CPEB4 promotes cell migration and invasion via upregulating Vimentin expression in breast cancer
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS
Authors: Lu, Ran; Zhou, Zhiqiang; Yu, Wenfei; Xia, Yifu; Zhi, Xuting
Abstract
Cytoplasmic polyadenylation element binding protein 4 (CPEB4) is a member of CPEB family which is overexpressed in variety of cancers. However, the biological role and regulatory mechanism of CPEB4 in cancers remain unknown. Here, we first investigate the role of CPEB4 in breast cancer progression and metastasis. The expression of CPEB4 is elevated in breast cancer tissues compared with adjacent normal tissues. Furthermore, high expression levels of CPEB4 is associated with tumor metastasis in breast cancer patients. Ectopic expression of CPEB4 dramatically promotes EMT, migration and invasion of breast cancer cells, while silencing CPEB4 expression significantly reduces these events. Mechanically, overexpression of CPEB4 upregulates Vimentin expression and silencing Vimentin expression blocks CPEB4-induced migration and invasion of breast cancer cells. These results implicate the potential role of CPEB4 and Vimentin in breast cancer metastasis, which is further confirmed by the finding that there is a physical interaction between the two proteins. Altogether, our results provide a novel insight into CPEB4 in regulating breast cancer progression and metastasis. (C) 2017 Elsevier Inc. All rights reserved.
A Genomewide Integrative Analysis of GWAS and eQTLs Data Identifies Multiple Genes and Gene Sets Associated with Obesity
BIOMED RESEARCH INTERNATIONAL
Authors: Liu, Li; Fan, Qianrui; Zhang, Feng; Guo, Xiong; Liang, Xiao; Du, Yanan; Li, Ping; Wen, Yan; Hao, Jingcan; Wang, Wenyu; He, Awen
Abstract
To identify novel susceptibility genes and gene sets for obesity, we conducted a genomewide expression association analysis of obesity via integrating genomewide association study (GWAS) and expression quantitative trait loci (eQTLs) data. GWAS summary data of body mass index (BMI) and waist-to-hip ratio (WHR) was driven from a published study, totally involving 339,224 individuals. The eQTLs dataset (containing 927,753 eQTLs) was obtained from eQTLs meta-analysis of 5,311 subjects. Integrative analysis of GWAS and eQTLs data was conducted by SMR software. The SMR single gene analysis results were further subjected to gene set enrichment analysis (GSEA) for identifying obesity associated gene sets. A total of 13,311 annotated gene sets were analyzed in this study. SMR single gene analysis identified 20 BMI associated genes (TUFM, SPI1, APOB48R, etc.). Also 3 WHR associated genes were detected (CPEB4, WARS2, and L3MBTL3). The significant association between Chr16p11 and BMI was observed by GSEA (FDR adjusted.. value = 0.040). The TGCTGCT, MIR-15A, MIR-16, MIR-15B, MIR-195, MIR-424, and MIR-497 (FDR adjusted.. value = 0.049) gene set appeared to be linked with WHR. Our results provide novel clues for the genetic mechanism studies of obesity. This study also illustrated the good performance of SMR for susceptibility gene mapping.