Lost expression of cell adhesion molecule 1 is associated with bladder cancer progression and recurrence and its overexpression inhibited tumor cell malignant behaviors
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Cell adhesion molecule 1 (CADM1) regulates cell-cell adhesion and an altered expression level is associated with tumorigenesis and progression. The present study assessed CADM1 expression level in 84 bladder tissues to investigate the association with clinicopathological parameters from bladder cancer patients and then investigated the effects of CADM1 overexpression on T24 bladder cancer cells in vitro. The results demonstrated that expression level of CADM1 protein was significantly reduced in bladder cancer tissues (0.26±0.14) compared with in normal bladder mucosa (0.69±0.092; P<0.01), and methylation of CADM1 promoter was responsible for silencing of CADM1 protein expression and significantly associated with tumor size, recurrence, pathology classification and clinical stage (P<0.05). Overexpression of CADM1 protein inhibited tumor cell proliferation, reduced tumor cell invasion capacity and induced tumor cell apoptosis in vitro. At the gene level, CADM1 expression level upregulated caspase-3 activity and expression of Bax and p27 protein and downregulated levels of B cell lymphoma-2, cyclinD1, cyclinE1 and cyclin dependent kinase 2 proteins. Furthermore, overexpression of CADM1 regulated the expression level of epithelial to mesenchymal transition markers, including increased expression level of E-cadherin and β-catenin, whereas it decreased the levels of Vimentin. The present study demonstrated that lost expression of CADM1 protein may exert an essential role in the development and progression of bladder cancer and suggested that CADM1 may be a novel molecular target for the control of this disease in clinical practice.Keywords: biomarker; bladder cancer; cell adhesion molecule 1; epithelial to mesenchymal transition; tumor cell proliferation and invasion.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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