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

BackgroundThis 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.MethodsOriginal 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.ResultsFourteen 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)).ConclusionsComprehensive 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

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 (p0.001) 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-, 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 (p0.001). 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

Development of Non-Targeted Mass Spectrometry Method for Distinguishing Spelt and Wheat

Food fraud, even when not in the news, is ubiquitous and demands the development of innovative strategies to combat it. A new non-targeted method (NTM) for distinguishing spelt and wheat is described, which aids in food fraud detection and authenticity testing. A highly resolved fingerprint in the form of spectra is obtained for several cultivars of spelt and wheat using liquid chromatography coupled high-resolution mass spectrometry (LC-HRMS). Convolutional neural network (CNN) models are built using a nested cross validation (NCV) approach by appropriately training them using a calibration set comprising duplicate measurements of eleven cultivars of wheat and spelt, each. The results reveal that the CNNs automatically learn patterns and representations to best discriminate tested samples into spelt or wheat. This is further investigated using an external validation set comprising artificially mixed spectra, samples for processed goods (spelt bread and flour), eleven untypical spelt, and six old wheat cultivars. These cultivars were not part of model building. We introduce a metric called the D score to quantitatively evaluate and compare the classification decisions. Our results demonstrate that NTMs based on NCV and CNNs trained using appropriately chosen spectral data can be reliable enough to be used on a wider range of cultivars and their mixes

Synergistic Adverse Effects of Azithromycin and Hydroxychloroquine on Human Cardiomyocytes at a Clinically Relevant Treatment Duration

Adverse effects of drug combinations and their underlying mechanisms are highly relevant for safety evaluation, but often not fully studied. Hydroxychloroquine (HCQ) and azithromycin (AZM) were used as a combination therapy in the treatment of COVID-19 patients at the beginning of the pandemic, leading to higher complication rates in comparison to respective monotherapies. Here, we used human-induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) to systematically investigate the effects of HCQ, AZM, and their combination on the structure and functionality of cardiomyocytes, and to better understand the underlying mechanisms. Our results demonstrate synergistic adverse effects of AZM and HCQ on electrophysiological and contractile function of iPSC-CMs. HCQ-induced prolongation of field potential duration (FPDc) was gradually increased during 7-day treatment period and was strongly enhanced by combination with AZM, although AZM alone slightly shortened FPDc in iPSC-CMs. Combined treatment with AZM and HCQ leads to higher cardiotoxicity, more severe structural disarrangement, more pronounced contractile dysfunctions, and more elevated conduction velocity, compared to respective monotreatments. Mechanistic insights underlying the synergistic effects of AZM and HCQ on iPSC-CM functionality are provided based on increased cellular accumulation of HCQ and AZM as well as increased Cx43- and Nav1.5-protein levels

Toxicological profiling of water samples with in vitro bioassays and assessment using effect-based trigger values

In vitro bioassays including cell-based bioassays and low-complexity whole-organism assays have been applied for decades in water quality monitoring. However, there is no common understanding what level or response is acceptable. As of now, bioassay results were only benchmarked against each other but not against an absolute measure of chemical water quality. The EU environmental quality standards (EQS) differentiate between poor and acceptable surface water concentrations for individual chemicals of concern but cannot capture the thousands of chemicals that are in water and their biological action as mixtures. We developed a method that reads across from existing EQS and makes additional mixture considerations to assure that the derived EBT are protective for complex mixtures as they occur in surface water. The EBT derivation method was applied to 48 in vitro bioassays with 37 of them having sufficient information to yield preliminary EBTs. 30 of those were considered robust enough to pursue further and for the remainder it is necessary to obtain more experimental data for single chemicals but also to derive more EQS values. To assess the practicability and robustness of the proposed approach, we tested the EBTs numerous case studies from the literature where wastewater treatment plants and surface water were evaluated with bioanalytical tools. In this presentation, we highlight specifically case studies from the EU project SOLUTIONS, where water quality was assessed in large streams (e.g., Danube), hot spots of contamination (e.g., disposal of untreated wastewater into the Danube in Novi Sad) and influence of wastewater treatment plant effluent into small creeks (case study of small Rhine tributaries in Switzerland). In many cases the proposed EBTs were able to differentiate wastewater from surface water and EBTs for different bioassays gave very consistent results indicating the benefit of a common derivation method. Despite the limitations due to limited effect data availability and limitations of the existing lists of EQS, the proposed generic methods to derive EBTs is a first step to harmonise existing approaches and explore various different options of a large diversity of in vitro bioassays commonly applied for water quality assessment. Acknowledgement – This study was a joint effort of the EU project SOLUTIONS (grant 603437) and the workgroup bioassays of the NORMAN network

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