Mouse anti-Human CCNA1 monoclonal antibody, clone 5B226C6

Background Long noncoding RNA (lncRNA) plays a vital role in the development of many diseases. The abnormal expression of lncRNA is closely related to the occurrence and development of different kinds of tumors including prostate cancer (PCa). Methods Differentially expressed lncRNA LINC00304 was identified using a publicly available gene expression data set (GSE38241) and quantitative polymerase chain reaction validation. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis were used to predict the molecular function of LINC00304. A lncRNA microarray, bioinformatic analysis, and chromatin immunoprecipitation assay were carried out to verify the upstream androgen receptor (AR) signaling pathway. Subsequently, the function of LINC00304 was observed by a series of in vitro assays. Results We observed higher expression of LINC00304 in PCa cells and samples compared with normal prostate cells and tissues. Functional analysis of LINC00304 showed it was related to regulating cell cycle process, cellular developmental process, and focal adhesion. Further, we identified androgen-inhibited lncRNA, LINC00304 as a direct target of AR. A series of functional studies revealed that overexpression of LINC00304 could significantly promote cell proliferation and cell cycle progression in PCa cells. We also find that LINC00304 can significantly promote CCNA1 expression in PCa cells. Conclusions Our results indicate that LINC00304 may represent a new diagnostic and therapeutic biomarker for PCa.

Acquired erlotinib resistance (AER) during cancer treatment remains a major clinical challenge that results in the recurrence and metastasis of cancers. Therefore, we sought to identify differentially expressed genes (DEGs) by performing a meta-analysis of AER-related microarray datasets and discover biomarkers by conducting a systemic in-silico analysis. Using the RankProd algorithm, we identified 775 DEGs (536 up-regulated and 239 down-regulated). Functional enrichment analyses of the total DEG s suggested that "cell adhesion" and "cytokine-cytokine receptor interactions" may be closely associated with AER process. Some DEGs shared target sites of the potential microRNA including miR-21, miR-200b/c, miR-429 and miR-9. Target sites of FOXJ1, NFAT, FOXO4, and JUN were also significantly enriched. From the protein-protein interaction network, we clustered four functional modules by p-value and node density and found hub genes with many interacting neighbors. Finally, we identified seven candidate hub DEGs (TIMP3, SPARC, ITGA1, CCNA1, SOX2, KRT14, and PTPRZ1) for AER development.