Analysis of genetic variants in myeloproliferative neoplasms using a 22-gene next-generation sequencing panel

被引:2
作者
Tan, Jaymi [1 ]
Chow, Yock Ping [2 ]
Abidin, Norziha Zainul [3 ]
Chang, Kian Meng [4 ]
Selvaratnam, Veena [5 ]
Tumian, Nor Rafeah [6 ]
Poh, Yang Ming [7 ]
Veerakumarasivam, Abhi [1 ]
Laffan, Michael Arthur [8 ,9 ]
Wong, Chieh Lee [1 ,2 ,3 ,4 ,8 ,9 ]
机构
[1] Sunway Univ, Sch Med & Life Sci, Dept Biol Sci, Petaling Jaya, Selangor, Malaysia
[2] Sunway Med Ctr, Clin Res Ctr, Petaling Jaya, Selangor Darul, Malaysia
[3] Sunway Med Ctr, Mol Diagnost Lab, Petaling Jaya, Selangor Darul, Malaysia
[4] Sunway Med Ctr, Dept Med, Haematol Unit, Petaling Jaya, Selangor Darul, Malaysia
[5] Ampang Hosp, Haematol Dept, Kuala Lumpur, Malaysia
[6] Univ Kebangsaan Malaysia, Dept Med, Haematol Unit, Med Ctr, Kuala Lumpur, Malaysia
[7] Perdana Univ, Sch Data Sci, Serdang, Selangor, Malaysia
[8] Hammersmith Hosp, Ctr Haematol, London, England
[9] Imperial Coll London, Fac Med, London, England
关键词
Myeloproliferative neoplasm; Next-generation sequencing; Gene; Mutation; Variant; Bioinformatics; disease management; ESSENTIAL THROMBOCYTHEMIA; MUTATION ORDER; SANGER; TET2; ASXL1; CLASSIFICATION; INHIBITOR; LANDSCAPE; DIAGNOSIS; RECURRENT;
D O I
10.1186/s12920-021-01145-0
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Background The Philadelphia (Ph)-negative myeloproliferative neoplasms (MPNs), namely essential thrombocythaemia (ET), polycythaemia vera (PV) and primary myelofibrosis (PMF), are a group of chronic clonal haematopoietic disorders that have the propensity to advance into bone marrow failure or acute myeloid leukaemia; often resulting in fatality. Although driver mutations have been identified in these MPNs, subtype-specific markers of the disease have yet to be discovered. Next-generation sequencing (NGS) technology can potentially improve the clinical management of MPNs by allowing for the simultaneous screening of many disease-associated genes. Methods The performance of a custom, in-house designed 22-gene NGS panel was technically validated using reference standards across two independent replicate runs. The panel was subsequently used to screen a total of 10 clinical MPN samples (ET n = 3, PV n = 3, PMF n = 4). The resulting NGS data was then analysed via a bioinformatics pipeline. Results The custom NGS panel had a detection limit of 1% variant allele frequency (VAF). A total of 20 unique variants with VAFs above 5% (4 of which were putatively novel variants with potential biological significance) and one pathogenic variant with a VAF of between 1 and 5% were identified across all of the clinical MPN samples. All single nucleotide variants with VAFs >= 15% were confirmed via Sanger sequencing. Conclusions The high fidelity of the NGS analysis and the identification of known and novel variants in this study cohort support its potential clinical utility in the management of MPNs. However, further optimisation is needed to avoid false negatives in regions with low sequencing coverage, especially for the detection of driver mutations in MPL.
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