Thesis

ERK signal duration decoding by mRNA dynamics

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Abstract

Der RAF-MEK-ERK-Signalweg steuert grundlegende, oftmals entgegengesetzte zelluläre Prozesse wie die Proliferation und Apoptose von Zellen. Die Dauer des vermittelten Signals wurde als entscheidener Faktor für die Steuerung dieser Prozesse identifiziert. Es ist jedoch nicht eindeutig geklärt, wie die verschiedenen früh und spät reagierenden Genexpressionsmodule kurze und lange Signale unterscheiden können und durch welche kinetischen Merkmale ihre Antwortzeit bestimmt wird. In der vorliegenden Arbeit wurden sowohl Proteinphosphorylierungsdaten als auch Genexpressionsdaten aus HEK293-Zellen gewonnen, die ein induzierbares Konstrukt des Proto-Onkogens RAF tragen. Hierbei wurde ein neues Genexpressionsmodul identifiziert, dass sich aus sofort induzierten aber spät antwortenden Genen zusammensetzt. Es unterscheidet sich in der Genexpressionsdynamik und Genfunktion von anderen Modulen, und wurde mit Hilfe mathematischer Modellierung experimenteller Daten identifiziert. Es wurde festgestellt, dass diese Gene aufgrund von langen Halbwertszeiten der vermitteltenden mRNA in der Lage sind spät auf das eingehende Signal zu reagieren und die Dauer des Signals in die Amplitude der Genantwort zu übersetzen. Trotz der langsamen Akkumulation und damit späten Antwortzeit, konnte aufgrund einer GC-reichen Promoterstruktur zunächst vermutet und mit Hilfe eines Markerverfahrens bestätigt werden, dass die Transkription dieser Gene instantan mit Beginn der ERK-Aktivierung startet. Eine vergleichende Analyse zeigte, dass das Prinzip der Signaldauer-Entschlüsselung in PC12-Zellen und MCF7-Zellen, zwei paradigmatischen Zellsystemen für die ERK-Signaldauer, konserviert ist. Insgesamt deuten die Ergebnisse der Untersuchung darauf hin, dass das neu identifizierte Genexpressionsmodul der Entschlüsselung der ERK-Signaldauer dient und das mRNA Halbwertszeiten sowohl hierfür, als auch für die zeitliche Abfolge der Genantwort eine entscheidende Rolle spielen.

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In the early 1900s, numerous seminal publications reported that high rates of cancer occurred in certain occupations. During this period, work with infectious agents produced only meager results which seemed irrelevant to humans. Then in the 1980s ground breaking evidence began to emerge that a variety of viruses also cause cancer in humans. There is now sufficient evidence of carcinogenicity in humans for human T-cell lymphotrophic virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, human papillomavirus, Epstein-Barr virus, and human herpes virus 8 according to the International Agency for Research on Cancer (IARC). Many other causes of cancer have also been identified by the IARC, which include: Sunlight, tobacco, pharmaceuticals, hormones, alcohol, parasites, fungi, bacteria, salted fish, wood dust, and herbs. The World Cancer Research Fund and the American Institute for Cancer Research have determined additional causes of cancer, which include beta carotene, red meat, processed meats, low fibre diets, not breast feeding, obesity, increased adult height and sedentary lifestyles. In brief, a historical review of the discoveries of the causes of human cancer is presented with extended discussions of the difficulties encountered in identifying viral causes of cancer.
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It is believed that KRAS oncoproteins are constitutively active because their GTPase activity is disabled. With this in mind, drugs targeting the inactive or GDP-bound conformation are not expected to be effective. We now describe a mechanism that enables such drugs to inhibit KRASG12C-signaling and cancer cell growth. Inhibition requires intact GTPase activity and occurs because drug-bound KRASG12C is insusceptible to nucleotide exchange factors and thus trapped in its inactive state. Indeed, mutants completely lacking GTPase activity and those promoting exchange reduced the potency of the drug. Suppressing nucleotide exchange activity downstream of various tyrosine-kinases enhanced KRASG12C inhibition, whereas its potentiation had the opposite effect. These findings reveal that KRASG12C undergoes nucleotide cycling in cancer cells and provide a basis for developing effective therapies to treat KRASG12C-driven cancers.
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A central question in biology is whether variability between genetically identical cells exposed to the same culture conditions is largely stochastic or deterministic. Using image-based transcriptomics in millions of single human cells, we find that while variability of cytoplasmic transcript abundance is large, it is for most genes minimally stochastic and can be predicted with multivariate models of the phenotypic state and population context of single cells. Computational multiplexing of these predictive signatures across hundreds of genes revealed a complex regulatory system that controls the observed variability of transcript abundance between individual cells. Mathematical modeling and experimental validation show that nuclear retention and transport of transcripts between the nucleus and the cytoplasm is central to buffering stochastic transcriptional fluctuations in mammalian gene expression. Our work indicates that cellular compartmentalization confines transcriptional noise to the nucleus, thereby preventing it from interfering with the control of single-cell transcript abundance in the cytoplasm.
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A recent report that 93 per cent of invasive cervical cancers worldwide contain human papillomavirus (HPV) may be an underestimate, due to sample inadequacy or integration events affecting the HPV L1 gene, which is the target of the polymerase chain reaction (PCR)-based test which was used. The formerly HPV-negative cases from this study have therefore been reanalysed for HPV serum antibodies and HPV DNA. Serology for HPV 16 VLPs, E6, and E7 antibodies was performed on 49 of the 66 cases which were HPV-negative and a sample of 48 of the 866 cases which were HPV-positive in the original study. Moreover, 55 of the 66 formerly HPV-negative biopsies were also reanalysed by a sandwich procedure in which the outer sections in a series of sections are used for histological review, while the inner sections are assayed by three different HPV PCR assays targeting different open reading frames (ORFs). No significant difference was found in serology for HPV 16 proteins between the cases that were originally HPV PCR-negative and -positive. Type-specific E7 PCR for 14 high-risk HPV types detected HPV DNA in 38 (69 per cent) of the 55 originally HPV-negative and amplifiable specimens. The HPV types detected were 16, 18, 31, 33, 39, 45, 52, and 58. Two (4 per cent) additional cases were only HPV DNA-positive by E1 and/or L1 consensus PCR. Histological analysis of the 55 specimens revealed that 21 were qualitatively inadequate. Only two of the 34 adequate samples were HPV-negative on all PCR tests, as against 13 of the 21 that were inadequate ( p< 0·001). Combining the data from this and the previous study and excluding inadequate specimens, the worldwide HPV prevalence in cervical carcinomas is 99·7 per cent. The presence of HPV in virtually all cervical cancers implies the highest worldwide attributable fraction so far reported for a specific cause of any major human cancer. The extreme rarity of HPV-negative cancers reinforces the rationale for HPV testing in addition to, or even instead of, cervical cytology in routine cervical screening. Copyright
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Transcription factors (TFs) are commonly deregulated in the pathogenesis of human cancer and are a major class of cancer cell dependencies. Consequently, targeting of TFs can be highly effective in treating particular malignancies, as highlighted by the clinical efficacy of agents that target nuclear hormone receptors. In this review we discuss recent advances in our understanding of TFs as drug targets in oncology, with an emphasis on the emerging chemical approaches to modulate TF function. The remarkable diversity and potency of TFs as drivers of cell transformation justifies a continued pursuit of TFs as therapeutic targets for drug discovery.
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The epidermal growth factor receptor (EGFR) signaling pathway is one of the most important pathways that regulate growth, survival, proliferation, and differentiation in mammalian cells. Reflecting this importance, it is one of the best-investigated signaling systems, both experimentally and computationally, and several computational models have been developed for dynamic analysis. A map of molecular interactions of the EGFR signaling system is a valuable resource for research in this area. In this paper, we present a comprehensive pathway map of EGFR signaling and other related pathways. The map reveals that the overall architecture of the pathway is a bow-tie (or hourglass) structure with several feedback loops. The map is created using CellDesigner software that enables us to graphically represent interactions using a well-defined and consistent graphical notation, and to store it in Systems Biology Markup Language (SBML).
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Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data.Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).Contact: mrobinson@wehi.edu.au
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The events associated with recombination between loxP, a site in P1 EcoRI fragment 7, and loxB, a site in the bacterial chromosome, are described. When fragment 7 is in a α vector, the product of loxP × loxB recombination is the integration of the λ-P1: 7(loxP) DNA as prophage in the bacterial chromosome and the production of two new hybrid sites, loxR and loxL, flanking the prophage. Lambda phages containing loxL, loxR and loxB sites have been isolated and used to measure recombination frequencies between all four lox sites in paired phage crosses. Two principles emerge from these crosses: (1) loxP and loxL sites are much better substrates for recombination than are loxR and loxB sites. (2) Both partners in a recombination reaction must contain either loxP or loxL sites for recombination to be efficient. These results can explain all of our findings relating to the recombination between α-P1: 7 DNA and the bacterial chromosome. In particular, integration of that DNA into loxB is low because loxP × loxB recombination is inefficient, and excision of the resulting prophage DNA is low because loxL × loxR recombination is inefficient. In contrast, integration of λ-P1: 7 DNA into a chromosome already containing a λ-P1: 7 prophage at loxB is relatively high and is always accompanied by the excision and subsequent loss of the original prophage DNA. We call this process integration by prophage displacement, and we can account for it by postulating that two lox recombination events are involved (loxP × loxR and loxP × loxL), both of which are more efficient than is loxP × loxB recombination. Analysis of the physical structure of the various λlox phages indicates that loxP-containing DNA can integrate into loxB in both possible orientations, and that the loxP × loxB crossover point is located within a 100 base-pair region of P1 BamHI fragment 9, a subfragment of EcoRI fragment 7. The loxB site has been mapped to a region of the Escherichia coli chromosome between tolC (66 min) and dnaG (67 min).
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c-Raf-1 is a major effector of Ras proteins, responsible for activation of the ERK MAP kinase pathway and a critical regulator of both normal growth and oncogenic transformation. Using an inducible form of Raf in MDCK cells, we have shown that sustained activation of Raf alone is able to induce the transition from an epithelial to a mesenchymal phenotype. Raf promoted invasive growth in collagen gels, a characteristic of malignant cells; this was dependent on the operation of an autocrine loop involving TGFβ, whose secretion was induced by Raf. TGFβ induced growth inhibition and apoptosis in normal MDCK cells: Activation of Raf led to inhibition of the ability of TGFβ to induce apoptosis but not growth retardation. ERK has been reported previously to inhibit TGFβ signaling via phosphorylation of the linker region of Smads, which prevents their translocation to the nucleus. However, we found no evidence in this system that ERK can significantly influence the function of Smad2, Smad3, and Smad4 at the level of nuclear translocation, DNA binding, or transcriptional activation. Instead, strong activation of Raf caused a broad protection of these cells from various apoptotic stimuli, allowing them to respond to TGFβ with increased invasiveness while avoiding cell death. The Raf–MAP kinase pathway thus synergizes with TGFβ in promoting malignancy but does not directly impair TGFβ-induced Smad signaling. Keywords • Ras • Raf • TGFβ • SMAD • apoptosis
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RAF family kinases were among the first oncoproteins to be described more than 30 years ago. They primarily act as signalling relays downstream of RAS, and their close ties to cancer have fuelled a large number of studies. However, we still lack a systems-level understanding of their regulation and mode of action. The recent discovery that the catalytic activity of RAF depends on an allosteric mechanism driven by kinase domain dimerization is providing a vital new piece of information towards a comprehensive model of RAF function. The fact that current RAF inhibitors unexpectedly induce ERK signalling by stimulating RAF dimerization also calls for a deeper structural characterization of this family of kinases.
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Background: The BRAF inhibitors vemurafenib and dabrafenib have shown efficacy as monotherapies in patients with previously untreated metastatic melanoma with BRAF V600E or V600K mutations. Combining dabrafenib and the MEK inhibitor trametinib, as compared with dabrafenib alone, enhanced antitumor activity in this population of patients. Methods: In this open-label, phase 3 trial, we randomly assigned 704 patients with metastatic melanoma with a BRAF V600 mutation to receive either a combination of dabrafenib (150 mg twice daily) and trametinib (2 mg once daily) or vemurafenib (960 mg twice daily) orally as first-line therapy. The primary end point was overall survival. Results: At the preplanned interim overall survival analysis, which was performed after 77% of the total number of expected events occurred, the overall survival rate at 12 months was 72% (95% confidence interval [CI], 67 to 77) in the combination-therapy group and 65% (95% CI, 59 to 70) in the vemurafenib group (hazard ratio for death in the combination-therapy group, 0.69; 95% CI, 0.53 to 0.89; P=0.005). The prespecified interim stopping boundary was crossed, and the study was stopped for efficacy in July 2014. Median progression-free survival was 11.4 months in the combination-therapy group and 7.3 months in the vemurafenib group (hazard ratio, 0.56; 95% CI, 0.46 to 0.69; P<0.001). The objective response rate was 64% in the combination-therapy group and 51% in the vemurafenib group (P<0.001). Rates of severe adverse events and study-drug discontinuations were similar in the two groups. Cutaneous squamous-cell carcinoma and keratoacanthoma occurred in 1% of patients in the combination-therapy group and 18% of those in the vemurafenib group. Conclusions: Dabrafenib plus trametinib, as compared with vemurafenib monotherapy, significantly improved overall survival in previously untreated patients with metastatic melanoma with BRAF V600E or V600K mutations, without increased overall toxicity. (Funded by GlaxoSmithKline; ClinicalTrials.gov number, NCT01597908.).