Publications by authors named "Frank Juhn"

As more clinically relevant cancer genes are identified, comprehensive diagnostic approaches are needed to match patients to therapies, raising the challenge of optimization and analytical validation of assays that interrogate millions of bases of cancer genomes altered by multiple mechanisms. Here we describe a test based on massively parallel DNA sequencing to characterize base substitutions, short insertions and deletions (indels), copy number alterations and selected fusions across 287 cancer-related genes from routine formalin-fixed and paraffin-embedded (FFPE) clinical specimens. We implemented a practical validation strategy with reference samples of pooled cell lines that model key determinants of accuracy, including mutant allele frequency, indel length and amplitude of copy change.

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Applying a next-generation sequencing assay targeting 145 cancer-relevant genes in 40 colorectal cancer and 24 non-small cell lung cancer formalin-fixed paraffin-embedded tissue specimens identified at least one clinically relevant genomic alteration in 59% of the samples and revealed two gene fusions, C2orf44-ALK in a colorectal cancer sample and KIF5B-RET in a lung adenocarcinoma. Further screening of 561 lung adenocarcinomas identified 11 additional tumors with KIF5B-RET gene fusions (2.0%; 95% CI 0.

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Genome targeting methods enable cost-effective capture of specific subsets of the genome for sequencing. We present here an automated, highly scalable method for carrying out the Solution Hybrid Selection capture approach that provides a dramatic increase in scale and throughput of sequence-ready libraries produced. Significant process improvements and a series of in-process quality control checkpoints are also added.

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We present an automated, high throughput library construction process for 454 technology. Sample handling errors and cross-contamination are minimized via end-to-end barcoding of plasticware, along with molecular DNA barcoding of constructs. Automation-friendly magnetic bead-based size selection and cleanup steps have been devised, eliminating major bottlenecks and significant sources of error.

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An anionic amphiphilic dendrimer is reported that possesses increased cytotoxicological potency against prokaryotic cells compared to eukaryotic cells. The half-maximal effective concentration (EC50) for the dendrimer against Bacillus subtilis, a Gram-positive bacterial strain, was measured to be 4.1 x 10(-5) M, while that against human umbilical vein endothelial cells (HUVEC) was more than 36x greater at a value of 1.

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To identify pathways of carbon utilization in the metal-reducing marine bacterium Shewanella oneidensis MR-1, we assayed the expression of cells grown with various carbon sources using a high-density oligonucleotide Affymetrix microarray. Our expression profiles reveal genes and regulatory mechanisms which govern the sensing, import, and utilization of the nucleoside inosine, the chitin monomer N-acetylglucosamine, and a casein-derived mixture of amino acids. Our analysis suggests a prominent role for the pentose-phosphate and Entner-Doudoroff pathways in energy metabolism, and regulatory coupling between carbon catabolism and electron acceptor pathways.

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An iterative position-specific score matrix (PSSM)-based approach was used to predict sigma(28) promoters in 11 Shewanella genomes. The Shewanella Correlation Browser was used to distinguish true-positive predictions from false-positive predictions in Shewanella oneidensis MR-1 by generating a sigma(28)-regulated transcriptional network from transcriptional profiling data. This dual-pronged approach identified several genes that have sigma(28) promoters and that may be involved with motility or chemotaxis in Shewanella.

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Many Microbe Microarrays Database (M3D) is designed to facilitate the analysis and visualization of expression data in compendia compiled from multiple laboratories. M3D contains over a thousand Affymetrix microarrays for Escherichia coli, Saccharomyces cerevisiae and Shewanella oneidensis. The expression data is uniformly normalized to make the data generated by different laboratories and researchers more comparable.

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