@article {405, title = {Gene Expression Integration into Pathway Modules Reveals a Pan-Cancer Metabolic Landscape.}, journal = {Cancer Res}, volume = {78}, year = {2018}, month = {2018 11 01}, pages = {6059-6072}, abstract = {

Metabolic reprogramming plays an important role in cancer development and progression and is a well-established hallmark of cancer. Despite its inherent complexity, cellular metabolism can be decomposed into functional modules that represent fundamental metabolic processes. Here, we performed a pan-cancer study involving 9,428 samples from 25 cancer types to reveal metabolic modules whose individual or coordinated activity predict cancer type and outcome, in turn highlighting novel therapeutic opportunities. Integration of gene expression levels into metabolic modules suggests that the activity of specific modules differs between cancers and the corresponding tissues of origin. Some modules may cooperate, as indicated by the positive correlation of their activity across a range of tumors. The activity of many metabolic modules was significantly associated with prognosis at a stronger magnitude than any of their constituent genes. Thus, modules may be classified as tumor suppressors and oncomodules according to their potential impact on cancer progression. Using this modeling framework, we also propose novel potential therapeutic targets that constitute alternative ways of treating cancer by inhibiting their reprogrammed metabolism. Collectively, this study provides an extensive resource of predicted cancer metabolic profiles and dependencies. Combining gene expression with metabolic modules identifies molecular mechanisms of cancer undetected on an individual gene level and allows discovery of new potential therapeutic targets. .

}, keywords = {Cell Line, Tumor, Cluster Analysis, Disease Progression, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Gene Regulatory Networks, Humans, Kaplan-Meier Estimate, Metabolome, mutation, Neoplasms, Oncogenes, Phenotype, Prognosis, RNA, Small Interfering, Sequence Analysis, RNA, Transcriptome, Treatment Outcome}, issn = {1538-7445}, doi = {10.1158/0008-5472.CAN-17-2705}, author = {Cubuk, Cankut and Hidalgo, Marta R and Amadoz, Alicia and Pujana, Miguel A and Mateo, Francesca and Herranz, Carmen and Carbonell-Caballero, Jos{\'e} and Dopazo, Joaquin} } @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 {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 {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 {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} }