Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling

Cellular signal transduction generally involves cascades of post-translational protein modifications that rapidly catalyze changes in protein-DNA interactions and gene expression. High-throughput measurements are improving our ability to study each of these stages individually, but do not capture the connections between them. Here we present an approach for building a network of physical links among these data that can be used to prioritize targets for pharmacological intervention. Our method recovers the critical missing links between proteomic and transcriptional data by relating changes in chromatin accessibility to changes in expression and then uses these links to connect proteomic and transcriptome data. We applied our approach to integrate epigenomic, phosphoproteomic and transcriptome changes induced by the variant III mutation of the epidermal growth factor receptor (EGFRvIII) in a cell line model of glioblastoma multiforme (GBM). To test the relevance of the network, we used small molecules to target highly connected nodes implicated by the network model that were not detected by the experimental data in isolation and we found that a large fraction of these agents alter cell viability. Among these are two compounds, ICG-001, targeting CREB binding protein (CREBBP), and PKF118–310, targeting β-catenin (CTNNB1), which have not been tested previously for effectiveness against GBM. At the level of transcriptional regulation, we used chromatin immunoprecipitation sequencing (ChIP-Seq) to experimentally determine the genome-wide binding locations of p300, a transcriptional co-regulator highly connected in the network. Analysis of p300 target genes suggested its role in tumorigenesis. We propose that this general method, in which experimental measurements are used as constraints for building regulatory networks from the interactome while taking into account noise and missing data, should be applicable to a wide range of high-throughput datasets.National Science Foundation (U.S.) (DB1-0821391)National Institutes of Health (U.S.) (Grant U54-CA112967)National Institutes of Health (U.S.) (Grant R01-GM089903)National Institutes of Health (U.S.) (P30-ES002109

Operational Research: methods and applications

This is the final version. Available on open access from Taylor & Francis via the DOI in this recordThroughout its history, Operational Research has evolved to include methods, models and algorithms that have been applied to a wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first summarises the up-to-date knowledge and provides an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion and used as a point of reference by a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

Suicide ideators and attempters with schizophrenia--the role of 5-HTTLPR, rs25531, and 5-HTT VNTR Intron 2 variants

AIM: To examine the role of 5-HTTLPR, rs25531 and 5-HTT VNTR Intron 2 variants in subjects with psychotic disorders manifesting suicide ideation and behaviour. ----- METHODS: The study included 519 subsequently hospitalized subjects who were genotyped for 5-HTTLPR, rs25531 and 5-HTT VNTR In2 variants. Clinical assessments included structured psychiatric interview, sociodemographic characteristics, suicide ideation and behaviour (SIBQ), severity of psychopathology (PANSS) and depression (CDSS). ----- RESULTS: Three subgroups were identified: suicide attempters (N = 161), suicide ideators (N = 174) and subjects who never reported suicide ideation or behaviour (comparative group, N = 184). Major findings: 1) Suicide attempters scored highest on the CDSS, while no differences between the three clinical subgroups were detected in the PANSS scores; 2) Suicide attempters were more frequently the carriers of L(A) allele, while subjects in the comparative group were more frequently the carriers of low expression 5-HTTLPR/5-HTT rs25531 haplotype SL(G); 3) No difference was found between the three clinical groups in the 5-HTT VNTR In2 variants; 4) Subjects with 5-HTTLPR/5-HTT rs25531 intermediate expression haplotype (L(A)L(G,)SL(A)) scored higher on the PANSS general psychopathology subscale; 5) There was no association between suicide attempt or ideation and 5-HTTLPR/In2 or 5-HTTLPR/rs25531/In2 haplotype distribution. ----- CONCLUSION: The suicide ideators, attempters and controls did not differ significantly in 5-HTTLPR or 5-HTT VNTR In 2 variants, but 5-HTTLPR/5-HTT rs25531 haplotype might be a useful genetic marker in distinguishing these three clinical groups

A Memetic Algorithm for Vertex-Biconnectivity Augmentation

This paper considers the problem of augmenting a given graph by a cheapest possible set of additional edges in order to make the graph vertex-biconnected. A real-world instance of this problem is the enhancement of an already established computer network to become robust against single node failures. The presented memetic algorithm includes an effective preprocessing of problem data and a fast local improvement strategy which is applied during initialization, mutation, and recombination. Only feasible, locally optimal solutions are created as candidates. Empirica

Decomposition methods for the two-stage stochastic Steiner tree problem

International audienceA new algorithmic approach for solving the stochastic Steiner tree problem based on three procedures for computing lower bounds (dual ascent, Lagrangian relaxation, Benders decomposition) is introduced. Our method is derived from a new integer linear programming formulation, which is shown to be strongest among all known formulations. The resulting method, which relies on an interplay of the dual information retrieved from the respective dual procedures, computes upper and lower bounds and combines them with several rules for fixing variables in order to decrease the size of problem instances. The effectiveness of our method is compared in an extensive computational study with the state-of-the-art exact approach, which employs a Benders decomposition based on two-stage branch-and-cut, and a genetic algorithm introduced during the DIMACS implementation challenge on Steiner trees. Our results indicate that the presented method significantly outperforms existing ones, both on benchmark instances from literature, as well as on large-scale telecommunication networks

Location Problems in Telecommunications

Language of publication: enInternational audienceno abstrac