6 results on '"Juergen Lauber"'
Search Results
2. Detecting Complex Mutations in Myeloid Leukemia Using the GeneReader NGS System and QIAact Myeloid DNA UMI Panel
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Veronique Laloux, Jan K Larsen, Simon M. Hughes, Vikas Gupta, Dietrich Lueerssen, Olivier Biglia, Ferose Charifi, Sarah Lafi, Alexandre Bona, and Juergen Lauber
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Mutation ,Myeloid ,Immunology ,Myeloid leukemia ,Cell Biology ,Hematology ,Computational biology ,medicine.disease_cause ,Biochemistry ,law.invention ,Minor allele frequency ,medicine.anatomical_structure ,law ,medicine ,Indel ,Allele frequency ,Gene ,Polymerase chain reaction - Abstract
Introduction Somatic mutations acquired in key signalling pathway, transcription factor, spliceosome, epigenetic and tumor suppressor genes are of central importance in the development and progression of myeloid malignancies including myeloproliferative neoplasms (MPN), myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). To date, in order to evaluate all relevant genetic alterations, multiple tests are needed, requiring large amounts of DNA. As tests are typically performed sequentially this unnecessarily extends the time between sample acquisition and mutation detection. The QIAact Myeloid DNA UMI Panel in combination with the QIAGEN GeneReader NGS System provides a single solution to simultaneously test for actionable mutations, whilst also saving sample material (only 40ng DNA input required per sample), shortening test time and enabling simplification of lab operations. The QIAact Myeloid DNA UMI Panel is a multi-gene targeted sequencing panel designed to detect complex mutations throughout the most informative genes linked to myeloid disease. This allows reliable and sensitive detection of single nucleotide variants (SNV) and large Insertion/Deletion (InDel) mutations. Methods The QIAact Myeloid DNA UMI Panel targets 25 genes known to be important in myeloid leukemia. A key feature of the panel is the addition of a unique molecular index (UMI) to tag each individual original DNA molecule prior to target enrichment by PCR. UMIs enable sequencing and PCR bias corrections, allowing sensitive detection of mutations. To assess the assay performance, reference standards and blood and bone marrow samples were used. Following target enrichment, libraries were sequenced on the GeneReader NGS System and mutations analyzed using the QIAGEN Clinical Insight (QCI) Analyze software suite. Results To confirm DNA mutation detection, Horizon Discovery and SeraCare Reference Standards containing variants typical of myeloid malignancies were used. The anticipated DNA mutations were consistently identified both within and between runs. The samples used, including blood and bone marrow samples, demonstrated the ability of the assay to detect important large indels (52 bp deletion CALR type 1 variant) and key SNVs down to a minor allele fraction (MAF) of 1% for JAK2 (e.g. exon 12, 13, 14 & 15) and KIT (exon 8, 9, 10, 11 & 17). A sensitive variant detection of allele frequency Conclusion The QIAact Myeloid DNA UMI Panel in combination with the QIAGEN GeneReader NGS System offer a fully integrated DNA to variant detection and interpretation solution. The optimized chemistry allows superior analytical sensitivity resulting in accurate and efficient mutation detection of highly relevant genetic alterations for myeloid malignancy research. Disclosures Laloux: QIAGEN France S.A.S: Employment. Biglia:HalioDx: Employment. Bona:HalioDx: Employment. Lafi:HalioDx: Employment. Charifi:HalioDx: Employment. Larsen:QIAGEN Aarhus: Employment. Lueerssen:QIAGEN Manchester Ltd: Employment. Gupta:QIAGEN Aarhus: Employment. Lauber:QIAGEN GmbH: Employment. Hughes:QIAGEN Manchester Ltd: Employment.
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- 2018
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3. Using GeneReader NGS system to identify mutations in BRCA 1/2 genes in matched FFPE and blood samples
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Simon M. Hughes, Alexander Burton, Andrew Robb, Leif Schauser, Nathan Dennison, Bodil Oester, Adam Burke, Vishal Kapoor, Kyriakos Ttavas, Dietrich Lueerssen, Lea Thoegerson, Richard Dyson, and Juergen Lauber
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Oncology ,Cancer Research ,medicine.medical_specialty ,endocrine system diseases ,business.industry ,Germline mutation ,Clinical evidence ,Internal medicine ,Medicine ,Familial breast cancer ,skin and connective tissue diseases ,business ,Gene - Abstract
e17536Background: Supported by strong clinical evidence, testing for germline mutations in BRCA1 and BRCA2 in suspected familial breast cancer cases has gradually become common practice, especially...
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- 2018
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4. Using the GeneReader NGS system and QIAact lung all-in-one assay to detect complex mutations and fusions
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Vikas Gupta, Paola Arzuffi, Simon M. Hughes, John Blood, Alexander Burton, Dietrich Lueerssen, Leif Schauser, and Juergen Lauber
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Cancer Research ,Lung ,medicine.anatomical_structure ,Oncology ,Key genes ,Somatic cell ,business.industry ,Cancer research ,medicine ,Cancer ,Lung cancer ,medicine.disease ,business - Abstract
e21193Background: Lung cancer is the cause of 1 in 5 cancer deaths worldwide and is frequently driven by somatic mutations acquired in key genes. Targeted Next-Generation Sequencing (NGS) is a valu...
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- 2018
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5. The (strain CBS4732) genome sequencing and analysis
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Juergen Lauber, Holger Wedler, Christian Wagner, Kaj Albermann, Jean Hani, Cornelis P. Hollenberg, Ulrike Dahlems, Massoud Ramezani-Rad, Michael Piontek, Eike Griess, and Gerd Gellissen
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Genetics ,Genome evolution ,Open reading frame ,Sequence analysis ,General Medicine ,Genome project ,Biology ,ORFS ,Applied Microbiology and Biotechnology ,Microbiology ,Genome ,Genome size ,DNA sequencing - Abstract
The methylotrophic yeast Hansenula polymorpha is a recognised model system for investigation of peroxisomal function, special metabolic pathways like methanol metabolism, of nitrate assimilation or thermostability. Strain RB11, an odc1 derivative of the particular H. polymorpha isolate CBS4732 (synonymous to ATCC34438, NRRL-Y-5445, CCY38-22-2) has been developed as a platform for heterologous gene expression. The scientific and industrial significance of this organism is now being met by the characterisation of its entire genome. The H. polymorpha RB11 genome consists of approximately 9.5 Mb and is organised as six chromosomes ranging in size from 0.9 to 2.2 Mb. Over 90% of the genome was sequenced with concomitant high accuracy and assembled into 48 contigs organised on eight scaffolds (supercontigs). After manual annotation 4767 out of 5933 open reading frames (ORFs) with significant homologies to a non-redundant protein database were predicted. The remaining 1166 ORFs showed no significant similarity to known proteins. The number of ORFs is comparable to that of other sequenced budding yeasts of similar genome size.
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- 2003
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6. The Hansenula polymorpha (strain CBS4732) genome sequencing and analysis
- Author
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Massoud, Ramezani-Rad, Cornelis P, Hollenberg, Juergen, Lauber, Holger, Wedler, Eike, Griess, Christian, Wagner, Kaj, Albermann, Jean, Hani, Michael, Piontek, Ulrike, Dahlems, and Gerd, Gellissen
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Open Reading Frames ,Base Sequence ,Genes, Fungal ,Molecular Sequence Data ,Saccharomyces cerevisiae ,Sequence Analysis, DNA ,Genome, Fungal ,DNA, Fungal ,Databases, Protein ,Pichia ,Gene Library - Abstract
The methylotrophic yeast Hansenula polymorpha is a recognised model system for investigation of peroxisomal function, special metabolic pathways like methanol metabolism, of nitrate assimilation or thermostability. Strain RB11, an odc1 derivative of the particular H. polymorpha isolate CBS4732 (synonymous to ATCC34438, NRRL-Y-5445, CCY38-22-2) has been developed as a platform for heterologous gene expression. The scientific and industrial significance of this organism is now being met by the characterisation of its entire genome. The H. polymorpha RB11 genome consists of approximately 9.5 Mb and is organised as six chromosomes ranging in size from 0.9 to 2.2 Mb. Over 90% of the genome was sequenced with concomitant high accuracy and assembled into 48 contigs organised on eight scaffolds (supercontigs). After manual annotation 4767 out of 5933 open reading frames (ORFs) with significant homologies to a non-redundant protein database were predicted. The remaining 1166 ORFs showed no significant similarity to known proteins. The number of ORFs is comparable to that of other sequenced budding yeasts of similar genome size.
- Published
- 2003
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