James Andrew Rosinski

Cascades of transcriptional induction during dendritic cell maturation revealed by genome-wide expression analysis

Dendritic cells (DC) are central regulators of immunity. Signal‐induced maturation of DCs is assumed to be the starting point for specific immune responses. To further understand this process, we analyzed the alteration of transcript profiles along the time course of CD40 ligand‐induced maturation of human myeloid DCs by Affymetrix GeneChip® microarrays covering >6800 genes. Besides rediscovery of genes already described as associated with DC maturation proving reliability of the methods used, we identified clusterin as novel maturation marker. Looking across the time course, we observed synchronized kinetics of distinct functional groups of molecules whose temporal coregulation underscores known cellular events during dendritic cell maturation. For example, an early‐peaking wave of inflammatory chemokines was followed by a sustained increase of constitutive chemokines and accompanied by slow but continuous induction of survival proteins. After an immediate but transient induction of cytokine‐responsive transcripts, there was an increased expression of a group of genes involved in not only the regulation of cytokine effects, but also of transcription in general. Our results demonstrate that microarray studies along time courses combined with real‐time PCR not only discover new marker molecules with functional implications, but also dissect the molecular kinetics of biological processes identifying complex pathways of regulation.—Türeci, O. Bian, H., Nestle, F. O., Raddrizzani, L., Rosinski, J. A., Tassis, A., Hilton, H., Walstead, M., Sahin, U., Hammer, J. Cascades of transcriptional induction during dendritic cell maturation revealed by genome‐wide expression analysis FASEB J. 17, 836–847 (2003)

The effect of insulin on expression of genes and biochemical pathways in human skeletal muscle.

To study the insulin effects on gene expression in skeletal muscle, muscle biopsies were obtained from 20 insulin sensitive individuals before and after euglycemic hyperinsulinemic clamps. Using microarray analysis, we identified 779 insulin-responsive genes. Particularly noteworthy were effects on 70 transcription factors, and an extensive influence on genes involved in both protein synthesis and degradation. The genetic program in skeletal muscle also included effects on signal transduction, vesicular traffic and cytoskeletal function, and fuel metabolic pathways. Unexpected observations were the pervasive effects of insulin on genes involved in interacting pathways for polyamine and S-adenoslymethionine metabolism and genes involved in muscle development. We further confirmed that four insulin-responsive genes, RRAD, IGFBP5, INSIG1, and NGFI-B (NR4A1), were significantly up-regulated by insulin in cultured L6 skeletal muscle cells. Interestingly, insulin caused an accumulation of NGFI-B (NR4A1) protein in the nucleus where it functions as a transcription factor, without translocation to the cytoplasm to promote apoptosis. The role of NGFI-B (NR4A1) as a new potential mediator of insulin action highlights the need for greater understanding of nuclear transcription factors in insulin action.

Preclinical biomarkers for a cyclin-dependent kinase inhibitor translate to candidate pharmacodynamic biomarkers in phase I patients

A genomics-based approach to identify pharmacodynamic biomarkers was used for a cyclin-dependent kinase inhibitory drug. R547 is a potent cyclin-dependent kinase inhibitor with a potent antiproliferative effect at pharmacologically relevant doses and is currently in phase I clinical trials. Using preclinical data derived from microarray experiments, we identified pharmacodynamic biomarkers to test in blood samples from patients in clinical trials. These candidate biomarkers were chosen based on several criteria: relevance to the mechanism of action of R547, dose responsiveness in preclinical models, and measurable expression in blood samples. We identified 26 potential biomarkers of R547 action and tested their clinical validity in patient blood samples by quantitative real-time PCR analysis. Based on the results, eight genes (FLJ44342, CD86, EGR1, MKI67, CCNB1, JUN, HEXIM1, and PFAAP5) were selected as dose-responsive pharmacodynamic biomarkers for phase II clinical trials. [Mol Cancer Ther 2009;8(9):2517–25]