Martin-Lorenzo A.,University of Salamanca |
Martin-Lorenzo A.,Institute of Biomedical Research of Salamanca IBSAL |
Hauer J.,Heinrich Heine University Dusseldorf |
Vicente-Duenas C.,University of Salamanca |
And 26 more authors.
Cancer Discovery | Year: 2015
Earlier in the past century, infections were regarded as the most likely cause of childhood B-cell precursor acute lymphoblastic leukemia (pB-ALL). However, there is a lack of relevant biologic evidence supporting this hypothesis. We present in vivo genetic evidence mechanistically connecting inherited susceptibility to pB-ALL and postnatal infections by showing that pB-ALL was initiated in Pax5 heterozygous mice only when they were exposed to common pathogens. Strikingly, these murine pB-ALLs closely resemble the human disease. Tumor exome sequencing revealed activating somatic, nonsynonymous mutations of Jak3 as a second hit. Transplantation experiments and deep sequencing suggest that inactivating mutations in Pax5 promote leukemogenesis by creating an aberrant progenitor compartment that is susceptible to malignant transformation through accumulation of secondary Jak3 mutations. Thus, treatment of Pax5+/− leukemic cells with specific JAK1/3 inhibitors resulted in increased apoptosis. These results uncover the causal role of infection in pB-ALL development. Significance: These results demonstrate that delayed infection exposure is a causal factor in pB-ALL. Therefore, these findings have critical implications for the understanding of the pathogenesis of leukemia and for the development of novel therapies for this disease. © 2015 American Association for Cancer Research.
Santos-Garcia G.,University of Salamanca |
Santos-Garcia G.,Bioinformatics and Functional Genomics Research Group |
Santos-Garcia G.,SRI International
Advances in Intelligent Systems and Computing | Year: 2014
Biological pathways define complex interaction networks where multiple molecular elements work in a series of reactions to produce a response to different biomolecular signals. These biological systems are dynamic and we need mathematical methods that can analyze symbolic elements and complex interactions between them to produce adequate readouts of such systems. Rewriting logic procedures are adequate tools to handle dynamic systems which are applied to the study of specific biological pathways behaviour. Pathway Logic is a rewriting logic development applied to symbolic systems biology. Rewriting logic language Maude allows us to define transition rules and to set up queries about the flow in the biological system. In this paper we describe the use of Pathway Logic to model and analyze the dynamics in a well-known signaling transduction pathway: epidermal growth factor (EGF) pathway. We also use Pathway Logic Assistant (PLA) tool to browse and query this system. © Springer International Publishing Switzerland 2014.
Ferragud J.,Research Center Principe Felipe |
Avivar-Valderas A.,Research Center Principe Felipe |
Avivar-Valderas A.,Mount Sinai School of Medicine |
Pla A.,Research Center Principe Felipe |
And 2 more authors.
FEBS Letters | Year: 2011
Using transcriptomic gene expression profiling we found tumor suppressor DRO1 being repressed in AIB1 transgenic mice. In agreement, AIB1 represses DRO1 promoter and its expression levels inversely correlate with DRO1 in several cancer cell lines and in ectopic and silencing assays. Estrogen modulators treatment showed a regulation in an estrogen receptor-dependent fashion. Importantly, DRO1 overexpression resulted in BCLAF1 upregulation, a compelling concept given that BCLAF1 is a death-promoting transcriptional repressor. Additionally, DRO1 shuttles from Golgi to the endoplasmic reticulum upon apoptotic stimuli, where it is predicted to facilitate the apoptosis cascade. Finally, DRO1 repression is an important factor for AIB1-mediated inhibition of apoptosis. Collectively, our results reveal DRO1 as an AIB1-targeted tumor suppressor, providing a novel mechanism for AIB1-dependent inhibition of apoptosis. © 2011 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
De Las Rivas J.,Bioinformatics and Functional Genomics Research Group
BMC genomics | Year: 2014
BACKGROUND: Accurate analysis of whole-gene expression and individual-exon expression is essential to characterize different transcript isoforms and identify alternative splicing events in human genes. One of the omic technologies widely used in many studies on human samples are the exon-specific expression microarray platforms.RESULTS: Since there are not many validated comparative analyses to identify specific splicing events using data derived from these types of platforms, we have developed an algorithm (called ESLiM) to detect significant changes in exon use, and applied it to a reference dataset of 270 human genes that show alternative expression in different tissues. We compared the results with three other methodological approaches and provided the R source code to be applied elsewhere. The genes positively detected by these analyses also provide a verified subset of human genes that present tissue-regulated isoforms. Furthermore, we performed a validation analysis on human patient samples comparing two different subtypes of acute myeloid leukemia (AML) and we experimentally validated the splicing in several selected genes that showed exons with highly significant signal change.CONCLUSIONS: The comparative analyses with other methods using a fair set of human genes that show alternative splicing and the validation on clinical samples demonstrate that the proposed novel algorithm is a reliable tool for detecting differential splicing in exon-level expression data.
Diez P.,Cancer Research Center USAL IBSAL |
Diez P.,Proteomics Unit |
Droste C.,Bioinformatics and Functional Genomics Research Group |
Degano R.M.,Proteomics Unit |
And 12 more authors.
Journal of Proteome Research | Year: 2015
A comprehensive study of the molecular active landscape of human cells can be undertaken to integrate two different but complementary perspectives: transcriptomics, and proteomics. After the genome era, proteomics has emerged as a powerful tool to simultaneously identify and characterize the compendium of thousands of different proteins active in a cell. Thus, the Chromosome-centric Human Proteome Project (C-HPP) is promoting a full characterization of the human proteome combining high-throughput proteomics with the data derived from genome-wide expression profiling of protein-coding genes. Here we present a full proteomic profiling of a human lymphoma B-cell line (Ramos) performed using a nanoUPLC-LTQ-Orbitrap Velos proteomic platform, combined to an in-depth transcriptomic profiling of the same cell type. Data are available via ProteomeXchange with identifier PXD001933. Integration of the proteomic and transcriptomic data sets revealed a 94% overlap in the proteins identified by both -omics approaches. Moreover, functional enrichment analysis of the proteomic profiles showed an enrichment of several functions directly related to the biological and morphological characteristics of B-cells. In turn, about 30% of all protein-coding genes present in the whole human genome were identified as being expressed by the Ramos cells (stable average of 30% genes along all the chromosomes), revealing the size of the protein expression-set present in one specific human cell type. Additionally, the identification of missing proteins in our data sets has been reported, highlighting the power of the approach. Also, a comparison between neXtProt and UniProt database searches has been performed. In summary, our transcriptomic and proteomic experimental profiling provided a high coverage report of the expressed proteome from a human lymphoma B-cell type with a clear insight into the biological processes that characterized these cells. In this way, we demonstrated the usefulness of combining -omics for a comprehensive characterization of specific biological systems. © 2015 American Chemical Society.