Cyclo19,31[D-Cys19]-uPA19-31 is a potent competitive antagonist of the interaction of urokinase-type plasminogen activator with its receptor (CD87)

Urokinase-type plasminogen activator (uPA) represents a central molecule in pericellular proteolysis and is implicated in a variety of physiological and pathophysiological processes such as tissue remodelling, wound healing, tumor invasion, and metastasis. uPA binds with high affinity to a specific cell surface receptor, uPAR (CD87), via a well defined sequence within the N-terminal region of uPA (uPA(19-31)). This interaction directs the proteolytic activity of uPA to the cell surface which represents an important step in tumor cell proliferation, invasion, and metastasis. Due to its fundamental role in these processes, the uPA/uPAR-system has emerged as a novel target for tumor therapy. Previously, we have identified a synthetic, cyclic, uPA-derived peptide, cyclo(19,31)uPA(19-31), as a lead structure for the development of low molecular weight uPA-analogues, capable of blocking uPA/uPAR-interaction {[}Burgle et al., Biol. Chem. 378 (1997), 231-237]. We now searched for peptide variants of cyclo(19,31)uPA(19-31) with elevated affinities for uPAR binding. Among other tasks, we performed a systematic D-amino acid scan of quPA(19-31), in which each of the 13 L-amino acids was individually substituted by the corresponding D-amino acid. This led to the identification of cyclo(19,31) {[}D-Cys(19)]-uPA(19-31) as a potent inhibitor of uPA/uPAR-interaction, displaying only a 20 to 40-fold lower binding capacity as compared to the naturally occurring uPAR-ligands uPA and its amino-terminal fragment. Cyclo(19,31)[D-Cys(19)]-uPA(19-31) not only blocks binding of uPA to uPAR but is also capable of efficiently displacing uPAR-bound uPA from the cell surface and to inhibit uPA-mediated, tumor cell-associated plasminogen activation and fibrin degradation. Thus, cyclo(19,31)[D-Cys(19)]-uPA(19-31) represents a promising therapeutic agent to significantly affect the tumor-associated uPA/uPAR-system

The Predictive Value of PITX2 DNA Methylation for High-Risk Breast Cancer Therapy: Current Guidelines, Medical Needs, and Challenges

High-risk breast cancer comprises distinct tumor entities such as triple-negative breast cancer (TNBC) which is characterized by lack of estrogen (ER) and progesterone (PR) and the HER2 receptor and breast malignancies which have spread to more than three lymph nodes. For such patients, current (inter)national guidelines recommend anthracycline-based chemotherapy as the standard of care, but not all patients do equally benefit from such a chemotherapy. To further improve therapy decision-making, predictive biomarkers are of high, so far unmet, medical need. In this respect, predictive biomarkers would permit patient selection for a particular kind of chemotherapy and, by this, guide physicians to optimize the treatment plan for each patient individually. Besides DNA mutations, DNA methylation as a patient selection marker has received increasing clinical attention. For instance, significant evidence has accumulated that methylation of the PITX2 (paired-like homeodomain transcription factor 2) gene might serve as a novel predictive and prognostic biomarker, for a variety of cancer diseases. This review highlights the current understanding of treatment modalities of high-risk breast cancer patients with a focus on recommended treatment options, with special attention on the future clinical application of PITX2 as a predictive biomarker to personalize breast cancer management

Projections of global warming-induced impacts on winter storm losses in the German private household sector

We present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statistical-dynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971–2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6–35 % for 2011–2040, of 20–30 % for 2041–2070, and of 40–55 % for 2071–2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses

Clinical Validation of PITX2 DNA Methylation to Predict Outcome in High-Risk Breast Cancer Patients Treated with Anthracycline-Based Chemotherapy

Background: Breast cancer patients at high risk for recurrence are treated with anthracycline-based chemotherapy, but not all patients do equally benefit from such a regimen. To further improve therapy decision-making, biomarkers predicting outcome are of high unmet medical need. Methods: The percent DNA methylation ratio (PMR) of the promoter gene coding for the Paired-like homeodomain transcription factor 2 (PITX2) was determined by a validated methylation-specific real-time polymerase chain reaction (PCR) test. The multicenter study was conducted in routinely collected archived formalin-fixed paraffin-embedded (FFPE) tissue from 205 lymph node-positive breast cancer patients treated with adjuvant anthracycline-based chemotherapy. Results: The cut-off for the PITX2 methylation status (PMR = 12) was confirmed in a randomly selected cohort (n = 60) and validated (n = 145) prospectively with disease-free survival (DFS) at the 10-year follow-up. DFS was significantly different between the PMR ≤ 12 versus the PMR > 12 group with a hazard ratio (HR) of 2.74 (p < 0.001) in the validation cohort and also for the patient subgroup treated additionally with endocrine therapy (HR 2.47; p = 0.001). Conclusions: Early-stage lymph node-positive breast cancer patients with low PITX2 methylation do benefit from adjuvant anthracycline-based chemotherapy. Patients with a high PITX2 DNA methylation ratio, approximately 30%, show poor outcome and should thus be considered for alternative chemotherapy regimens

Clinical performance of an analytically validated assay in comparison to microarray technology to assess PITX2 DNA-methylation in breast cancer

Significant evidence has accumulated that DNA-methylation of the paired-like homeodomain transcription factor 2 (PITX2) gene can serve as a prognostic and predictive biomarker in breast cancer. PITX2 DNA-methylation data have been obtained so far from microarray and polymerase chain reaction (PCR)-based research tests. The availability of an analytically validated in vitro methylation-specific real-time PCR assay format (therascreen PITX2 RGQ PCR assay) intended for the determination of the percent methylation ratio (PMR) in the (PITX2) promoter 2 prompted us to investigate whether the clinical performance of these different assay systems generate comparable clinical outcome data. Mathematically converted microarray data of a previous breast cancer study (n = 204) into PMR values leads to a PITX2 cut-off value at PMR 14.73. Recalculation of the data to experimentally equivalent PMRs with the PCR PITX2 assay leads to a cut-off value at PMR 12 with the highest statistical significance. This cut-off predicts outcome of high-risk breast cancer patients to adjuvant anthracycline-based chemotherapy (n = 204; Hazard Ratio 2.48; p < 0.001) comparable to microarray generated results (n = 204; Hazard ratio 2.32; p < 0.0001). The therascreen PITX2 RGQ PCR assay is an analytically validated test with high reliability and robustness and predicts outcome of high-risk breast cancer patients to anthracycline-based chemotherapy

Construction and evaluation of a whole genome microarray of Chlamydomonas reinhardtii

Toepel J, Albaum S, Arvidsson S, et al. Construction and evaluation of a whole genome microarray of Chlamydomonas reinhardtii. BMC Genomics. 2011;12(1): 579.ABSTRACT: BACKGROUND: Chlamydomonas reinhardtii is widely accepted as a model organism regarding photosynthesis, circadian rhythm, cell mobility, phototaxis, and biotechnology. The complete annotation of the genome allows transcriptomic studies, however a new microarray platform was needed. Based on the completed annotation of Chlamydomonas reinhardtii a new microarray on an Agilent platform was designed using an extended JGI 3.1 genome data set which included 15000 transcript models. RESULTS: In total 44000 probes were determined (3 independent probes per transcript model) covering 93% of the transcriptome. Alignment studies with the recently published AUGUSTUS 10.2 annotation confirmed 11000 transcript models resulting in a very good coverage of 70% of the transcriptome (17000). Following the estimation of 10000 predicted genes in Chlamydomonas reinhardtii our new microarray, nevertheless, covers the expected genome by 90-95%. CONCLUSIONS: To demonstrate the capabilities of the new microarray, we analyzed transcript levels for cultures grown under nitrogen as well as sulfate limitation, and compared the results with recently published microarray and RNA-seq data. We could thereby confirm previous results derived from data on nutrient-starvation induced gene expression of a group of genes related to protein transport and adaptation of the metabolism as well as genes related to efficient light harvesting, light energy distribution and photosynthetic electron transport

Effects of Inhibition of Interleukin-6 Signalling on Insulin Sensitivity and Lipoprotein (A) Levels in Human Subjects with Rheumatoid Diseases

Interleukin-6 (IL-6) is a pro-inflammatory cytokine that has been found to be increased in type 2 diabetic subjects. However, it still remains unclear if these elevated IL-6 levels are co-incidental or if this cytokine is causally related to the development of insulin resistance and type 2 diabetes in humans. Therefore, in the present study we examined insulin sensitivity, serum adipokine levels and lipid parameters in human subjects before and after treatment with the IL-6 receptor antibody Tocilizumab.11 non-diabetic patients with rheumatoid disease were included in the study. HOMA-IR was calculated and serum levels for leptin, adiponectin, triglycerides, LDL-cholesterol, HDL-cholesterol and lipoprotein (a) (Lp (a)) were measured before as well as one and three months after Tocilizumab treatment. The HOMA index for insulin resistance decreased significantly. While leptin concentrations were not altered by inhibition of IL-6 signalling, adiponectin concentrations significantly increased. Thus the leptin to adiponectin ratio, a novel marker for insulin resistance, exhibited a significant decrease. Serum triglycerides, LDL-cholesterol and HDL-cholesterol tended to be increased whereas Lp (a) levels significantly decreased.Inhibition of IL-6 signalling improves insulin sensitivity in humans with immunological disease suggesting that elevated IL-6 levels in type 2 diabetic subjects might be causally involved in the pathogenesis of insulin resistance. Furthermore, our data indicate that inhibition of IL-6 signalling decreases Lp (a) serum levels, which might reduce the cardiovascular risk of human subjects

Sleep Loss Produces False Memories

People sometimes claim with high confidence to remember events that in fact never happened, typically due to strong semantic associations with actually encoded events. Sleep is known to provide optimal neurobiological conditions for consolidation of memories for long-term storage, whereas sleep deprivation acutely impairs retrieval of stored memories. Here, focusing on the role of sleep-related memory processes, we tested whether false memories can be created (a) as enduring memory representations due to a consolidation-associated reorganization of new memory representations during post-learning sleep and/or (b) as an acute retrieval-related phenomenon induced by sleep deprivation at memory testing. According to the Deese, Roediger, McDermott (DRM) false memory paradigm, subjects learned lists of semantically associated words (e.g., “night”, “dark”, “coal”,…), lacking the strongest common associate or theme word (here: “black”). Subjects either slept or stayed awake immediately after learning, and they were either sleep deprived or not at recognition testing 9, 33, or 44 hours after learning. Sleep deprivation at retrieval, but not sleep following learning, critically enhanced false memories of theme words. This effect was abolished by caffeine administration prior to retrieval, indicating that adenosinergic mechanisms can contribute to the generation of false memories associated with sleep loss

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection are often non-specific, and there is no definitive test for the accurate diagnosis of infection. The 'omics' approaches to identifying biomarkers from the host-response to bacterial infection are promising. In this study, lipidomic analysis was carried out with plasma samples obtained from febrile children with confirmed bacterial infection (n = 20) and confirmed viral infection (n = 20). We show for the first time that bacterial and viral infection produces distinct profile in the host lipidome. Some species of glycerophosphoinositol, sphingomyelin, lysophosphatidylcholine and cholesterol sulfate were higher in the confirmed virus infected group, while some species of fatty acids, glycerophosphocholine, glycerophosphoserine, lactosylceramide and bilirubin were lower in the confirmed virus infected group when compared with confirmed bacterial infected group. A combination of three lipids achieved an area under the receiver operating characteristic (ROC) curve of 0.911 (95% CI 0.81 to 0.98). This pilot study demonstrates the potential of metabolic biomarkers to assist clinicians in distinguishing bacterial from viral infection in febrile children, to facilitate effective clinical management and to the limit inappropriate use of antibiotics