Eberhard Korsching

Eberhard Korsching
University of Münster | WWU · Institute of Bioinformatics

Professor, PhD (Dr.rer.nat.)

About

147
Publications
8,881
Reads
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2,219
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Introduction
The analysis of the complexity of the biological cell is a tricky adventure and still far from being accomplished. The type diversity of molecular players as well as the number diversity of each molecular player spans an enormous combinatorial space. The expression and type variability reflects major core elements of this highly parallelized biochemical reaction network. We are using this perspective to explain important mechanistic details of the cellular system in cancer.
Additional affiliations
August 2009 - present
University of Münster
Position
  • PI
January 1997 - July 2009
University of Münster
Position
  • Researcher

Publications

Publications (147)
Article
Full-text available
In a prospective observational pilot study on patients undergoing elective cardiac surgery with cardiopulmonary bypass, we evaluated label-free quantitative phase imaging (QPI) with digital holographic microscopy (DHM) to describe perioperative inflammation by changes in biophysical cell properties of lymphocytes and monocytes. Blood samples from 2...
Article
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The E-cadherin protein (Cadherin 1, gene: CDH1), a master regulator of the human epithelial homeostasis, contributes to the epithelial-mesenchymal transition (EMT) which confers cell migratory features to the cells. The EMT is central to many pathophysiological changes in cancer. Therefore, a better understanding of this regulatory scenario is bene...
Article
Full-text available
One of the still open questions in Ewing sarcoma, a rare bone tumor with weak therapeutic options, is to identify the tumor-driving cell (sub) population and to understand the specifics in the biological network of these cells. This basic scientific insight might foster the development of more specific therapeutic target patterns. The experimental...
Article
Full-text available
Background: The CXCR4 receptor antagonist plerixafor (AMD3100) is raising interest as an anti-cancer agent that disrupts the CXCL12-CXCR4 chemokine - receptor interaction between neoplastic cells and their microenvironment in tumor progression and metastasis. Here, we investigated plerixafor for anti-cancer activity in Ewing sarcoma, a rare and ag...
Article
Background Early detection of cancers improves patients’ survival and decreases the treatment cost. Unfortunately, the current methods for diagnosis of bladder and prostate cancers, two most common urothelial malignancies, suffer from a low sensitivity and specificity. MicroRNAs, as a group of endogenously produced non‐coding RNAs, regulate gene ex...
Article
Full-text available
Understanding the mechanisms regulating human mammary epithelium requires knowledge of the cellular constituents of this tissue. Different and partially contradictory definitions and concepts describing the cellular hierarchy of mammary epithelium have been proposed, including our studies of keratins K5 and/or K14 as markers of progenitor cells. Fu...
Article
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Sulfur mustard is a vesicant chemical warfare agent, which has been used during Iraq-Iran-war. Many veterans and civilians still suffer from long-term complications of sulfur mustard exposure, especially in their lung. Although the lung lesions of these patients are similar to Chronic Obstructive Pulmonary Disease (COPD), there are some differences...
Data
miR-143-3p - G1 cell cycle arrest. (PDF)
Data
Conditions and data distributions. (PDF)
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miR-148-3p expression on individual samples. (PDF)
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Comparative scatter plots of conditions. (PDF)
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The affected cellular pathways influenced by 9 altered microRNAs in serum samples of SMVs, mild to severe intersection, BIOCARTA analysis. (XLSX)
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All candidate sets of Fig 4B in one table. (XLSX)
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The affected cellular pathways influenced by 15 altered microRNAs in serum samples of SMVs, normal to mild comparison, BIOCARTA analysis. (XLSX)
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The affected cellular pathways influenced by 29 altered microRNAs in serum samples of SMVs, normal to severe comparison, BIOCARTA analysis. (XLSX)
Article
Full-text available
In the search for novel therapeutic targets, RNA interference screening has become a valuable tool. High-throughput technologies are now broadly accessible but their assay development from baseline remains resource-intensive and challenging. Focusing on this assay development process, we here describe a target discovery screen using pooled shRNA li...
Data
Additional Bioanalyzer electrophoresis profiles. Bioanalyzer electrophoresis profiles of (A) purified PCR products generated from Decode ctrl and a representative test sample (corresponding to Fig 4D), and of (B) purified PCR products and (C) Ion Proton NGS libraries generated from screen replicate 1 (corresponding to Fig 4E). FU = fluorescent unit...
Data
Additional figure on shRNA read count distribution and reproducibility. (A) The minimum range of shRNA abundance, calculated as the minimum fold difference between the least and most abundant shRNAs for 70% of the shRNA population [12]. r1 and r2 indicate screen replicates 1 and 2, respectively. (B) Scatter plot matrix and Pearson correlation coeff...
Data
ProFED Workflow. Mathematical formulations underlying the ProFED tool. (PDF)
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Additional figure on target cell transduction and selection. (A) Representative flow cytometry scatter plots of A673 and HEK293 cells demonstrating GFP-positive and -negative cell populations 96 h after transduction with non-silencing shRNA. (B) Puromycin dose-response curve of native non-transduced A673 (left) and HEK293 (right) cells. Viable cell...
Data
Additional Ion Proton read length histograms. (A) Read length histogram of a technical NGS replicate of exp_A673 (corresponding to Fig 5A, top panel). (B) Bioanalyzer electrophoresis profile of an Ion proton NGS library (exp_A673 test sample) generated in an alternative strategy incorporating barcodes and platform adapters in an additional 16-cycle...
Data
Hit lists generated using the ProFED online application. These hit lists refer to the exemplary hit profile criteria described in Results and Discussion. (XLSX)
Article
Background: Postanalytic issues of Ki67 assessment in breast cancers like counting method standardisation and interrater bias have been subject of various studies, but little is known about analytic variability of Ki67 staining between pathology labs. Our aim was to study interlaboratory variability of Ki67 staining in breast cancer using tissue m...
Article
Full-text available
Background: Squamous cell carcinomas (SCCs) are the most prevalent malignant tumours within the head and neck. Evidence exists that distinct genes are differentially regulated in SCCs of the oral cavity compared to other head and neck regions. Given this background, the aim of this study was to investigate whether such tumour site-specific gene ex...
Article
Full-text available
We contend that knowledge about the cellular composition of normal breast epithelium is a prerequisite for understanding proliferative breast disease. Against this background, we used multicolor immunofluorescence to study normal breast epithelium and two types of intraepithelial proliferative breast lesion for expression of the p63, basal keratin...
Article
Full-text available
There are no satisfying tools in tissue microarray (TMA) data analysis up to now to analyze the cooperative behavior of all measured markers in a multifactorial TMA approach. The developed tool TMAinspiration is not only offering an analysis option to close this gap but also offering an ecosystem consisting of quality control concepts and supportin...
Article
Full-text available
Squamous cell carcinoma (SCC) of the oral cavity is a morphological heterogeneous disease. Various cytokeratin (CK) expression patterns with different prognostic values have been described, but little is known concerning the underlying biological cell mechanisms. Therefore, the present study investigated 193 cases of oral SCCs using immunohistochem...
Article
Full-text available
The most prominent brain region evaluating the significance of external stimuli immediately after their onset is the amygdala. Stimuli evaluated as being stressful actuate a number of physiological processes as an immediate stress response. Variation in the serotonin transporter gene has been associated with increased anxiety- and depression-like b...
Article
Full-text available
Despite multimodal treatment, long term outcome for patients with Ewing sarcoma is still poor. The second "European interdisciplinary Ewing sarcoma research summit" assembled a large group of scientific experts in the field to discuss their latest unpublished findings on the way to the identification of novel therapeutic targets and strategies. Ewi...
Article
Full-text available
Receptor tyrosine kinases (RTKs) have provided molecular targets for the development of novel, prognosis-improving agents in many cancers; however, resistances to these therapies occur. On the cellular level, one resistance mechanism is attributed to functional RTK redundancies and compensatory cross-signaling, leading to perception of RTKs as sign...
Article
A low mutation rate seems a general feature of pediatric cancers, in par-ticular in oncofusion gene driven tumors. Genetically, Ewing sarcoma (ES) is de-fined by balanced chromosomal EWS/ETS translocations, which give rise to onco-genic chimeric proteins (EWS-ETS). Other contributing somatic mutations involved in disease development have only been...
Article
Full-text available
Despite the option of multimodal therapy in the treatment strategies of osteosarcoma (OS), the most common primary malignant bone tumor, the standard therapy has not changed over the last decades and still involves multidrug chemotherapy and radical surgery. Although successfully applied in many patients a large number of patients eventually develo...
Article
Full-text available
Osteosarcoma (OS), a bone tumor, exhibit a complex karyotype. On the genomic level a highly variable degree of alterations in nearly all chromosomal regions and between individual tumors is observable. This hampers the identification of common drivers in OS biology. To identify the common molecular mechanisms involved in the maintenance of OS, we f...
Article
AimsMale breast cancer (MBC) is a rare and poorly characterized disease. In the present study we used a novel biomathematical model to further characterize MBC and to identify differences between male and female breast cancer (FBC).Methods134 cases of MBC were immunohistochemically stained for 13 key oncoproteins and staining percentages were used...
Article
Full-text available
Giant cell tumor of bone (GCTB) displays worrisome clinical features such as local recurrence and occasionally metastatic disease which are unpredictable by morphology. Additional routinely usable biomarkers do not exist. Gene expression profiles of six clinically defined groups of GCTB and one group of aneurysmal bone cyst (ABC) were determined by...
Article
Zielsetzung: Die Tumorproliferationsmessung durch Ki67-Labelling Index (Ki67-LI) wird beim Mammakarzinom zur Prognoseeinschatzung, spatestens seit 2011 auch zur Chemotherapieindikation bei luminalen Mammakarzinomen empfohlen. Trotz Zweifeln an der Reproduzierbarkeit, enthalten internationale und nationale Empfehlungen bereits Cut-Offs zur Definitio...
Article
Objective: Assessment of tumor proliferation using the Ki67 labeling index (Ki67-LI) is increasingly recommended for prognostication and adjuvant chemotherapy decisions in breast cancer. Our aim was to investigate interlaboratory variance of Ki67-LI results using TMA and centralised assessment to exclude preanalytic influences and postanalytic vari...
Article
Full-text available
Osteosarcoma (OS) is the most common primary bone cancer exhibiting high genomic instability. This genomic instability affects multiple genes and microRNAs to a varying extent depending on patient and tumor subtype. Massive research is ongoing to identify genes including their gene products and microRNAs that correlate with disease progression and...
Data
Osteosarcomas (OS) are complex bone tumors with various genomic alterations. These alterations affect the expression and function of several genes due to drastic changes in the underlying gene regulatory network. However, we know little about critical gene regulators and their functional consequences on the pathogenesis of OS. Therefore, we aimed t...
Data
Full-text available
Distribution of Dunn coefficients and indices determined by FCM clustering. (A) Assessing the optimal fuzziness parameter. The plot illustrates the Dunn coefficients (y-axis) among a range of fuzziness parameters (x-axis) for different cluster numbers. The fuzziness was set to 1.1, where the Dunn coefficient distribution exceeds 0.5 for all cluster...
Data
Module C2.1 target gene associations. The network is derived from the STRING 9.0 database [42]. It illustrates experimental and literature-mined functional associations between genes within the C2.1 network module. (TIF)
Data
Significant microRNA and TF co-regulatory 4-node motifs. The table summarizes the number of interacting target genes of each non-random microRNA and TF co-regulatory pair with corresponding statistics. (XLS)
Data
Full-text available
Enrichment of proliferation-related microRNAs. The barplot of enrichment scores (ESs) of observed microRNA target genes (cyan) and randomly selected targets (grey). The ES of randomly selected microRNA targets is illustrated as mean±stdev. Per microRNA we computed 1,000 random ESs. P-values between observed and random ESs were obtained by counting...
Data
Full-text available
MicroRNA and TF co-regulatory network modules derived from C1. The figure shows network modules defined by the walktrap algorithm. The modules C1.1 to C2.6 are labeled from (A) to (F). Node shapes correspond to the distinct node types: microRNAs (diamond), TFs (triangle), primary target (rectangle), and secondary target (ellipse). Yellow edges mark...
Data
MicroRNA and TF co-regulatory network modules derived from C2. The figure shows network modules defined by the walktrap algorithm. The modules C2.1 to C2.6 are labeled from (A) to (F). Node shapes correspond to the distinct node types: microRNAs (diamond), TFs (triangle), primary target (rectangle), and secondary target (ellipse). Yellow edges mark...
Data
miR-9-5p and SP1 target gene associations. The network is derived from the STRING 9.0 database [42]. It illustrates experimental and literature-mined functional associations between miR-9-5p and SP1 target genes. (TIF)
Data
Significant microRNA and TF co-regulatory 3-node motifs. The table summarizes the number of common target genes of each non-random microRNA and TF co-regulatory pair with corresponding statistics. (XLS)
Data
MicroRNA and TF co-regulatory network hubs. The table holds the node degree and betweenness parameters of hub genes within the co-regulatory network of C1 and C2 for each node type. (XLS)
Data
Full-text available
Node degree distribution of the microRNA and TF co-regulatory networks. The plots show the fraction of proteins (y-axis) among all node degrees (x-axis) from the microRNA and TF co-regulatory networks (grey) of (A) C1 and (B) C2. Different colors indicate distinct degree distributions of different node types. Horizontal lines mark the average node...
Data
Enrichment of proliferation-related microRNA target genes. Results of the hypergeometric test to examine significantly enriched microRNA target genes within the list of DE genes. The table marks the total number of predicted target genes, the number of DE target genes, and the corresponding FDR. (XLS)
Data
Individual microRNA and TF co-regulatory 3-node and 4-node motifs of C1. (XLS)
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Individual microRNA and TF co-regulatory 3-node and 4-node motifs of C2. (XLS)
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Over-represented KEGG pathways. (XLS)
Article
Full-text available
Osteosarcomas (OS) are complex bone tumors with various genomic alterations. These alterations affect the expression and function of several genes due to drastic changes in the underlying gene regulatory network. However, we know little about critical gene regulators and their functional consequences on the pathogenesis of OS. Therefore, we aimed t...
Article
Full-text available
The most prominent brain region evaluating the significance of external stimuli immediately after their onset is the amygdala. Stimuli evaluated as being stressful actuate a number of physiological processes as an immediate stress response. Variation in the serotonin transporter gene has been associated with increased anxiety- and depression-like b...
Data
Gene list report of differentially regulated amygdala genes in mouse groups related to condition of acute stress or control (stress or con) and 5-HTT genotype (WT or KO). (DOC)
Data
Comparison between Array- and Taqman-based gene expression in the genes Robo2, Cdh9, Ace, Anxa1, and Adra2a, showing the direction of regulation (up- or down-regulated), fold changes (FC), and P-values in the group comparisons related to condition (acute stress or control) and 5-HTT genotype (WT or KO) of mice. (DOC)