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Genetic diagnosis of neurofibromatosis type 1: targeted next- generation sequencing with Multiple Ligation-Dependent Probe Amplification analysis
Neurofibromatosis type 1 (NF1) is a dominantly inherited tumor predisposition syndrome that targets the peripheral nervous system. It is caused by mutations of the NF1 gene which serve as a negative regulator of the cellular Ras/MAPK (mitogen-activated protein kinases) signaling pathway. Owing to th...
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Published in: | Journal of biomedical science 2018-10, Vol.25 (1), p.72-72, Article 72 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Neurofibromatosis type 1 (NF1) is a dominantly inherited tumor predisposition syndrome that targets the peripheral nervous system. It is caused by mutations of the NF1 gene which serve as a negative regulator of the cellular Ras/MAPK (mitogen-activated protein kinases) signaling pathway. Owing to the complexity in some parts of clinical diagnoses and the need for better understanding of its molecular relationships, a genetic characterization of this disorder will be helpful in the clinical setting.
In this study, we present a customized targeted gene panel of NF1/KRAS/BRAF/p53 and SPRED1 genes combined with Multiple Ligation-Dependent Probe Amplification analysis for the NF1 mutation screening in a cohort of patients clinically suspected as NF1.
In this study, we identified 73 NF1 mutations and two BRAF novel variants from 100 NF1 patients who were suspected as having NF1. These genetic alterations are heterogeneous and distribute in a complicated way without clustering in either cysteine-serine-rich domain or within the GAP-related domain. We also detected fifteen multi-exon deletions within the NF1 gene by MLPA Analysis.
Our results suggested that a genetic screening using a NGS panel with high coverage of Ras-signaling components combined with Multiple Ligation-Dependent Probe Amplification analysis will enable differential diagnosis of patients with overlapping clinical features. |
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ISSN: | 1423-0127 1021-7770 1423-0127 |
DOI: | 10.1186/s12929-018-0474-9 |