An ultra-deep sequencing strategy to detect sub-clonal TP53 mutations in presentation chronic lymphocytic leukemia cases using multiple polymerases
| Autor: | Reuben Tooze, Paul Evans, Peter Hillmen, Praveen Baskaran, Darren J. Newton, Sheila J.M. O’Connor, Lisa Worrillow, Andy C. Rawstron, Talha Munir, Abraham M. Varghese, Matthew A. Care, Lee Hazelwood |
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| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Adult Male Cancer Research DNA damage Biology Deep sequencing 03 medical and health sciences chemistry.chemical_compound Genetics medicine Humans Molecular Biology Gene Transcription factor neoplasms Aged Cancer High-Throughput Nucleotide Sequencing Cell cycle Middle Aged medicine.disease Prognosis Leukemia Lymphocytic Chronic B-Cell Fludarabine 030104 developmental biology chemistry Mutation Cancer research Female Neoplasm Recurrence Local Tumor Suppressor Protein p53 DNA medicine.drug |
| ISSN: | 0950-9232 |
| Popis: | Chronic lymphocytic leukaemia (CLL) is the most common clonal B-cell disorder characterized by clonal diversity, a relapsing and remitting course, and in its aggressive forms remains largely incurable. Current front-line regimes include agents such as fludarabine, which act primarily via the DNA damage response pathway. Key to this is the transcription factor p53. Mutations in the TP53 gene, altering p53 functionality, are associated with genetic instability, and are present in aggressive CLL. Furthermore, the emergence of clonal TP53 mutations in relapsed CLL, refractory to DNA-damaging therapy, suggests that accurate detection of sub-clonal TP53 mutations prior to and during treatment may be indicative of early relapse. In this study, we describe a novel deep sequencing workflow using multiple polymerases to generate sequencing libraries (MuPol-Seq), facilitating accurate detection of TP53 mutations at a frequency as low as 0.3%, in presentation CLL cases tested. As these mutations were mostly clustered within the regions of TP53 encoding DNA-binding domains, essential for DNA contact and structural architecture, they are likely to be of prognostic relevance in disease progression. The workflow described here has the potential to be implemented routinely to identify rare mutations across a range of diseases. |
| Databáze: | OpenAIRE |
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