Extensive rewiring of the EGFR network in colorectal cancer cells expressing transforming levels of KRASG13D

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.This work was supported by European Union FP7 Grant No. 278568 “PRIMES” and Science Foundation Ireland Investigator Program Grant 14/IA/2395 to W.K. B.K. is supported by SmartNanoTox (Grant no. 686098), NanoCommons (Grant no. 731032), O.R. by MSCA-IF-2016 SAMNets (Grant no. 750688). D.M. is supported by Science Foundation Ireland Career Development award 15-CDA-3495. I.J. is supported by the Canada Research Chair Program (CRC #225404), Krembil Foundation, Ontario Research Fund (GL2-01-030 and #34876), Natural Sciences Research Council (NSERC #203475), Canada Foundation for Innovation (CFI #225404, #30865), and IBM. O.S. is supported by ERC investigator Award ColonCan 311301 and CRUK. I.S. is supported by the Canadian Cancer Society Research Institute (#703889), Genome Canada via Ontario Genomics (#9427 & #9428), Ontario Research fund (ORF/ DIG-501411 & RE08-009), Consortium Québécois sur la Découverte du Médicament (CQDM Quantum Leap) & Brain Canada (Quantum Leap), and CQDM Explore and OCE (#23929). T.C. was supported by a Teagasc Walsh Fellowshi

Motor and cognitive performance differences between children with and without developmental coordination disorder (DCD)

The current study adopts the PASS theory of information processing to investigate the probable differences in specific motor and cognitive abilities between children with and without developmental coordination disorder (DCD). Participants were 108 5- and 6-year-old preschoolers (54 children with DCD and 54 children without DCD). The Movement Assessment Battery for Children assessed motor function. Running speed and agility were measured using the Bruininks-Oseretsky Test of Motor Proficiency. Finally, the Planning, Attention and Simultaneous Scales from the Das-Naglieri Cognitive Assessment System evaluated cognitive ability. Children with DCD differed significantly from those without DCD performing at a lower level on all motor and cognitive tasks. A correlation analysis revealed significant relationships between cognitive processes and motor skills. Simultaneous cognitive processing and manual dexterity were significantly correlated for both groups. Furthermore, a significant relationship was revealed between planning cognitive processing and balance for the non-DCD group. Thus, early assessment might identify specific cognitive-motor difficulties. Furthermore, early intervention might prevent some of the developmental comorbidities in the academic and everyday lives of children with movement difficulties. © 2012 Elsevier Ltd

The role of cash flows and accruals in explaining security returns: evidence for the UK

The assessment of earnings usefulness in returns studies has been at the forefront of accounting research since the seminal work of Ball and Brown (1968). Recently, regulatory bodies worldwide have paid increased attention to cash flow reporting. Empirical research provides evidence that earnings information dominates cash flows in market-based accounting research. This study extends the growing empirical literature on the association of earnings and cash flows with security returns. We hypothesize that the association of cash flows with security returns improves (i) the smaller the absolute magnitude of aggregate accruals, (ii) the longer the measurement interval and (iii) the shorter the firm's operating cycle. The dataset consists of all UK firms included in the Global vantage database for the period 1984–1992. This study provides evidence that cash flows play a more important role in the marketplace when the operating cycle, magnitude of accruals and the measurement interval are taken into consideration. Moreover, results indicate that cash flows have more information content than earnings in explaining security returns.

Drug genetic associations with COVID-19 manifestations: a data mining and network biology approach

Available drugs have been used as an urgent attempt through clinical trials to minimize severe cases of hospitalizations with Coronavirus disease (COVID-19), however, there are limited data on common pharmacogenomics affecting concomitant medications response in patients with comorbidities. To identify the genomic determinants that influence COVID-19 susceptibility, we use a computational, statistical, and network biology approach to analyze relationships of ineffective concomitant medication with an adverse effect on patients. We statistically construct a pharmacogenetic/biomarker network with significant drug-gene interactions originating from gene-disease associations. Investigation of the predicted pharmacogenes encompassing the gene-disease-gene pharmacogenomics (PGx) network suggests that these genes could play a significant role in COVID-19 clinical manifestation due to their association with autoimmune, metabolic, neurological, cardiovascular, and degenerative disorders, some of which have been reported to be crucial comorbidities in a COVID-19 patient. © 2022, The Author(s), under exclusive licence to Springer Nature Limited

MAGE: An Open-Source Tool for Meta-Analysis of Gene Expression Studies

MAGE (Meta-Analysis of Gene Expression) is a Python open-source software package designed to perform meta-analysis and functional enrichment analysis of gene expression data. We incorporate standard methods for the meta-analysis of gene expression studies, bootstrap standard errors, corrections for multiple testing, and meta-analysis of multiple outcomes. Importantly, the MAGE toolkit includes additional features for the conversion of probes to gene identifiers, and for conducting functional enrichment analysis, with annotated results, of statistically significant enriched terms in several formats. Along with the tool itself, a web-based infrastructure was also developed to support the features of this package. © 2022 by the authors. Licensee MDPI, Basel, Switzerland