@article {812, title = {Shared germline genomic variants in two patients with double primary gastrointestinal stromal tumours (GISTs).}, journal = {J Med Genet}, volume = {61}, year = {2024}, month = {2024 Sep 24}, pages = {927-934}, abstract = {

BACKGROUND: Gastrointestinal stromal tumours (GISTs) are prevalent mesenchymal tumours of the gastrointestinal tract, commonly exhibiting structural variations in and genes. While the mutational profiling of somatic tumours is well described, the genes behind the susceptibility to develop GIST are not yet fully discovered. This study explores the genomic landscape of two primary GIST cases, aiming to identify shared germline pathogenic variants and shed light on potential key players in tumourigenesis.

METHODS: Two patients with distinct genotypically and phenotypically GISTs underwent germline whole genome sequencing. CNV and single nucleotide variant (SNV) analyses were performed.

RESULTS: Both patients harbouring low-risk GISTs with different mutations ( and ) shared homozygous germline pathogenic deletions in both and genes. CNV analysis revealed additional shared pathogenic deletions in other genes such as . No particular pathogenic SNV shared by both patients was detected.

CONCLUSION: Our study provides new insights into germline variants that can be associated with the development of GISTs, namely, and deep deletions. Further functional validation is warranted to elucidate the precise contributions of identified germline mutations in GIST development.

}, keywords = {DNA Copy Number Variations, Female, Gastrointestinal Neoplasms, Gastrointestinal Stromal Tumors, Genetic Predisposition to Disease, Germ-Line Mutation, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Proto-Oncogene Proteins c-kit, Receptor, Platelet-Derived Growth Factor alpha, Whole Genome Sequencing}, issn = {1468-6244}, doi = {10.1136/jmg-2024-110109}, author = {Moura, David S and L{\'o}pez L{\'o}pez, Daniel and di Lernia, Davide and Martin-Ruiz, Marta and Lopez-Alvarez, Maria and Ramos, Rafael and Merino, Jose and Dopazo, Joaquin and Lopez-Guerrero, Jose and Mondaza-Hernandez, Jose L and Romero, Pablo and Hindi, Nadia and Garcia-Foncillas, Jesus and Martin-Broto, Javier} } @article {665, title = {Optimised molecular genetic diagnostics of Fanconi anaemia by whole exome sequencing and functional studies.}, journal = {J Med Genet}, volume = {57}, year = {2020}, month = {2020 04}, pages = {258-268}, abstract = {

PURPOSE: Patients with Fanconi anaemia (FA), a rare DNA repair genetic disease, exhibit chromosome fragility, bone marrow failure, malformations and cancer susceptibility. FA molecular diagnosis is challenging since FA is caused by point mutations and large deletions in 22 genes following three heritability patterns. To optimise FA patients{\textquoteright} characterisation, we developed a simplified but effective methodology based on whole exome sequencing (WES) and functional studies.

METHODS: 68 patients with FA were analysed by commercial WES services. Copy number variations were evaluated by sequencing data analysis with RStudio. To test missense variants, wt FANCA cDNA was cloned and variants were introduced by site-directed mutagenesis. Vectors were then tested for their ability to complement DNA repair defects of a FANCA-KO human cell line generated by TALEN technologies.

RESULTS: We identified 93.3\% of mutated alleles including large deletions. We determined the pathogenicity of three FANCA missense variants and demonstrated that two variants reported in mutations databases as {\textquoteright}affecting functions{\textquoteright} are SNPs. Deep analysis of sequencing data revealed patients{\textquoteright} true mutations, highlighting the importance of functional analysis. In one patient, no pathogenic variant could be identified in any of the 22 known FA genes, and in seven patients, only one deleterious variant could be identified (three patients each with FANCA and FANCD2 and one patient with FANCE mutations) CONCLUSION: WES and proper bioinformatics analysis are sufficient to effectively characterise patients with FA regardless of the rarity of their complementation group, type of mutations, mosaic condition and DNA source.

}, keywords = {Cell Line, DNA Copy Number Variations, DNA Repair, DNA-Binding Proteins, Fanconi Anemia, Fanconi Anemia Complementation Group A Protein, Female, Gene Knockout Techniques, Genetic Predisposition to Disease, Humans, Male, Mutation, Missense, Polymorphism, Single Nucleotide, whole exome sequencing}, issn = {1468-6244}, doi = {10.1136/jmedgenet-2019-106249}, author = {Bogliolo, Massimo and Pujol, Roser and Aza-Carmona, Miriam and Mu{\~n}oz-Subirana, N{\'u}ria and Rodriguez-Santiago, Benjamin and Casado, Jos{\'e} Antonio and Rio, Paula and Bauser, Christopher and Reina-Castill{\'o}n, Judith and Lopez-Sanchez, Marcos and Gonzalez-Quereda, Lidia and Gallano, Pia and Catal{\'a}, Albert and Ruiz-Llobet, Ana and Badell, Isabel and Diaz-Heredia, Cristina and Hladun, Raquel and Senent, Leonort and Argiles, Bienvenida and Bergua Burgues, Juan Miguel and Ba{\~n}ez, Fatima and Arrizabalaga, Beatriz and L{\'o}pez Almaraz, Ricardo and Lopez, Monica and Figuera, {\'A}ngela and Molin{\'e}s, Antonio and P{\'e}rez de Soto, Inmaculada and Hernando, In{\'e}s and Mu{\~n}oz, Juan Antonio and Del Rosario Marin, Maria and Balma{\~n}a, Judith and Stjepanovic, Neda and Carrasco, Estela and Cuesta, Isabel and Cosuelo, Jos{\'e} Miguel and Regueiro, Alexandra and Moraleda Jimenez, Jos{\'e} and Galera-Mi{\~n}arro, Ana Maria and Rosi{\~n}ol, Laura and Carri{\'o}, Anna and Bel{\'e}ndez-Bieler, Cristina and Escudero Soto, Antonio and Cela, Elena and de la Mata, Gregorio and Fern{\'a}ndez-Delgado, Rafael and Garcia-Pardos, Maria Carmen and S{\'a}ez-Villaverde, Raquel and Barraga{\~n}o, Marta and Portugal, Raquel and Lendinez, Francisco and Hernadez, Ines and Vagace, Jos{\'e} Manue and Tapia, Maria and Nieto, Jos{\'e} and Garcia, Marta and Gonzalez, Macarena and Vicho, Cristina and Galvez, Eva and Valiente, Alberto and Antelo, Maria Luisa and Ancliff, Phil and Garc{\'\i}a, Francisco and Dopazo, Joaquin and Sevilla, Julian and Paprotka, Tobias and P{\'e}rez-Jurado, Luis Alberto and Bueren, Juan and Surralles, Jordi} } @article {384, title = {Genomic expression differences between cutaneous cells from red hair color individuals and black hair color individuals based on bioinformatic analysis.}, journal = {Oncotarget}, volume = {8}, year = {2017}, month = {2017 Feb 14}, pages = {11589-11599}, abstract = {

The MC1R gene plays a crucial role in pigmentation synthesis. Loss-of-function MC1R variants, which impair protein function, are associated with red hair color (RHC) phenotype and increased skin cancer risk. Cultured cutaneous cells bearing loss-of-function MC1R variants show a distinct gene expression profile compared to wild-type MC1R cultured cutaneous cells. We analysed the gene signature associated with RHC co-cultured melanocytes and keratinocytes by Protein-Protein interaction (PPI) network analysis to identify genes related with non-functional MC1R variants. From two detected networks, we selected 23 nodes as hub genes based on topological parameters. Differential expression of hub genes was then evaluated in healthy skin biopsies from RHC and black hair color (BHC) individuals. We also compared gene expression in melanoma tumors from individuals with RHC versus BHC. Gene expression in normal skin from RHC cutaneous cells showed dysregulation in 8 out of 23 hub genes (CLN3, ATG10, WIPI2, SNX2, GABARAPL2, YWHA, PCNA and GBAS). Hub genes did not differ between melanoma tumors in RHC versus BHC individuals. The study suggests that healthy skin cells from RHC individuals present a constitutive genomic deregulation associated with the red hair phenotype and identify novel genes involved in melanocyte biology.

}, keywords = {Adult, Coculture Techniques, Computational Biology, gene expression, Genetic Predisposition to Disease, Genomics, Hair Color, Humans, Keratinocytes, Melanocytes, Middle Aged, Phenotype, Receptor, Melanocortin, Type 1}, issn = {1949-2553}, doi = {10.18632/oncotarget.14140}, url = {http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget\&page=article\&op=view\&path\%5B\%5D=14140\&path\%5B\%5D=45094}, author = {Puig-Butille, Joan Anton and Gimenez-Xavier, Pol and Visconti, Alessia and Nsengimana, J{\'e}r{\'e}mie and Garcia-Garcia, Francisco and Tell-Marti, Gemma and Escamez, Maria Jos{\'e} and Newton-Bishop, Julia and Bataille, Veronique and Del Rio, Marcela and Dopazo, Joaquin and Falchi, Mario and Puig, Susana} } @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 {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 {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} } @article {549, title = {Exploring the link between germline and somatic genetic alterations in breast carcinogenesis.}, journal = {PLoS One}, volume = {5}, year = {2010}, month = {2010 Nov 22}, pages = {e14078}, abstract = {

Recent genome-wide association studies (GWASs) have identified candidate genes contributing to cancer risk through low-penetrance mutations. Many of these genes were unexpected and, intriguingly, included well-known players in carcinogenesis at the somatic level. To assess the hypothesis of a germline-somatic link in carcinogenesis, we evaluated the distribution of somatic gene labels within the ordered results of a breast cancer risk GWAS. This analysis suggested frequent influence on risk of genetic variation in loci encoding for "driver kinases" (i.e., kinases encoded by genes that showed higher somatic mutation rates than expected by chance and, therefore, whose deregulation may contribute to cancer development and/or progression). Assessment of these predictions using a population-based case-control study in Poland replicated the association for rs3732568 in EPHB1 (odds ratio (OR) = 0.79; 95\% confidence interval (CI): 0.63-0.98; P(trend) = 0.031). Analyses by early age at diagnosis and by estrogen receptor α (ERα) tumor status indicated potential associations for rs6852678 in CDKL2 (OR = 0.32, 95\% CI: 0.10-1.00; P(recessive) = 0.044) and rs10878640 in DYRK2 (OR = 2.39, 95\% CI: 1.32-4.30; P(dominant) = 0.003), and for rs12765929, rs9836340, rs4707795 in BMPR1A, EPHA3 and EPHA7, respectively (ERα tumor status P(interaction)<0.05). The identification of three novel candidates as EPH receptor genes might indicate a link between perturbed compartmentalization of early neoplastic lesions and breast cancer risk and progression. Together, these data may lay the foundations for replication in additional populations and could potentially increase our knowledge of the underlying molecular mechanisms of breast carcinogenesis.

}, keywords = {Adult, Bone Morphogenetic Protein Receptors, Type I, Breast, Breast Neoplasms, Calcium-Calmodulin-Dependent Protein Kinases, Case-Control Studies, Cyclin-Dependent Kinases, Disease Progression, Estrogen Receptor alpha, Female, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Germ-Line Mutation, Humans, Odds Ratio, Poland, Polymorphism, Single Nucleotide, Protein Serine-Threonine Kinases, Protein-Tyrosine Kinases, Receptor Protein-Tyrosine Kinases, Receptor, EphA3, Receptor, EphA7, Receptor, EphB1, Risk Factors}, issn = {1932-6203}, doi = {10.1371/journal.pone.0014078}, author = {Bonifaci, N{\'u}ria and G{\'o}rski, Bohdan and Masoj{\'c}, Bartlomiej and Woko{\l}orczyk, Dominika and Jakubowska, Anna and D{\k e}bniak, Tadeusz and Berenguer, Antoni and Serra Musach, Jordi and Brunet, Joan and Dopazo, Joaquin and Narod, Steven A and Lubi{\'n}ski, Jan and L{\'a}zaro, Conxi and Cybulski, Cezary and Pujana, Miguel Angel} } @article {600, title = {Use of estimated evolutionary strength at the codon level improves the prediction of disease-related protein mutations in humans.}, journal = {Hum Mutat}, volume = {29}, year = {2008}, month = {2008 Jan}, pages = {198-204}, abstract = {

Predicting the functional impact of protein variation is one of the most challenging problems in bioinformatics. A rapidly growing number of genome-scale studies provide large amounts of experimental data, allowing the application of rigorous statistical approaches for predicting whether a given single point mutation has an impact on human health. Up until now, existing methods have limited their source data to either protein or gene information. Novel in this work, we take advantage of both and focus on protein evolutionary information by using estimated selective pressures at the codon level. Here we introduce a new method (SeqProfCod) to predict the likelihood that a given protein variant is associated with human disease or not. Our method relies on a support vector machine (SVM) classifier trained using three sources of information: protein sequence, multiple protein sequence alignments, and the estimation of selective pressure at the codon level. SeqProfCod has been benchmarked with a large dataset of 8,987 single point mutations from 1,434 human proteins from SWISS-PROT. It achieves 82\% overall accuracy and a correlation coefficient of 0.59, indicating that the estimation of the selective pressure helps in predicting the functional impact of single-point mutations. Moreover, this study demonstrates the synergic effect of combining two sources of information for predicting the functional effects of protein variants: protein sequence/profile-based information and the evolutionary estimation of the selective pressures at the codon level. The results of large-scale application of SeqProfCod over all annotated point mutations in SWISS-PROT (available for download at http://sgu.bioinfo.cipf.es/services/Omidios/; last accessed: 24 August 2007), could be used to support clinical studies.

}, keywords = {Algorithms, Codon, Computational Biology, Databases, Protein, DNA Mutational Analysis, Evolution, Molecular, Genetic Predisposition to Disease, Genetic Variation, Genome, Human, Humans, Iduronic Acid, Point Mutation, Polymorphism, Single Nucleotide, Proteins, Tumor Suppressor Protein p53}, issn = {1098-1004}, doi = {10.1002/humu.20628}, author = {Capriotti, Emidio and Arbiza, Leonardo and Casadio, Rita and Dopazo, Joaquin and Dopazo, Hern{\'a}n and Marti-Renom, Marc A} }