Anti-PRPS1 (aa 1-318) polyclonal antibody

Cold atmospheric plasma ( CAP) has gained attention for use in cancer treatment owing to its ability to preferentially induce cancer cell death; however, the involved molecular mechanism remains to be elucidated. Herein, an epigenetic effect of CAP on cancer cells was examined by performing a genome-wide ChIP-seq for H3K4me3 in MCF-7 breast cancer cell line. Consequently, 899 genes showed significantly changed methylation level at H3K4 with constructing "Cellular Compromise, DNA Replication, Recombination, Repair, and Cell Cycle" as the top network. Comparisons with expression array data revealed a coincidence between histone modification and gene expression for 18 genes, and the association was confirmed by ChIP-PCR and qRT-PCR for selected genes. The expression of the affected genes, such as HSCB and PRPS1, was recovered when a histone demethylase JARID1A was inhibited. Furthermore, JARID1A was induced by CAP via the reactive oxygen species signaling. The two genes are known as oncogenes and show a higher expression in breast cancer tissue, and this was supported by the decreased colony formation ability of MCF-7 cells when the cells were treated with siRNAs against each gene. Taken together, these data indicate that CAP inhibits cancer cell proliferation by modulating the methylation level of H3K4 corresponding to oncogenes.

Although several researches have explored the similarity across development and tumorigenesis in cellular behavior and underlying molecular mechanisms, not many have investigated the developmental characteristics at proteomic level and further extended to cancer clinical outcome. In this study, we used iTRAQ to quantify the protein expression changes during macaque rhesus brain development from fetuses at gestation 70 days to after born 5 years. Then, we performed weighted gene co-expression network analysis (WGCNA) on protein expression data of brain development to identify co-expressed modules that highly expressed on distinct development stages, including early stage, middle stage and late stage. Moreover, we used the univariate cox regression model to evaluate the prognostic potentials of these genes in two independent glioblastoma multiforme (GBM) datasets. The results showed that the modules highly expressed on early stage contained more reproducible prognostic genes, including ILF2, CCT7, CCT4, RPL10A, MSN, PRPS1, TFRC and APEX1. These genes were not only associated with clinical outcome, but also tended to influence chemoresponse. These signatures identified from embryonic brain development might contribute to precise prediction of GBM prognosis and identification of novel drug targets in GBM therapies. Thus, the development could become a viable reference model for researching cancers, including identifying novel prognostic markers and promoting new therapies.