Frank Staedtler

cell type–specific gene expression differences in complex tissues

We describe cell type–specific significance analysis of microarrays (csSAM) for analyzing differential gene expression for each cell type in a biological sample from microarray data and relative cell-type frequencies. First, we validated csSAM with predesigned mixtures and then applied it to whole-blood gene expression datasets from stable post-transplant kidney transplant recipients and those experiencing acute transplant rejection, which revealed hundreds of differentially expressed genes that were otherwise undetectable.

Urinary clusterin, cystatin C, β2-microglobulin and total protein as markers to detect drug-induced kidney injury

Earlier and more reliable detection of drug-induced kidney injury would improve clinical care and help to streamline drug-development. As the current standards to monitor renal function, such as blood urea nitrogen (BUN) or serum creatinine (SCr), are late indicators of kidney injury, we conducted ten nonclinical studies to rigorously assess the potential of four previously described nephrotoxicity markers to detect drug-induced kidney and liver injury. Whereas urinary clusterin outperformed BUN and SCr for detecting proximal tubular injury, urinary total protein, cystatin C and β2-microglobulin showed a better diagnostic performance than BUN and SCr for detecting glomerular injury. Gene and protein expression analysis, in-situ hybridization and immunohistochemistry provide mechanistic evidence to support the use of these four markers for detecting kidney injury to guide regulatory decision making in drug development. The recognition of the qualification of these biomarkers by the EMEA and FDA will significantly enhance renal safety monitoring.

A panel of urinary biomarkers to monitor reversibility of renal injury and a serum marker with improved potential to assess renal function

The Predictive Safety Testing Consortiums first regulatory submission to qualify kidney safety biomarkers revealed two deficiencies. To address the need for biomarkers that monitor recovery from agent-induced renal damage, we scored changes in the levels of urinary biomarkers in rats during recovery from renal injury induced by exposure to carbapenem A or gentamicin. All biomarkers responded to histologic tubular toxicities to varied degrees and with different kinetics. After a recovery period, all biomarkers returned to levels approaching those observed in uninjured animals. We next addressed the need for a serum biomarker that reflects general kidney function regardless of the exact site of renal injury. Our assay for serum cystatin C is more sensitive and specific than serum creatinine (SCr) or blood urea nitrogen (BUN) in monitoring generalized renal function after exposure of rats to eight nephrotoxicants and two hepatotoxicants. This sensitive serum biomarker will enable testing of renal function in animal studies that do not involve urine collection.

Selective and Specific Inhibition of the Plasmodium falciparum Lysyl-tRNA Synthetase by the Fungal Secondary Metabolite Cladosporin

Summary With renewed calls for malaria eradication, next-generation antimalarials need be active against drug-resistant parasites and efficacious against both liver- and blood-stage infections. We screened a natural product library to identify inhibitors of Plasmodium falciparum blood- and liver-stage proliferation. Cladosporin, a fungal secondary metabolite whose target and mechanism of action are not known for any species, was identified as having potent, nanomolar, antiparasitic activity against both blood and liver stages. Using postgenomic methods, including a yeast deletion strains collection, we show that cladosporin specifically inhibits protein synthesis by directly targeting P. falciparum cytosolic lysyl-tRNA synthetase. Further, cladosporin is >100-fold more potent against parasite lysyl-tRNA synthetase relative to the human enzyme, which is conferred by the identity of two amino acids within the enzyme active site. Our data indicate that lysyl-tRNA synthetase is an attractive, druggable, antimalarial target that can be selectively inhibited.

Performance of Novel Kidney Biomarkers in Preclinical Toxicity Studies

The kidney is one of the main targets of drug toxicity, but early detection of renal damage is often difficult. As part of the InnoMed PredTox project, a collaborative effort aimed at assessing the value of combining omics technologies with conventional toxicology methods for improved preclinical safety assessment, we evaluated the performance of a panel of novel kidney biomarkers in preclinical toxicity studies. Rats were treated with a reference nephrotoxin or one of several proprietary compounds that were dropped from drug development in part due to renal toxicity. Animals were dosed at two dose levels for 1, 3, and 14 days. Putative kidney markers, including kidney injury molecule-1 (Kim-1), lipocalin-2 (Lcn2), clusterin, and tissue inhibitor of metalloproteinases-1, were analyzed in kidney and urine using quantitative real-time PCR, ELISA, and immunohistochemistry. Changes in gene/protein expression generally correlated well with renal histopathological alterations and were frequently detected at earlier time points or at lower doses than the traditional clinical parameters blood urea nitrogen and serum creatinine. Urinary Kim-1 and clusterin reflected changes in gene/protein expression and histopathological alterations in the target organ in the absence of functional changes. This confirms clusterin and Kim-1 as early and sensitive, noninvasive markers of renal injury. Although Lcn2 did not appear to be specific for kidney toxicity, its rapid response to inflammation and tissue damage in general may suggest its utility in routine toxicity testing.

Effects of clofibric acid on mRNA expression profiles in primary cultures of rat, mouse and human hepatocytes

The mRNA expression profile in control and clofibric acid (CLO)-treated mouse, rat, and human hepatocytes was analyzed using species-specific oligonucleotide DNA microarrays (Affymetrix). A statistical empirical Bayes procedure was applied in order to select the significantly differentially expressed genes. Treatment with the peroxisome proliferator CLO induced up-regulation of genes involved in peroxisome proliferation and in cell proliferation as well as down-regulation of genes involved in apoptosis in hepatocytes of rodent but not of human origin. CLO treatment induced up-regulation of microsomal cytochrome P450 4a genes in rodent hepatocytes and in two of six human hepatocyte cultures. In addition, genes encoding phenobarbital-inducible cytochrome P450s were also up-regulated by CLO in rodent and human hepatocyte cultures. Up-regulation of phenobarbital-inducible UDP-glucuronosyl-transferase genes by CLO was observed in both rat and human but not in mouse hepatocytes. CLO treatment induced up-regulation of L-fatty acid binding protein (L-FABP) gene in hepatocytes of both rodent and human origin. However, while genes of the cytosolic, microsomal, and mitochondrial pathways involved in fatty acid transport and metabolism were up-regulated by CLO in both rodent and human hepatocyte cultures, genes of the peroxisomal pathway of lipid metabolism were up-regulated in rodents only. An up-regulation of hepatocyte nuclear factor 1alpha (HNF1alpha) by CLO was observed only in human hepatocyte cultures, suggesting that this trans-activating factor may play a key role in the regulation of fatty acid metabolism in human liver as well as in the nonresponsiveness of human liver to CLO-induced regulation of cell proliferation and apoptosis.

Optimal Deconvolution of Transcriptional Profiling Data Using Quadratic Programming with Application to Complex Clinical Blood Samples

Large-scale molecular profiling technologies have assisted the identification of disease biomarkers and facilitated the basic understanding of cellular processes. However, samples collected from human subjects in clinical trials possess a level of complexity, arising from multiple cell types, that can obfuscate the analysis of data derived from them. Failure to identify, quantify, and incorporate sources of heterogeneity into an analysis can have widespread and detrimental effects on subsequent statistical studies. We describe an approach that builds upon a linear latent variable model, in which expression levels from mixed cell populations are modeled as the weighted average of expression from different cell types. We solve these equations using quadratic programming, which efficiently identifies the globally optimal solution while preserving non-negativity of the fraction of the cells. We applied our method to various existing platforms to estimate proportions of different pure cell or tissue types and gene expression profilings of distinct phenotypes, with a focus on complex samples collected in clinical trials. We tested our methods on several well controlled benchmark data sets with known mixing fractions of pure cell or tissue types and mRNA expression profiling data from samples collected in a clinical trial. Accurate agreement between predicted and actual mixing fractions was observed. In addition, our method was able to predict mixing fractions for more than ten species of circulating cells and to provide accurate estimates for relatively rare cell types (<10% total population). Furthermore, accurate changes in leukocyte trafficking associated with Fingolomid (FTY720) treatment were identified that were consistent with previous results generated by both cell counts and flow cytometry. These data suggest that our method can solve one of the open questions regarding the analysis of complex transcriptional data: namely, how to identify the optimal mixing fractions in a given experiment.

High-resolution chemical dissection of a model eukaryote reveals targets, pathways and gene functions

Due to evolutionary conservation of biology, experimental knowledge captured from genetic studies in eukaryotic model organisms provides insight into human cellular pathways and ultimately physiology. Yeast chemogenomic profiling is a powerful approach for annotating cellular responses to small molecules. Using an optimized platform, we provide the relative sensitivities of the heterozygous and homozygous deletion collections for nearly 1800 biologically active compounds. The data quality enables unique insights into pathways that are sensitive and resistant to a given perturbation, as demonstrated with both known and novel compounds. We present examples of novel compounds that inhibit the therapeutically relevant fatty acid synthase and desaturase (Fas1p and Ole1p), and demonstrate how the individual profiles facilitate hypothesis-driven experiments to delineate compound mechanism of action. Importantly, the scale and diversity of tested compounds yields a dataset where the number of modulated pathways approaches saturation. This resource can be used to map novel biological connections, and also identify functions for unannotated genes. We validated hypotheses generated by global two-way hierarchical clustering of profiles for (i) novel compounds with a similar mechanism of action acting upon microtubules or vacuolar ATPases, and (ii) an un-annotated ORF, YIL060w, that plays a role in respiration in the mitochondria. Finally, we identify and characterize background mutations in the widely used yeast deletion collection which should improve the interpretation of past and future screens throughout the community. This comprehensive resource of cellular responses enables the expansion of our understanding of eukaryotic pathway biology.

Perturbation of microRNAs in Rat Heart during Chronic Doxorubicin Treatment

Anti-cancer therapy based on anthracyclines (DNA intercalating Topoisomerase II inhibitors) is limited by adverse effects of these compounds on the cardiovascular system, ultimately causing heart failure. Despite extensive investigations into the effects of doxorubicin on the cardiovascular system, the molecular mechanisms of toxicity remain largely unknown. MicroRNAs are endogenously transcribed non-coding 22 nucleotide long RNAs that regulate gene expression by decreasing mRNA stability and translation and play key roles in cardiac physiology and pathologies. Increasing doses of doxorubicin, but not etoposide (a Topoisomerase II inhibitor devoid of cardiovascular toxicity), specifically induced the up-regulation of miR-208b, miR-216b, miR-215, miR-34c and miR-367 in rat hearts. Furthermore, the lowest dosing regime (1 mg/kg/week for 2 weeks) led to a detectable increase of miR-216b in the absence of histopathological findings or alteration of classical cardiac stress biomarkers. In silico microRNA target predictions suggested that a number of doxorubicin-responsive microRNAs may regulate mRNAs involved in cardiac tissue remodeling. In particular miR-34c was able to mediate the DOX-induced changes of Sipa1 mRNA (a mitogen-induced Rap/Ran GTPase activating protein) at the post-transcriptional level and in a seed sequence dependent manner. Our results show that integrated heart tissue microRNA and mRNA profiling can provide valuable early genomic biomarkers of drug-induced cardiac injury as well as novel mechanistic insight into the underlying molecular pathways.

Integrated Epigenetics of Human Breast Cancer: Synoptic Investigation of Targeted Genes, MicroRNAs and Proteins upon Demethylation Treatment

Background The contribution of aberrant DNA methylation in silencing of tumor suppressor genes (TSGs) and microRNAs has been investigated. Since these epigenetic alterations are reversible, it became of interest to determine the effects of the 5-aza-2′-deoxycytidine (DAC) demethylation therapy in breast cancer at different molecular levels. Methods and Findings Here we investigate a synoptic model to predict complete DAC treatment effects at the level of genes, microRNAs and proteins for several human breast cancer lines. The present study assessed an effective treatment dosage based on the cell viability, cytotoxicity, apoptosis and methylation assays for the investigated cell lines. A highly aggressive and a non-aggressive cell line were investigated using omics approaches such as MALDI-TOF MS, mRNA- and microRNA expression arrays, 2-D gel electrophoresis and LC-MS-MS. Complete molecular profiles including the biological interaction and possible early and late systematic stable or transient effects of the methylation inhibition were determined. Beside the activation of several epigenetically suppressed TSGs, we also showed significant dysregulation of some important oncogenes, oncomiRs and oncosuppressors miRNAs as well as drug tolerance genes/miRNAs/proteins. Conclusions In the present study, the results denote some new molecular DAC targets and pathways based on the chemical modification of DNA methylation in breast cancer. The outlined approach might prove to be useful as an epigenetic treatment model also for other human solid tumors in the management of cancer patients.