Klemens Vierlinger

Meta-analysis of gene expression signatures defining the epithelial to mesenchymal transition during cancer progression.

The epithelial to mesenchymal transition (EMT) represents a crucial event during cancer progression and dissemination. EMT is the conversion of carcinoma cells from an epithelial to a mesenchymal phenotype that associates with a higher cell motility as well as enhanced chemoresistance and cancer stemness. Notably, EMT has been increasingly recognized as an early event of metastasis. Numerous gene expression studies (GES) have been conducted to obtain transcriptome signatures and marker genes to understand the regulatory mechanisms underlying EMT. Yet, no meta-analysis considering the multitude of GES of EMT has been performed to comprehensively elaborate the core genes in this process. Here we report the meta-analysis of 18 independent and published GES of EMT which focused on different cell types and treatment modalities. Computational analysis revealed clustering of GES according to the type of treatment rather than to cell type. GES of EMT induced via transforming growth factor-β and tumor necrosis factor-α treatment yielded uniformly defined clusters while GES of models with alternative EMT induction clustered in a more complex fashion. In addition, we identified those up- and downregulated genes which were shared between the multitude of GES. This core gene list includes well known EMT markers as well as novel genes so far not described in this process. Furthermore, several genes of the EMT-core gene list significantly correlated with impaired pathological complete response in breast cancer patients. In conclusion, this meta-analysis provides a comprehensive survey of available EMT expression signatures and shows fundamental insights into the mechanisms that are governing carcinoma progression.

Identification of human pathogens isolated from blood using microarray hybridisation and signal pattern recognition

BackgroundPathogen identification in clinical routine is based on the cultivation of microbes with subsequent morphological and physiological characterisation lasting at least 24 hours. However, early and accurate identification is a crucial requisite for fast and optimally targeted antimicrobial treatment. Molecular biology based techniques allow fast identification, however discrimination of very closely related species remains still difficult.ResultsA molecular approach is presented for the rapid identification of pathogens combining PCR amplification with microarray detection. The DNA chip comprises oligonucleotide capture probes for 25 different pathogens including Gram positive cocci, the most frequently encountered genera of Enterobacteriaceae, non-fermenter and clinical relevant Candida species. The observed detection limits varied from 10 cells (e.g. E. coli) to 105 cells (S. aureus) per mL artificially spiked blood. Thus the current low sensitivity for some species still represents a barrier for clinical application. Successful discrimination of closely related species was achieved by a signal pattern recognition approach based on the k-nearest-neighbour method. A prototype software providing this statistical evaluation was developed, allowing correct identification in 100 % of the cases at the genus and in 96.7 % at the species level (n = 241).ConclusionThe newly developed molecular assay can be carried out within 6 hours in a research laboratory from pathogen isolation to species identification. From our results we conclude that DNA microarrays can be a useful tool for rapid identification of closely related pathogens particularly when the protocols are adapted to the special clinical scenarios.

A survey of tools for the analysis of quantitative PCR (qPCR) data

Real-time quantitative polymerase-chain-reaction (qPCR) is a standard technique in most laboratories used for various applications in basic research. Analysis of qPCR data is a crucial part of the entire experiment, which has led to the development of a plethora of methods. The released tools either cover specific parts of the workflow or provide complete analysis solutions. Here, we surveyed 27 open-access software packages and tools for the analysis of qPCR data. The survey includes 8 Microsoft Windows, 5 web-based, 9 R-based and 5 tools from other platforms. Reviewed packages and tools support the analysis of different qPCR applications, such as RNA quantification, DNA methylation, genotyping, identification of copy number variations, and digital PCR. We report an overview of the functionality, features and specific requirements of the individual software tools, such as data exchange formats, availability of a graphical user interface, included procedures for graphical data presentation, and offered statistical methods. In addition, we provide an overview about quantification strategies, and report various applications of qPCR. Our comprehensive survey showed that most tools use their own file format and only a fraction of the currently existing tools support the standardized data exchange format RDML. To allow a more streamlined and comparable analysis of qPCR data, more vendors and tools need to adapt the standardized format to encourage the exchange of data between instrument software, analysis tools, and researchers.

Serum miRNA Signatures Are Indicative of Skeletal Fractures in Postmenopausal Women With and Without Type 2 Diabetes and Influence Osteogenic and Adipogenic Differentiation of Adipose Tissue-Derived Mesenchymal Stem Cells In Vitro

Standard DXA measurements, including Fracture Risk Assessment Tool (FRAX) scores, have shown limitations in assessing fracture risk in Type 2 Diabetes (T2D), underscoring the need for novel biomarkers and suggesting that other pathomechanisms may drive diabetic bone fragility. MicroRNAs (miRNAs) are secreted into the circulation from cells of various tissues proportional to local disease severity and were recently found to be crucial to bone homeostasis and T2D. Here, we studied, if and which circulating miRNAs or combinations of miRNAs can discriminate best fracture status in a well‐characterized study of diabetic bone disease and postmenopausal osteoporosis (n = 80 postmenopausal women). We then tested the most discriminative and most frequent miRNAs in vitro. Using miRNA‐qPCR‐arrays, we showed that 48 miRNAs can differentiate fracture status in T2D women and that several combinations of four miRNAs can discriminate diabetes‐related fractures with high specificity and sensitivity (area under the receiver‐operating characteristic curve values [AUCs], 0.92 to 0.96; 95% CI, 0.88 to 0.98). For the osteoporotic study arm, 23 miRNAs were fracture‐indicative and potential combinations of four miRNAs showed AUCs from 0.97 to 1.00 (95% CI, 0.93 to 1.00). Because a role in bone homeostasis for those miRNAs that were most discriminative and most present among all miRNA combinations had not been described, we performed in vitro functional studies in human adipose tissue–derived mesenchymal stem cells to investigate the effect of miR‐550a‐5p, miR‐188‐3p, and miR‐382‐3p on osteogenesis, adipogenesis, and cell proliferation. We found that miR‐382‐3p significantly enhanced osteogenic differentiation (p < 0.001), whereas miR‐550a‐5p inhibited this process (p < 0.001). Both miRNAs, miR‐382‐3p and miR‐550a‐5p, impaired adipogenic differentiation, whereas miR‐188‐3p did not exert an effect on adipogenesis. None of the miRNAs affected significantly cell proliferation. Our data suggest for the first time that miRNAs are linked to fragility fractures in T2D postmenopausal women and should be further investigated for their diagnostic potential and their detailed function in diabetic bone.

Soluble ST2 Is Regulated by p75 Neurotrophin Receptor and Predicts Mortality in Diabetic Patients With Critical Limb Ischemia

Objective—The p75 neurotrophin receptor (p75NTR) contributes to diabetes mellitus−induced defective postischemic neovascularization. The interleukin-33 receptor ST2 is expressed as transmembrane (ST2L) and soluble (sST2) isoforms. Here, we studied the following: (1) the impact of p75NTR in the healing of ischemic and diabetic calf wounds; (2) the link between p75NTR and ST2; and (3) circulating sST2 levels in critical limb ischemia (CLI) patients. Methods and Results—Diabetes mellitus was induced in p75NTR knockout (p75KO) mice and wild-type (WT) littermates by streptozotocin. Diabetic and nondiabetic p75KO and WT mice received left limb ischemia induction and a full-thickness wound on the ipsilateral calf. Diabetes mellitus impaired wound closure and angiogenesis and increased ST2 expression in WT, but not in p75KO wounds. In cultured endothelial cells, p75NTR promoted ST2 (both isoforms) expression through p38MAPK/activating transcription factor 2 pathway activation. Next, sST2 was measured in the serum of patients with CLI undergoing either revascularization or limb amputation and in the 2 nondiabetic groups (with CLI or nonischemic individuals). Serum sST2 increased in diabetic patients with CLI and was directly associated with higher mortality at 1 year from revascularization. Conclusion—p75NTR inhibits the healing of ischemic lower limb wounds in diabetes mellitus and promotes ST2 expression. Circulating sST2 predicts mortality in diabetic CLI patients.

Diagnostic Performance of Plasma DNA Methylation Profiles in Lung Cancer, Pulmonary Fibrosis and COPD.

Disease-specific alterations of the cell-free DNA methylation status are frequently found in serum samples and are currently considered to be suitable biomarkers. Candidate markers were identified by bisulfite conversion-based genome-wide methylation screening of lung tissue from lung cancer, fibrotic ILD, and COPD. cfDNA from 400 μl serum (n = 204) served to test the diagnostic performance of these markers. Following methylation-sensitive restriction enzyme digestion and enrichment of methylated DNA via targeted amplification (multiplexed MSRE enrichment), a total of 96 markers were addressed by highly parallel qPCR. Lung cancer was efficiently separated from non-cancer and controls with a sensitivity of 87.8%, (95%CI: 0.67–0.97) and specificity 90.2%, (95%CI: 0.65–0.98). Cancer was distinguished from ILD with a specificity of 88%, (95%CI: 0.57–1), and COPD from cancer with a specificity of 88% (95%CI: 0.64–0.97). Separation of ILD from COPD and controls was possible with a sensitivity of 63.1% (95%CI: 0.4–0.78) and a specificity of 70% (95%CI: 0.54–0.81). The results were confirmed using an independent sample set (n = 46) by use of the four top markers discovered in the study (HOXD10, PAX9, PTPRN2, and STAG3) yielding an AUC of 0.85 (95%CI: 0.72–0.95). This technique was capable of distinguishing interrelated complex pulmonary diseases suggesting that multiplexed MSRE enrichment might be useful for simple and reliable diagnosis of diverse multifactorial disease states.

Identification of SERPINA1 as single marker for papillary thyroid carcinoma through microarray meta analysis and quantification of its discriminatory power in independent validation

BackgroundSeveral DNA microarray based expression signatures for the different clinically relevant thyroid tumor entities have been described over the past few years. However, reproducibility of these signatures is generally low, mainly due to study biases, small sample sizes and the highly multivariate nature of microarrays. While there are new technologies available for a more accurate high throughput expression analysis, we show that there is still a lot of information to be gained from data deposited in public microarray databases. In this study we were aiming (1) to identify potential markers for papillary thyroid carcinomas through meta analysis of public microarray data and (2) to confirm these markers in an independent dataset using an independent technology.MethodsWe adopted a meta analysis approach for four publicly available microarray datasets on papillary thyroid carcinoma (PTC) nodules versus nodular goitre (NG) from N2-frozen tissue. The methodology included merging of datasets, bias removal using distance weighted discrimination (DWD), feature selection/inference statistics, classification/crossvalidation and gene set enrichment analysis (GSEA). External Validation was performed on an independent dataset using an independent technology, quantitative RT-PCR (RT-qPCR) in our laboratory.ResultsFrom meta analysis we identified one gene (SERPINA1) which identifies papillary thyroid carcinoma against benign nodules with 99% accuracy (n = 99, sensitivity = 0.98, specificity = 1, PPV = 1, NPV = 0.98). In the independent validation data, which included not only PTC and NG, but all major histological thyroid entities plus a few variants, SERPINA1 was again markedly up regulated (36-fold, p = 1:3*10-10) in PTC and identification of papillary carcinoma was possible with 93% accuracy (n = 82, sensitivity = 1, specificity = 0.90, PPV = 0.76, NPV = 1). We also show that the extracellular matrix pathway is strongly activated in the meta analysis data, suggesting an important role of tumor-stroma interaction in the carcinogenesis of papillary thyroid carcinoma.ConclusionsWe show that valuable new information can be gained from meta analysis of existing microarray data deposited in public repositories. While single microarray studies rarely exhibit a sample number which allows robust feature selection, this can be achieved by combining published data using DWD. This approach is not only efficient, but also very cost-effective. Independent validation shows the validity of the results from this meta analysis and confirms SERPINA1 as a potent mRNA marker for PTC in a total (meta analysis plus validation) of 181 samples.

Characterization of the drugged human genome

Human drug targets are a part of our genome of special relevance to human disease. However, the number and nature of drug target genes has not yet been conclusively assessed. We analyzed involvement in biochemical functions, biological processes and pathways, with chromosome, cellular and tissue distribution of the 392 human drug targets collected in DrugBank. Comparison with the whole human genome reveals their scarcely diverse characteristics, largely dominated by rhodopsin-like 7 transmembrane receptors involved in the neuroactive ligand-receptor interaction pathway and located in the plasma membrane. Drug target genes are frequently expressed in multiple tissues, suggesting drug application in distinct disease classes. Intersections with other clinically relevant gene sets, such as the Mendelian disorder-linked genes and various molecular cancer signatures, are discussed.

The Influence of Gender, Age, and RET Polymorphisms on C-Cell Hyperplasia and Medullary Thyroid Carcinoma

BACKGROUND RET germline mutations predispose to the development of hereditary medullary thyroid carcinoma (hMTC). Several single nucleotide polymorphisms (SNPs) are described associated with sporadic MTC (sMTC). However, the findings regarding their influence on the clinical course and biological behavior of this disorder are discordant. To clarify the contradictory findings, we studied the association of certain SNPs considering age, gender, and histopathology in a large Austrian cohort with C-cell hyperplasia (CCH) and MTC. METHODS Genotyping of SNPs located in RET codons 691, 769, 836, and 904 from 199 patients with MTC and CCH (basal calcitonin > 10 pg/mL, pentagastrin stimulated > 100 pg/mL) was performed, and the results were analyzed considering gender, age at diagnosis, and histopathology. RESULTS No significant difference of SNP frequencies was found in the study patients versus normal controls. In sMTC and sporadic CCH (sCCH) no significant association of SNP frequency with the age at diagnosis was found. In patients with sporadic C-cell disease (sCCH and sMTC), 3.7 times more males than females suffered synchronously from papillary or follicular thyroid cancer (20/97 [20.6%] males; 3/54 [5.6%] females; p = 0.02). sCCH was revealed more frequently in males (89/97, 91.7%) than in females (27/54, 50%; p = 10(-8)). In contrast to males, the ratio of CCH to total C-cell disease was significantly higher in females with hereditary (26/32, 81%) compared to those with sporadic disease (27/54, 50%; p = 0.006). CONCLUSIONS In this study RET SNPs had no clinical impact on the development of sporadic C-cell disease when the age of diagnosis or gender is considered. C-cell disease seems to predispose males to the development of papillary and follicular thyroid cancer. In addition, at least in females with CCH RET germline mutation, screening is recommended even if the family history is negative for MTC.

Microarray-Based In Vitro Test System for the Discrimination of Contact Allergens and Irritants: Identification of Potential Marker Genes

BACKGROUND Animal tests have been used to characterize the potential of chemicals to produce allergic contact dermatitis, but this approach is increasingly a matter of public and political concern. Our aim was to develop and validate an alternative in vitro test that can identify contact allergens. METHODS We developed a targeted microarray containing oligonucleotide probes for 66 immune-relevant genes and analyzed gene expression in monocyte-derived dendritic cells (Mo-DCs) treated with 1 irritant (SDS) and 2 prominent contact allergens, nickel and Bandrowskis base (BB), which is the oxidation product of the most important hair dye allergen, p-phenylenediamine. RESULTS Comparing RNA amounts in chemical-treated and solvent-treated cells, we identified significant changes in the expression of 21 genes and 10 genes after exposure of immature DCs (iDCs) to nickel and BB, respectively, but not after exposure to SDS. Eight genes were differentially expressed after application of both nickel and BB. Real-time PCR was used to confirm the results for selected genes. CONCLUSION We propose a microarray-based in vitro test that might allow the identification of contact allergens. Independently from donor variability, several immune-relevant genes were up- or downregulated after the application of the tested sensitizers to iDCs, therefore presenting potential marker genes. While reducing the number of laboratory animals used, this test would also enable reliable analysis of chemicals using a human system.