12 research outputs found

    Evaluation of HER2 expression in urothelial carcinoma cells as a biomarker for circulating tumor cells

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    Background Detection of circulating tumor cells (CTC) by techniques based on epithelial cell adhesion molecule (EpCAM) is suboptimal in urothelial carcinoma (UC). As HER2 is thought to be broadly expressed in UC, we explored its utility for CTC detection. Methods HER2 and EpCAM expression was analyzed in 18 UC cell lines (UCCs) by qRT-PCR, western blot and fluorescence-activated cell scanning (FACS) and compared to the strongly HER2-expressing breast cancer cell line SKBR3 and other controls. HER2 expression in UC patient tissues was measured by qRT PCR and correlated with data on survival and risk for metastasis. UCCs with high EpCAM and variable HER2 expression were used for spike-in experiments in the CellSearch system. Twenty-one blood samples from 13 metastatic UC patients were analyzed for HER2-positive CTCs with CellSearch. Results HER2 mRNA and protein were broadly expressed in UCC, with some heterogeneity, but at least 10-fold lower than in the HER-2+ SKBR3 cells. Variations were unrelated to cellular phenotype or clinicopathological characteristics. EpCAM expression was essentially restricted to UCCs with epitheloid phenotypes. Heterogeneity of EpCAM and HER2 expression was observed also in spike-in experiments. The 7 of 21 blood samples from 6 of 13 patients were enumerated as CTC positive via EpCAM, but only one sample stained weakly positive (1+) for HER2. Conclusions Detection rate of CTCs by EpCAM in UC is poor, even in metastatic patients. Because of its widespread expression, particularly in patients with high risk of metastasis, detection of HER2 could improve identification of UC CTCs, which is why combined detection using antibodies for EpCAM and HER2 may be beneficial

    Correction to: EGFR/Ras-induced CCL20 production modulates the tumour microenvironment

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    The article ‘EGFR/Ras-induced CCL20 production modulates the tumour microenvironment’, written by Andreas Hippe, Stephan Alexander Braun, PĂ©ter OlĂĄh, Peter Arne Gerber, Anne Schorr, Stephan Seeliger, Stephanie Holtz, Katharina Jannasch, Andor Pivarcsi, Bettina Buhren, Holger Schrumpf, Andreas Kislat, Erich BĂŒnemann, Martin Steinhoff, Jens Fischer, SĂ©rgio A. Lira, Petra Boukamp, Peter Hevezi, Nikolas Hendrik Stoecklein, Thomas Hoffmann, Frauke Alves, Jonathan Sleeman, Thomas Bauer, Jörg Klufa, Nicole Amberg, Maria Sibilia, Albert Zlotnik, Anja MĂŒller- Homey and Bernhard Homey, was originally published electronically on the publisher’s internet portal on 30 June 2020 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 16 September 2021 to © The Author(s) 2021 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/ licenses/by/4.0/. Open Access funding enabled and organized by Projekt DEAL

    A New Workflow for Whole-Genome Sequencing of Single Human Cells

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    Binder V, Bartenhagen C, Okpanyi V, et al. A New Workflow for Whole-Genome Sequencing of Single Human Cells. Human mutation. 2014;35(10):1260-1270.: Unbiased amplification of the whole-genome amplification (WGA) of single cells is crucial to study cancer evolution and genetic heterogeneity, but is challenging due to the high complexity of the human genome. Here, we present a new workflow combining an efficient adapter-linker PCR-based WGA method with second-generation sequencing. This approach allows comparison of single cells at base pair resolution. Amplification recovered up to 74% of the human genome. Copy-number variants and loss of heterozygosity detected in single cell genomes showed concordance of up to 99% to pooled genomic DNA. Allele frequencies of mutations could be determined accurately due to an allele dropout rate of only 2%, clearly demonstrating the low bias of our PCR-based WGA approach. Sequencing with paired-end reads allowed genome-wide analysis of structural variants. By direct comparison to other WGA methods, we further endorse its suitability to analyze genetic heterogeneity
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