Karina Hettwer

Development and assessment of a novel Arxula adeninivorans androgen screen (A-YAS) assay and its application in analysis of cattle urine

The novel A-YAS assay for the detection of androgenic activity in liquid samples such as urine has been developed and assessed. The assay is based on transgenic Arxula adeninivorans yeast cells as the bio-component. The cells were engineered to co-express the human androgen receptor (hAR) gene and the inducible phytase reporter gene (phyK, derived from Klebsiella sp. ASR1), under the control of an Arxula derived glucoamylase (GAA) promoter, which had been modified by the insertion of hormone-responsive elements (HREs). The Arxula transformation/expression platform Xplor®2 was used to select stable mitotic resistance marker free transformants and the most suitable cells were characterized for performance as a sensor bio-component. The assay is easy-to-use, fast (6-25 h) and is currently the most sensitive yeast-based androgen screen with an EC50, limit of detection and of quantification values for 5α-dihydrotestosterone (DHT) of 277.1±53.0, 56.5±4.1 and 76.5±6.7 ng L(-1), respectively. Furthermore, the assay allows the determination of androgenic and anti-androgenic activity of various compounds such as naturally occurring androgens and estrogens, pharmaceuticals and biocides. The robustness of the A-YAS assay enables it to be used for analysis of complex samples such as urine. The results of the analysis of a number of cattle urine samples achieved by the A-YAS assay correlate well with GC-MS analysis of the same samples.

Effect-based trigger values for in vitro and in vivo bioassays performed on surface water extracts supporting the environmental quality standards (EQS) of the European Water Framework Directive

Effect-based methods including cell-based bioassays, reporter gene assays and whole-organism assays have been applied for decades in water quality monitoring and testing of enriched solid-phase extracts. There is no common EU-wide agreement on what level of bioassay response in water extracts is acceptable. At present, bioassay results are only benchmarked against each other but not against a consented measure of chemical water quality. The EU environmental quality standards (EQS) differentiate between acceptable and unacceptable surface water concentrations for individual chemicals but cannot capture the thousands of chemicals in water and their biological action as mixtures. We developed a method that reads across from existing EQS and includes additional mixture considerations with the goal that the derived effect-based trigger values (EBT) indicate acceptable risk for complex mixtures as they occur in surface water. Advantages and limitations of various approaches to read across from EQS are discussed and distilled to an algorithm that translates EQS into their corresponding bioanalytical equivalent concentrations (BEQ). The proposed EBT derivation method was applied to 48 in vitro bioassays with 32 of them having sufficient information to yield preliminary EBTs. To assess the practicability and robustness of the proposed approach, we compared the tentative EBTs with observed environmental effects. The proposed method only gives guidance on how to derive EBTs but does not propose final EBTs for implementation. The EBTs for some bioassays such as those for estrogenicity are already mature and could be implemented into regulation in the near future, while for others it will still take a few iterations until we can be confident of the power of the proposed EBTs to differentiate good from poor water quality with respect to chemical contamination.

Carcinoembryonic antigen and cytokeratin-19 fragments for assessment of therapy response in non-small cell lung cancer: a systematic review and meta-analysis

Background:This meta-analysis evaluated whether pretherapy serum levels of carcinoembryonic antigen (CEA) and cytokeratin-19 fragments (CYFRA 21-1) are predictive of response to therapy in non-small cell lung cancer (NSCLC) and whether changes in these markers during vs pretherapy are indicative of response.Methods:Original peer-reviewed studies enrolling adults with untreated advanced NSCLC were identified using PubMed. Two reviewers independently extracted data from eligible studies and assessed study heterogeneity and the risk of study bias.Results:Fourteen studies were eligible; 11 had objective response as an end point and three evaluated clinical benefit (i.e., response and stable disease). Study bias was relatively low. Both markers showed comparable modest predictive value across studies, with baseline CYFRA 21-1 numerically better in predicting treatment benefit. A good performance in identifying objective response during treatment was seen (AUC 0.724 (95% CI 0.667–0.785) for CYFRA 21-1 and 0.728 (95% CI, 0.599–0.871) for CEA). A decline in CYFRA 21-1 levels during treatment was highly indicative for objective response (sensitivity 79.1% (95% CI 71.5–85.1)).Conclusions:Comprehensive analysis of study heterogeneity and bias provides a high level of evidence for the clinical utility of CEA and CYFRA 21-1 for the prediction and monitoring of response in NSCLC.

Validation of Arxula Yeast Estrogen Screen assay for detection of estrogenic activity in water samples: Results of an international interlaboratory study

Endocrine-active substances can adversely impact the aquatic ecosystems. A special emphasis is laid, among others, on the effects of estrogens and estrogen mimicking compounds. Effect-based screening methods like in vitro bioassays are suitable tools to detect and quantify endocrine activities of known and unknown mixtures. This study describes the validation of the Arxula-Yeast Estrogen Screen (A-YES®) assay, an effect-based method for the detection of the estrogenic potential of water and waste water. This reporter gene assay, provided in ready to use format, is based on the activation of the human estrogen receptor alpha. The user-friendly A-YES® enables inexperienced operators to rapidly become competent with the assay. Fourteen laboratories from four countries with different training levels analyzed 17β-estradiol equivalent concentrations (EEQ) in spiked and unspiked waste water effluent and surface water samples, in waste water influent and spiked salt water samples and in a mixture of three bisphenols. The limit of detection (LOD) for untreated samples was 1.8ng/L 17β-estradiol (E2). Relative repeatability and reproducibility standard deviation for samples with EEQ above the LOD (mean EEQ values between 6.3 and 20.4ng/L) ranged from 7.5 to 21.4% and 16.6 to 28.0%, respectively. Precision results are comparable to other frequently used analytical methods for estrogens. The A-YES® has been demonstrated to be an accurate, precise and robust bioassay. The results have been included in the ISO draft standard. The assay was shown to be applicable for testing of typical waste water influent, effluent and saline water. Other studies have shown that the assay can be used with enriched samples, which lower the LOD to the pg/L range. The validation of the A-YES® and the development of a corresponding international standard constitute a step further towards harmonized and reliable bioassays for the effect-based analysis of estrogens and estrogen-like compounds in water samples.

Improved sensitivity for detection of breast cancer by combination of miR-34a and tumor markers CA 15-3 or CEA

Background MicroRNAs biomarkers have shown value for diagnosis and prognosis of various cancers. Combination with established tumor markers has rarely been done. Results Breast cancer patients had significantly higher serum RNA loads (AUC 0.665), lower miR-34a (AUC 0.772), higher CEA and CA 15-3 levels (AUCs 0.717 and 0.721) than healthy controls. miR-34a correlated with tumor stage and hormone receptor status. There was no significant difference between groups for all other miRNAs. Combination of miR-34a with CEA or CA 15-3 led to improved AUCs of 0.844 and 0.800, respectively. Sensitivity of miR-34a and CA 15-3 reached 56.1% at 95% specificity. When compared with benign breast diseases, combination of miR-34a (AUC 0.719) and CEA (0.623) or CA 15-3 (0.619) resulted in improved performances (0.794 and 0.741). Sensitivity of miR-34a and CA 15-3 reached 53.7% at 95% specificity. Conclusion While miR-34a provides valuable information for diagnosis and staging, combination with tumor markers CA15-3 or CEA improves the sensitivity for breast cancer detection. Patients and Methods The diagnostic relevance of the miR-21, miR-34a, miR-92a, miR-155, miR-222 and miR-let-7c was tested in sera of 103 individuals (55 breast cancer, 20 benign breast diseases, 28 healthy controls). MiRNAs were detected by quantitative rt-PCR after extraction and reverse transcription. Cel-miR-39 and miR-16 were used for normalization. Established tumor markers CEA, CA 15-3, CA 19-9 and CA 125 were measured by automatized immunoassays. Diagnostic performance was tested by areas under the curve (AUC) of receiver operating characteristic (ROC) curves and sensitivities at 90% and 95% specificity.

Kinetic Analyses of Data from a Human Serum Albumin Assay Using the liSPR System.

We used the interaction between human serum albumin (HSA) and a high-affinity antibody to evaluate binding affinity measurements by the bench-top liSPR system (capitalis technology GmbH). HSA was immobilized directly onto a carboxylated sensor layer, and the mechanism of interaction between the antibody and HSA was investigated. The bivalence and heterogeneity of the antibody caused a complex binding mechanism. Three different interaction models (1:1 binding, heterogeneous analyte, bivalent analyte) were compared, and the bivalent analyte model best fit the curves obtained from the assay. This model describes the interaction of a bivalent analyte with one or two ligands (A + L ↔ LA + L ↔ LLA). The apparent binding affinity for this model measured 37 pM for the first reaction step, and 20 pM for the second step.

Diagnostic relevance of a novel multiplex immunoassay panel in breast cancer

Multiple factors contribute to the development and progression of breast cancer. Markers of tumor growth and invasion, cell death, immune activation, and angiogenesis can be assessed in parallel by a novel multiplex immunoassay panel. The diagnostic performance of a multiplex cancer biomarker magnetic bead panel comprising 24 tumor associated parameters was evaluated in sera of 154 women including 77 patients with breast cancer, 10 with precancerous lesions, 31 with benign breast diseases, and 36 healthy controls. Marker levels were log-transformed for variance stabilization. Significance testing was done using t-test or Wilcoxon rank-sum test with correction of p values for multiple testing. Furthermore, receiver operating characteristic analyses were performed. Serum levels of several biomarkers were significantly (p ≤ 0.001) higher in cancer patients than in healthy controls, particularly alpha-fetoprotein, cancer antigen 15-3, cancer antigen 19-9, migration inhibitory factor, carcinoembryonic antigen, cancer antigen 125, hepatocyte growth factor, soluble Fas, tumor necrosis factor-α, stem cell factor, and osteopontin. As most markers were also elevated in benign breast diseases, only cancer antigen 15-3 showed significant differences to cancer patients (p ≤ 0.001). The resulting areas under the curve in receiver operating characteristic curves for discrimination between benign and malignant breast diseases achieved 0.71 with a sensitivity of 33.8% at 95% specificity. Multiplexing enables parallel analysis of different biomarker classes for cancer detection. Established cancer antigen 15-3 proved to be most relevant for differential diagnosis.

Statistisch abgesicherte Interpretation von SPR-Biochipsignalen via SPRING / Statistically Verified SPR Data Analysis via SPRING

Zusammenfassung Für das Datenmanagement bei Messungen der Oberflächenplasmonresonanz (SPR) wurden neue mathematische Verfahren entwickelt und in die eigens entwickelte Software SPRING integriert. Die Software ermöglicht eine Auswertung von SPR-Messdaten und liefert statistisch abgesicherte Aussagen zur Charakterisierung molekularer Interaktionen. Versuchsparameter, Sensorgramme und die statistische Bewertung werden in einem umfangreichen Report zur Verfügung gestellt. Summary For data management of surface plasmon resonance (SPR) data new mathematical processes were developed and integrated in the specifically developed software SPRING. The software enables the evaluation of SPR data and provides statistically verified statements for the characterisation of molecular interactions. Test parameters, sensorgrams, and the statistical evaluation are provided in a comprehensive report.