274223, rs3765524) polymorphisms are associated with cancer susceptibility.

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Meta-Analysis of EMT Datasets Reveals Different Types of EMT.

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