Now showing 1 - 7 of 7
  • Publication
    Extensive rewiring of the EGFR network in colorectal cancer cells expressing transforming levels of KRAS G13D
    Protein-protein-interaction networks (PPINs) organize fundamental biological processes, but how oncogenic mutations impact these interactions and their functions at a network-level scale is poorly understood. Here, we analyze how a common oncogenic KRAS mutation (KRASG13D) affects PPIN structure and function of the Epidermal Growth Factor Receptor (EGFR) network in colorectal cancer (CRC) cells. Mapping >6000 PPIs shows that this network is extensively rewired in cells expressing transforming levels of KRASG13D (mtKRAS). The factors driving PPIN rewiring are multifactorial including changes in protein expression and phosphorylation. Mathematical modelling also suggests that the binding dynamics of low and high affinity KRAS interactors contribute to rewiring. PPIN rewiring substantially alters the composition of protein complexes, signal flow, transcriptional regulation, and cellular phenotype. These changes are validated by targeted and global experimental analysis. Importantly, genetic alterations in the most extensively rewired PPIN nodes occur frequently in CRC and are prognostic of poor patient outcomes.
  • Publication
    The Ins and Outs of RAS Effector Complexes
    RAS oncogenes are among the most commonly mutated proteins in human cancers. They regulate a wide range of effector pathways that control cell proliferation, survival, differentiation, migration and metabolic status. Including aberrations in these pathways, RAS-dependent signaling is altered in more than half of human cancers. Targeting mutant RAS proteins and their downstream oncogenic signaling pathways has been elusive. However, recent results comprising detailed molecular studies, large scale omics studies and computational modeling have painted a new and more comprehensive portrait of RAS signaling that helps us to understand the intricacies of RAS, how its physiological and pathophysiological functions are regulated, and how we can target them. Here, we review these efforts particularly trying to relate the detailed mechanistic studies with global functional studies. We highlight the importance of computational modeling and data integration to derive an actionable understanding of RAS signaling that will allow us to design new mechanism-based therapies for RAS mutated cancers.
    Scopus© Citations 31  42
  • Publication
    Analysis of Ras-effector interaction competition in large intestine and colorectal cancer context
    Cancer is the second leading cause of death globally, and colorectal cancer (CRC) is among the five most common cancers. The small GTPase KRAS is an oncogene that is mutated in ~30% of all CRCs. Pharmacological treatments of CRC are currently unsatisfactory, but much hope rests on network-centric approaches to drug development and cancer treatment. These approaches, however, require a better understanding of how networks downstream of Ras oncoproteins are connected in a particular tissue context–here colon and CRC. Previously we have shown that competition for binding to a ‘hub’ protein, such as Ras, can induce a rewiring of signal transduction networks. In this study, we analysed 56 established and predicted effectors that contain a structural domain with the potential ability to bind to Ras oncoproteins and their link to pathways coordinating intestinal homoeostasis and barrier function. Using protein concentrations in colon tissue and Ras-effector binding affinities, a computational network model was generated that predicted how effectors differentially and competitively bind to Ras in colon context. The model also predicted both qualitative and quantitative changes in Ras-effector complex formations with increased levels of active Ras–to simulate its upregulation in cancer–simply as an emergent property of competition for the same binding interface on the surface of Ras. We also considered how the number of Ras-effector complexes at the membrane can be increased by additional domains present in some effectors that are recruited to the membrane in response to specific conditions (inputs/stimuli/growth factors) in colon context and CRC.
      240Scopus© Citations 12
  • Publication
    Simple and complex retinal dystrophies are associated with profoundly different disease networks
    Retinopathies are a group of monogenetic or complex retinal diseases associated with high unmet medical need. Monogenic disorders are caused by rare genetic variation and usually arise early in life. Other diseases, such as age-related macular degeneration (AMD), develop late in life and are considered to be of complex origin as they develop from a combination of genetic, ageing, environmental and lifestyle risk factors. Here, we contrast the underlying disease networks and pathological mechanisms of monogenic as opposed to complex retinopathies, using AMD as an example of the latter. We show that, surprisingly, genes associated with the different forms of retinopathies in general do not overlap despite their overlapping retinal phenotypes. Further, AMD risk genes participate in multiple networks with interaction partners that link to different ubiquitous pathways affecting general tissue integrity and homeostasis. Thus AMD most likely represents an endophenotype with differing underlying pathogenesis in different subjects. Localising these pathomechanisms and processes within and across different retinal anatomical compartments provides a novel representation of AMD that may be extended to complex disease in general. This approach may generate improved treatment options that target multiple processes with the aim of restoring tissue homeostasis and maintaining vision.
      130Scopus© Citations 11
  • Publication
    Repository of proposed pathways and protein–protein interaction networks in age-related macular degeneration
    Age-related macular degeneration (AMD) is one of the commonest causes of sight loss in the elderly population and to date there is no intervention that slows or prevents early AMD disease progressing to blinding neovascularization or geographic atrophy. AMD is a complex disease and factors proposed to contribute to the development and progression of disease include aging, genetics, epigenetics, oxidative stress, pro-inflammatory state, and life-style factors such as smoking, alcohol, and high fat diet. Here, we generate a knowledge repository of pathways and protein–protein interaction (PPI) networks likely to be implicated in AMD pathogenesis, such as complement activation, lipid trafficking and metabolism, vitamin A cycle, oxidative stress, proteostasis, bioenergetics, autophagy/mitophagy, extracellular matrix (ECM) turnover, and choroidal vascular dropout. Two disctinct clusters ermerged from the networks for parainflamation and ECM homeostasis, which may represent two different disease modules underlying AMD pathology. Our analyses also suggest that the disease manifests primarily in RPE/choroid and less in neural retina. The use of standardized syntax when generating maps of these biological processes (SBGN standard) and networks (PSI standard) enables visualization of complex information in graphical programs such as CellDesigner and Cytoscape and enhances reusability and extension of data. The ability to focus onto subnetworks, multiple visualizations and simulation options will enable the AMD research community to computationally model subnetworks or to test experimentally new hypotheses arising from connectivities in the AMD pathway map.
    Scopus© Citations 23  295
  • Publication
    VarQ: A Tool for the Structural and Functional Analysis of Human Protein Variants
    Understanding the functional effect of Single Amino acid Substitutions (SAS), derived from the occurrence of single nucleotide variants (SNVs), and their relation to disease development is a major issue in clinical genomics. Despite the existence of several bioinformatic algorithms and servers that predict if a SAS is pathogenic or not, they give little or no information at all on the reasons for pathogenicity prediction and on the actual predicted effect of the SAS on the protein function. Moreover, few actual methods take into account structural information when available for automated analysis. Moreover, many of these algorithms are able to predict an effect that no necessarily translates directly into pathogenicity. VarQ is a bioinformatic pipeline that incorporates structural information for the detailed analysis and prediction of SAS effect on protein function. It is an online tool which uses UniProt id and automatically analyzes known and user provided SAS for their effect on protein activity, folding, aggregation and protein interactions, among others. We show that structural information, when available, can improve the SAS pathogenicity diagnosis and more important explain its causes. We show that VarQ is able to correctly reproduce previous analysis of RASopathies related mutations, saving extensive and time consuming manual curation. VarQ assessment was performed over a set of previously manually curated RASopathies (diseases that affects the RAS/MAPK signaling pathway) related variants, showing its ability to correctly predict the phenotypic outcome and its underlying cause. This resource is available online at Supporting Information & Tutorials may be found in the webpage of the tool.
      245Scopus© Citations 10
  • Publication
    Systems level expression correlation of Ras GTPase regulators
    Background: Proteins of the ubiquitously expressed core proteome are quantitatively correlated across multiple eukaryotic species. In addition, it was found that many protein paralogues exhibit expression anticorrelation, suggesting that the total level of protein with a given functionality must be kept constant. Methods: We performed Spearman's rank correlation analyses of gene expression levels for the RAS GTPase subfamily and their regulatory GEF and GAP proteins across tissues and across individuals for each tissue. A large set of published data for normal tissues from a wide range of species, human cancer tissues and human cell lines was analysed. Results: We show that although the multidomain regulatory proteins of Ras GTPases exhibit considerable tissue and individual gene expression variability, their total amounts are balanced in normal tissues. In a given tissue, the sum of activating (GEFs) and deactivating (GAPs) domains of Ras GTPases can vary considerably, but each person has balanced GEF and GAP levels. This balance is impaired in cell lines and in cancer tissues for some individuals. Conclusions: Our results are relevant for critical considerations of knock out experiments, where functionally related homologs may compensate for the down regulation of a protein.
      242Scopus© Citations 3