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Next-generation deep sequencing improves detection of BCR-ABL1 kinase domain mutations emerging under tyrosine kinase inhibitor treatment of chronic myeloid leukemia patients in chronic phase
K. Machova Polakova, V. Kulvait, A. Benesova, J. Linhartova, H. Klamova, M. Jaruskova, C. de Benedittis, T. Haferlach, M. Baccarani, G. Martinelli, T. Stopka, T. Ernst, A. Hochhaus, A. Kohlmann, S. Soverini,
Jazyk angličtina Země Německo
Typ dokumentu časopisecké články, práce podpořená grantem
Grantová podpora
NT11555
MZ0
CEP - Centrální evidence projektů
NT13899
MZ0
CEP - Centrální evidence projektů
Digitální knihovna NLK
Plný text - Článek
Zdroj
NLK
PubMed Central
od 1979
ProQuest Central
od 2012-01-01 do 2017-12-31
Medline Complete (EBSCOhost)
od 2003-04-01
Health & Medicine (ProQuest)
od 2012-01-01 do 2017-12-31
Public Health Database (ProQuest)
od 2012-01-01 do 2017-12-31
ROAD: Directory of Open Access Scholarly Resources
od 1997
- MeSH
- bcr-abl fúzní proteiny genetika MeSH
- benzamidy terapeutické užití MeSH
- chronická myeloidní leukemie farmakoterapie genetika MeSH
- dospělí MeSH
- inhibitory proteinkinas terapeutické užití MeSH
- lidé středního věku MeSH
- lidé MeSH
- longitudinální studie MeSH
- mutace účinky léků MeSH
- piperaziny terapeutické užití MeSH
- polymerázová řetězová reakce s reverzní transkripcí MeSH
- protinádorové látky terapeutické užití MeSH
- pyrimidiny terapeutické užití MeSH
- retrospektivní studie MeSH
- senioři MeSH
- tyrosinkinasy antagonisté a inhibitory MeSH
- výpočetní biologie MeSH
- vysoce účinné nukleotidové sekvenování * MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
PURPOSE: Here, we studied whether amplicon next-generation deep sequencing (NGS) could improve the detection of emerging BCR-ABL1 kinase domain mutations in chronic phase chronic myeloid leukemia (CML) patients under tyrosine kinase inhibitor (TKI) treatment and discussed the clinical relevance of such sensitive mutational detection. METHODS: For NGS data evaluation including extraction of biologically relevant low-level variants from background error noise, we established and applied a robust and versatile bioinformatics approach. RESULTS: Results from a retrospective longitudinal analysis of 135 samples of 15 CML patients showed that NGS could have revealed emerging resistant mutants 2-11 months earlier than conventional sequencing. Interestingly, in cases who later failed first-line imatinib treatment, NGS revealed that TKI-resistant mutations were already detectable at the time of major or deeper molecular response. Identification of emerging mutations by NGS was mirrored by BCR-ABL1 transcript level expressed either fluctuations around 0.1 %(IS) or by slight transcript level increase. NGS also allowed tracing mutations that emerged during second-line TKI therapy back to the time of switchover. Compound mutants could be detected in three cases, but were not found to outcompete single mutants. CONCLUSIONS: This work points out, that next-generation deep sequencing, coupled with a robust bioinformatics approach for mutation calling, may be just in place to ensure reliable detection of emerging BCR-ABL1 mutations, allowing early therapy switch and selection of the most appropriate therapy. Further, prospective assessment of how to best integrate NGS in the molecular monitoring and clinical decision algorithms is warranted.
Citace poskytuje Crossref.org
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