Lab Med Qual Assur 2022; 44(2): 76-81
Published online June 30, 2022
https://doi.org/10.15263/jlmqa.2022.44.2.76
Copyright © Korean Association of External Quality Assessment Service.
Miyoung Kim1 , Nan Young Kim2
, Sangkyoon Hong2
, Jiwon Lee3
, Yonggeun Cho4
, Han-Sung Kim4
, Hee Jung Kang4
, and Young Kyung Lee4
1Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul; 2Hallym Institute of Translational Genomics and Bioinformatics, Hallym University Medical Center, Anyang; 3Department of Laboratory Medicine, Green Cross Laboratories, Yongin; 4Department of Laboratory Medicine, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Korea
Correspondence to:Miyoung Kim
Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Korea
Tel +82-2-3010-4498
E-mail miyoungkim@amc.seoul.kr
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background: The ASXL1 codon 646 variant is the most common ASXL1 variant that negatively impacts the prognoses of patients with myeloid malignancies, particularly those with myelodysplastic syndromes and acute myeloid leukemia. However, it has been suggested that this mutation is not somatic but rather an artifact of next-generation sequencing (NGS) owing to its location in an 8 bp guanine mononucleotide repeat. In this study, we evaluated the performance of amplicon-based NGS in discriminating the ASXL1 codon 646 variant.
Methods: Amplicon-based NGS was performed on the Myeloid DNA Reference Standard HD829 in varying reference material dilution ratios using the TruSight Myeloid panel and a MiSeqDx system.
Results: The expected and measured variant allele frequencies (VAFs) of the ASXL1 codon 646 mutation in the reference material were 40.00% and 18.65%, respectively. The measured VAFs in reference materials serially diluted at 1:1, 1:2, 1:4, and 1:8 were 9.09%, 5.82%, 1.92%, and 2.87%, respectively (y=0.4391x+0.8642; r2=0.9846). Most of the other variants showed VAFs comparable to expected VAFs.
Conclusions: The measured allele frequencies of the ASXL1 codon 646 variant in the serially diluted reference materials were approximately half their expected values, suggesting difficulties in the correct detection of the variant using amplicon-based NGS.
Keywords: ASXL1, Amplicon, Variant allele frequency, Next-generation sequencing
이에 본 연구에서는 환자 검체와 상품화된 정도관리물질을 이용하여 엠플리콘 기반의 차세대염기서열분석법의
상품화된 정도관리물질인 Myeloid DNA Reference Standard (Horizon Discovery Ltd., Cambridge, UK)를 사용하였다. 이 물질은
골수구계 종양에서 흔히 변이가 관찰되는 54개의 유전자에 대한 엠플리콘 기반 차세대염기서열 분석패널인 TruSight Myeloid (Illumina, San Diego, CA, USA) 패널을 이용해 염기순서분석 라이브러리(library)를 제작하였고, MiSeq Dx (Illumina) 기기로 분석하였다. “Phred” 질 점수(quality score)가 30 이상, 염기순서분석 깊이(read depth)가 500× 이상인 변이를 포함하였다.
Myeloid DNA Reference Standard에서 관찰되는 것으로 알려진 변이의 존재 유무를 비교하고, VAF의 기대값과 측정값의 관계를 Pearson’s correlation을 통해 분석하였다. VAF의 기대값과 측정값의 차이는 “discrepancy (%)”로 나타냈으며, 이 값은 [(측정 VAF–예상 VAF)/예상 VAF×100]으로 하였다. 분석에는 Excel 2016 (Microsoft Corp., Redmond, WA, USA)을 이용하였다.
Myeloid DNA Reference Standard에 존재하는 것으로 알려진 22개 변이는 원액으로 검사하였을 때 모두 검출되었다. 원액에서의 discrepancy (%)는
Table 1 . Expected and measured VAFs of 21 variants in different dilution ratios using amplicon-based next-generation sequencing
Variants | Dilution ratio (%) | Equation | |||||
---|---|---|---|---|---|---|---|
Undiluted | 1:1 | 1:2 | 1:4 | 1:8 | |||
y=1.3059x–0.3469 | 0.9445 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 6.61 | 2.20 | 0.70 | 0.80 | 0.61 | ||
Discrepancy* | 32.27 | –12.05 | –44.24 | 28.31 | 93.66 | ||
y=1.0839x–0.0400 | 0.9948 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 5.45 | 2.58 | 1.11 | 0.82 | 0.34 | ||
Discrepancy | 9.00 | 3.20 | –11.20 | 31.20 | 8.80 | ||
y=0.7530x+0.2850 | 0.9919 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 4.02 | 2.30 | 1.11 | 0.63 | 0.66 | ||
Discrepancy | –19.60 | –8.00 | –11.20 | 0.80 | 111.20 | ||
y=0.4017x–0.3717 | 0.8243 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 2.42 | 1.05 | 1.43 | 0.64 | 0.21 | ||
Discrepancy | –51.60 | –58.00 | 14.40 | 2.40 | –32.80 | ||
y=1.0351x+0.1804 | 0.9545 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 5.64 | 2.02 | 1.77 | 0.92 | 0.58 | ||
Discrepancy | 12.80 | –19.20 | 41.60 | 47.20 | 85.60 | ||
y=0.9507x–0.0779 | 0.9873 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 4.77 | 2.22 | 0.80 | 0.58 | 0.45 | ||
Discrepancy | –4.60 | –11.20 | –36.00 | –7.20 | 44.00 | ||
y=0.6163x+0.6779 | 0.8493 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 3.52 | 2.44 | 2.18 | 0.91 | 0.31 | ||
Discrepancy | –29.60 | –2.40 | 74.40 | 45.60 | –0.80 | ||
y=1.2016x+0.3079 | 0.9230 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 5.89 | 4.45 | 1.31 | 0.98 | 0.55 | ||
Discrepancy | 17.80 | 78.00 | 4.80 | 56.80 | 76.00 | ||
y=0.9561x–0.0504 | 0.9833 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 4.58 | 2.57 | 1.43 | 0.33 | 0.10 | ||
Discrepancy | –8.40 | 2.80 | 14.40 | –47.20 | –68.00 | ||
y=0.7071x–0.4121 | 0.8533 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 3.53 | 0.37 | 0.68 | 0.21 | 0.00 | ||
Discrepancy | –29.40 | –85.20 | –45.60 | –66.40 | –100.00 | ||
y=0.4414x+0.4988 | 0.6824 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 2.34 | 2.23 | 1.63 | 0.13 | 0.44 | ||
Discrepancy | –53.20 | –10.80 | 30.40 | –79.20 | 40.80 | ||
y=0.8877x+0.0521 | 0.9967 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 4.48 | 2.36 | 1.01 | 0.60 | 0.41 | ||
Discrepancy | –10.40 | –5.60 | –19.20 | –4.00 | 31.20 | ||
y=1.2071x–0.2808 | 0.8669 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 6.42 | 1.16 | 1.53 | 0.63 | 0.55 | ||
Discrepancy | 28.40 | –53.60 | 22.40 | 0.80 | 76.00 | ||
y=1.000x+0.4704 | 0.9603 | ||||||
Expected VAF | 5.00 | 2.50 | 1.25 | 0.63 | 0.31 | ||
Measured VAF | 5.38 | 2.92 | 2.39 | 0.80 | 0.55 | ||
Discrepancy | 7.60 | 16.80 | 91.20 | 28.00 | 76.00 | ||
y=0.8621x+0.8854 | 0.9116 | ||||||
Expected VAF | 10.00 | 5.00 | 2.50 | 1.25 | 0.63 | ||
Measured VAF | 9.82 | 4.15 | 3.47 | 3.29 | 0.40 | ||
Discrepancy | –1.80 | –17.00 | 38.80 | 163.20 | –36.00 | ||
y=1.0731x+5.0021 | 0.9729 | ||||||
Expected VAF | 35.00 | 17.50 | 8.75 | 4.38 | 2.19 | ||
Measured VAF | 40.74 | 27.78 | 14.71 | 8.06 | 6.49 | ||
Discrepancy | 16.40 | 58.74 | 68.11 | 84.23 | 196.69 | ||
y=1.043x–1.0113 | 0.9801 | ||||||
Expected VAF | 35.00 | 17.50 | 8.75 | 4.38 | 2.19 | ||
Measured VAF | 34.31 | 20.56 | 6.60 | 2.60 | 1.60 | ||
Discrepancy | –1.97 | 17.49 | –24.57 | –40.57 | –26.86 | ||
y=0.4391x+0.8642 | 0.9846 | ||||||
Expected VAF | 40.00 | 20.00 | 10.00 | 5.00 | 2.50 | ||
Measured VAF | 18.65 | 9.09 | 5.82 | 1.92 | 2.87 | ||
Discrepancy | –53.38 | –54.55 | –41.80 | –61.60 | 14.80 | ||
y=0.9612x+0.9617 | 0.9944 | ||||||
Expected VAF | 40.00 | 20.00 | 10.00 | 5.00 | 2.50 | ||
Measured VAF | 38.57 | 21.75 | 11.20 | 5.52 | 2.26 | ||
Discrepancy | –3.58 | 8.75 | 12.00 | 10.40 | –9.60 | ||
y=0.9654x–0.6417 | 0.9942 | ||||||
Expected VAF | 70.00 | 35.00 | 17.50 | 8.75 | 4.38 | ||
Measured VAF | 68.06 | 30.21 | 17.88 | 6.69 | 4.89 | ||
Discrepancy | –2.77 | –13.69 | 2.17 | –23.54 | 11.77 |
Abbreviation: VAF, variant allele frequency
*Discrepancy: (measured VAF–expected VAF)/expected VAF×100
본 연구는
분석대상이었던 21개의 변이는 원액에서 모두 검출되었다. 또한 정량적인 부분에 있어
원액의 VAF가 10% 이상인 6개의 변이 중
반면,
연구의 한계점으로는 위에서도 언급된 바와 같이 본 연구에서 관찰된 결과가 일회성인지, 일반적인 결과인지를 확인하기 위한 반복검사가 시행되지 못했다는 점이다. 추후 연구에서 반복 측정하여 평균값이나 중위값을 산출하는 것이 결과의 일반화에 도움이 될 것이다. 또 하나의 한계점으로는 검체 희석에 사용한 혈액종양으로 진단받지 않은 환자의 gDNA에 대해
본 연구에서는 희석을 통한 다양한 농도의 상품화된 정도관리물질을 이용하여 특정 패널과 기기를 이용한 차세대염기서열분석법의 경우
이 연구는 대한임상검사정도관리협회의 2020년도 학술연구과제 연구비 지원으로 수행되었다(과제번호: 2020-11).
Supplementary materials can be found via https://doi.org/10.15263/jlmqa.2022.44.2.76
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