246 research outputs found

    The Impact of the Service Innovativeness on Perceived Overall Service Quality, Customer Loyalty and Perceived Customer Value in Shopping Sites

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    Associated with the change of lifestyle, due to reasons such as time constraints, information access, and alternatives comparison easiness, consumers prefer directed shopping on the internet. Shopping is done along with the initiation by the internet, in the scope of study such as website service innovativeness, perceived overall service quality, customer loyalty, and perceived customer value. What are the effects of service innovativeness on perceived overall service quality, customer loyalty, and perceived customer value? In order to answer this question, theoretical and empirical research is structured. From a holistic point of view the results suggest the positive effect of service innovativeness on perceived overall service quality, customer loyalty, and perceived customer value. Website service innovativeness influences behavioural intentions such as perceived overall service quality, customer loyalty, and perceived customer value. Following the examination of the results, the present article discussed the implications for practice and future research

    Joint Estimation of DNA Copy Number From Multiple Platforms

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    DNA copy number variants (CNV) are gains and losses of segments of chromosomes, and comprise an important class of genetic variation. Recently, various microarray hybridization based techniques have been developed for high throughput measurement of DNA copy number. In many studies, multiple technical platforms or different versions of the same platform were used to interrogate the same samples; and it became necessary to pool information across these multiple sources to derive a consensus molecular profile for each sample. An integrated analysis is expected to maximize resolution and accuracy, yet currently there is no well formulated statistical method to address the between-platform differences in probe design, assay methods, sensitivity, and analytical complexity. The conventional approach is to apply one of the CNV detection (a.k.a. “segmentation”) algorithms to search for DNA segments of altered signal intensity. The results from three platforms are combined after segmentation. Here we propose a new method, Multi-Platform Circular Binary Segmentation (MPCBS), which pools statistical evidence across platforms during segmentation, and does not require pre-standardization of different data sources. It involves a weighted sum of t-statistics, which arises naturally from the generalized log-likelihood ratio of a multi-platform model. We show by comparing the integrated analysis of Affymetrix and Illumina SNP array data with fosmid clone end-sequencing results on 8 HapMap samples that MPCBS achieves improved spatial resolution, detection power, and provide a natural consensus across platforms. We also apply the new method to analyze the multi-platform data from TCGA. The R package for MPCBS is registered on R-Forge under project name MPCB

    Assessing the function of chromatin modifying enzymes in medulloblastoma

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    Medulloblastoma is the most common pediatric brain tumor that arises during infancy and childhood and is a major cause of cancer related-morbidity and mortality in children. Recently, medulloblastomas are described as four distinct molecular subgroups (Wnt, sonic hedgehog, Group 3 and Group 4), which have distinct transcriptional, cytogenetic, and mutational spectra

    Examining the role of chromatin modifying enzymes in medulloblastoma by utilizing a chemical library

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    Medulloblastoma (MB) is the most common paediatric brain tumor that arises during infancy and childhood and is a major cause of cancer related-morbidity and mortality in children. Recently, medulloblastomas are described as four distinct molecular subgroups (Wnt, sonic hedgehog, Group 3 and Group 4), which have distinct transcriptional, cytogenetic, and mutational spectra. Next-generation studies have revealed that adult medulloblastomas involve remarkably more somatic SNVs and indels than paediatric counterparts, suggesting that epigenetic deregulation might have a foremost role in the initiation and progression of paediatric medulloblastomas

    Emerging landscape of oncogenic signatures across human cancers.

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    Cancer therapy is challenged by the diversity of molecular implementations of oncogenic processes and by the resulting variation in therapeutic responses. Projects such as The Cancer Genome Atlas (TCGA) provide molecular tumor maps in unprecedented detail. The interpretation of these maps remains a major challenge. Here we distilled thousands of genetic and epigenetic features altered in cancers to ∼500 selected functional events (SFEs). Using this simplified description, we derived a hierarchical classification of 3,299 TCGA tumors from 12 cancer types. The top classes are dominated by either mutations (M class) or copy number changes (C class). This distinction is clearest at the extremes of genomic instability, indicating the presence of different oncogenic processes. The full hierarchy shows functional event patterns characteristic of multiple cross-tissue groups of tumors, termed oncogenic signature classes. Targetable functional events in a tumor class are suggestive of class-specific combination therapy. These results may assist in the definition of clinical trials to match actionable oncogenic signatures with personalized therapies

    Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

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    Summary Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (TP53, ATRX, RB1) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types

    Classification of clear cell renal cell carcinoma based on PKM alternative splicing

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    Clear cell renal cell carcinoma (ccRCC) accounts for 70–80% of kidney cancer diagnoses and displays high molecular and histologic heterogeneity. Hence, it is necessary to reveal the underlying molecular mechanisms involved in progression of ccRCC to better stratify the patients and design effective treatment strategies. Here, we analyzed the survival outcome of ccRCC patients as a consequence of the differential expression of four transcript isoforms of the pyruvate kinase muscle type (PKM). We first extracted a classification biomarker consisting of eight gene pairs whose within-sample relative expression orderings (REOs) could be used to robustly classify the patients into two groups with distinct molecular characteristics and survival outcomes. Next, we validated our findings in a validation cohort and an independent Japanese ccRCC cohort. We finally performed drug repositioning analysis based on transcriptomic expression profiles of drug-perturbed cancer cell lines and proposed that paracetamol, nizatidine, dimethadione and conessine can be repurposed to treat the patients in one of the subtype of ccRCC whereas chenodeoxycholic acid, fenoterol and hexylcaine can be repurposed to treat the patients in the other subtype

    Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer

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    Pancreatic ductal adenocarcinoma is a lethal cancer with fewer than 7% of patients surviving past 5 years. T-cell immunity has been linked to the exceptional outcome of the few long-term survivors1,2, yet the relevant antigens remain unknown. Here we use genetic, immunohistochemical and transcriptional immunoprofiling, computational biophysics, and functional assays to identify T-cell antigens in long-term survivors of pancreatic cancer. Using whole-exome sequencing and in silico neoantigen prediction, we found that tumours with both the highest neoantigen number and the most abundant CD8+ T-cell infiltrates, but neither alone, stratified patients with the longest survival. Investigating the specific neoantigen qualities promoting T-cell activation in long-term survivors, we discovered that these individuals were enriched in neoantigen qualities defined by a fitness model, and neoantigens in the tumour antigen MUC16 (also known as CA125). A neoantigen quality fitness model conferring greater immunogenicity to neoantigens with differential presentation and homology to infectious disease-derived peptides identified long-term survivors in two independent datasets, whereas a neoantigen quantity model ascribing greater immunogenicity to increasing neoantigen number alone did not. We detected intratumoural and lasting circulating T-cell reactivity to both high-quality and MUC16 neoantigens in long-term survivors of pancreatic cancer, including clones with specificity to both high-quality neoantigens and predicted cross-reactive microbial epitopes, consistent with neoantigen molecular mimicry. Notably, we observed selective loss of high-quality and MUC16 neoantigenic clones on metastatic progression, suggesting neoantigen immunoediting. Our results identify neoantigens with unique qualities as T-cell targets in pancreatic ductal adenocarcinoma. More broadly, we identify neoantigen quality as a biomarker for immunogenic tumours that may guide the application of immunotherapies
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