To gain insight into the genomic basis of diffuse large B-cell lymphoma (DLBCL), we performed massively parallel whole-exome sequencing of 55 primary tumor samples from patients with DLBCL and matched normal tissue. We identified recurrent mutations in genes that are well known to be functionally relevant in DLBCL, including MYD88, CARD11, EZH2, and CREBBP. We also identified somatic mutations in genes for which a functional role in DLBCL has not been previously suspected. These genes include MEF2B, MLL2, BTG1, GNA13, ACTB, P2RY8, PCLO, and TNFRSF14. Further, we show that BCL2 mutations commonly occur in patients with BCL2/IgH rearrangements as a result of somatic hypermutation normally occurring at the IgH locus. The BCL2 point mutations are primarily synonymous, and likely caused by activation-induced cytidine deaminase-mediated somatic hypermutation, as shown by comprehensive analysis of enrichment of mutations in WRCY target motifs. Those nonsynonymous mutations that are observed tend to be found outside of the functionally important BH domains of the protein, suggesting that strong negative selection against BCL2 loss-of-function mutations is at play. Last, by using an algorithm designed to identify likely functionally relevant but infrequent mutations, we identify KRAS, BRAF, and NOTCH1 as likely drivers of DLBCL pathogenesis in some patients. Our data provide an unbiased view of the landscape of mutations in DLBCL, and this in turn may point toward new therapeutic strategies for the disease.next-generation sequencing | human genetics | activation-induced deaminase D iffuse large B-cell lymphoma (DLBCL) is an aggressive nonHodgkin lymphoma that affects 30,000 new patients in the United States every year (1, 2). The standard of care for the treatment of most cases of DLBCL is the R-CHOP regimen (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) consisting of multiagent chemotherapy plus a therapeutic antibody directed against CD20, a marker of B lymphocytes. The 3-year event-free survival rate is approximately 60%, with the majority of the remaining 40% dying of their disease (3). To date, treatment strategies to improve outcome have largely included increased doses of standard agents in the context of autologous stem cell transplantation (4). Therefore, there is a great medical need to define the genetic abnormalities that are associated with DLBCL to define novel targets for therapy.Germinal centers (GCs) in lymphoid tissues are sites of clonal expansion and editing of the Ig receptor in B lymphocytes, and this GC reaction is a physiological component of the humoral immune response. Somatic hypermutation (SHM) is part of the GC reaction, and its dysregulation contributes to the accumulation of somatic mutations in oncogenes and tumor-suppressor genes in B lymphocytes.Traditionally, DLBCL has been classified by the morphology and immunophenotype of the malignant B-cells but more recently, molecular classifications have been reported. Specifically, gene expression-based classification o...

Mexico is developing the basis for genomic medicine to improve healthcare of its population. The extensive study of genetic diversity and linkage disequilibrium structure of different populations has made it possible to develop tagging and imputation strategies to comprehensively analyze common genetic variation in association studies of complex diseases. We assessed the benefit of a Mexican haplotype map to improve identification of genes related to common diseases in the Mexican population. We evaluated genetic diversity, linkage disequilibrium patterns, and extent of haplotype sharing using genomewide data from Mexican Mestizos from regions with different histories of admixture and particular population dynamics. Ancestry was evaluated by including 1 Mexican Amerindian group and data from the HapMap. Our results provide evidence of genetic differences between Mexican subpopulations that should be considered in the design and analysis of association studies of complex diseases. In addition, these results support the notion that a haplotype map of the Mexican Mestizo population can reduce the number of tag SNPs required to characterize common genetic variation in this population. This is one of the first genomewide genotyping efforts of a recently admixed population in Latin America.admixture ͉ genetic variation ͉ population genetics ͉ SNP tagging

Pathway analysis is a set of widely used tools for research in life sciences intended to give meaning to high-throughput biological data. The methodology of these tools settles in the gathering and usage of knowledge that comprise biomolecular functioning, coupled with statistical testing and other algorithms. Despite their wide employment, pathway analysis foundations and overall background may not be fully understood, leading to misinterpretation of analysis results. This review attempts to comprise the fundamental knowledge to take into consideration when using pathway analysis as a hypothesis generation tool. We discuss the key elements that are part of these methodologies, their capabilities and current deficiencies. We also present an overview of current and all-time popular methods, highlighting different classes across them. In doing so, we show the exploding diversity of methods that pathway analysis encompasses, point out commonly overlooked caveats, and direct attention to a potential new class of methods that attempt to zoom the analysis scope to the sample scale.

Breast cancer is a complex heterogeneous disease. Common hallmark features of cancer can be found. Their origin may be traced back to their intricate relationships governing regulatory programs during the development of this disease. To unveil distinctive features of the transcriptional regulation program in breast cancer, a pipeline for RNA-seq analysis in 780 breast cancer and 101 healthy breast samples, at gene expression and network level, was implemented. Inter-chromosomal relationships between genes resulted strikingly scarce in a cancer network, in comparison to its healthy counterpart. We suggest that inter-chromosomal regulation loss may be a novel feature in breast cancer. Additional evidence was obtained by independent validation in microarray and Hi-C data as well as supplementary computational analyses. Functional analysis showed upregulation in processes related to cell cycle and division; while migration, adhesion and cell-to-cell communication, were downregulated. Both the BRCA1 DNA repairing signalling and the Estrogen-mediated G1/S phase entry pathways were found upregulated. In addition, a synergistic underexpression of the γ-protocadherin complex, located at Chr5q31 is also shown. This region has previously been reported to be hypermethylated in breast cancer. These findings altogether provide further evidence for the central role of transcriptional regulatory programs in shaping malignant phenotypes.

Transmitter exocytosis from the neuronal soma is evoked by brief trains of high frequency electrical activity and continues for several minutes. Here we studied how active vesicle transport towards the plasma membrane contributes to this slow phenomenon in serotonergic leech Retzius neurons, by combining electron microscopy, the kinetics of exocytosis obtained from FM1-43 dye fluorescence as vesicles fuse with the plasma membrane, and a diffusion equation incorporating the forces of local confinement and molecular motors. Electron micrographs of neurons at rest or after stimulation with 1 Hz trains showed cytoplasmic clusters of dense core vesicles at 1.5±0.2 and 3.7±0.3 µm distances from the plasma membrane, to which they were bound through microtubule bundles. By contrast, after 20 Hz stimulation vesicle clusters were apposed to the plasma membrane, suggesting that transport was induced by electrical stimulation. Consistently, 20 Hz stimulation of cultured neurons induced spotted FM1-43 fluorescence increases with one or two slow sigmoidal kinetics, suggesting exocytosis from an equal number of vesicle clusters. These fluorescence increases were prevented by colchicine, which suggested microtubule-dependent vesicle transport. Model fitting to the fluorescence kinetics predicted that 52–951 vesicles/cluster were transported along 0.60–6.18 µm distances at average 11–95 nms−1 velocities. The ATP cost per vesicle fused (0.4–72.0), calculated from the ratio of the ΔGprocess/ΔGATP, depended on the ratio of the traveling velocity and the number of vesicles in the cluster. Interestingly, the distance-dependence of the ATP cost per vesicle was bistable, with low energy values at 1.4 and 3.3 µm, similar to the average resting distances of the vesicle clusters, and a high energy barrier at 1.6–2.0 µm. Our study confirms that active vesicle transport is an intermediate step for somatic serotonin exocytosis by Retzius neurons and provides a quantitative method for analyzing similar phenomena in other cell types.

Periodontitis is a common inflammatory disease of infectious origins that often evolves into a chronic condition. Aside from its importance as a stomatologic ailment, chronic periodontitis has gained relevance since it has been shown that it can develop into a systemic condition characterized by unresolved hyper-inflammation, disruption of the innate and adaptive immune system, dysbiosis of the oral, gut and other location's microbiota and other system-wide alterations that may cause, coexist or aggravate other health issues associated to elevated morbi-mortality. The relationships between the infectious, immune, inflammatory, and systemic features of periodontitis and its many related diseases are far from being fully understood and are indeed still debated. However, to date, a large body of evidence on the different biological, clinical, and policy-enabling sources of information, is available. The aim of the present work is to summarize many of these sources of information and contextualize them under a systemic inflammation framework that may set the basis to an integral vision, useful for basic, clinical, and therapeutic goals.

Cancer is the quintessential complex disease. As technologies evolve faster each day, we are able to quantify the different layers of biological elements that contribute to the emergence and development of malignancies. In this multi-omics context, the use of integrative approaches is mandatory in order to gain further insights on oncological phenomena, and to move forward toward the precision medicine paradigm. In this review, we will focus on computational oncology as an integrative discipline that incorporates knowledge from the mathematical, physical, and computational fields to further the biomedical understanding of cancer. We will discuss the current roles of computation in oncology in the context of multi-omic technologies, which include: data acquisition and processing; data management in the clinical and research settings; classification, diagnosis, and prognosis; and the development of models in the research setting, including their use for therapeutic target identification. We will discuss the machine learning and network approaches as two of the most promising emerging paradigms, in computational oncology. These approaches provide a foundation on how to integrate different layers of biological description into coherent frameworks that allow advances both in the basic and clinical settings.

Over the last years, microRNAs (miRs) have shown to be crucial for breast tumour establishment and progression. To understand the influence that miRs have over transcriptional regulation in breast cancer, we constructed mutual information networks from 86 TCGA matched breast invasive carcinoma and control tissue RNA-Seq and miRNA-Seq sequencing data. We show that miRs are determinant for tumour and control data network structure. In tumour data network, miR-200, miR-199 and neighbour miRs seem to cooperate on the regulation of the acquisition of epithelial and mesenchymal traits by the biological processes: Epithelial-Mesenchymal Transition (EMT) and Mesenchymal to Epithelial Transition (MET). Despite structural differences between tumour and control networks, we found a conserved set of associations between miR-200 family members and genes such as VIM, ZEB-1/2 and TWIST-1/2. Further, a large number of miRs observed in tumour network mapped to a specific chromosomal location in DLK1-DIO3 (Chr14q32); some of those miRs have also been associated with EMT and MET regulation. Pathways related to EMT and TGF-beta reinforce the relevance of miR-200, miR-199 and DLK1-DIO3 cluster in breast cancer. With this approach, we stress that miR inclusion in gene regulatory network construction improves our understanding of the regulatory mechanisms underlying breast cancer biology.