@article {407, title = {The modular network structure of the mutational landscape of Acute Myeloid Leukemia.}, journal = {PLoS One}, volume = {13}, year = {2018}, month = {2018}, pages = {e0202926}, abstract = {

Acute myeloid leukemia (AML) is associated with the sequential accumulation of acquired genetic alterations. Although at diagnosis cytogenetic alterations are frequent in AML, roughly 50\% of patients present an apparently normal karyotype (NK), leading to a highly heterogeneous prognosis. Due to this significant heterogeneity, it has been suggested that different molecular mechanisms may trigger the disease with diverse prognostic implications. We performed whole-exome sequencing (WES) of tumor-normal matched samples of de novo AML-NK patients lacking mutations in NPM1, CEBPA or FLT3-ITD to identify new gene mutations with potential prognostic and therapeutic relevance to patients with AML. Novel candidate-genes, together with others previously described, were targeted resequenced in an independent cohort of 100 de novo AML patients classified in the cytogenetic intermediate-risk (IR) category. A mean of 4.89 mutations per sample were detected in 73 genes, 35 of which were mutated in more than one patient. After a network enrichment analysis, we defined a single in silico model and established a set of seed-genes that may trigger leukemogenesis in patients with normal karyotype. The high heterogeneity of gene mutations observed in AML patients suggested that a specific alteration could not be as essential as the interaction of deregulated pathways.

}, keywords = {Adult, Aged, Cytodiagnosis, Female, Gene Regulatory Networks, Genetic Association Studies, Genetic Heterogeneity, Humans, Karyotype, Leukemia, Myeloid, Acute, Male, Middle Aged, mutation, Neoplasm Proteins, Nucleophosmin, Prognosis, whole exome sequencing}, issn = {1932-6203}, doi = {10.1371/journal.pone.0202926}, author = {Ib{\'a}{\~n}ez, Mariam and Carbonell-Caballero, Jos{\'e} and Such, Esperanza and Garc{\'\i}a-Alonso, Luz and Liquori, Alessandro and L{\'o}pez-Pav{\'\i}a, Mar{\'\i}a and LLop, Marta and Alonso, Carmen and Barrag{\'a}n, Eva and G{\'o}mez-Segu{\'\i}, In{\'e}s and Neef, Alexander and Herv{\'a}s, David and Montesinos, Pau and Sanz, Guillermo and Sanz, Miguel Angel and Dopazo, Joaquin and Cervera, Jos{\'e}} } @article {453, title = {The Mutational Landscape of Acute Promyelocytic Leukemia Reveals an Interacting Network of Co-Occurrences and Recurrent Mutations.}, journal = {PLoS One}, volume = {11}, year = {2016}, month = {2016}, pages = {e0148346}, abstract = {

Preliminary Acute Promyelocytic Leukemia (APL) whole exome sequencing (WES) studies have identified a huge number of somatic mutations affecting more than a hundred different genes mainly in a non-recurrent manner, suggesting that APL is a heterogeneous disease with secondary relevant changes not yet defined. To extend our knowledge of subtle genetic alterations involved in APL that might cooperate with PML/RARA in the leukemogenic process, we performed a comprehensive analysis of somatic mutations in APL combining WES with sequencing of a custom panel of targeted genes by next-generation sequencing. To select a reduced subset of high confidence candidate driver genes, further in silico analysis were carried out. After prioritization and network analysis we found recurrent deleterious mutations in 8 individual genes (STAG2, U2AF1, SMC1A, USP9X, IKZF1, LYN, MYCBP2 and PTPN11) with a strong potential of being involved in APL pathogenesis. Our network analysis of multiple mutations provides a reliable approach to prioritize genes for additional analysis, improving our knowledge of the leukemogenesis interactome. Additionally, we have defined a functional module in the interactome of APL. The hypothesis is that the number, or the specific combinations, of mutations harbored in each patient might not be as important as the disturbance caused in biological key functions, triggered by several not necessarily recurrent mutations.

}, keywords = {Exome, Gene Regulatory Networks, Genome, Human, Humans, INDEL Mutation, Leukemia, Promyelocytic, Acute, mutation, Mutation Rate, Polymorphism, Single Nucleotide, Reproducibility of Results}, issn = {1932-6203}, doi = {10.1371/journal.pone.0148346}, author = {Ib{\'a}{\~n}ez, Mariam and Carbonell-Caballero, Jos{\'e} and Garc{\'\i}a-Alonso, Luz and Such, Esperanza and Jim{\'e}nez-Almaz{\'a}n, Jorge and Vidal, Enrique and Barrag{\'a}n, Eva and L{\'o}pez-Pav{\'\i}a, Mar{\'\i}a and LLop, Marta and Mart{\'\i}n, Iv{\'a}n and G{\'o}mez-Segu{\'\i}, In{\'e}s and Montesinos, Pau and Sanz, Miguel A and Dopazo, Joaquin and Cervera, Jos{\'e}} } @article {460, title = {A Pan-Cancer Catalogue of Cancer Driver Protein Interaction Interfaces.}, journal = {PLoS Comput Biol}, volume = {11}, year = {2015}, month = {2015 Oct}, pages = {e1004518}, abstract = {

Despite their importance in maintaining the integrity of all cellular pathways, the role of mutations on protein-protein interaction (PPI) interfaces as cancer drivers has not been systematically studied. Here we analyzed the mutation patterns of the PPI interfaces from 10,028 proteins in a pan-cancer cohort of 5,989 tumors from 23 projects of The Cancer Genome Atlas (TCGA) to find interfaces enriched in somatic missense mutations. To that end we use e-Driver, an algorithm to analyze the mutation distribution of specific protein functional regions. We identified 103 PPI interfaces enriched in somatic cancer mutations. 32 of these interfaces are found in proteins coded by known cancer driver genes. The remaining 71 interfaces are found in proteins that have not been previously identified as cancer drivers even that, in most cases, there is an extensive literature suggesting they play an important role in cancer. Finally, we integrate these findings with clinical information to show how tumors apparently driven by the same gene have different behaviors, including patient outcomes, depending on which specific interfaces are mutated.

}, keywords = {Animals, Base Sequence, Biomarkers, Tumor, Catalogs as Topic, Chromosome Mapping, Computer Simulation, DNA Mutational Analysis, Genetic Predisposition to Disease, Humans, Models, Genetic, Molecular Sequence Data, mutation, Neoplasm Proteins, Neoplasms, Polymorphism, Single Nucleotide, Protein Interaction Mapping, Signal Transduction}, issn = {1553-7358}, doi = {10.1371/journal.pcbi.1004518}, author = {Porta-Pardo, Eduard and Garc{\'\i}a-Alonso, Luz and Hrabe, Thomas and Dopazo, Joaquin and Godzik, Adam} } @article {494, title = {The role of the interactome in the maintenance of deleterious variability in human populations.}, journal = {Mol Syst Biol}, volume = {10}, year = {2014}, month = {2014 Sep 26}, pages = {752}, abstract = {

Recent genomic projects have revealed the existence of an unexpectedly large amount of deleterious variability in the human genome. Several hypotheses have been proposed to explain such an apparently high mutational load. However, the mechanisms by which deleterious mutations in some genes cause a pathological effect but are apparently innocuous in other genes remain largely unknown. This study searched for deleterious variants in the 1,000 genomes populations, as well as in a newly sequenced population of 252 healthy Spanish individuals. In addition, variants causative of monogenic diseases and somatic variants from 41 chronic lymphocytic leukaemia patients were analysed. The deleterious variants found were analysed in the context of the interactome to understand the role of network topology in the maintenance of the observed mutational load. Our results suggest that one of the mechanisms whereby the effect of these deleterious variants on the phenotype is suppressed could be related to the configuration of the protein interaction network. Most of the deleterious variants observed in healthy individuals are concentrated in peripheral regions of the interactome, in combinations that preserve their connectivity, and have a marginal effect on interactome integrity. On the contrary, likely pathogenic cancer somatic deleterious variants tend to occur in internal regions of the interactome, often with associated structural consequences. Finally, variants causative of monogenic diseases seem to occupy an intermediate position. Our observations suggest that the real pathological potential of a variant might be more a systems property rather than an intrinsic property of individual proteins.

}, keywords = {Alleles, Exome, Gene Library, Genetic Variation, Genetics, Population, Genome, Human, Genomics, Humans, Models, Genetic, mutation, Phenotype, Protein Conformation, Protein Interaction Maps, Sequence Analysis, DNA, Whites}, issn = {1744-4292}, doi = {10.15252/msb.20145222}, author = {Garc{\'\i}a-Alonso, Luz and Jim{\'e}nez-Almaz{\'a}n, Jorge and Carbonell-Caballero, Jos{\'e} and Vela-Boza, Alicia and Santoyo-L{\'o}pez, Javier and Anti{\v n}olo, Guillermo and Dopazo, Joaquin} } @article {495, title = {Pathways systematically associated to Hirschsprung{\textquoteright}s disease.}, journal = {Orphanet J Rare Dis}, volume = {8}, year = {2013}, month = {2013 Dec 02}, pages = {187}, abstract = {

Despite it has been reported that several loci are involved in Hirschsprung{\textquoteright}s disease, the molecular basis of the disease remains yet essentially unknown. The study of collective properties of modules of functionally-related genes provides an efficient and sensitive statistical framework that can overcome sample size limitations in the study of rare diseases. Here, we present the extension of a previous study of a Spanish series of HSCR trios to an international cohort of 162 HSCR trios to validate the generality of the underlying functional basis of the Hirschsprung{\textquoteright}s disease mechanisms previously found. The Pathway-Based Analysis (PBA) confirms a strong association of gene ontology (GO) modules related to signal transduction and its regulation, enteric nervous system (ENS) formation and other processes related to the disease. In addition, network analysis recovers sub-networks significantly associated to the disease, which contain genes related to the same functionalities, thus providing an independent validation of these findings. The functional profiles of association obtained for patients populations from different countries were compared to each other. While gene associations were different at each series, the main functional associations were identical in all the five populations. These observations would also explain the reported low reproducibility of associations of individual disease genes across populations.

}, keywords = {Female, Genetic Predisposition to Disease, Genotype, Hirschsprung Disease, Humans, Male, Polymorphism, Single Nucleotide}, issn = {1750-1172}, doi = {10.1186/1750-1172-8-187}, author = {Fern{\'a}ndez, Raquel M and Bleda, Marta and Luz{\'o}n-Toro, Berta and Garc{\'\i}a-Alonso, Luz and Arnold, Stacey and Sribudiani, Yunia and Besmond, Claude and Lantieri, Francesca and Doan, Betty and Ceccherini, Isabella and Lyonnet, Stanislas and Hofstra, Robert Mw and Chakravarti, Aravinda and Anti{\v n}olo, Guillermo and Dopazo, Joaquin and Borrego, Salud} } @article {512, title = {Discovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments.}, journal = {Nucleic Acids Res}, volume = {40}, year = {2012}, month = {2012 Nov 01}, pages = {e158}, abstract = {

Genomic experiments (e.g. differential gene expression, single-nucleotide polymorphism association) typically produce ranked list of genes. We present a simple but powerful approach which uses protein-protein interaction data to detect sub-networks within such ranked lists of genes or proteins. We performed an exhaustive study of network parameters that allowed us concluding that the average number of components and the average number of nodes per component are the parameters that best discriminate between real and random networks. A novel aspect that increases the efficiency of this strategy in finding sub-networks is that, in addition to direct connections, also connections mediated by intermediate nodes are considered to build up the sub-networks. The possibility of using of such intermediate nodes makes this approach more robust to noise. It also overcomes some limitations intrinsic to experimental designs based on differential expression, in which some nodes are invariant across conditions. The proposed approach can also be used for candidate disease-gene prioritization. Here, we demonstrate the usefulness of the approach by means of several case examples that include a differential expression analysis in Fanconi Anemia, a genome-wide association study of bipolar disorder and a genome-scale study of essentiality in cancer genes. An efficient and easy-to-use web interface (available at http://www.babelomics.org) based on HTML5 technologies is also provided to run the algorithm and represent the network.

}, keywords = {Bipolar Disorder, Fanconi Anemia, Gene Regulatory Networks, Genes, Neoplasm, Genome-Wide Association Study, Genomics, Humans, Protein Interaction Mapping}, issn = {1362-4962}, doi = {10.1093/nar/gks699}, author = {Garc{\'\i}a-Alonso, Luz and Alonso, Roberto and Vidal, Enrique and Amadoz, Alicia and De Maria, Alejandro and Minguez, Pablo and Medina, Ignacio and Dopazo, Joaquin} } @article {515, title = {Four new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung{\textquoteright}s disease.}, journal = {Orphanet J Rare Dis}, volume = {7}, year = {2012}, month = {2012 Dec 28}, pages = {103}, abstract = {

Finding gene associations in rare diseases is frequently hampered by the reduced numbers of patients accessible. Conventional gene-based association tests rely on the availability of large cohorts, which constitutes a serious limitation for its application in this scenario. To overcome this problem we have used here a combined strategy in which a pathway-based analysis (PBA) has been initially conducted to prioritize candidate genes in a Spanish cohort of 53 trios of short-segment Hirschsprung{\textquoteright}s disease. Candidate genes have been further validated in an independent population of 106 trios. The study revealed a strong association of 11 gene ontology (GO) modules related to signal transduction and its regulation, enteric nervous system (ENS) formation and other HSCR-related processes. Among the preselected candidates, a total of 4 loci, RASGEF1A, IQGAP2, DLC1 and CHRNA7, related to signal transduction and migration processes, were found to be significantly associated to HSCR. Network analysis also confirms their involvement in the network of already known disease genes. This approach, based on the study of functionally-related gene sets, requires of lower sample sizes and opens new opportunities for the study of rare diseases.

}, keywords = {Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Hirschsprung Disease, Humans, Male}, issn = {1750-1172}, doi = {10.1186/1750-1172-7-103}, author = {Fern{\'a}ndez, Raquel Ma and Bleda, Marta and N{\'u}{\~n}ez-Torres, Roc{\'\i}o and Medina, Ignacio and Luz{\'o}n-Toro, Berta and Garc{\'\i}a-Alonso, Luz and Torroglosa, Ana and Marb{\`a}, Martina and Enguix-Riego, Ma Valle and Montaner, David and Anti{\v n}olo, Guillermo and Dopazo, Joaquin and Borrego, Salud} }