107 research outputs found

    Genome-wide chromatin accessibility, DNA methylation and gene expression analysis of histone deacetylase inhibition in triple-negative breast cancer.

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    Triple-negative breast cancer (TNBC), especially the subset with a basal phenotype, represents the most aggressive subtype of breast cancer. Unlike other solid tumors, TNBCs harbor a low number of driver mutations. Conversely, we and others have demonstrated a significant impact of epigenetic alterations, including DNA methylation and histone post-translational modifications, affecting TNBCs. Due to the promising results in pre-clinical studies, histone deacetylase inhibitors (HDACi) are currently being tested in several clinical trials for breast cancer and other solid tumors. However, the genome-wide epigenetic and transcriptomic implications of HDAC inhibition are still poorly understood. Here, we provide detailed information about the design of a multi-platform dataset that describes the epigenomic and transcriptomic effects of HDACi. This dataset includes genome-wide chromatin accessibility (assessed by ATAC-Sequencing), DNA methylation (assessed by Illumina HM450K BeadChip) and gene expression (assessed by RNA-Sequencing) analyses before and after HDACi treatment of HCC1806 and MDA-MB-231, two human TNBC cell lines with basal-like phenotype

    Epigenetic Regulation of KPC1 Ubiquitin Ligase Affects the NF-κB Pathway in Melanoma.

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    Purpose: Abnormal activation of the NF-κB pathway induces a more aggressive phenotype of cutaneous melanoma. Understanding the mechanisms involved in melanoma NF-κB activation may identify novel targets for this pathway. KPC1, an E3 ubiquitin ligase, is a regulator of the NF-κB pathway. The objective of this study was to investigate the mechanisms regulating KPC1 expression and its clinical impact in melanoma.Experimental Design: The clinical impact of KPC1 expression and its epigenetic regulation were assessed in large cohorts of clinically well-annotated melanoma tissues (tissue microarrays; n = 137, JWCI cohort; n = 40) and The Cancer Genome Atlas database (TCGA cohort, n = 370). Using melanoma cell lines, we investigated the functional interactions between KPC1 and NF-κB, and the epigenetic regulations of KPC1, including DNA methylation and miRNA expression.Results: We verified that KPC1 suppresses melanoma proliferation by processing NF-κB1 p105 into p50, thereby modulating NF-κB target gene expression. Concordantly, KPC1 expression was downregulated in American Joint Committee on Cancer stage IV melanoma compared with early stages (stage I/II P = 0.013, stage III P = 0.004), and low KPC1 expression was significantly associated with poor overall survival in stage IV melanoma (n = 137; HR 1.810; P = 0.006). Furthermore, our data showed that high miR-155-5p expression, which is controlled by DNA methylation at its promoter region (TCGA; Pearson\u27s r -0.455; P \u3c 0.001), is significantly associated with KPC1 downregulation (JWCI; P = 0.028, TCGA; P = 0.003).Conclusions: This study revealed novel epigenetic regulation of KPC1 associated with NF-κB pathway activation, promoting metastatic melanoma progression. These findings suggest the potential utility of KPC1 and its epigenetic regulation as theranostic targets. Clin Cancer Res; 23(16); 4831-42. ©2017 AACR

    The ADAMTS (A Disintegrin and Metalloproteinase with Thrombospondin motifs) family

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    The ADAMTS (A Disintegrin and Metalloproteinase with Thrombospondin motifs) enzymes are secreted, multi-domain matrix-associated zinc metalloendopeptidases that have diverse roles in tissue morphogenesis and patho-physiological remodeling, in inflammation and in vascular biology. The human family includes 19 members that can be sub-grouped on the basis of their known substrates, namely the aggrecanases or proteoglycanases (ADAMTS1, 4, 5, 8, 9, 15 and 20), the procollagen N-propeptidases (ADAMTS2, 3 and 14), the cartilage oligomeric matrix protein-cleaving enzymes (ADAMTS7 and 12), the von-Willebrand Factor proteinase (ADAMTS13) and a group of orphan enzymes (ADAMTS6, 10, 16, 17, 18 and 19). Control of the structure and function of the extracellular matrix (ECM) is a central theme of the biology of the ADAMTS, as exemplified by the actions of the procollagen-N-propeptidases in collagen fibril assembly and of the aggrecanases in the cleavage or modification of ECM proteoglycans. Defects in certain family members give rise to inherited genetic disorders, while the aberrant expression or function of others is associated with arthritis, cancer and cardiovascular disease. In particular, ADAMTS4 and 5 have emerged as therapeutic targets in arthritis. Multiple ADAMTSs from different sub-groupings exert either positive or negative effects on tumorigenesis and metastasis, with both metalloproteinase-dependent and -independent actions known to occur. The basic ADAMTS structure comprises a metalloproteinase catalytic domain and a carboxy-terminal ancillary domain, the latter determining substrate specificity and the localization of the protease and its interaction partners; ancillary domains probably also have independent biological functions. Focusing primarily on the aggrecanases and proteoglycanases, this review provides a perspective on the evolution of the ADAMTS family, their links with developmental and disease mechanisms, and key questions for the future

    Black or White? How to Develop an AutoTuner for Memory-based Analytics [Extended Version]

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    There is a lot of interest today in building autonomous (or, self-driving) data processing systems. An emerging school of thought is to leverage AI-driven "black box" algorithms for this purpose. In this paper, we present a contrarian view. We study the problem of autotuning the memory allocation for applications running on modern distributed data processing systems. For this problem, we show that an empirically-driven "white-box" algorithm, called RelM, that we have developed provides a close-to-optimal tuning at a fraction of the overheads compared to state-of-the-art AI-driven "black box" algorithms, namely, Bayesian Optimization (BO) and Deep Distributed Policy Gradient (DDPG). The main reason for RelM's superior performance is that the memory management in modern memory-based data analytics systems is an interplay of algorithms at multiple levels: (i) at the resource-management level across various containers allocated by resource managers like Kubernetes and YARN, (ii) at the container level among the OS, pods, and processes such as the Java Virtual Machine (JVM), (iii) at the application level for caching, aggregation, data shuffles, and application data structures, and (iv) at the JVM level across various pools such as the Young and Old Generation. RelM understands these interactions and uses them in building an analytical solution to autotune the memory management knobs. In another contribution, called GBO, we use the RelM's analytical models to speed up Bayesian Optimization. Through an evaluation based on Apache Spark, we showcase that RelM's recommendations are significantly better than what commonly-used Spark deployments provide, and are close to the ones obtained by brute-force exploration; while GBO provides optimality guarantees for a higher, but still significantly lower compared to the state-of-the-art AI-driven policies, cost overhead.Comment: Main version in ACM SIGMOD 202

    Mutations in SLC20A2 are a major cause of familial idiopathic basal ganglia calcification

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    Familial idiopathic basal ganglia calcification (IBGC) or Fahr's disease is a rare neurodegenerative disorder characterized by calcium deposits in the basal ganglia and other brain regions, which is associated with neuropsychiatric and motor symptoms. Familial IBGC is genetically heterogeneous and typically transmitted in an autosomal dominant fashion. We performed a mutational analysis of SLC20A2, the first gene found to cause IBGC, to assess its genetic contribution to familial IBGC. We recruited 218 subjects from 29 IBGC-affected families of varied ancestry and collected medical history, neurological exam, and head CT scans to characterize each patient's disease status. We screened our patient cohort for mutations in SLC20A2. Twelve novel (nonsense, deletions, missense, and splice site) potentially pathogenic variants, one synonymous variant, and one previously reported mutation were identified in 13 families. Variants predicted to be deleterious cosegregated with disease in five families. Three families showed nonsegregation with clinical disease of such variants, but retrospective review of clinical and neuroimaging data strongly suggested previous misclassification. Overall, mutations in SLC20A2 account for as many as 41 % of our familial IBGC cases. Our screen in a large series expands the catalog of SLC20A2 mutations identified to date and demonstrates that mutations in SLC20A2 are a major cause of familial IBGC. Non-perfect segregation patterns of predicted deleterious variants highlight the challenges of phenotypic assessment in this condition with highly variable clinical presentation

    Китаб Ибрагима Хосеневича из коллекции Национальной библиотеки Республики Беларусь как исторический источник : реферат к дипломной работе / Инна Чеславовна Кевра; БГУ, Исторический факультет, Кафедра источниковедения; науч. рук. Белявский А.М.

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    The construct of individualism–collectivism (IND-COL) has become the definitive standard in cross-cultural psychology, management, and related fields. It is also among the most controversial, in particular, with regard to the ambiguity of its dimensionality: Some view IND and COL as the opposites of a single continuum, whereas others argue that the two are independent constructs. We explored the issue through seven different tests using original individual-level data from 50 studies and meta-analytic data from 149 empirical publications yielding a total of 295 sample-level observations that were collected using six established instruments for assessing IND and COL as separate constructs. Results indicated that the dimensionality of IND-COL may depend on (a) the specific instrument used to collect the data, (b) the sample characteristics and the cultural region from which the data were collected, and (c) the level of analysis. We also review inconsistencies, deficiencies, and challenges of conceptualizing IND-COL and provide guidelines for developing and selecting instruments for measuring the construct, and for reporting and meta-analyzing results from this line of research
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