A new approach for evaluating in vivo anti-leukemic activity using the SCE assay. An application on three newly synthesised anti-tumour steroidal esters

Three newly synthesised steroidal esteric derivatives of nitrogen mustard (compounds 1-3) were comparatively studied on a molar basis regarding their ability to induce sister chromatid exchanges (SCEs) in normal human lymphocytes in vitro and therapeutic effects on leukemia P388 bearing mice. Compounds 1 and 3 are modified steroidal esters of p-methyl-m-N,N-bis(2-chloroethyl)amino benzoic acid, and compound 2 is a modified steroidal ester of chlorambucil. All compounds induced statistically significant increases in SCEs and decreases in proliferation rate indices (PRIs) of cultured human lymphocytes and significantly increased the life span of P388 bearing mice. In this study, the doses applied for therapeutic purposes upon leukemia P388 bearing mice in vivo were derived from cytogenetic observations in normal human lymphocytes in vitro. A substantially better therapeutic effect was obtained compared to the effect achieved after the use of quite higher doses related with LD(10) values. We have demonstrated that the order of anti-tumour effectiveness of the treatment schedules of the three newly synthesised compounds tested (at doses derived from cytogenetic observations) coincides with the order of the cytogenetic effects they induce. The SCE assay appears to have an application in the clinical prediction of tumour sensitivity to potential chemotherapeutics.     

Subtype-specific neuronal differentiation of PC12 cells transfected with alpha2-adrenergic receptors

Cells of the PC12 rat pheochromocytoma cell line acquire characteristics of sympathetic neurons under appropriate treatment. Stably transfected PC12 cells expressing individual alpha2-adrenergic receptor (alpha2-AR) subtypes were used to assess the role of alpha2-ARs in neuronal differentiation and to characterise the signalling pathways activated by the alpha2-AR agonist epinephrine in these cells. The effects of alpha2-AR activation were compared with the differentiating action and the signalling mechanisms of nerve growth factor (NGF). Epinephrine induced neuronal differentiation of PC12alpha2 cells through alpha2-AR activation in a subtype-dependent manner, internalization of all human alpha2-AR subtypes, and activation of mitogen-activated protein kinase (MAPK) and the serine-threonine protein kinase Akt. Epinephrine and NGF showed synergism in their differentiating effects. The MAPK kinase (MEK-1) inhibitor PD 98059 abolished the differentiating effect of epinephrine indicating that the differentiation is dependent on MAPK activation. Activating protein-1 (AP-1) DNA-binding activity was increased after epinephrine treatment in all three PC12alpha2 subtype clones. Evaluation of the potential physiological consequences of these findings requires further studies on endogenously expressed alpha2-ARs in neuronal cells.     

Synthetic approaches for the synthesis of a cytostatic steroidal B-D bilactam

A new synthetic procedure and a modification of the original method described in the literature for the synthesis of the steroidal B-D bilactam, 3 beta-hydroxy-7 alpha,17 alpha-diaza-B,D-dihomo-5-androsten-7,17-dione are reported. The key step in the modified method involved protection of the D-lactamic nitrogen atom of 3 beta-acetoxy-17 alpha-aza-D-homo-5-androsten-17-one using a reagent of specific electrophilicity (due to the stereoelectronic properties of the cyclic amide), as Beckmann rearrangement of the B-steroidal ring was hindered, possibly via long range effects, by the presence of the unprotected D-lactamic moiety. Using the 3 beta-acetoxy-5-androsten-17-one as starting material, a new synthetic procedure was developed through ketalization of the 17-ketone and allylic oxidation to the 7-ketone, which was subsequently followed by Beckmann rearrangement of the B- and D-steroid rings. Both approaches resulted in 45 and 67% yields of the desired B,D-bilactam, respectively, in contrast to the 15% yield, which has been reported in the literature.     

Integration Analysis of Three Omics Data Using Penalized Regression Methods: An Application to Bladder Cancer

Omics data integration is becoming necessary to investigate the genomic mechanisms involved in complex diseases. During the integration process, many challenges arise such as data heterogeneity, the smaller number of individuals in comparison to the number of parameters, multicollinearity, and interpretation and validation of results due to their complexity and lack of knowledge about biological processes. To overcome some of these issues, innovative statistical approaches are being developed. In this work, we propose a permutation-based method to concomitantly assess significance and correct by multiple testing with the MaxT algorithm. This was applied with penalized regression methods (LASSO and ENET) when exploring relationships between common genetic variants, DNA methylation and gene expression measured in bladder tumor samples. The overall analysis flow consisted of three steps: (1) SNPs/CpGs were selected per each gene probe within 1Mb window upstream and downstream the gene; (2) LASSO and ENET were applied to assess the association between each expression probe and the selected SNPs/CpGs in three multivariable models (SNP, CPG, and Global models, the latter integrating SNPs and CPGs); and (3) the significance of each model was assessed using the permutation-based MaxT method. We identified 48 genes whose expression levels were significantly associated with both SNPs and CPGs. Importantly, 36 (75%) of them were replicated in an independent data set (TCGA) and the performance of the proposed method was checked with a simulation study. We further support our results with a biological interpretation based on an enrichment analysis. The approach we propose allows reducing computational time and is flexible and easy to implement when analyzing several types of omics data. Our results highlight the importance of integrating omics data by applying appropriate statistical strategies to discover new insights into the complex genetic mechanisms involved in disease conditions.