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  • 1
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    German Medical Science; Düsseldorf, Köln
    In:  27. Deutscher Krebskongress; 20060322-20060326; Berlin; DOCPE095 /20060320/
    Publication Date: 2006-04-21
    Keywords: ddc: 610
    Language: English
    Type: conferenceObject
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  • 2
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    German Medical Science; Düsseldorf, Köln
    In:  27. Deutscher Krebskongress; 20060322-20060326; Berlin; DOCPO080 /20060320/
    Publication Date: 2006-04-21
    Keywords: ddc: 610
    Language: English
    Type: conferenceObject
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  • 3
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    German Medical Science GMS Publishing House; Düsseldorf
    In:  37. Jahrestagung der Deutschsprachigen Arbeitsgemeinschaft für Verbrennungsbehandlung (DAV 2019); 20190109-20190112; Schladming, Österreich; DOC55 /20190108/
    Publication Date: 2019-01-09
    Keywords: ddc: 610
    Language: German
    Type: conferenceObject
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  • 4
    Keywords: proliferation ; IDENTIFICATION ; MASS-SPECTROMETRY ; TUMOR-MARKERS ; TRANSFER-RNA ; MODIFIED URINARY NUCLEOSIDES ; METHYLTHIOADENOSINE PHOSPHORYLASE ; NICOTINAMIDE RIBOSIDE ; MS ANALYSIS ; 1-METHYLADENOSINE
    Abstract: Cancer cells show characteristic effects on cellular turnover and DNA/RNA modifications leading to elevated levels of excreted modified nucleosides. We investigated the molecular signature of different subtypes of breast cancer cell lines and the breast epithelial cell line MCF-10A. Prepurification of cell culture supernatants was performed by cis-diol specific affinity chromatography using boronate-derivatized polyacrylamide gel. Samples were analyzed by application of reversed phase chromatography coupled to a triple quadrupole mass spectrometer. Collectively, we determined 23 compounds from RNA metabolism, two from purine metabolism, five from polyamine/methionine cycle, one from histidine metabolism and two from nicotinate and nicotinamide metabolism. We observed major differences of metabolite excretion pattern between the breast cancer cell lines and MCF-10A, just as well as between the different breast cancer cell lines themselves. Differences in metabolite excretion resulting from cancerous metabolism can be integrated into altered processes on the cellular level. Modified nucleosides have great potential as biomarkers in due consideration of the heterogeneity of breast cancer that is reflected by the different molecular subtypes of breast cancer. Our data suggests that the metabolic signature of breast cancer cell lines might be a more subtype-specific tool to predict breast cancer, rather than a universal approach.
    Type of Publication: Journal article published
    PubMed ID: 26293811
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  • 5
    Abstract: In recent years, knowledge about metabolite changes which are characteristic for the physiologic state of cancer cells has been acquired by liquid chromatography coupled to mass spectrometry. Distinct molecularly characterized breast cancer cell lines provide an unbiased and standardized in vitro tumor model reflecting the heterogeneity of the disease. Tandem mass spectrometry is a widely applied analytical platform and highly sensitive technique for analysis of complex biological samples. Endo- and exometabolite analysis of the breast cancer cell lines MDA-MB-231, -453 and BT-474 as well as the breast epithelial cell line MCF-10A has been performed using two different analytical platforms: UPLC-ESI-Q-TOF based on a scheduled precursor list has been applied for highlighting of significant differences between cell lines and HPLC-ESI-QqQ using multiple reaction monitoring has been utilized for a targeted approach focusing on RNA metabolism and interconnected pathways, respectively. Statistical analysis enabled a clear discrimination of the breast epithelial from the breast cancer cell lines. As an effect of oxidative stress, a decreased GSH/GSSG ratio has been detected in breast cancer cell lines. The triple negative breast cancer cell line MDA-MB-231 showed an elevation in nicotinamide, 1-ribosyl-nicotinamide and NAD+ reflecting the increased energy demand in triple negative breast cancer, which has a more aggressive clinical course than other forms of breast cancer. Obtained distinct metabolite pattern could be correlated with distinct molecular characteristics of breast cancer cells. Results and methodology of this preliminary in vitro study could be transferred to in vivo studies with breast cancer patients.
    Type of Publication: Journal article published
    PubMed ID: 27188315
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  • 6
    Abstract: The presence of circulating tumor cells (CTCs) in the blood of ovarian cancer patients was shown to correlate with decreased overall survival, whereby CTCs with epithelial-mesenchymal-transition (EMT) or stem-like traits are supposed to be involved in metastatic progression and recurrence. Thus, investigating the transcriptional profiles of CTCs might help to identify therapy resistant tumor cells and to overcome treatment failure. For this purpose, we established a multi-marker panel for the molecular characterization of single CTCs, detecting epithelial (EpCAM, Muc-1, CK5/7), EMT (N-cadherin, Vimentin, Snai1/2, CD117, CD146, CD49f) and stem cell (CD44, ALDH1A1, Nanog, SOX2, Notch1/4, Oct4, Lin28) associated transcripts. First primer specificity and PCR-performance of the multiplex-RT-PCRs were successfully validated on genomic DNA and cDNA isolated from OvCar3 cells. The assay sensitivity of the epithelial panel was evaluated by adding defined numbers of tumor cells into the blood of healthy donors and performing a subsequent immunomagnetic tumor cell enrichment (AdnaTest OvarianCancerSelect), resulting in a 100% concordance for the epithelial markers EpCAM and Muc-1 to the AdnaTest OvarianCancerDetect. Additionally, by processing blood from ovarian cancer patients, high assay sensitivity could be verified. In blood of healthy donors no signals for epithelial markers were detected, for EMT and stem cell markers, however, signals were obtained mainly originating from leukocytes which calls for single cell analysis. To that aim by using the ovarian cancer cell line OvCar3, we successfully established a workflow enabling the characterization of single CTCs. It consists of a density gradient-dependent enrichment for nucleated cells, a depletion of CD45-positive cells of hematopoietic origin followed by immunofluorescent labeling of CTCs by EpCAM and Muc-1. Single CTCs are then isolated by micromanipulation and processed for panel gene expression profiling. Finally, fifteen single CTCs from three ovarian cancer patients were analyzed and found to be positive for stem cell (CD44, ALDH1A1, Nanog, Oct4) and EMT markers (N-cadherin, Vimentin, Snai2, CD117, CD146). Albeit, inter-cellular and intra/inter-patient heterogeneity and co-expression of epithelial, mesenchymal and stem cell transcripts on the same CTC was observed. We have established a robust workflow to perform sensitive single cell panel gene expression analysis without the need of pre-amplification steps. Our data point towards a heterogeneous expression of stem cell and EMT associated transcripts in ovarian cancer CTCs.
    Type of Publication: Journal article published
    PubMed ID: 27157930
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  • 7
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    German Medical Science GMS Publishing House; Düsseldorf
    In:  37. Jahrestagung der Deutschsprachigen Arbeitsgemeinschaft für Verbrennungsbehandlung (DAV 2019); 20190109-20190112; Schladming, Österreich; DOC57 /20190108/
    Publication Date: 2019-01-09
    Keywords: ddc: 610
    Language: German
    Type: conferenceObject
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  • 8
    Keywords: EXPRESSION ; GENE ; PROTEIN ; DIFFERENTIATION ; METASTASIS ; DISSEMINATED TUMOR-CELLS ; micrometastasis ; MAMMARY-GLAND ; SELF-RENEWAL ; CTBP
    Abstract: Regulatory pathways that drive early hematogenous dissemination of tumor cells are insufficiently defined. Here, we used the presence of disseminated tumor cells (DTC) in the bone marrow to define patients with early disseminated breast cancer and identified low retinoic acid-induced 2 (RAI2) expression to be significantly associated with DTC status. Low RAI2 expression was also shown to be an independent poor prognostic factor in 10 different cancer datasets. Depletion of RAI2 protein in luminal breast cancer cell lines resulted in dedifferentiation marked by downregulation of ERalpha, FOXA1, and GATA3, together with increased invasiveness and activation of AKT signaling. Functional analysis of the previously uncharacterized RAI2 protein revealed molecular interaction with CtBP transcriptional regulators and an overlapping function in controlling the expression of a number of key target genes involved in breast cancer. These results suggest that RAI2 is a new metastasis-associated protein that sustains differentiation of luminal breast epithelial cells. SIGNIFICANCE: We identified downregulation of RAI2 as a novel metastasis-associated genetic alteration especially associated with early occurring bone metastasis in ERalpha-positive breast tumors. We specified the role of the RAI2 protein to function as a transcriptional regulator that controls the expression of several key regulators of breast epithelial integrity and cancer. Cancer Discov; 5(5); 506-19. (c)2015 AACR. See related commentary by Esposito and Kang, p. 466 This article is highlighted in the In This Issue feature, p. 453.
    Type of Publication: Journal article published
    PubMed ID: 25716347
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  • 9
    Abstract: Circulating tumor cells (CTC) are rare cells which have left the primary tumor to enter the blood stream. Although only a small CTC subgroup is capable of extravasating, the presence of CTCs is associated with an increased risk of metastasis and a shorter overall survival. Understanding the heterogeneous CTC biology will optimize treatment decisions and will thereby improve patient outcome. For this, robust workflows for detection and isolation of CTCs are urgently required. Here, we present a workflow to characterize CTCs by combining the advantages of both the CellSearch((R)) and the CellCelector micromanipulation system. CTCs were isolated from CellSearch((R)) cartridges using the CellCelector system and were deposited into PCR tubes for subsequent molecular analysis (whole genome amplification (WGA) and massive parallel multigene sequencing). By a CellCelector screen we reidentified 97% of CellSearch((R)) SKBR-3 cells. Furthermore, we isolated 97% of CellSearch((R)) -proven patient CTCs using the CellCelector system. Therein, we found an almost perfect correlation of R(2 ) = 0.98 (Spearman's rho correlation, n = 20, p 〈 0.00001) between the CellSearch((R)) CTC count (n = 271) and the CellCelector detected CTCs (n = 252). Isolated CTCs were analyzed by WGA and massive parallel multigene sequencing. In total, single nucleotide polymorphisms (SNPs) could be detected in 50 genes in seven CTCs, 12 MCF-7, and 3 T47D cells, respectively. Taken together, CTC quantification via the CellCelector system ensures a comprehensive detection of CTCs preidentified by the CellSearch((R)) system. Moreover, the isolation of CTCs after CellSearch((R)) using the CellCelector system guarantees for CTC enrichment without any contaminants enabling subsequent high throughput genomic analyses on single cell level. (c) 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:125-132, 2017.
    Type of Publication: Journal article published
    PubMed ID: 27126369
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  • 10
    Keywords: CANCER ; tumor ; evaluation ; Germany ; MODEL ; MODELS ; DIAGNOSIS ; SUPPORT ; DISEASE ; DISEASES ; SAMPLE ; SAMPLES ; PATIENT ; MARKER ; BREAST ; breast cancer ; BREAST-CANCER ; VECTOR ; WOMEN ; MARKERS ; MASS-SPECTROMETRY ; CANCER-PATIENTS ; NETHERLANDS ; CHROMATOGRAPHY ; LIQUID-CHROMATOGRAPHY ; PREDICTION ; sensitivity ; specificity ; CLINICAL-DIAGNOSIS ; CANCER PATIENTS ; HEALTHY ; AFFINITY-CHROMATOGRAPHY ; URINE ; PERFORMANCE LIQUID-CHROMATOGRAPHY ; SERUM ; CHEMISTRY ; NUCLEOSIDES ; PHASE ; metabolomics ; SET ; biological markers ; support vector machine ; TUMOR-MARKERS ; affinity chromatography ; chromatography with ultraviolett detection (HPLC-UV) ; high performance liquid ; k-nearest-neighbor classifier (k-NN) ; NEURAL-NETWORK ; PSEUDOURIDINE ; RNA MODIFICATION ; Support Vector Machine (SVM) ; TOF-MS ; TUMOR MARKERS ; URINARY MODIFIED NUCLEOSIDES
    Abstract: It is known that patients suffering from cancer diseases excrete increased amounts of modified nucleosides with their urine. Especially methylated nucleosides have been proposed to be potential tumor markers for early diagnosis of cancer. For determination of nucleosides in randomly collected urine samples, the nucleosides were extracted using affinity chromatography and then analyzed via reversed phase high-performance liquid chromatography (HPLC) with UV-detection. Eleven nucleosides were quantified in urine samples from 51 breast cancer patients and 65 healthy women. The measured concentrations were used to train a Support Vector Machine (SVM) and a k-nearest-neighbor classifier (k-NN) to discriminate between healthy control subjects and patients suffering from breast cancer. Evaluations of the learned models by computing the leave-one-out error and the prediction error on an independent test set of 29 subjects (15 healthy, 14 breast cancer patients) showed that by using the eleven nucleosides, the occurrence of breast cancer could be forecasted with 86% specificity and 94% sensitivity when using an SVM and 86% for both specificity and sensitivity with the k-NN model. (C) 2008 Elsevier B.V. All rights reserved
    Type of Publication: Journal article published
    PubMed ID: 18501242
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