Comparative analysis of targeted next-generation sequencing panels for the detection of gene mutations in chronic lymphocytic leukemia: an ERIC multi-center study
Language English Country Italy Media electronic
Document type Journal Article, Multicenter Study, Research Support, Non-U.S. Gov't
Grant support
C34999/A18087
Cancer Research UK - United Kingdom
PubMed
32273480
PubMed Central
PMC7927885
DOI
10.3324/haematol.2019.234716
PII: haematol.2019.234716
Knihovny.cz E-resources
- MeSH
- Leukemia, Lymphocytic, Chronic, B-Cell * diagnosis genetics MeSH
- Humans MeSH
- Mutation MeSH
- Reproducibility of Results MeSH
- High-Throughput Nucleotide Sequencing MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Multicenter Study MeSH
- Research Support, Non-U.S. Gov't MeSH
Next-generation sequencing (NGS) has transitioned from research to clinical routine, yet the comparability of different technologies for mutation profiling remains an open question. We performed a European multicenter (n=6) evaluation of three amplicon-based NGS assays targeting 11 genes recurrently mutated in chronic lymphocytic leukemia. Each assay was assessed by two centers using 48 pre-characterized chronic lymphocytic leukemia samples; libraries were sequenced on the Illumina MiSeq instrument and bioinformatics analyses were centralized. Across all centers the median percentage of target reads ≥100x ranged from 94.2- 99.8%. In order to rule out assay-specific technical variability, we first assessed variant calling at the individual assay level i.e., pairwise analysis of variants detected amongst partner centers. After filtering for variants present in the paired normal sample and removal of PCR/sequencing artefacts, the panels achieved 96.2% (Multiplicom), 97.7% (TruSeq) and 90% (HaloPlex) concordance at a variant allele frequency (VAF) >0.5%. Reproducibility was assessed by looking at the inter-laboratory variation in detecting mutations and 107 of 115 (93% concordance) mutations were detected by all six centers, while the remaining eight variants (7%) were undetected by a single center. Notably, 6 of 8 of these variants concerned minor subclonal mutations (VAF <5%). We sought to investigate low-frequency mutations further by using a high-sensitivity assay containing unique molecular identifiers, which confirmed the presence of several minor subclonal mutations. Thus, while amplicon-based approaches can be adopted for somatic mutation detection with VAF >5%, after rigorous validation, the use of unique molecular identifiers may be necessary to reach a higher sensitivity and ensure consistent and accurate detection of low-frequency variants.
AP HP Hopital Pitie Salpetriere Department of Hematology Sorbonne Université Paris France
Cancer Sciences Faculty of Medicine University of Southampton Southampton UK;
Clinical Genetics Karolinska University Laboratory Karolinska University Hospital Stockholm Sweden
Department of Hematology Royal Bournemouth Hospital Bournemouth UK
Department of Internal Medicine 3 Ulm University Ulm Germany
Department of Molecular Medicine and Surgery Karolinska Institutet Stockholm Sweden
Institute of Applied Biosciences Center for Research and Technology Thessaloniki Greec
See more in PubMed
Fabbri G, Rasi S, Rossi D, et al. . Analysis of the chronic lymphocytic leukemia coding genome: role of NOTCH1 mutational activation. J Exp Med. 2011;208(7):1389-1401. PubMed PMC
Puente XS, Pinyol M, Quesada V, et al. . Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia. Nature. 2011;475(7354):101-105. PubMed PMC
Quesada V, Conde L, Villamor N, et al. . Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia. Nat Genet. 2011;44(1):47-52. PubMed
Wang LL, Lawrence MS, Wan YZ, et al. . SF3B1 and other novel cancer genes in chronic lymphocytic leukemia. N Engl J Med. 2011;365(26):2497-2506. PubMed PMC
Puente XS, Bea S, Valdes-Mas R, et al. . Noncoding recurrent mutations in chronic lymphocytic leukaemia. Nature. 2015; 526(7574):519-524. PubMed
Landau DA, Tausch E, Taylor-Weiner AN, et al. . Mutations driving CLL and their evolution in progression and relapse. Nature. 2015;526(7574):525-530. PubMed PMC
Sutton LA, Rosenquist R. Deciphering the molecular landscape in chronic lymphocytic leukemia: time frame of disease evolution. Haematologica. 2015;100(1):7-16. PubMed PMC
Mansouri L, Sutton LA, Ljungstrom V, et al. . Functional loss of I kappa B epsilon leads to NF-kappa B deregulation in aggressive chronic lymphocytic leukemia. J Exp Med. 2015;212(6):833-843. PubMed PMC
Ljungstrom V, Cortese D, Young E, et al. . Whole-exome sequencing in relapsing chronic lymphocytic leukemia: clinical impact of recurrent RPS15 mutations. Blood. 2016;127(8):1007-1016. PubMed PMC
Young E, Noerenberg D, Mansouri L, et al. . EGR2 mutations define a new clinically aggressive subgroup of chronic lymphocytic leukemia. Leukemia. 2017;31(7):1547-1554. PubMed PMC
Zenz T, Eichhorst B, Busch R, et al. . TP53 mutation and survival in chronic lymphocytic leukemia. J Clin Oncol. 2010;28(29): 4473-4479. PubMed
Del Giudice I, Rossi D, Chiaretti S, et al. . NOTCH1 mutations in+12 chronic lymphocytic leukemia (CLL) confer an unfavorable prognosis, induce a distinctive transcriptional profiling and refine the intermediate prognosis of+12 CLL. Haematologica. 2012; 97(3):437-441. PubMed PMC
Rossi D, Fangazio M, Rasi S, et al. . Disruption of BIRC3 associates with fludarabine chemorefractoriness in TP53 wildtype chronic lymphocytic leukemia. Blood. 2012;119(12):2854-2862. PubMed
Rossi D, Rasi S, Spina V, et al. . Integrated mutational and cytogenetic analysis identifies new prognostic subgroups in chronic lymphocytic leukemia. Blood. 2013; 121(8):1403-1412. PubMed PMC
Strefford JC, Sutton LA, Baliakas P, et al. . Distinct patterns of novel gene mutations in poor-prognostic stereotyped subsets of chronic lymphocytic leukemia: the case of SF3B1 and subset #2. Leukemia. 2013;27(11):2196-2199. PubMed
Cortese D, Sutton LA, Cahill N, et al. . On the way towards a 'CLL prognostic index': focus on TP53, BIRC3, SF3B1, NOTCH1 and MYD88 in a population-based cohort. Leukemia. 2014;28(3):710-713. PubMed
Jeromin S, Weissmann S, Haferlach C, et al. . SF3B1 mutations correlated to cytogenetics and mutations in NOTCH1, FBXW7, MYD88, XPO1 and TP53 in 1160 untreated CLL patients. Leukemia. 2014;28(1):108-117. PubMed
Stilgenbauer S, Schnaiter A, Paschka P, et al. . Gene mutations and treatment outcome in chronic lymphocytic leukemia: results from the CLL8 trial. Blood. 2014;123(21):3247-3254. PubMed
Baliakas P, Hadzidimitriou A, Sutton LA, et al. . Recurrent mutations refine prognosis in chronic lymphocytic leukemia. Leukemia. 2015;29(2):329-336. PubMed
Sutton LA, Young E, Baliakas P, et al. . Different spectra of recurrent gene mutations in subsets of chronic lymphocytic leukemia harboring stereotyped B-cell receptors. Haematologica. 2016;101(8):959-967. PubMed PMC
Rossi D, Khiabanian H, Spina V, et al. . Clinical impact of small TP53 mutated subclones in chronic lymphocytic leukemia. Blood. 2014;123(14):2139-2147. PubMed PMC
Malcikova J, Stano-Kozubik K, Tichy B, et al. . Detailed analysis of therapy-driven clonal evolution of TP53 mutations in chronic lymphocytic leukemia. Leukemia. 2015;29(4): 877-885. PubMed PMC
Nadeu F, Delgado J, Royo C, et al. . Clinical impact of clonal and subclonal TP53, SF3B1, BIRC3, NOTCH1, and ATM mutations in chronic lymphocytic leukemia. Blood. 2016;127(17):2122-2130. PubMed PMC
Brieghel C, Kinalis S, Yde CW, et al. . Deep targeted sequencing of TP53 in chronic lymphocytic leukemia: clinical impact at diagnosis and at time of treatment. Haematologica. 2019;104(4):789-796. PubMed PMC
Schuh A, Becq J, Humphray S, et al. . Monitoring chronic lymphocytic leukemia progression by whole genome sequencing reveals heterogeneous clonal evolution patterns. Blood. 2012;120(20):4191-4196. PubMed
Landau DA, Carter SL, Stojanov P, et al. . Evolution and impact of subclonal mutations in chronic lymphocytic leukemia. Cell. 2013;152(4):714-726. PubMed PMC
Rasi S, Khiabanian H, Ciardullo C, et al. . Clinical impact of small subclones harboring NOTCH1, SF3B1 or BIRC3 mutations in chronic lymphocytic leukemia. Haematologica. 2016;101(4):e135-e138. PubMed PMC
Nadeu F, Clot G, Delgado J, et al. . Clinical impact of the subclonal architecture and mutational complexity in chronic lymphocytic leukemia. Leukemia. 2018;32(3):645-653. PubMed PMC
Leeksma AC, Taylor J, Wu B, et al. . Clonal diversity predicts adverse outcome in chronic lymphocytic leukemia. Leukemia. 2019; 33(2):390-402. PubMed PMC
Mansouri L, Sutton LA, Ljungstrom V, et al. . Feasibility of targeted next-generation sequencing of the TP53 and ATM genes in chronic lymphocytic leukemia. Leukemia. 2014;28(3):694-696. PubMed
Sutton LA, Ljungstrom V, Mansouri L, et al. . Targeted next-generation sequencing in chronic lymphocytic leukemia: a highthroughput yet tailored approach will facilitate implementation in a clinical setting. Haematologica. 2015;100(3):370-376. PubMed PMC
Hallek M, Cheson BD, Catovsky D, et al. . iwCLL guidelines for diagnosis, indications for treatment, response assessment, and supportive management of CLL. Blood. 2018;131(25):2745-2760. PubMed
Gargis AS, Kalman L, Berry MW, et al. . Assuring the quality of next-generation sequencing in clinical laboratory practice. Nat Biotechnol. 2012;30(11):1033-1036. PubMed PMC
Rehm HL, Bale SJ, Bayrak-Toydemir P, et al. . ACMG clinical laboratory standards for next-generation sequencing. Genet Med. 2013;15(9):733-747. PubMed PMC
Aziz N, Zhao Q, Bry L, et al. . College of American Pathologists' laboratory standards for next-generation sequencing clinical tests. Arch Pathol Lab Med. 2015;139(4):481-493. PubMed
Jennings LJ, Arcila ME, Corless C, et al. . Guidelines for Validation of next-generation sequencing-based oncology panels: a joint consensus recommendation of the Association for Molecular Pathology and College of American Pathologists. J Mol Diagn. 2017;19(3):341-365. PubMed PMC
Roy S, Coldren C, Karunamurthy A, et al. . Standards and guidelines for validating nextgeneration sequencing bioinformatics pipelines a joint recommendation of the Association for Molecular Pathology and the College of American Pathologists. J Mol Diagn. 2018;20(1):4-27. PubMed
Haslam K, Catherwood MA, Dobbin E, Sproul A, Langabeer SE, Mills KI. Inter-laboratory evaluation of a next-generation sequencing panel for acute myeloid leukemia. Mol Diagn Ther. 2016;20(5):457-461. PubMed
Hirsch B, Endris V, Lassmann S, et al. . Multicenter validation of cancer gene panelbased next-generation sequencing for translational research and molecular diagnostics. Virchows Arch. 2018;472(4):557-565. PubMed PMC
Rossi D, Khiabanian H, Rasi S, et al. . Small subclones harboring NOTCH1, SF3B1 or BIRC3 mutations are clinically irrelevant in chronic lymphocytic leukemia. Blood. 2014; 124(21):295. PubMed
Ahn IE, Underbayev C, Albitar A, et al. . Clonal evolution leading to ibrutinib resistance in chronic lymphocytic leukemia. Blood. 2017;129(11):1469-1479. PubMed PMC
Blombery P, Anderson MA, Gong JN, et al. . Acquisition of the recurrent Gly101Val mutation in BCL2 confers resistance to venetoclax in patients with progressive chronic lymphocytic leukemia. Cancer Discov. 2019;9(3):342-353. PubMed
Woyach JA, Furman RR, Liu TM, et al. . Resistance mechanisms for the Bruton's tyrosine kinase inhibitor ibrutinib. N Engl J Med. 2014;370(24):2286-2294. PubMed PMC
Tausch E, Close W, Dolnik A, et al. . Venetoclax resistance and acquired BCL2 mutations in chronic lymphocytic leukemia. Haematologica. 2019;104(9):e434-e437. PubMed PMC
Malcikova J, Tausch E, Rossi D, et al. . ERIC recommendations for TP53 mutation analysis in chronic lymphocytic leukemia-update on methodological approaches and results interpretation. Leukemia. 2018;32(5):1070-1080. PubMed PMC