Ulrike Korf

A Systems Biology Approach to Deciphering the Etiology of Steatosis Employing Patient-Derived Dermal Fibroblasts and iPS Cells

Non-alcoholic fatty liver disease comprises a broad spectrum of disease states ranging from simple steatosis to non-alcoholic steatohepatitis. As a result of increases in the prevalences of obesity, insulin resistance, and hyperlipidemia, the number of people with hepatic steatosis continues to increase. Differences in susceptibility to steatohepatitis and its progression to cirrhosis have been attributed to a complex interplay of genetic and external factors all addressing the intracellular network. Increase in sugar or refined carbohydrate consumption results in an increase of insulin and insulin resistance that can lead to the accumulation of fat in the liver. Here we demonstrate how a multidisciplinary approach encompassing cellular reprogramming, transcriptomics, proteomics, metabolomics, modeling, network reconstruction, and data management can be employed to unveil the mechanisms underlying the progression of steatosis. Proteomics revealed reduced AKT/mTOR signaling in fibroblasts derived from steatosis patients and further establishes that the insulin-resistant phenotype is present not only in insulin-metabolizing central organs, e.g., the liver, but is also manifested in skin fibroblasts. Transcriptome data enabled the generation of a regulatory network based on the transcription factor SREBF1, linked to a metabolic network of glycerolipid, and fatty acid biosynthesis including the downstream transcriptional targets of SREBF1 which include LIPIN1 (LPIN) and low density lipoprotein receptor. Glutathione metabolism was among the pathways enriched in steatosis patients in comparison to healthy controls. By using a model of the glutathione pathway we predict a significant increase in the flux through glutathione synthesis as both gamma-glutamylcysteine synthetase and glutathione synthetase have an increased flux. We anticipate that a larger cohort of patients and matched controls will confirm our preliminary findings presented here.

Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance

BackgroundIn breast cancer, overexpression of the transmembrane tyrosine kinase ERBB2 is an adverse prognostic marker, and occurs in almost 30% of the patients. For therapeutic intervention, ERBB2 is targeted by monoclonal antibody trastuzumab in adjuvant settings; however, de novo resistance to this antibody is still a serious issue, requiring the identification of additional targets to overcome resistance. In this study, we have combined computational simulations, experimental testing of simulation results, and finally reverse engineering of a protein interaction network to define potential therapeutic strategies for de novo trastuzumab resistant breast cancer.ResultsFirst, we employed Boolean logic to model regulatory interactions and simulated single and multiple protein loss-of-functions. Then, our simulation results were tested experimentally by producing single and double knockdowns of the network components and measuring their effects on G1/S transition during cell cycle progression. Combinatorial targeting of ERBB2 and EGFR did not affect the response to trastuzumab in de novo resistant cells, which might be due to decoupling of receptor activation and cell cycle progression. Furthermore, examination of c-MYC in resistant as well as in sensitive cell lines, using a specific chemical inhibitor of c-MYC (alone or in combination with trastuzumab), demonstrated that both trastuzumab sensitive and resistant cells responded to c-MYC perturbation.ConclusionIn this study, we connected ERBB signaling with G1/S transition of the cell cycle via two major cell signaling pathways and two key transcription factors, to model an interaction network that allows for the identification of novel targets in the treatment of trastuzumab resistant breast cancer. Applying this new strategy, we found that, in contrast to trastuzumab sensitive breast cancer cells, combinatorial targeting of ERBB receptors or of key signaling intermediates does not have potential for treatment of de novo trastuzumab resistant cells. Instead, c-MYC was identified as a novel potential target protein in breast cancer cells.

MiR-200bc/429 cluster targets PLCγ1 and differentially regulates proliferation and EGF-driven invasion than miR-200a/141 in breast cancer

The genes encoding microRNAs of the human miR-200 family map to fragile chromosomal regions and are frequently downregulated upon tumor progression. Although having been reported to regulate epithelial-to-mesenchymal transition and transforming growth factor-beta-driven cell invasion, the role of the miR-200 family in EGF-driven breast cancer cell invasion, viability, apoptosis and cell cycle progression is still unknown. In particular, there is no study comparing the roles of the two clusters of this miRNA family. In this study, we show for the first time that miR-200 family members differentially regulate EGF-driven invasion, viability, apoptosis and cell cycle progression of breast cancer cells. We showed that, all miR-200 family members regulate EGF-driven invasion, with the miR-200bc/429 cluster showing stronger effects than the miR-200a/141 cluster. Furthermore, expression of the miR-200a/141 cluster results in G1 arrest supported by increased p27/Kip1 and decreased cyclin dependent kinase 6 expression. In contrast, expression of the 200bc/429 cluster decreases G1 population and increases G2/M phase, in line with the observed reduction of p27/Kip1 and upregulation of the inhibitory phosphorylation of Cdc25C, respectively. To test the hypothesis that phenotypical differences observed between the two clusters are caused by differential targeting spectrums, we performed genome-wide microarray profiling in combination with gain-of-function studies. This identified phospholipase C gamma 1 (PLCG1), which was downregulated only by the miR-200bc/429 cluster, as a potential candidate contributing to these phenotypical differences. Luciferase reporter assays validated PLCG1 as a direct functional target of miR-200bc/429 cluster, but not of miR-200a/141 cluster. Finally, loss of PLCG1 in part mimicked the effect of miR-200bc/429 overexpression in viability, apoptosis and EGF-driven cell invasion of breast cancer cells. Our results suggest that the miR-200 family has a tumor-suppressor function by negatively regulating EGF-driven cell invasion, viability and cell cycle progression in breast cancer.

Global microRNA level regulation of EGFR-driven cell-cycle protein network in breast cancer

The EGFR‐driven cell‐cycle pathway has been extensively studied due to its pivotal role in breast cancer proliferation and pathogenesis. Although several studies reported regulation of individual pathway components by microRNAs (miRNAs), little is known about how miRNAs coordinate the EGFR protein network on a global miRNA (miRNome) level. Here, we combined a large‐scale miRNA screening approach with a high‐throughput proteomic readout and network‐based data analysis to identify which miRNAs are involved, and to uncover potential regulatory patterns. Our results indicated that the regulation of proteins by miRNAs is dominated by the nucleotide matching mechanism between seed sequences of the miRNAs and 3′‐UTR of target genes. Furthermore, the novel network‐analysis methodology we developed implied the existence of consistent intrinsic regulatory patterns where miRNAs simultaneously co‐regulate several proteins acting in the same functional module. Finally, our approach led us to identify and validate three miRNAs (miR‐124, miR‐147 and miR‐193a‐3p) as novel tumor suppressors that co‐target EGFR‐driven cell‐cycle network proteins and inhibit cell‐cycle progression and proliferation in breast cancer.

TMPRSS2-ERG -specific transcriptional modulation is associated with prostate cancer biomarkers and TGF-β signaling

BackgroundTMPRSS2-ERG gene fusions occur in about 50% of all prostate cancer cases and represent promising markers for molecular subtyping. Although TMPRSS2-ERG fusion seems to be a critical event in prostate cancer, the precise functional role in cancer development and progression is still unclear.MethodsWe studied large-scale gene expression profiles in 47 prostate tumor tissue samples and in 48 normal prostate tissue samples taken from the non-suspect area of clinical low-risk tumors using Affymetrix GeneChip Exon 1.0 ST microarrays.ResultsComparison of gene expression levels among TMPRSS2-ERG fusion-positive and negative tumors as well as benign samples demonstrated a distinct transcriptional program induced by the gene fusion event. Well-known biomarkers for prostate cancer detection like CRISP3 were found to be associated with the gene fusion status. WNT and TGF-β/BMP signaling pathways were significantly associated with genes upregulated in TMPRSS2-ERG fusion-positive tumors.ConclusionsThe TMPRSS2-ERG gene fusion results in the modulation of transcriptional patterns and cellular pathways with potential consequences for prostate cancer progression. Well-known biomarkers for prostate cancer detection were found to be associated with the gene fusion. Our results suggest that the fusion status should be considered in retrospective and future studies to assess biomarkers for prostate cancer detection, progression and targeted therapy.

Infrared-based protein detection arrays for quantitative proteomics

The advancement of efficient technologies to comply with the needs of systems biology and drug discovery has so far not received adequate attention. A substantial bottleneck for the time‐resolved quantitative description of signaling networks is the limited throughput and the inadequate sensitivity of currently established methods. Here, we present an improved protein microarray‐based approach towards the sensitive detection of proteins in the fg‐range which is based on signal detection in the near‐infrared range. The high sensitivity of the assay permits the specific quantification of proteins derived from as little as only 20 000 cells with an error rate of only 5%. The capacity is limited to the analysis of up to 500 different samples per microarray. Protein abundance is determined qualitatively, and quantitatively, if recombinant protein is available. This novel approach was called IPAQ (infrared‐based protein arrays with quantitative readout). IPAQ offers a highly sensitive experimental approach superior to the established standard protein quantification technologies, and is suitable for quantitative proteomics. Employing the IPAQ approach, a detailed analysis of activated signaling networks in biopsy samples and of crosstalk between signaling modules as required in drug discovery strategies can easily be performed.

Realizing the Promise of Reverse Phase Protein Arrays for Clinical, Translational, and Basic Research: A Workshop Report The RPPA (Reverse Phase Protein Array) Society

Reverse phase protein array (RPPA) technology introduced a miniaturized “antigen-down” or “dot-blot” immunoassay suitable for quantifying the relative, semi-quantitative or quantitative (if a well-accepted reference standard exists) abundance of total protein levels and post-translational modifications across a variety of biological samples including cultured cells, tissues, and body fluids. The recent evolution of RPPA combined with more sophisticated sample handling, optical detection, quality control, and better quality affinity reagents provides exquisite sensitivity and high sample throughput at a reasonable cost per sample. This facilitates large-scale multiplex analysis of multiple post-translational markers across samples from in vitro, preclinical, or clinical samples. The technical power of RPPA is stimulating the application and widespread adoption of RPPA methods within academic, clinical, and industrial research laboratories. Advances in RPPA technology now offer scientists the opportunity to quantify protein analytes with high precision, sensitivity, throughput, and robustness. As a result, adopters of RPPA technology have recognized critical success factors for useful and maximum exploitation of RPPA technologies, including the following: preservation and optimization of pre-analytical sample quality, application of validated high-affinity and specific antibody (or other protein affinity) detection reagents, dedicated informatics solutions to ensure accurate and robust quantification of protein analytes, and quality-assured procedures and data analysis workflows compatible with application within regulated clinical environments. In 2011, 2012, and 2013, the first three Global RPPA workshops were held in the United States, Europe, and Japan, respectively. These workshops provided an opportunity for RPPA laboratories, vendors, and users to share and discuss results, the latest technology platforms, best practices, and future challenges and opportunities. The outcomes of the workshops included a number of key opportunities to advance the RPPA field and provide added benefit to existing and future participants in the RPPA research community. The purpose of this report is to share and disseminate, as a community, current knowledge and future directions of the RPPA technology.

Combinatorial RNAi for quantitative protein network analysis

The elucidation of cross-talk events between intersecting signaling pathways is one main challenge in biological research. The complexity of protein networks, composed of different pathways, requires novel strategies and techniques to reveal relevant interrelations. Here, we established a combinatorial RNAi strategy for systematic single, double, and triple knockdown, and we measured the residual mRNAs and proteins quantitatively by quantitative real-time PCR and reverse-phase protein arrays, respectively, as a prerequisite for data analysis. Our results show that the parallel knockdown of at least three different genes is feasible while keeping both untargeted silencing and cytotoxicity low. The technique was validated by investigating the interplay of tyrosine kinase receptor ErbB2 and its downstream targets Akt-1 and MEK1 in cell invasion. This experimental approach combines multiple gene knockdown with a subsequent quantitative validation of reduced protein expression and is a major advancement toward the analysis of signaling pathways in systems biology.

RPPanalyzer: Analysis of reverse-phase protein array data

SUMMARY RPPanalyzer is a statistical tool developed to read reverse-phase protein array data, to perform the basic data analysis and to visualize the resulting biological information. The R-package provides different functions to compare protein expression levels of different samples and to normalize the data. Implemented plotting functions permit a quality control by monitoring data distribution and signal validity. Finally, the data can be visualized in heatmaps, boxplots, time course plots and correlation plots. RPPanalyzer is a flexible tool and tolerates a huge variety of different experimental designs. AVAILABILITY The RPPAanalyzer is open source and freely available as an R-Package on the CRAN platform http://cran.r-project.org/.

Comparison of protein expression profiles between monolayer and spheroid cell culture of HT-29 cells revealed fragmentation of CK18 in three-dimensional cell culture.

The use of three‐dimensional cell culture models, so‐called multicellular tumor spheroids, is a special approach in experimental cancer research, because spheroids are similar to in vivo tumors in structural as well as functional sense. Cells grown in spheroids exhibit alterations of cell cycle regulation, induction of apoptosis and differentiation and can acquire multidrug resistance. In this study we investigated the protein expression in human colorectal cancer cells grown in monolayer and in spheroid cultures using proteomics. Evaluation by computer‐assisted image analysis revealed overexpression of three cytokeratin 18 fragments that were generated in vivo. Cytokeratin 18 has previously been described as a target for caspase‐mediated cleavage during apoptosis and our results indicate that apoptosis may take place in spheroids. Other proteins upregulated in spheroids include calreticulin precursor, a rho GDP dissociation inhibitor variant, several cytokeratins and peroxiredoxin 4. Some of these proteins have already been linked to chemoresistance and apoptotic phenomena.