FTS and 2-DG induce pancreatic cancer cell death and tumor shrinkage in mice

The Ras inhibitor S-trans-trans farnesylthiosalicylic acid (FTS) inhibits active Ras, which controls cell proliferation, differentiation, survival, and metabolism. FTS also inhibits HIF1α expression in cancer cells, leading to an energy crisis. The synthetic glucose analog 2-deoxy-D-glucose (2-DG), which inhibits glycolysis, is selectively directed to tumor cells that exhibit increased glucose consumption. The 2-DG enters tumor cells, where it competes with glucose for glycolytic enzymes. In cancer models, as well as in human phase 1 trials, 2-DG inhibits tumor growth without toxicity. We postulated that under normoxic conditions, tumor cells treated with FTS would be more sensitive than normal cells to 2-DG. We show here that combined treatment with FTS and 2-DG inhibited cancer cell proliferation additively, yet induced apoptotic cell death synergistically both in vitro and in vivo. The induced apoptosis was inferred from QVD-OPH inhibition, an increase in cleaved caspase 3, and loss of survivin. FTS and 2-DG when combined, but not separately, also induced an increase in fibrosis of the tumor tissue, chronic inflammation, and tumor shrinkage. Overall, these results suggest a possible new treatment of pancreatic tumors by the combined administration of FTS and 2-DG, which together induce pancreatic tumor cell death and tumor shrinkage under non-toxic conditions

A literature-based similarity metric for biological processes

BACKGROUND: Recent analyses in systems biology pursue the discovery of functional modules within the cell. Recognition of such modules requires the integrative analysis of genome-wide experimental data together with available functional schemes. In this line, methods to bridge the gap between the abstract definitions of cellular processes in current schemes and the interlinked nature of biological networks are required. RESULTS: This work explores the use of the scientific literature to establish potential relationships among cellular processes. To this end we haveused a document based similarity method to compute pair-wise similarities of the biological processes described in the Gene Ontology (GO). The method has been applied to the biological processes annotated for the Saccharomyces cerevisiae genome. We compared our results with similarities obtained with two ontology-based metrics, as well as with gene product annotation relationships. We show that the literature-based metric conserves most direct ontological relationships, while reveals biologically sounded similarities that are not obtained using ontology-based metrics and/or genome annotation. CONCLUSION: The scientific literature is a valuable source of information from which to compute similarities among biological processes. The associations discovered by literature analysis are a valuable complement to those encoded in existing functional schemes, and those that arise by genome annotation. These similarities can be used to conveniently map the interlinked structure of cellular processes in a particular organism

Allelic penetrance approach as a tool to model two-locus interaction in complex binary traits.

Many binary phenotypes do not follow a classical Mendelian inheritance pattern. Interaction between genetic and environmental factors is thought to contribute to the incomplete penetrance phenomena often observed in these complex binary traits. Several two-locus models for penetrance have been proposed to aid the genetic dissection of binary traits. Such models assume linear genetic effects of both loci in different mathematical scales of penetrance, resembling the analytical framework of quantitative traits. However, changes in phenotypic scale are difficult to envisage in binary traits and limited genetic interpretation is extractable from current modeling of penetrance. To overcome this limitation, we derived an allelic penetrance approach that attributes incomplete penetrance to the stochastic expression of the alleles controlling the phenotype, the genetic background and environmental factors. We applied this approach to formulate dominance and recessiveness in a single diallelic locus and to model different genetic mechanisms for the joint action of two diallelic loci. We fit the models to data on the genetic susceptibility of mice following infections with Listeria monocytogenes and Plasmodium berghei. These models gain in genetic interpretation, because they specify the alleles that are responsible for the genetic (inter)action and their genetic nature (dominant or recessive), and predict genotypic combinations determining the phenotype. Further, we show via computer simulations that the proposed models produce penetrance patterns not captured by traditional two-locus models. This approach provides a new analysis framework for dissecting mechanisms of interlocus joint action in binary traits using genetic crosses