@article {403, title = {A comparison of mechanistic signaling pathway activity analysis methods.}, journal = {Brief Bioinform}, volume = {20}, year = {2019}, month = {2019 Sep 27}, pages = {1655-1668}, abstract = {

Understanding the aspects of cell functionality that account for disease mechanisms or drug modes of action is a main challenge for precision medicine. Classical gene-based approaches ignore the modular nature of most human traits, whereas conventional pathway enrichment approaches produce only illustrative results of limited practical utility. Recently, a family of new methods has emerged that change the focus from the whole pathways to the definition of elementary subpathways within them that have any mechanistic significance and to the study of their activities. Thus, mechanistic pathway activity (MPA) methods constitute a new paradigm that allows recoding poorly informative genomic measurements into cell activity quantitative values and relate them to phenotypes. Here we provide a review on the MPA methods available and explain their contribution to systems medicine approaches for addressing challenges in the diagnostic and treatment of complex diseases.

}, keywords = {Algorithms, Humans, Postmortem Changes, Signal Transduction, Systems biology, Transcriptome}, issn = {1477-4054}, doi = {10.1093/bib/bby040}, author = {Amadoz, Alicia and Hidalgo, Marta R and Cubuk, Cankut and Carbonell-Caballero, Jos{\'e} and Dopazo, Joaquin} } @article {404, title = {Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome.}, journal = {Biol Direct}, volume = {13}, year = {2018}, month = {2018 Aug 22}, pages = {16}, abstract = {

BACKGROUND: Despite the progress in neuroblastoma therapies the mortality of high-risk patients is still high (40-50\%) and the molecular basis of the disease remains poorly known. Recently, a mathematical model was used to demonstrate that the network regulating stress signaling by the c-Jun N-terminal kinase pathway played a crucial role in survival of patients with neuroblastoma irrespective of their MYCN amplification status. This demonstrates the enormous potential of computational models of biological modules for the discovery of underlying molecular mechanisms of diseases.

RESULTS: Since signaling is known to be highly relevant in cancer, we have used a computational model of the whole cell signaling network to understand the molecular determinants of bad prognostic in neuroblastoma. Our model produced a comprehensive view of the molecular mechanisms of neuroblastoma tumorigenesis and progression.

CONCLUSION: We have also shown how the activity of signaling circuits can be considered a reliable model-based prognostic biomarker.

REVIEWERS: This article was reviewed by Tim Beissbarth, Wenzhong Xiao and Joanna Polanska. For the full reviews, please go to the Reviewers{\textquoteright} comments section.

}, keywords = {Computational Biology, Gene Expression Regulation, Neoplastic, Humans, JNK Mitogen-Activated Protein Kinases, Models, Theoretical, Neuroblastoma, Signal Transduction}, issn = {1745-6150}, doi = {10.1186/s13062-018-0219-4}, author = {Hidalgo, Marta R and Amadoz, Alicia and Cubuk, Cankut and Carbonell-Caballero, Jos{\'e} and Dopazo, Joaquin} } @article {434, title = {High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes.}, journal = {Oncotarget}, volume = {8}, year = {2017}, month = {2017 Jan 17}, pages = {5160-5178}, abstract = {

Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is a main challenge for precision medicine. Here we propose a new method that models cell signaling using biological knowledge on signal transduction. The method recodes individual gene expression values (and/or gene mutations) into accurate measurements of changes in the activity of signaling circuits, which ultimately constitute high-throughput estimations of cell functionalities caused by gene activity within the pathway. Moreover, such estimations can be obtained either at cohort-level, in case/control comparisons, or personalized for individual patients. The accuracy of the method is demonstrated in an extensive analysis involving 5640 patients from 12 different cancer types. Circuit activity measurements not only have a high diagnostic value but also can be related to relevant disease outcomes such as survival, and can be used to assess therapeutic interventions.

}, keywords = {Computational Biology, gene expression, Gene Regulatory Networks, Humans, mutation, Neoplasms, Precision Medicine, Sequence Analysis, RNA, Signal Transduction}, issn = {1949-2553}, doi = {10.18632/oncotarget.14107}, author = {Hidalgo, Marta R and Cubuk, Cankut and Amadoz, Alicia and Salavert, Francisco and Carbonell-Caballero, Jos{\'e} and Dopazo, Joaquin} } @article {483, title = {Sequencing and functional analysis of the genome of a nematode egg-parasitic fungus, Pochonia chlamydosporia.}, journal = {Fungal Genet Biol}, volume = {65}, year = {2014}, month = {2014 Apr}, pages = {69-80}, abstract = {

Pochonia chlamydosporia is a worldwide-distributed soil fungus with a great capacity to infect and destroy the eggs and kill females of plant-parasitic nematodes. Additionally, it has the ability to colonize endophytically roots of economically-important crop plants, thereby promoting their growth and eliciting plant defenses. This multitrophic behavior makes P. chlamydosporia a potentially useful tool for sustainable agriculture approaches. We sequenced and assembled \~{}41 Mb of P. chlamydosporia genomic DNA and predicted 12,122 gene models, of which many were homologous to genes of fungal pathogens of invertebrates and fungal plant pathogens. Predicted genes (65\%) were functionally annotated according to Gene Ontology, and 16\% of them found to share homology with genes in the Pathogen Host Interactions (PHI) database. The genome of this fungus is highly enriched in genes encoding hydrolytic enzymes, such as proteases, glycoside hydrolases and carbohydrate esterases. We used RNA-Seq technology in order to identify the genes expressed during endophytic behavior of P. chlamydosporia when colonizing barley roots. Functional annotation of these genes showed that hydrolytic enzymes and transporters are expressed during endophytism. This structural and functional analysis of the P. chlamydosporia genome provides a starting point for understanding the molecular mechanisms involved in the multitrophic lifestyle of this fungus. The genomic information provided here should also prove useful for enhancing the capabilities of this fungus as a biocontrol agent of plant-parasitic nematodes and as a plant growth-promoting organism.

}, keywords = {Animals, Ascomycota, Female, Gene Expression Regulation, Fungal, Gene ontology, Genome, Fungal, Hordeum, Host-Pathogen Interactions, Nematoda, Ovum, Phylogeny, Plant Roots, Sequence Analysis, DNA, Signal Transduction, Transcriptome}, issn = {1096-0937}, doi = {10.1016/j.fgb.2014.02.002}, author = {Larriba, Eduardo and Jaime, Mar{\'\i}a D L A and Carbonell-Caballero, Jos{\'e} and Conesa, Ana and Dopazo, Joaquin and Nislow, Corey and Mart{\'\i}n-Nieto, Jos{\'e} and Lopez-Llorca, Luis Vicente} }