589 research outputs found

    VarDict: a novel and versatile variant caller for next-generation sequencing in cancer research

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    Accurate variant calling in next generation sequencing (NGS) is critical to understand cancer genomes better. Here we present VarDict, a novel and versatile variant caller for both DNA- and RNA-sequencing data. VarDict simultaneously calls SNV, MNV, InDels, complex and structural variants, expanding the detected genetic driver landscape of tumors. It performs local realignments on the fly for more accurate allele frequency estimation. VarDict performance scales linearly to sequencing depth, enabling ultra-deep sequencing used to explore tumor evolution or detect tumor DNA circulating in blood. In addition, VarDict performs amplicon aware variant calling for polymerase chain reaction (PCR)-based targeted sequencing often used in diagnostic settings, and is able to detect PCR artifacts. Finally, VarDict also detects differences in somatic and loss of heterozygosity variants between paired samples. VarDict reprocessing of The Cancer Genome Atlas (TCGA) Lung Adenocarcinoma dataset called known driver mutations in KRAS, EGFR, BRAF, PIK3CA and MET in 16% more patients than previously published variant calls. We believe VarDict will greatly facilitate application of NGS in clinical cancer research

    Immune Cell Abundance and T-cell Receptor Landscapes Suggest New Patient Stratification Strategies in Head and Neck Squamous Cell Carcinoma

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    Head and neck squamous cell carcinoma (HNSCC) is a molecularly and spatially heterogeneous disease frequently characterized by impairment of immunosurveillance mechanisms. Despite recent success with immunotherapy treatment, disease progression still occurs quickly after treatment in the majority of cases, suggesting the need to improve patient selection strategies. In the quest for biomarkers that may help inform response to checkpoint blockade, we characterized the tumor microenvironment (TME) of 162 HNSCC primary tumors of diverse etiologic and spatial origin, through gene expression and IHC profiling of relevant immune proteins, T-cell receptor (TCR) repertoire analysis, and whole-exome sequencing. We identified five HNSCC TME categories based on immune/stromal composition: (i) cytotoxic, (ii) plasma cell rich, (iii) dendritic cell rich, (iv) macrophage rich, and (v) immune-excluded. Remarkably, the cytotoxic and plasma cell rich subgroups exhibited a phenotype similar to tertiary lymphoid structures (TLS), which have been previously linked to immunotherapy response. We also found an increased richness of the TCR repertoire in these two subgroups and in never smokers. Mutational patterns evidencing APOBEC activity were enriched in the plasma cell high subgroup. Furthermore, specific signal propagation patterns within the Ras/ERK and PI3K/AKT pathways associated with distinct immune phenotypes. While traditionally CD8/CD3 T-cell infiltration and immune checkpoint expression (e.g., PD-L1) have been used in the patient selection process for checkpoint blockade treatment, we suggest that additional biomarkers, such as TCR productive clonality, smoking history, and TLS index, may have the ability to pull out potential responders to benefit from immunotherapeutic agents. // Significance: Here we present our findings on the genomic and immune landscape of primary disease in a cohort of 162 patients with HNSCC, benefitting from detailed molecular and clinical characterization. By employing whole-exome sequencing and gene expression analysis of relevant immune markers, TCR profiling, and staining of relevant proteins involved in immune response, we highlight how distinct etiologies, cell intrinsic, and environmental factors combine to shape the landscape of HNSCC primary disease

    Focused Ion Beam Fabrication

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    Contains reports on five research projects.DARPA/Naval Electronic Systems Command (Contract MDA-903-85-C-0215)Charles Stark Draper Laboratory (Contract DL-H-261827)U.S. Navy - Office of Naval Research (Contract N00014-84-K-0073)Nippon Telephone and TelegraphHitachi Central Research Laborator

    The Fibroid Growth Study: Determinants of Therapeutic Intervention

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    The demographics, ethnicity, symptoms, lifestyle characteristics, and treatment outcomes are analyzed in participants of a study designed to evaluate uterine leiomyoma growth and correlate symptoms and outcomes in a clinically relevant population of women (Fibroid Growth Study)

    GoMiner: a resource for biological interpretation of genomic and proteomic data

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    We have developed GoMiner, a program package that organizes lists of 'interesting' genes (for example, under- and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology. GoMiner provides quantitative and statistical output files and two useful visualizations. The first is a tree-like structure analogous to that in the AmiGO browser and the second is a compact, dynamically interactive 'directed acyclic graph'. Genes displayed in GoMiner are linked to major public bioinformatics resources

    Impact of DNA damage repair alterations on prostate cancer progression and metastasis

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    Prostate cancer is among the most common diseases worldwide. Despite recent progress with treatments, patients with advanced prostate cancer have poor outcomes and there is a high unmet need in this population. Understanding molecular determinants underlying prostate cancer and the aggressive phenotype of disease can help with design of better clinical trials and improve treatments for these patients. One of the pathways often altered in advanced prostate cancer is DNA damage response (DDR), including alterations in BRCA1/2 and other homologous recombination repair (HRR) genes. Alterations in the DDR pathway are particularly prevalent in metastatic prostate cancer. In this review, we summarise the prevalence of DDR alterations in primary and advanced prostate cancer and discuss the impact of alterations in the DDR pathway on aggressive disease phenotype, prognosis and the association of germline pathogenic1 alterations in DDR genes with risk of developing prostate cancer

    Three microarray platforms: an analysis of their concordance in profiling gene expression

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    BACKGROUND: Microarrays for the analysis of gene expression are of three different types: short oligonucleotide (25–30 base), long oligonucleotide (50–80 base), and cDNA (highly variable in length). The short oligonucleotide and cDNA arrays have been the mainstay of expression analysis to date, but long oligonucleotide platforms are gaining in popularity and will probably replace cDNA arrays. As part of a validation study for the long oligonucleotide arrays, we compared and contrasted expression profiles from the three formats, testing RNA from six different cell lines against a universal reference standard. RESULTS: The three platforms had 6430 genes in common. In general, correlation of gene expression levels across the platforms was good when defined by concordance in the direction of expression difference (upregulation or downregulation), scatter plot analysis, principal component analysis, cell line correlation or quantitative RT-PCR. The overall correlations (r values) between platforms were in the range 0.7 to 0.8, as determined by analysis of scatter plots. When concordance was measured for expression ratios significant at p-values of <0.05 and at expression threshold levels of 1.5 and 2-fold, the agreement among the platforms was very high, ranging from 93% to 100%. CONCLUSION: Our results indicate that the long oligonucleotide platform is highly suitable for expression analysis and compares favorably with the cDNA and short oligonucleotide varieties. All three platforms can give similar and reproducible results if the criterion is the direction of change in gene expression and minimal emphasis is placed on the magnitude of change
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