Small lytic peptides escape the inhibitory effect of heparan sulfate on the surface of cancer cells

Several naturally occurring cationic antimicrobial peptides (CAPs), including bovine lactoferricin (LfcinB), display promising anticancer activities. These peptides are unaffected by multidrug resistance mechanisms and have been shown to induce a protective immune response against solid tumors, thus making them interesting candidates for developing novel lead structures for anticancer treatment. Recently, we showed that the anticancer activity by LfcinB was inhibited by the presence of heparan sulfate (HS) on the surface of tumor cells. Based on extensive structure-activity relationship studies performed on LfcinB, shorter and more potent peptides have been constructed. In the present study, we have investigated the anticancer activity of three chemically modified 9-mer peptides and the influence of HS and chondroitin sulfate (CS) on their cytotoxic activity. Various cell lines and red blood cells were used to investigate the anticancer activity and selectivity of the peptides. The cytotoxic effect of the peptides against the different cell lines was measured by use of a colorimetric MTT viability assay. The influence of HS and CS on their cytotoxic activity was evaluated by using HS/CS expressing and HS/CS deficient cell lines. The ability of soluble HS and CS to inhibit the cytotoxic activity of the peptides and the peptides’ affinity for HS and CS were also investigated. The 9-mer peptides displayed selective anticancer activity. Cells expressing HS/CS were equally or more susceptible to the peptides than cells not expressing HS/CS. The peptides displayed a higher affinity for HS compared to CS, and exogenously added HS inhibited the cytotoxic effect of the peptides. In contrast to the previously reported inhibitory effect of HS on LfcinB, the present study shows that the cytotoxic activity of small lytic peptides was increased or not affected by cell surface HS

Identification and Analysis of Co-Occurrence Networks with NetCutter

BACKGROUND: Co-occurrence analysis is a technique often applied in text mining, comparative genomics, and promoter analysis. The methodologies and statistical models used to evaluate the significance of association between co-occurring entities are quite diverse, however. METHODOLOGY/PRINCIPAL FINDINGS: We present a general framework for co-occurrence analysis based on a bipartite graph representation of the data, a novel co-occurrence statistic, and software performing co-occurrence analysis as well as generation and analysis of co-occurrence networks. We show that the overall stringency of co-occurrence analysis depends critically on the choice of the null-model used to evaluate the significance of co-occurrence and find that random sampling from a complete permutation set of the bipartite graph permits co-occurrence analysis with optimal stringency. We show that the Poisson-binomial distribution is the most natural co-occurrence probability distribution when vertex degrees of the bipartite graph are variable, which is usually the case. Calculation of Poisson-binomial P-values is difficult, however. Therefore, we propose a fast bi-binomial approximation for calculation of P-values and show that this statistic is superior to other measures of association such as the Jaccard coefficient and the uncertainty coefficient. Furthermore, co-occurrence analysis of more than two entities can be performed using the same statistical model, which leads to increased signal-to-noise ratios, robustness towards noise, and the identification of implicit relationships between co-occurring entities. Using NetCutter, we identify a novel protein biosynthesis related set of genes that are frequently coordinately deregulated in human cancer related gene expression studies. NetCutter is available at http://bio.ifom-ieo-campus.it/NetCutter/). CONCLUSION: Our approach can be applied to any set of categorical data where co-occurrence analysis might reveal functional relationships such as clinical parameters associated with cancer subtypes or SNPs associated with disease phenotypes. The stringency of our approach is expected to offer an advantage in a variety of applications

The anticancer activity of lytic peptides is inhibited by heparan sulfate on the surface of the tumor cells

<p>Abstract</p> <p>Background</p> <p>Cationic antimicrobial peptides (CAPs) with antitumor activity constitute a promising group of novel anticancer agents. These peptides induce lysis of cancer cells through interactions with the plasma membrane. It is not known which cancer cell membrane components influence their susceptibility to CAPs. We have previously shown that CAPs interact with the two glycosaminoglycans (GAGs), heparan sulfate (HS) and chondroitin sulfate (CS), which are present on the surface of most cells. The purpose of this study was to investigate the role of the two GAGs in the cytotoxic activity of CAPs.</p> <p>Methods</p> <p>Various cell lines, expressing different levels of cell surface GAGs, were exposed to bovine lactoferricin (LfcinB) and the designer peptide, KW5. The cytotoxic effect of the peptides was investigated by use of the colorimetric MTT viability assay. The cytotoxic effect on wild type CHO cells, expressing normal amounts of GAGs on the cell surface, and the mutant pgsA-745, that has no expression of GAGs on the cell surface, was also investigated.</p> <p>Results</p> <p>We show that cells not expressing HS were more susceptible to CAPs than cells expressing HS at the cell surface. Further, exogenously added heparin inhibited the cytotoxic effect of the peptides. Chondroitin sulfate had no effect on the cytotoxic activity of KW5 and only minor effects on LfcinB cytotoxicity.</p> <p>Conclusion</p> <p>Our results show for the first time that negatively charged molecules at the surface of cancer cells inhibit the cytotoxic activity of CAPs. Our results indicate that HS at the surface of cancer cells sequesters CAPs away from the phospholipid bilayer and thereby impede their ability to induce cytolysis.</p