Identifying common prognostic factors in genomic cancer studies: A novel index for censored outcomes

Background  

With the growing number of public repositories for high-throughput genomic data, it is of great interest to combine the results produced by independent research groups. Such a combination allows the identification of common genomic factors across multiple cancer types and provides new insights into the disease process. In the framework of the proportional hazards model, classical procedures, which consist of ranking genes according to the estimated hazard ratio or the p-value obtained from a test statistic of no association between survival and gene expression level, are not suitable for gene selection across multiple genomic datasets with different sample sizes. We propose a novel index for identifying genes with a common effect across heterogeneous genomic studies designed to remain stable whatever the sample size and which has a straightforward interpretation in terms of the percentage of separability between patients according to their survival times and gene expression measurements.     

Molecular recognition of anions by synthetic receptors

Over the past year, several significant developments have been made in the field of anion binding. The fundamental principles of molecular recognition are increasingly being better understood, and of particular interest are reports of several synthetic anion receptors able to perform their task in complex natural media. Additionally, macroscopic devices such as anion specific electrodes and membranes based on a molecular recognition approach are now being made.     

Lipase-catalyzed transamidation of non-activated amides in organic solvent

A novel biocatalytic reaction of transamidation of non-activated amides with amines is reported. Among 45 different lipolytic and proteolytic enzymes tested, only the lipase from Candida antarcticawas able to catalyze this reaction. The reaction proceeded with up to ca. 80% conversion in anhydrous methyl tert-butyl ether and worked with both N-substituted and unsubstituted amides. The biocatalytic transamidation is an equilibrium process and, therefore, higher conversions to the desired amide were achieved by using increased concentrations of the amine nucleophile.     

Expression of Mitochondrial Regulators PGC1α and TFAM as Putative Markers of Subtype and Chemoresistance in Epithelial Ovarian Carcinoma

Epithelial ovarian carcinoma (EOC), the major cause of gynaecological cancer death, is a heterogeneous disease classified into five subtypes. Each subtype has distinct clinical characteristics and is associated with different genetic risk factors and molecular events, but all are treated with surgery and platinum/taxane regimes. Tumour progression and chemoresistance is generally associated with major metabolic alterations, notably altered mitochondrial function(s). Here, we report for the first time that the expression of the mitochondrial regulators PGC1α and TFAM varies between EOC subtypes; furthermore, we have identified a profile in clear-cell carcinoma consisting of undetectability of PGC1α/TFAM, and low ERα/Ki-67. By contrast, high-grade serous carcinomas were characterised by a converse state of PGC1α/TFAM, ERα positivity and a high Ki-67 index. Interestingly, loss of PGC1α/TFAM and ERα was found also in a non-clear cell EOC cell line made highly resistant to platinum in vitro. Similar to clear-cell carcinomas, these resistant cells also showed accumulation of glycogen. Altogether, our data provide mechanistic insights into the chemoresistant nature of ovarian clear-cell carcinomas. Furthermore, these findings corroborate the need to take into account the diversity of EOC and to develop subtype specific treatment strategies.     

A MONTE CARLO SIMULATION OF CLONE GROWTH

A Monte Carlo simulation of clone growth is discussed from the point of view of clonal volume. It is shown that clone volume is a good representation of the number of cells per clone for a wide range of single cell growth equations. However, the rate at which the coefficient of variation in clonal volume approaches that of cell number per clone is strongly dependent upon the particular growth equation.