@article {763, title = {Endoglin and MMP14 Contribute to Ewing Sarcoma Spreading by Modulation of Cell-Matrix Interactions.}, journal = {Int J Mol Sci}, volume = {23}, year = {2022}, month = {2022 Aug 04}, abstract = {

Endoglin (ENG) is a mesenchymal stem cell (MSC) marker typically expressed by active endothelium. This transmembrane glycoprotein is shed by matrix metalloproteinase 14 (MMP14). Our previous work demonstrated potent preclinical activity of first-in-class anti-ENG antibody-drug conjugates as a nascent strategy to eradicate Ewing sarcoma (ES), a devastating rare bone/soft tissue cancer with a putative MSC origin. We also defined a correlation between ENG and MMP14 expression in ES. Herein, we show that ENG expression is significantly associated with a dismal prognosis in a large cohort of ES patients. Moreover, both ENG/MMP14 are frequently expressed in primary ES tumors and metastasis. To deepen in their functional relevance in ES, we conducted transcriptomic and proteomic profiling of in vitro ES models that unveiled a key role of ENG and MMP14 in cell mechano-transduction. Migration and adhesion assays confirmed that loss of ENG disrupts actin filament assembly and filopodia formation, with a concomitant effect on cell spreading. Furthermore, we observed that ENG regulates cell-matrix interaction through activation of focal adhesion signaling and protein kinase C expression. In turn, loss of MMP14 contributed to a more adhesive phenotype of ES cells by modulating the transcriptional extracellular matrix dynamics. Overall, these results suggest that ENG and MMP14 exert a significant role in mediating correct spreading machinery of ES cells, impacting the aggressiveness of the disease.

}, keywords = {Bone Neoplasms, Endoglin, Humans, Matrix Metalloproteinase 14, Proteomics, Receptors, Growth Factor, Sarcoma, Ewing, Signal Transduction}, issn = {1422-0067}, doi = {10.3390/ijms23158657}, author = {Puerto-Camacho, Pilar and Diaz-Martin, Juan and Olmedo-Pelayo, Joaqu{\'\i}n and Bolado-Carrancio, Alfonso and Salguero-Aranda, Carmen and Jord{\'a}n-P{\'e}rez, Carmen and Esteban-Medina, Marina and Alamo-Alvarez, Inmaculada and Delgado-Bellido, Daniel and Lobo-Selma, Laura and Dopazo, Joaquin and Sastre, Ana and Alonso, Javier and Gr{\"u}newald, Thomas G P and Bernabeu, Carmelo and Byron, Adam and Brunton, Valerie G and Amaral, Ana Teresa and de Alava, Enrique} } @article {610, title = {Exploring the druggable space around the Fanconi anemia pathway using machine learning and mechanistic models.}, journal = {BMC Bioinformatics}, volume = {20}, year = {2019}, month = {2019 Jul 02}, pages = {370}, abstract = {

BACKGROUND: In spite of the abundance of genomic data, predictive models that describe phenotypes as a function of gene expression or mutations are difficult to obtain because they are affected by the curse of dimensionality, given the disbalance between samples and candidate genes. And this is especially dramatic in scenarios in which the availability of samples is difficult, such as the case of rare diseases.

RESULTS: The application of multi-output regression machine learning methodologies to predict the potential effect of external proteins over the signaling circuits that trigger Fanconi anemia related cell functionalities, inferred with a mechanistic model, allowed us to detect over 20 potential therapeutic targets.

CONCLUSIONS: The use of artificial intelligence methods for the prediction of potentially causal relationships between proteins of interest and cell activities related with disease-related phenotypes opens promising avenues for the systematic search of new targets in rare diseases.

}, keywords = {Databases, Factual, Fanconi Anemia, Genomics, Humans, Machine Learning, Phenotype, Proteins, Signal Transduction}, issn = {1471-2105}, doi = {10.1186/s12859-019-2969-0}, author = {Esteban-Medina, Marina and Pe{\~n}a-Chilet, Maria and Loucera, Carlos and Dopazo, Joaquin} } @article {456, title = {The EGR2 gene is involved in axonal Charcot-Marie-Tooth disease.}, journal = {Eur J Neurol}, volume = {22}, year = {2015}, month = {2015 Dec}, pages = {1548-55}, abstract = {

BACKGROUND AND PURPOSE: A three-generation family affected by axonal Charcot-Marie-Tooth disease (CMT) was investigated with the aim of discovering genetic defects and to further characterize the phenotype.

METHODS: The clinical, nerve conduction studies and muscle magnetic resonance images of the patients were reviewed. A whole exome sequencing was performed and the changes were investigated by genetic studies, in silico analysis and luciferase reporter assays.

RESULTS: A novel c.1226G>A change (p.R409Q) in the EGR2 gene was identified. Patients presented with a typical, late-onset axonal CMT phenotype with variable severity that was confirmed in the ancillary tests. The in silico studies showed that the residue R409 is an evolutionary conserved amino acid. The p.R409Q mutation, which is predicted as probably damaging, would alter the conformation of the protein slightly and would cause a decrease of gene expression.

CONCLUSIONS: This is the first report of an EGR2 mutation presenting as an axonal CMT phenotype with variable severity. This study broadens the phenotype of the EGR2-related neuropathies and suggests that the genetic testing of patients suffering from axonal CMT should include the EGR2 gene.

}, keywords = {Adult, Aged, Aged, 80 and over, Axons, Charcot-Marie-Tooth Disease, Early Growth Response Protein 2, Exome, Female, Humans, Male, Middle Aged, mutation, Pedigree, Phenotype, Severity of Illness Index, Young Adult}, issn = {1468-1331}, doi = {10.1111/ene.12782}, author = {Sevilla, T and Sivera, R and Mart{\'\i}nez-Rubio, D and Lupo, V and Chumillas, M J and Calpena, E and Dopazo, J and V{\'\i}lchez, J J and Palau, F and Espin{\'o}s, C} } @article {1171, title = {Exome sequencing reveals a high genetic heterogeneity on familial Hirschsprung disease.}, journal = {Scientific reports}, volume = {5}, year = {2015}, month = {2015}, pages = {16473}, abstract = {Hirschsprung disease (HSCR; OMIM 142623) is a developmental disorder characterized by aganglionosis along variable lengths of the distal gastrointestinal tract, which results in intestinal obstruction. Interactions among known HSCR genes and/or unknown disease susceptibility loci lead to variable severity of phenotype. Neither linkage nor genome-wide association studies have efficiently contributed to completely dissect the genetic pathways underlying this complex genetic disorder. We have performed whole exome sequencing of 16 HSCR patients from 8 unrelated families with SOLID platform. Variants shared by affected relatives were validated by Sanger sequencing. We searched for genes recurrently mutated across families. Only variations in the FAT3 gene were significantly enriched in five families. Within-family analysis identified compound heterozygotes for AHNAK and several genes (N = 23) with heterozygous variants that co-segregated with the phenotype. Network and pathway analyses facilitated the discovery of polygenic inheritance involving FAT3, HSCR known genes and their gene partners. Altogether, our approach has facilitated the detection of more than one damaging variant in biologically plausible genes that could jointly contribute to the phenotype. Our data may contribute to the understanding of the complex interactions that occur during enteric nervous system development and the etiopathology of familial HSCR.}, keywords = {babelomics, Hirschprung, NGS, prioritization}, issn = {2045-2322}, doi = {10.1038/srep16473}, url = {http://www.nature.com/articles/srep16473}, author = {Luz{\'o}n-Toro, Berta and Gui, Hongsheng and Ruiz-Ferrer, Macarena and Sze-Man Tang, Clara and Fern{\'a}ndez, Raquel M and Sham, Pak-Chung and Torroglosa, Ana and Kwong-Hang Tam, Paul and Espino-Pais{\'a}n, Laura and Cherny, Stacey S and Bleda, Marta and Enguix-Riego, Mar{\'\i}a Del Valle and Joaqu{\'\i}n Dopazo and Anti{\v n}olo, Guillermo and Garcia-Barcel{\'o}, Maria-Merc{\`e} and Borrego, Salud} } @article {471, title = {Exome sequencing reveals a high genetic heterogeneity on familial Hirschsprung disease}, journal = {Scientific Reports}, volume = {5}, year = {2015}, month = {Jan-12-2015}, doi = {10.1038/srep16473}, url = {http://www.nature.com/articles/srep16473http://www.nature.com/articles/srep16473.pdfhttp://www.nature.com/articles/srep16473.pdfhttp://www.nature.com/articles/srep16473}, author = {Luz{\'o}n-Toro, Berta and Gui, Hongsheng and Ruiz-Ferrer, Macarena and Sze-Man Tang, Clara and Fern{\'a}ndez, Raquel M. and Sham, Pak-Chung and Torroglosa, Ana and Kwong-Hang Tam, Paul and Espino-Pais{\'a}n, Laura and Cherny, Stacey S. and Bleda, Marta and Enguix-Riego, Mar{\'\i}a Del Valle and Dopazo, Joaquin and Anti{\v n}olo, Guillermo and Garcia-Barcel{\'o}, Maria-Merc{\`e} and Borrego, Salud} } @article {566, title = {Exome sequencing identifies a new mutation in SERAC1 in a patient with 3-methylglutaconic aciduria.}, journal = {Mol Genet Metab}, volume = {110}, year = {2013}, month = {2013 Sep-Oct}, pages = {73-7}, abstract = {

3-Methylglutaconic aciduria (3-MGA-uria) is a heterogeneous group of syndromes characterized by an increased excretion of 3-methylglutaconic and 3-methylglutaric acids. Five types of 3-MGA-uria (I to V) with different clinical presentations have been described. Causative mutations in TAZ, OPA3, DNAJC19, ATP12, ATP5E, and TMEM70 have been identified. After excluding the known genetic causes of 3-MGA-uria we used exome sequencing to investigate a patient with Leigh syndrome and 3-MGA-uria. We identified a homozygous variant in SERAC1 (c.202C>T; p.Arg68*), that generates a premature stop codon at position 68 of SERAC1 protein. Western blot analysis in patient{\textquoteright}s fibroblasts showed a complete absence of SERAC1 that was consistent with the prediction of a truncated protein and supports the pathogenic role of the mutation. During the course of this project a parallel study identified mutations in SERAC1 as the genetic cause of the disease in 15 patients with MEGDEL syndrome, which was compatible with the clinical and biochemical phenotypes of the patient described here. In addition, our patient developed microcephaly and optic atrophy, two features not previously reported in MEGDEL syndrome. We highlight the usefulness of exome sequencing to reveal the genetic bases of human rare diseases even if only one affected individual is available.

}, keywords = {Adolescent, Adult, Carboxylic Ester Hydrolases, Child, Exome, Female, High-Throughput Nucleotide Sequencing, Humans, Infant, Male, Metabolism, Inborn Errors, mutation}, issn = {1096-7206}, doi = {10.1016/j.ymgme.2013.04.021}, author = {Tort, Frederic and Garc{\'\i}a-Silva, Mar{\'\i}a Teresa and Ferrer-Cort{\`e}s, X{\`e}nia and Navarro-Sastre, Aleix and Garcia-Villoria, Judith and Coll, Maria Josep and Vidal, Enrique and Jim{\'e}nez-Almaz{\'a}n, Jorge and Dopazo, Joaquin and Briones, Paz and Elpeleg, Orly and Ribes, Antonia} } @article {12824315, title = {EVA: Evaluation of protein structure prediction servers}, journal = {Nucleic Acids Res}, volume = {31}, number = {13}, year = {2003}, note = {Koh, Ingrid Y Y Eyrich, Volker A Marti-Renom, Marc A Przybylski, Dariusz Madhusudhan, Mallur S Eswar, Narayanan Grana, Osvaldo Pazos, Florencio Valencia, Alfonso Sali, Andrej Rost, Burkhard 1-P50-GM62413-01/GM/NIGMS NIH HHS/United States 5-P20-LM7276/LM/NLM NIH HHS/United States P50 GM62529/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States R01-GM63029-01/GM/NIGMS NIH HHS/United States Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, Non-P.H.S. Research Support, U.S. Gov{\textquoteright}t, P.H.S. England Nucleic acids research Nucleic Acids Res. 2003 Jul 1;31(13):3311-5.}, pages = {3311-5}, abstract = {EVA (http://cubic.bioc.columbia.edu/eva/) is a web server for evaluation of the accuracy of automated protein structure prediction methods. The evaluation is updated automatically each week, to cope with the large number of existing prediction servers and the constant changes in the prediction methods. EVA currently assesses servers for secondary structure prediction, contact prediction, comparative protein structure modelling and threading/fold recognition. Every day, sequences of newly available protein structures in the Protein Data Bank (PDB) are sent to the servers and their predictions are collected. The predictions are then compared to the experimental structures once a week; the results are published on the EVA web pages. Over time, EVA has accumulated prediction results for a large number of proteins, ranging from hundreds to thousands, depending on the prediction method. This large sample assures that methods are compared reliably. As a result, EVA provides useful information to developers as well as users of prediction methods.}, keywords = {Automation Databases, Protein, Protein Internet *Protein Conformation Protein Folding Protein Structure, Protein Structural Homology, Secondary Proteins/chemistry Reproducibility of Results *Sequence Analysis}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12824315}, author = {Koh, I. Y. and Eyrich, V. A. and M. A. Marti-Renom and Przybylski, D. and Madhusudhan, M. S. and Eswar, N. and Grana, O. and Pazos, F. and Valencia, A. and Sali, A. and Rost, B.} } @article {11751240, title = {EVA: continuous automatic evaluation of protein structure prediction servers}, journal = {Bioinformatics}, volume = {17}, number = {12}, year = {2001}, note = {Eyrich, V A Marti-Renom, M A Przybylski, D Madhusudhan, M S Fiser, A Pazos, F Valencia, A Sali, A Rost, B England Bioinformatics (Oxford, England) Bioinformatics. 2001 Dec;17(12):1242-3.}, pages = {1242-3}, abstract = {Evaluation of protein structure prediction methods is difficult and time-consuming. Here, we describe EVA, a web server for assessing protein structure prediction methods, in an automated, continuous and large-scale fashion. Currently, EVA evaluates the performance of a variety of prediction methods available through the internet. Every week, the sequences of the latest experimentally determined protein structures are sent to prediction servers, results are collected, performance is evaluated, and a summary is published on the web. EVA has so far collected data for more than 3000 protein chains. These results may provide valuable insight to both developers and users of prediction methods. AVAILABILITY: http://cubic.bioc.columbia.edu/eva. CONTACT: eva@cubic.bioc.columbia.edu}, keywords = {Automation Internet *Protein Conformation Proteins/*analysis *Software}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=11751240}, author = {Eyrich, V. A. and M. A. Marti-Renom and Przybylski, D. and Madhusudhan, M. S. and Fiser, A. and Pazos, F. and Valencia, A. and Sali, A. and Rost, B.} }