Human EMP3 (Epithelial membrane protein 3) ELISA Kit

Background/Aim: Understanding of the molecular events associated with progression and survival differences in patients with lower-grade gliomas (LGGs) is still unclear. The comparison of findings across studies using different datasets and methods is essential for a new molecular-based classification system. The aim of the study was to identify biomarkers for prognostic classification of patients with LGGs, and furthermore to lay a foundation for future development of targeted therapies for LGGs. Patients and Methods: Using information-theoretic and statistical approaches, we analyzed mRNA expression data for 18,413 genes from LGG samples in order to identify candidate biomarkers for survival. The candidate genes were then evaluated for their potential as prognostic biomarkers using multivariable Cox regression analyses that adjusted for the effects of age and grade. Results: WEE1, EMP3, E2F7, CD58 and NSUN7 genes were identified as candidate biomarkers of LGGs and their high expression was associated with significantly shorter survival. The hazard ratios for mortality were 5.02 (95% CI=3 .40-7 .40) for WEE1, 5.45 (95% CI=3 .63-8.18) for EMP3, 4.49 (95% CI=3 .03-6 .66) for E2F7, 4.77 (95% CI=3 .22-7.06) for CD58 and 4.38 (95% CI=2 .97-6 .47) for NSUN7. In addition, the expression pattern of these genes, associated with shorter survival in LGGs, was also observed in glioblastoma multiforme. Conclusion: Identification of genes associated with poor outcomes will provide insights into novel biological mechanisms that may lead to improvement in progression and survival for patients with LGGs.

To investigate changes in gene expression associated with ERBB2, expression profiting of immortalized human mammary luminal epithelial cells and variants expressing a moderate and high level of ERBB2 has been carried out using cDNA microarrays corresponding to approximately 6000 unique genes/ESTs. A total of 61 significantly up- or downregulated (>2.0-fold) genes were identified and further validated by RT-PCR analysis as well as microarray comparisons with a spontaneously ERBB2-overexpressing breast cancer cell line and ERBB2-positive primary breast tumors. The expression and clinical relevance of proteins predicted to be associated with ERBB2 overexpression in breast cancers were analysed together with their clinical relevance by antibody screening using a tissue array. Differentially regulated genes include those involved in cell-matrix interactions including proline 4-hydroxylase (P4HA2), galectin 1 (LGALS1) and galectin 3 (LGALS3), fibronectin 1 (FN1) and p-cadherin (CDH3), and cell proliferation (CRIP1, IGFBP3) and transformation (S100P, S100A4). A number of genes associated with MYC signalling were also differentially expressed, including NDRG1, USF2 and the epithelial membrane proteins 1 and 3 (EMP1, EMP3). These data represent profiles of the transcriptional changes associated with ERBB2-related pathways in the breast, and identify novel and potentially useful targets for prognosis and therapy.