Sensitivity of tumor cells towards CIGB‐300 anticancer peptide relies on its nucleolar localization

CIGB‐300 is a novel anticancer peptide that impairs the casein kinase 2‐mediated phosphorylation by direct binding to the conserved phosphoacceptor site on their substrates. Previous findings indicated that CIGB‐300 inhibits tumor cell proliferation in vitro and induces tumor growth delay in vivo in cancer animal models. Interestingly, we had previously demonstrated that the putative oncogene B23/nucleophosmin (NPM) is the major intracellular target for CIGB‐300 in a sensitive human lung cancer cell line. However, the ability of this peptide to target B23/NPM in cancer cells with differential CIGB‐300 response phenotype remained to be determined. Interestingly, in this work, we evidenced that CIGB‐300's antiproliferative activity on tumor cells strongly correlates with its nucleolar localization, the main subcellular localization of the previously identified B23/NPM target. Likewise, using CIGB‐300 equipotent doses (concentration that inhibits 50% of proliferation), we demonstrated that this peptide interacts and inhibits B23/NPM phosphorylation in different cancer cell lines as evidenced by in vivo pull‐down and metabolic labeling experiments. Moreover, such inhibition was followed by a fast apoptosis on CIGB‐300‐treated cells and also an impairment of cell cycle progression mainly after 5 h of treatment. Altogether, our data not only validates B23/NPM as a main target for CIGB‐300 in cancer cells but also provides the first experimental clues to explain their differential antiproliferative response. Importantly, our findings suggest that further improvements to this cell penetrating peptide‐based drug should entail its more efficient intracellular delivery at such subcellular localization. Copyright © 2012 European Peptide Society and John Wiley & Sons, Ltd.     

Targeting ERK/COX-2 signaling pathway in permethrin-induced testicular toxicity: a possible modulating effect of matrine

Molecular Biology Reports - Permethrin (PER), the prevalent synthetic pyrethroid, was reported to have genotoxic effects along with male reproductive organs impairment. Matrine, the Chinese herb...     

Synthesis and reactions of some new pyrrolylthieno[2,3-D]quinoxaline and pyrrolopyrazinothienoquinoxalines

The synthesis of 3-pyrrolyl-2-substituted thieno[2,3-b]quinoxalines from the precursor 3-amino derivatives are described. Synthesized compounds were subjected to reactions with other reagents to synthe-size polyfused heterocyclic incorporated thienoquinoxaline moiety. Some of the synthesized compounds were screened for their antibacterial and antifungal activities.     

Detection of biomarkers for Hepatocellular Carcinoma using a hybrid univariate gene selection methods

ABSTRACT: BACKGROUND: Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC). The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC. RESULTS: In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson's correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators) in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery) databases. The top ten genes selected using Pearson's correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers) genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy). A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer) in the top ten genes of the list of intersected genes. CONCLUSIONS: To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when used individually according to biological interpretation and the examination of gene expression signal profiles.