Treatment of BRAF‐mutant melanomas with MAP kinase pathway inhibitors is paradigmatic of the promise of precision cancer therapy but also highlights problems with drug resistance that limit patient benefit. We use live‐cell imaging, single‐cell analysis, and molecular profiling to show that exposure of tumor cells to RAF/MEK inhibitors elicits a heterogeneous response in which some cells die, some arrest, and the remainder adapt to drug. Drug‐adapted cells up‐regulate markers of the neural crest (e.g., NGFR), a melanocyte precursor, and grow slowly. This phenotype is transiently stable, reverting to the drug‐naïve state within 9 days of drug withdrawal. Transcriptional profiling of cell lines and human tumors implicates a c‐Jun/ECM/FAK/Src cascade in de‐differentiation in about one‐third of cell lines studied; drug‐induced changes in c‐Jun and NGFR levels are also observed in xenograft and human tumors. Drugs targeting the c‐Jun/ECM/FAK/Src cascade as well as BET bromodomain inhibitors increase the maximum effect (E max) of RAF/MEK kinase inhibitors by promoting cell killing. Thus, analysis of reversible drug resistance at a single‐cell level identifies signaling pathways and inhibitory drugs missed by assays that focus on cell populations.

Cell surface receptors convert extracellular cues into receptor activation, thereby triggering intracellular signaling networks and controlling cellular decisions. A major unresolved issue is the identification of receptor properties that critically determine processing of ligand-encoded information. We show by mathematical modeling of quantitative data and experimental validation that rapid ligand depletion and replenishment of the cell surface receptor are characteristic features of the erythropoietin (Epo) receptor (EpoR). The amount of Epo-EpoR complexes and EpoR activation integrated over time corresponds linearly to ligand input; this process is carried out over a broad range of ligand concentrations. This relation depends solely on EpoR turnover independent of ligand binding, which suggests an essential role of large intracellular receptor pools. These receptor properties enable the system to cope with basal and acute demand in the hematopoietic system.

Dynamical models of cellular processes promise to yield new insights into the underlying systems and their biological interpretation. The processes are usually nonlinear, high dimensional, and time-resolved experimental data of the processes are sparse. Therefore, parameter estimation faces the challenges of structural and practical nonidentifiability. Nonidentifiability of parameters induces nonobservability of trajectories, reducing the predictive power of the model. We will discuss a generic approach for nonlinear models that allows for identifiability and observability analysis by means of a realistic example from systems biology. The results will be utilized to design new experiments that enhance model predictiveness, illustrating the iterative cycle between modeling and experimentation in systems biology.

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Structural and functional studies recently indicated that the erythropoietin receptor exists as a preassembled homodimer whose activation by ligand binding requires self-interaction of its transmembrane segment. Here, we probed the interface formed by the transmembrane segments by asparagine-scanning mutagenesis in a natural membrane. We show that this interface is based on a leucine zipper-like heptad repeat pattern of amino acids. The strongest impact of asparagine was observed at position 241, suggesting the highest packing density around this position, which is in agreement with results obtained upon mutation to alanine. Interestingly, the same face of the transmembrane helix had previously been shown to enter a heterophilic interaction with the transmembrane segment of gp55-P, a viral membrane protein that leads to ligand-independent receptor activation in infected cells. Further, functional characterization of an erythropoietin receptor mutant with asparagine at position 241 in a hematopoietic cell line showed that this protein could still be activated by erythropoietin yet was not constitutively active. This suggests that forced self-interaction of the transmembrane segments does not suffice to induce signaling of the erythropoietin receptor.

IntroductionPancreatic cancer (PCA) is an aggressive tumor that associates with high mortality rates. Majority of PCA patients are diagnosed usually at late tumor stages when the therapeutic options are limited. MicroRNAs (miRNA) are involved in tumor development and are commonly dysregulated in PCA. As a proof-of-principle study, we aimed to evaluate the potential of fecal miRNAs as biomarkers for pancreatic cancer.Materials and MethodsTotal RNA was extracted from feces using Qiagen's miRNA Mini Kit. For miRNA expression analyses we selected a subset of 7 miRNAs that are frequently dysregulated in PCA (miR-21, -143, -155, -196a, -210, -216a, -375). Subsequently, expression levels of these miRNAs were determined in fecal samples from controls (n = 15), chronic pancreatitis (n = 15) and PCA patients (n = 15) using quantitative TaqMan-PCR assays.ResultsAll selected miRNAs were detectable in fecal samples with high reproducibility. Four of seven miRNAs (miR-216a, -196a, -143 und -155) were detected at lower concentrations in feces of PCA patients when compared to controls (p<0.05). Analysis of fecal miRNA expression in controls and patients with chronic pancreatitis and PCA revealed that the expression of miR-216a, -196a, -143 und -155 were highest in controls and lowest in PCA. The expression of the remaining three miRNAs (miR-21, -210 and -375) remained unchanged among controls and the patients with either chronic pancreatitis or PCA.ConclusionOur data provide novel evidence for the differential expression of miRNAs in feces of patients with PCA. If successfully validated in large-scale prospective studies, the fecal miRNA biomarkers may offer novel tools for PCA screening research.

To elucidate the role of electrical signaling in the phloem of maize the tips of attached leaves were stimulated by chilling and wounding. Two different signals were detected in the phloem at the middle of the leaf using the aphid stylet technique: (1) action potentials (AP) arose in the phloem after chilling; and (2) variation potentials (VPs) were evoked after wounding the leaf tip. Combined electric potential and gas exchange measurements showed that while the wound-induced VP moved rapidly towards the middle of the leaf to induce a reduction in both the net-CO2 uptake rate and the stomatal conductance, there was no response in the gas exchange to the cold-induced AP. To determine if electrical signaling had any impact on assimilate transport the middle of the leaf was exposed to 14CO2. Autoradiography of labeled assimilates provided evidence that phloem and intercellular transport of assimilates from mesophyll to bundle sheath cells was strongly reduced while the cold-induced AP moved through. In contrast, wound-induced VP did not inhibit assimilate translocation but did reduce the amount of the labeled assimilate in phloem and bundle sheath cells. Biochemical analysis revealed that callose content increased significantly in chilled leaves while starch increased in chilled but decreased in wounded leaves. The results led to the conclusion that different stimulation types incite characteristic phloem-transmitted electrical signals, each with a specific influence on gas exchange and assimilate transport.

Complex intracellular signalling networks integrate extracellular signals and convert them into cellular responses. In cancer cells, the tightly regulated and fine-tuned dynamics of information processing in signalling networks is altered, leading to uncontrolled cell proliferation, survival and migration. Systems biology combines mathematical modelling with comprehensive, quantitative, time-resolved data and is most advanced in addressing dynamic properties of intracellular signalling networks. Here, we introduce different modelling approaches and their application to medical systems biology, focusing on the identifiability of parameters in ordinary differential equation models and their importance in network modelling to predict cellular decisions. Two related examples are given, which include processing of ligand-encoded information and dual feedback regulation in erythropoietin (Epo) receptor signalling. Finally, we review the current understanding of how systems biology could foster the development of new treatment strategies in the context of lung cancer and anaemia.