Breaking up is hard to do: RalA, mitochondrial fission and cancer

The small GTPases RalA and RalB are activated downstream of oncogenic Ras. While activation of RalA is critically important for tumor initiation and growth of Ras-driven cancers, the highly similar small GTPase RalB is implicated in cell survival and metastasis. This difference in function between these two related proteins maps to the C-terminus, a 30 amino acid region that regulates subcellular localization and contains several potential phosphorylation sites. Here we discuss our recent evidence that phosphorylation by the mitotic kinase Aurora A promotes RalA relocalization to mitochondrial membranes, where it recruits the effector RalBP1 and the large dynamin-related GTPase Drp1 to promote mitochondrial fission. As upregulation of both RalA and Aurora A have been observed in human tumors, and phosphorylation of RalA at the site targeted by Aurora A promotes tumorigenesis, it is possible that regulation of mitochondrial fission is one mechanism by which RalA promotes cancer

A QTL on chromosome 3q23 influences processing speed in humans

Processing speed is a psychological construct that refers to the speed with which an individual can perform any cognitive operation. Processing speed correlates strongly with general cognitive ability, declines sharply with age, and is impaired across a number of neurological and psychiatric disorders. Thus, identifying genes that influence processing speed will likely improve understanding of the genetics of intelligence, biological aging, and the etiologies of numerous disorders. Previous genetics studies of processing speed have relied on simple phenotypes (e.g., mean reaction time) derived from single tasks. This strategy assumes, erroneously, that processing speed is a unitary construct. In the present study, we aimed to characterize the genetic architecture of processing speed by using a multi-dimensional model applied to a battery of cognitive tasks. Linkage and QTL-specific association analyses were performed on the factors from this model. The randomly ascertained sample comprised 1291 Mexican-American individuals from extended pedigrees. We found that performance on all three distinct processing-speed factors (Psychomotor Speed; Sequencing and Shifting and Verbal Fluency) were moderately and significantly heritable. We identified a genome-wide significant QTL on chromosome 3q23 for Psychomotor Speed (LOD = 4.83). Within this locus, we identified a plausible and interesting candidate gene for Psychomotor Speed (Z = 2.90, p = 1.86×10−03)

Turing instabilities in a mathematical model for signaling networks

GTPase molecules are important regulators in cells that continuously run through an activation/deactivation and membrane-attachment/membrane-detachment cycle. Activated GTPase is able to localize in parts of the membranes and to induce cell polarity. As feedback loops contribute to the GTPase cycle and as the coupling between membrane-bound and cytoplasmic processes introduces different diffusion coefficients a Turing mechanism is a natural candidate for this symmetry breaking. We formulate a mathematical model that couples a reaction-diffusion system in the inner volume to a reaction-diffusion system on the membrane via a flux condition and an attachment/detachment law at the membrane. We present a reduction to a simpler non-local reaction-diffusion model and perform a stability analysis and numerical simulations for this reduction. Our model in principle does support Turing instabilities but only if the lateral diffusion of inactivated GTPase is much faster than the diffusion of activated GTPase.Comment: 23 pages, 5 figures; The final publication is available at http://www.springerlink.com http://dx.doi.org/10.1007/s00285-011-0495-

A framework for Distributional Formal Semantics

Formal semantics and distributional semantics offer complementary strengths in capturing the meaning of natural language. As such, a considerable amount of research has sought to unify them, either by augmenting formal semantic systems with a distributional component, or by defining a formal system on top of distributed representations. Arriving at such a unified framework has, however, proven extremely challenging. One reason for this is that formal and distributional semantics operate on a fundamentally different `representational currency': formal semantics defines meaning in terms of models of the world, whereas distributional semantics defines meaning in terms of linguistic co-occurrence. Here, we pursue an alternative approach by deriving a vector space model that defines meaning in a distributed manner relative to formal models of the world. We will show that the resulting Distributional Formal Semantics offers probabilistic distributed representations that are also inherently compositional, and that naturally capture quantification and entailment. We moreover show that, when used as part of a neural network model, these representations allow for capturing incremental meaning construction and probabilistic inferencing. This framework thus lays the groundwork for an integrated distributional and formal approach to meaning

Binding Properties and Stability of the Ras-Association Domain of Rap1-GTP Interacting Adapter Molecule (RIAM)

The Rap1-GTP interacting adapter protein (RIAM) is an important protein in Rap1-mediated integrin activation. By binding to both Rap1 GTPase and talin, RIAM recruits talin to the cell membrane, thus facilitating talin-dependent integrin activation. In this article, we studied the role of the RIAM Ras-association (RA) and pleckstrin-homology (PH) domains in the interaction with Rap1. We found that the RA domain was sufficient for GTP-dependent interaction with Rap1B, and the addition of the PH domain did not change the binding affinity. We also detected GTP-independent interaction of Rap1B with the N-terminus of RIAM. In addition, we found that the PH domain stabilized the RA domain both in vitro and in cells

Oncogenic K-Ras decouples glucose and glutamine metabolism to support cancer cell growth

A systems approach using 13C metabolic flux analysis (MFA), non-targeted tracer fate detection (NTFD), and transcriptional profiling was applied to investigate the role of oncogenic K-Ras in metabolic transformation.K-Ras transformed cells exhibit an increased glycolytic rate and lower flux through the oxidative tricarboxylic acid (TCA) cycle.K-Ras transformed cells show a relative increase in glutamine anaplerosis and reductive TCA metabolism.Transcriptional changes driven by oncogenic K-Ras suggest control nodes associated with the metabolic reprogramming of cancer cells

Impact of the Specific Mutation in KRAS Codon 12 Mutated Tumors on Treatment Efficacy in Patients with Metastatic Colorectal Cancer Receiving Cetuximab-Based First-Line Therapy: A Pooled Analysis of Three Trials

Purpose: This study investigated the impact of specific mutations in codon 12 of the Kirsten-ras (KRAS) gene on treatment efficacy in patients with metastatic colorectal cancer (mCRC). Patients: Overall, 119 patients bearing a KRAS mutation in codon 12 were evaluated. All patients received cetuximab-based first-line chemotherapy within the Central European Cooperative Oncology Group (CECOG), AIO KRK-0104 or AIO KRK-0306 trials. Results: Patients with KRAS codon 12 mutant mCRC showed a broad range of outcome when treated with cetuximab-based first-line regimens. Patients with tumors bearing a KRAS p.G12D mutation showed a strong trend to a more favorable outcome compared to other mutations (overall survival 23.3 vs. 14-18 months; hazard ratio 0.66, range 0.43-1.03). An interaction model illustrated that KRAS p.G12C was associated with unfavorable outcome when treated with oxaliplatin plus cetuximab. Conclusion: The present analysis suggests that KRAS codon 12 mutation may not represent a homogeneous entity in mCRC when treated with cetuximab-based first-line therapy. Copyright (C) 2012 S. Karger AG, Base

Mathematical modeling of the metastatic process

Mathematical modeling in cancer has been growing in popularity and impact since its inception in 1932. The first theoretical mathematical modeling in cancer research was focused on understanding tumor growth laws and has grown to include the competition between healthy and normal tissue, carcinogenesis, therapy and metastasis. It is the latter topic, metastasis, on which we will focus this short review, specifically discussing various computational and mathematical models of different portions of the metastatic process, including: the emergence of the metastatic phenotype, the timing and size distribution of metastases, the factors that influence the dormancy of micrometastases and patterns of spread from a given primary tumor.Comment: 24 pages, 6 figures, Revie

Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway

This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2009 Orton et al.BACKGROUND: The Epidermal Growth Factor Receptor (EGFR) activated Extracellular-signal Regulated Kinase (ERK) pathway is a critical cell signalling pathway that relays the signal for a cell to proliferate from the plasma membrane to the nucleus. Deregulation of the EGFR/ERK pathway due to alterations affecting the expression or function of a number of pathway components has long been associated with numerous forms of cancer. Under normal conditions, Epidermal Growth Factor (EGF) stimulates a rapid but transient activation of ERK as the signal is rapidly shutdown. Whereas, under cancerous mutation conditions the ERK signal cannot be shutdown and is sustained resulting in the constitutive activation of ERK and continual cell proliferation. In this study, we have used computational modelling techniques to investigate what effects various cancerous alterations have on the signalling flow through the ERK pathway. RESULTS: We have generated a new model of the EGFR activated ERK pathway, which was verified by our own experimental data. We then altered our model to represent various cancerous situations such as Ras, B-Raf and EGFR mutations, as well as EGFR overexpression. Analysis of the models showed that different cancerous situations resulted in different signalling patterns through the ERK pathway, especially when compared to the normal EGF signal pattern. Our model predicts that cancerous EGFR mutation and overexpression signals almost exclusively via the Rap1 pathway, predicting that this pathway is the best target for drugs. Furthermore, our model also highlights the importance of receptor degradation in normal and cancerous EGFR signalling, and suggests that receptor degradation is a key difference between the signalling from the EGF and Nerve Growth Factor (NGF) receptors. CONCLUSION: Our results suggest that different routes to ERK activation are being utilised in different cancerous situations which therefore has interesting implications for drug selection strategies. We also conducted a comparison of the critical differences between signalling from different growth factor receptors (namely EGFR, mutated EGFR, NGF, and Insulin) with our results suggesting the difference between the systems are large scale and can be attributed to the presence/absence of entire pathways rather than subtle difference in individual rate constants between the systems.This work was funded by the Department of Trade and Industry (DTI), under their Bioscience Beacon project programme. AG was funded by an industrial PhD studentship from Scottish Enterprise and Cyclacel