Martin Letzkus

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.

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.

Gene expression is differently affected by pimecrolimus and betamethasone in lesional skin of atopic dermatitis

To cite this article: Jensen JM, Scherer A, Wanke C, Bräutigam M, Bongiovanni S, Letzkus M, Staedtler F, Kehren J, Zuehlsdorf M, Schwarz T, Weichenthal M, Fölster‐Holst R, Proksch E. Gene expression is differently affected by pimecrolimus and betamethasone in lesional skin of atopic dermatitis. Allergy 2012; 67: 413–423.

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.

The Molecular Signature of Oxidative Metabolism and the Mode of Macrophage Activation Determine the Shift From Acute to Chronic Disease in Experimental Arthritis Critical Role of Interleukin-12p40

OBJECTIVE Repeated injection of streptococcal cell wall (SCW) fragments results in chronic arthritis in mice. The objective of this study was to identify genes and pathways that determine disease progression based on gene expression profiling in this model. METHODS Chronic arthritis was induced in mice by 4 injections of SCW fragments. RNA samples were isolated from synovial tissue obtained at various time points and were analyzed using mouse genome array and quantitative reverse transcription-polymerase chain reaction techniques. The functional role of potential key genes was evaluated in mice with specific gene deletions. RESULTS Gene expression analyses revealed a shift in molecular signature. In contrast to an up-regulation of the inflammatory response pathway, the pathways involved in oxidative metabolism were significantly down-regulated during the chronic phase of arthritis. Since oxidative metabolism determines the mode of macrophage activation, we investigated phenotype switching in macrophages. Markers of alternatively activated macrophages, such as arginase 1, were at maximal levels during acute inflammation. In contrast, induction of markers of classically activated macrophages (M1), such as interleukin-1beta (IL-1beta) and inducible nitric oxide synthase (iNOS), was relatively low during the acute phase of disease, but highly increased toward the chronic phase. M1 polarization during the chronic phase was accompanied by a Th1 signature, characterized by IL-12p40, IL-12p35, and interferon-gamma. However, the absence of IL-12p40, but not IL-12p35, significantly inhibited the chronic phase of arthritis and was marked by a reduction in IL-17 and iNOS levels, as well as restored expression of oxidative metabolism genes. CONCLUSION M1 polarization accompanied by a decline in oxidative metabolism determine the chronic phase of arthritis. IL-12p40, most likely acting through the IL-23/IL-17 axis, plays a critical role in this process.

Canakinumab reverses overexpression of inflammatory response genes in tumour necrosis factor receptor-associated periodic syndrome

Objective To explore whether gene expression profiling can identify a molecular mechanism for the clinical benefit of canakinumab treatment in patents with tumour necrosis factor receptor-associated periodic syndrome (TRAPS). Methods Blood samples were collected from 20 patients with active TRAPS who received canakinumab 150 mg every 4 weeks for 4 months in an open-label proof-of-concept phase II study, and from 20 aged-matched healthy volunteers. Gene expression levels were evaluated in whole blood samples by microarray analysis for arrays passing quality control checks. Results Patients with TRAPS exhibited a gene expression signature in blood that differed from that in healthy volunteers. Upon treatment with canakinumab, many genes relevant to disease pathogenesis moved towards levels seen in the healthy volunteers. Canakinumab downregulated the TRAPS-causing gene (TNF super family receptor 1A (TNFRSF1A)), the drug-target gene (interleukin (IL)-1B) and other inflammation-related genes (eg, MAPK14). In addition, several inflammation-related pathways were evident among the differentially expressed genes. Canakinumab treatment reduced neutrophil counts, but the observed expression differences remained after correction for this. Conclusions These gene expression data support a model in which canakinumab produces clinical benefit in TRAPS by increasing neutrophil apoptosis and reducing pro-inflammatory signals resulting from the inhibition of IL-1β. Notably, treatment normalised the overexpression of TNFRSF1A, suggesting that canakinumab has a direct impact on the main pathogenic mechanism in TRAPS. Trial registration number NCT01242813.

Robust and tissue-independent gender-specific transcript biomarkers

Abstract Context: Correct gender assignment in humans at the molecular level is crucial in many scientific disciplines and applied areas. Materials and methods: Candidate gender markers were identified through supervised statistical analysis of genome wide microarray expression data from human blood samples (N = 123, 58 female, 65 male) as a training set. The potential of the markers to predict undisclosed tissue donor gender was tested on microarray data from 13 healthy and 11 cancerous human tissue collections (internal) and external datasets from samples of varying tissue origin. The abundance of some genes in the marker panel was quantified by RT-PCR as alternative analytical technology. Results: We identified and qualified predictive, gender-specific transcript markers based on a set of five genes (RPS4Y1, EIF1AY, DDX3Y, KDM5D and XIST). Conclusion: Gene expression marker panels can be used as a robust tissue- and platform-independent predictive approach for gender determination.

Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials

BackgroundClinically useful biomarkers for patient stratification and monitoring of disease progression and drug response are in big demand in drug development and for addressing potential safety concerns. Many diseases influence the frequency and phenotype of cells found in the peripheral blood and the transcriptome of blood cells. Changes in cell type composition influence whole blood gene expression analysis results and thus the discovery of true transcript level changes remains a challenge. We propose a robust and reproducible procedure, which includes whole transcriptome gene expression profiling of major subsets of immune cell cells directly sorted from whole blood.MethodsTarget cells were enriched using magnetic microbeads and an autoMACS® Pro Separator (Miltenyi Biotec). Flow cytometric analysis for purity was performed before and after magnetic cell sorting. Total RNA was hybridized on HGU133 Plus 2.0 expression microarrays (Affymetrix, USA). CEL files signal intensity values were condensed using RMA and a custom CDF file (EntrezGene-based).ResultsPositive selection by use of MACS® Technology coupled to transcriptomics was assessed for eight different peripheral blood cell types, CD14+ monocytes, CD3+, CD4+, or CD8+ T cells, CD15+ granulocytes, CD19+ B cells, CD56+ NK cells, and CD45+ pan leukocytes. RNA quality from enriched cells was above a RIN of eight. GeneChip analysis confirmed cell type specific transcriptome profiles. Storing whole blood collected in an EDTA Vacutainer® tube at 4°C followed by MACS does not activate sorted cells. Gene expression analysis supports cell enrichment measurements by MACS.ConclusionsThe proposed workflow generates reproducible cell-type specific transcriptome data which can be translated to clinical settings and used to identify clinically relevant gene expression biomarkers from whole blood samples. This procedure enables the integration of transcriptomics of relevant immune cell subsets sorted directly from whole blood in clinical trial protocols.

A microarray analysis of full depth knee cartilage of ovariectomized rats

BackgroundThis short communication focuses the on articular cartilage and the subchondral bone, both of which play important roles in the development of osteoarthritis (OA). There are indications that estrogen-deficiency, as the post-menopausal state, accelerate the development of OA.FindingsWe investigated, which extracellular matrix (ECM) protein, proteases and different pro-inflammatory factors was up- or down-regulated in the knee joint tissue in response to estrogen-deficiency in rats induced by ovariectomy. These data support previous findings that several metalloproteinases (MMPs) and cysteine proteases are co-regulated with numerous collagens and proteoglycans that are important for cartilage integrity. Furthermore quite a few pro-inflammatory cytokines were regulated by estrogen deprivation.ConclusionWe found multiple genes where regulated in the joint by estrogen-deficiency, many of which correspond well with our current knowledge of the pathogenesis of OA. It supports that estrogen-deficiency (e.g. OVX) may accelerate joint deterioration. However, there are also data that draw attention the need for better understanding of the synergy between proteases and tissue turnover.

Omalizumab normalizes the gene expression signature of lesional skin in patients with chronic spontaneous urticaria: A randomized, double-blind, placebo-controlled study

Omalizumab, a humanized recombinant monoclonal anti‐IgE antibody, proved to be effective in patients with chronic spontaneous urticaria (CSU), including severe and treatment‐refractory CSU. Here, we report omalizumabs effect on gene expression in skin biopsies from CSU patients enrolled in a double‐blind, placebo‐controlled study.