Assessment of the clinical utility of four NGS panels in myeloid malignancies. Suggestions for NGS panel choice or design
Autoři:
Almudena Aguilera-Diaz aff001; Iria Vazquez aff002; Beñat Ariceta aff003; Amagoia Mañú aff003; Zuriñe Blasco-Iturri aff003; Sara Palomino-Echeverría aff003; María José Larrayoz aff002; Ramón García-Sanz aff004; María Isabel Prieto-Conde aff004; María del Carmen Chillón aff004; Ana Alfonso-Pierola aff005; Felipe Prosper aff001; Marta Fernandez-Mercado aff001; María José Calasanz aff002
Působiště autorů:
Advanced Genomics Laboratory, Hemato-Oncology, Center for Applied Medical Research (CIMA), University of Navarra, Pamplona, Spain
aff001; Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
aff002; Hematological Diseases Laboratory, CIMA LAB Diagnostics, University of Navarra, Pamplona, Spain
aff003; Hematology Department, University Hospital of Salamanca, IBSAL and CIBERONC, Salamanca, Spain
aff004; Hematology Department, Clinica Universidad de Navarra (CUN), Pamplona, Spain
aff005; Biomedical Engineering Department, School of Engineering, University of Navarra, San Sebastian, Spain
aff006; Scientific Co-Director of CIMA LAB Diagnostics, CIMA LAB Diagnostics, University of Navarra, Pamplona, Spain
aff007
Vyšlo v časopise:
PLoS ONE 15(1)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0227986
Souhrn
The diagnosis of myeloid neoplasms (MN) has significantly evolved through the last few decades. Next Generation Sequencing (NGS) is gradually becoming an essential tool to help clinicians with disease management. To this end, most specialized genetic laboratories have implemented NGS panels targeting a number of different genes relevant to MN. The aim of the present study is to evaluate the performance of four different targeted NGS gene panels based on their technical features and clinical utility. A total of 32 patient bone marrow samples were accrued and sequenced with 3 commercially available panels and 1 custom panel. Variants were classified by two geneticists based on their clinical relevance in MN. There was a difference in panel’s depth of coverage. We found 11 discordant clinically relevant variants between panels, with a trend to miss long insertions. Our data show that there is a high risk of finding different mutations depending on the panel of choice, due both to the panel design and the data analysis method. Of note, CEBPA, CALR and FLT3 genes, remains challenging the use of NGS for diagnosis of MN in compliance with current guidelines. Therefore, conventional molecular testing might need to be kept in place for the correct diagnosis of MN for now.
Klíčová slova:
Acute myeloid leukemia – Cancer detection and diagnosis – Gene sequencing – Genomic libraries – Human genetics – Mutation detection – Next-generation sequencing – Prognosis
Zdroje
1. Korn Claudia and Simón Méndez-Ferrer. Myeloid malignancies and the microenvironment. Blood. 2018;129: 811–823. doi: 10.1182/blood-2016-09-670224 28064238
2. Arber DA, Orazi A, Hasserjian R, Borowitz MJ, Beau MM Le, Bloomfield CD, et al. The 2016 revision to the World Health Organization classi fi cation of myeloid neoplasms and acute leukemia. Blood. 2016;127: 2391–2406. doi: 10.1182/blood-2016-03-643544 27069254
3. Papaemmanuil E, Gerstung M, Malcovati L, Tauro S, Gundem G, Loo P Van, et al. CME Article Clinical and biological implications of driver mutations in myelodysplastic syndromes. Blood. 2013;122: 3616–3627. doi: 10.1182/blood-2013-08-518886 24030381
4. Haferlach T, Nagata Y, Grossmann V, Okuno Y, Bacher U, Nagae G, et al. Landscape of genetic lesions in 944 patients with myelodysplastic syndromes. Leukemia. 2014;28: 241–247. doi: 10.1038/leu.2013.336 24220272
5. Mughal TI, Cross NCP, Padron E, Tiu R V., Savona M, Malcovati L, et al. An international MDS/MPN working group’s perspective and recommendations on molecular pathogenesis, diagnosis and clinical characterization of myelodysplastic/myeloproliferative neoplasms. Haematologica. 2015;100: 1117–1130. doi: 10.3324/haematol.2014.114660 26341525
6. Itzykson R, Kosmider O, Renneville A, Gelsi-Boyer V, Meggendorfer M, Morabito M, et al. Prognostic Score Including Gene Mutations in Chronic Myelomonocytic Leukemia. J Clin Oncol. 2013;31: 2428–2436. doi: 10.1200/JCO.2012.47.3314 23690417
7. Meggendorfer M, Bacher U, Alpermann T, Haferlach C, Kern W, Gambacorti-Passerini C, et al. SETBP1 mutations occur in 9% of MDS/MPN and in 4% of MPN cases and are strongly associated with atypical CML, monosomy 7, isochromosome i(17)(q10), ASXL1 and CBL mutations. Leukemia. 2013;27: 1852–1860. doi: 10.1038/leu.2013.133 23628959
8. Patnaik MM, Tefferi A. Cytogenetic and molecular abnormalities in chronic myelomonocytic leukemia. Blood Cancer J. 2016;6: 1–8. doi: 10.1038/bcj.2016.5 26849014
9. Mangaonkar AA, Lasho TL, Finke CM, Gangat N, Al-Kali A, Elliott MA, et al. Prognostic interaction between bone marrow morphology and SF3B1 and ASXL1 mutations in myelodysplastic syndromes with ring sideroblasts. Blood Cancer J. 2018;8: 1–4. doi: 10.1038/s41408-017-0043-6
10. Bejar R, Stevenson KE, Caughey B, Lindsley RC, Mar BG, Stojanov P, et al. Somatic Mutations Predict Poor Outcome in Patients With Myelodysplastic Syndrome After Hematopoietic Stem-Cell Transplantation. J Clin Oncol. 2014;32: 2691–2698. doi: 10.1200/JCO.2013.52.3381 25092778
11. Tefferi A, Lasho TL, Patnaik MM, Saeed L, Mudireddy M, Idossa D, et al. Targeted next-generation sequencing in myelodysplastic syndromes and prognostic interaction between mutations and IPSS-R. Am J Hematol. 2017;92: 1311–1317. doi: 10.1002/ajh.24901 28875545
12. Serratì S, De Summa S, Pilato B, Petriella D, Lacalamita R, Tommasi S, et al. Next-generation sequencing: advances and applications in cancer diagnosis. Onco Targets Ther. 2016;9: 7355–7365. doi: 10.2147/OTT.S99807 27980425
13. Rack KA, Berg E van den, Haferlach C, Beverloo HB, Costa D, Espinet B, et al. European recommendations and quality assurance for cytogenomic analysis of haematological neoplasms. Leukemia. 2019. doi: 10.1038/s41375-019-0378-z 30696948
14. Palomo L, Ibáñez M, Abáigar M, Vázquez I, Álvarez S, Cabezón M, et al. Spanish Guidelines for the use of targeted deep sequencing in myelodysplastic syndromes and chronic myelomonocytic leukaemia. Br J Haematol. 2019;October: bjh.16175. doi: 10.1111/bjh.16175 31621063
15. Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G1, et al. Integrative genomics viewer. Nat Biotechnol. 2011;29: 24–26. doi: 10.1038/nbt.1754 21221095
16. Gombart AF, Hofmann W, Kawano S, Takeuchi S, Krug U, Kwok SH, et al. Mutations in the gene encoding the transcription factor CCAAT / enhancer binding protein α in myelodysplastic syndromes and acute myeloid leukemias. 2013;99: 1332–1340. doi: 10.1182/blood.V99.4.1332 11830484
17. Lin L-I, Chen C-Y, Lin D-T, Tsay W, Tang J-L, Yeh Y-C, et al. Characterization of CEBPA Mutations in Acute Myeloid Leukemia: Most Patients with CEBPA Mutations Have Biallelic Mutations and Show a Distinct Immunophenotype of the Leukemic Cells. Clin Cancer Res. 2005;11: 1372–1379. doi: 10.1158/1078-0432.CCR-04-1816 15746035
18. Nangalia J, Massie CE, Baxter EJ, Nice FL, Gundem G, Wedge DC, et al. Somatic CALR Mutations in Myeloproliferative Neoplasms with Nonmutated JAK2. N Engl J Med. 2013;369: 2391–2405. doi: 10.1056/NEJMoa1312542 24325359
19. Nakao M, Yokota S, Iwai T, Kaneko H, Horiike S, Kashima K, et al. Internal tandem duplication of the flt3 gene found in acute myeloid leukemia. Leukemia. 1996;10: 1911–1918. 8946930
20. Thomas M, Sukhai MA, Zhang T, Dolatshahi R, Harbi D, Garg S, et al. Integration of Technical, Bioinformatic, and Variant Assessment Approaches in the Validation of a Targeted Next-Generation Sequencing Panel for Myeloid Malignancies. Arch Pathol Lab Med. 2017;141: 759–775. doi: 10.5858/arpa.2016-0547-RA 28557600
21. Yamamoto Y, Kiyoi H, Nakano Y, Suzuki R, Kodera Y, Miyawaki S, et al. Activating mutation of D835 within the activation loop of FLT3 in human hematologic malignancies. Blood. 2001;97: 2434–2439. doi: 10.1182/blood.v97.8.2434 11290608
22. Pellagatti A, Armstrong RN, Steeples V, Sharma E, Repapi E, Singh S, et al. Impact of spliceosome mutations on RNA splicing in myelodysplasia: Dysregulated genes/pathways and clinical associations. Blood. 2018;132: 1225–1240. doi: 10.1182/blood-2018-04-843771 29930011
23. Kim KH, Roberts CWM. Targeting EZH2 in cancer. Nat Med. 2016;22: 128–134. doi: 10.1038/nm.4036 26845405
24. Makishima H, Yoshizato T, Yoshida K, Sekeres MA, Radivoyevitch T, Suzuki H, et al. Dynamics of clonal evolution in myelodysplastic syndromes. Nat Genet. 2017;49: 204–212. doi: 10.1038/ng.3742 27992414
25. Murati A, Brecqueville M, Devillier R, Mozziconacci MJ, Gelsi-Boyer V, Birnbaum D. Myeloid malignancies: mutations, models and management. BMC Cancer. 2012;12. doi: 10.1186/1471-2407-12-304 22823977
26. Gill H, Leung A, Kwong Y-L. Molecular and Cellular Mechanisms of Myelodysplastic Syndrome: Implications on Targeted Therapy. Int J Mol Sci. 2016;17: 440. doi: 10.3390/ijms17040440 27023522
27. Lee JH, Jeong H, Choi JW, Oh H, Kim Y-S. Clinicopathologic significance of MYD88 L265P mutation in diffuse large B-cell lymphoma: a meta-analysis. Sci Rep. 2017;7: 1–8. doi: 10.1038/s41598-016-0028-x
28. Hu Y, Su H, Liu C, Wang Z, Huang L, Wang Q, et al. DEPTOR is a direct NOTCH1 target that promotes cell proliferation and survival in T-cell leukemia. Oncogene. 2017;36: 1038–1047. doi: 10.1038/onc.2016.275 27593934
29. Stenzinger A, Endris V, Pfarr N, Andrulis M, Jöhrens K, Klauschen F, et al. Targeted ultra-deep sequencing reveals recurrent and mutually exclusive mutations of cancer genes in blastic plasmacytoid dendritic cell neoplasm. Oncotarget. 2014;5: 6404–6413. doi: 10.18632/oncotarget.2223 25115387
30. Bello E, Pellagatti A, Shaw J, Mecucci C, Kušec R, Killick S, et al. CSNK1A1 mutations and gene expression analysis in myelodysplastic syndromes with del(5q). Br J Haematol. 2015;171: 210–214. doi: 10.1111/bjh.13563 26085061
31. Boudry-Labis E, Roche-Lestienne C, Nibourel O, Boissel N, Terre C, Perot C, et al. Neurofibromatosis-1 gene deletions and mutations in de novo adult acute myeloid leukemia. Am J Hematol. 2013;88: 306–311. doi: 10.1002/ajh.23403 23460398
32. Wong TN, Miller CA, Jotte MRM, Bagegni N, Baty JD, Schmidt AP, et al. Cellular stressors contribute to the expansion of hematopoietic clones of varying leukemic potential. Nat Commun. 2018;9: 1–10. doi: 10.1038/s41467-017-02088-w
33. Maslah N, Cassinat B, Verger E, Kiladjian JJ, Velazquez L. The role of LNK/SH2B3 genetic alterations in myeloproliferative neoplasms and other hematological disorders. Leukemia. 2017;31: 1661–1670. doi: 10.1038/leu.2017.139 28484264
34. Patnaik MM. The importance of FLT3 mutational analysis in acute myeloid leukemia. Leuk Lymphoma. 2018;59: 2273–2286. doi: 10.1080/10428194.2017.1399312 29164965
35. Bullinger L, Döhner K, Dohner H. Genomics of acute myeloid leukemia diagnosis and pathways. J Clin Oncol. 2017;35: 934–946. doi: 10.1200/JCO.2016.71.2208 28297624
36. Metzeler KH, Herold T, Rothenberg-Thurley M, Amler S, Sauerland MC, Görlich D, et al. Spectrum and prognostic relevance of driver gene mutations in acute myeloid leukemia. Blood. 2016;128: 686–698. doi: 10.1182/blood-2016-01-693879 27288520
37. Zoi K, Cross NCP. Genomics of myeloproliferative neoplasms. J Clin Oncol. 2017;35: 947–955. doi: 10.1200/JCO.2016.70.7968 28297629
38. Pardanani A, Lasho TL, Laborde RR, Elliott M, Hanson CA, Knudson RA, et al. CSF3R T618I is a highly prevalent and specific mutation in chronic neutrophilic leukemia. Leukemia. 2013;27: 1870–1873. doi: 10.1038/leu.2013.122 23604229
39. Perry AM, Attar EC. New Insights in AML Biology From Genomic Analysis. Semin Hematol. 2014;51: 282–297. doi: 10.1053/j.seminhematol.2014.08.005 25311741
40. Makishima H. Somatic SETBP1 mutations in myeloid neoplasms. Int J Hematol. 2017;105: 732–742. doi: 10.1007/s12185-017-2241-1 28447248
41. Lasho TL, Finke CM, Hanson CA, Jimma T, Knudson RA, Ketterling RP, et al. SF3B1 mutations in primary myelofibrosis: Clinical, histopathology and genetic correlates among 155 patients. Leukemia. 2012;26: 1135–1137. doi: 10.1038/leu.2011.320 22064353
42. Pellagatti A, Boultwood J. The molecular pathogenesis of the myelodysplastic syndromes. Eur J Haematol. 2015;95: 3–15. doi: 10.1111/ejh.12515 25645650
43. Terada K, Yamaguchi H, Ueki T, Usuki K, Kobayashi Y, Tajika K, et al. Usefulness of BCOR gene mutation as a prognostic factor in acute myeloid leukemia with intermediate cytogenetic prognosis. Genes Chromosom Cancer. 2018;57: 401–408. doi: 10.1002/gcc.22542 29663558
44. Crispino JD, Horwitz MS. GATA factor mutations in hematologic disease. Blood. 2017;129: 2103–2110. doi: 10.1182/blood-2016-09-687889 28179280
45. Song J, Hussaini M, Zhang H, Shao H, Qin D, Zhang X, et al. Comparison of the Mutational Profiles of Primary Myelofibrosis, Polycythemia Vera, and Essential Thrombocytosis. Am J Clin Pathol. 2017;147: 444–452. doi: 10.1093/ajcp/aqw222 28419183
46. Mori T, Nagata Y, Makishima H, Sanada M, Shiozawa Y, Kon A, et al. Somatic PHF6 mutations in 1760 cases with various myeloid neoplasms. Leukemia. 2016;30: 2270–2273. doi: 10.1038/leu.2016.212 27479181
47. Herbaux C, Duployez N, Badens C, Poret N, Gardin C, Decamp M, et al. Incidence of ATRX mutations in myelodysplastic syndromes, the value of microcytosis. Am J Hematol. 2015;90: 737–738. doi: 10.1002/ajh.24073 26017030
48. Wong CC, Martincorena I, Rust AG, Rashid M, Alifrangis C, Alexandrov LB, et al. Inactivating CUX1 mutations promote tumorigenesis. Nat Genet. 2014;46: 33–38. doi: 10.1038/ng.2846 24316979
49. Hirabayashi S, Wlodarski MW, Kozyra E, Niemeyer CM. Heterogeneity of GATA2-related myeloid neoplasms. Int J Hematol. 2017;106: 175–182. doi: 10.1007/s12185-017-2285-2 28643018
50. Jäger R, Gisslinger H, Passamonti F, Rumi E, Berg T, Gisslinger B, et al. Deletions of the transcription factor Ikaros in myeloproliferative neoplasms. Leukemia. 2010;24: 1290–1298. doi: 10.1038/leu.2010.99 20508609
51. Thol F, Bollin R, Gehlhaar M, Walter C, Dugas M, Suchanek KJ, et al. Mutations in the cohesin complex in acute myeloid leukemia: clinical and prognostic implications. Blood. 2014;123: 914–920. doi: 10.1182/blood-2013-07-518746 24335498
52. Kon A, Shih LY, Minamino M, Sanada M, Shiraishi Y, Nagata Y, et al. Recurrent mutations in multiple components of the cohesin complex in myeloid neoplasms. Nat Genet. 2013;45: 1232–1237. doi: 10.1038/ng.2731 23955599
53. Ha Jung-Sook and Jeon Dong-Seok. Possible new LNK mutations in myeloproliferative neoplasms. Am J Hematol. 2011;86: 866–868. doi: 10.1002/ajh.22107 21922527
54. Hurtado C, Erquiaga I, Aranaz P, Miguéliz I, García-Delgado M, Novo FJ, et al. LNK can also be mutated outside PH and SH2 domains in myeloproliferative neoplasms with and without V617FJAK2 mutation. Leuk Res. 2011;35: 1537–1539. doi: 10.1016/j.leukres.2011.07.009 21794913
55. Lasho TL, Tefferi A, Finke C, Pardanani A. Clonal hierarchy and allelic mutation segregation in a myelofibrosis patient with two distinct LNK mutations. Leukemia. 2011;25: 1056–1058. doi: 10.1038/leu.2011.45 21415853
56. Kantarjian HM, Keating MJ, Freireich EJ. Toward the potential cure of leukemias in the next decade. Cancer. 2018;124: 4301–4313. doi: 10.1002/cncr.31669 30291792
57. Stone RM. Which new agents will be incorporated into frontline therapy in acute myeloid leukemia? Best Pract Res Clin Haematol. 2017;30: 312–316. doi: 10.1016/j.beha.2017.09.006 29156201
58. Bejar R, Lord A, Stevenson K, Bar-Natan M, Pérez-Ladaga A, Zaneveld J, et al. TET2 mutations predict response to hypomethylating agents in myelodysplastic syndrome patients. Blood. 2014;124: 2705–2712. doi: 10.1182/blood-2014-06-582809 25224413
59. Metzeler KH, Walker A, Geyer S, Garzon R, Klisovic RB, Bloomfield D, et al. DNMT3A mutations and response to the hypomethylating agent decitabine in acute myeloid leukemia. Leukemia. Nature Publishing Group; 2012. doi: 10.1038/leu.2011.342 22124213
60. Luskin MR, Lee JW, Fernandez HF, Abdel-Wahab O, Bennett JM, Ketterling RP, et al. Benefit of high-dose daunorubicin in AML induction extends across cytogenetic and molecular groups. Blood. 2016;127: 1551–1558. doi: 10.1182/blood-2015-07-657403 26755712
61. Pabst T, Eyholzer M, Fos J, Mueller BU. Heterogeneity within AML with CEBPA mutations; Only CEBPA double mutations, but not single CEBPA mutations are associated with favourable prognosis. Br J Cancer. 2009;100: 1343–1346. doi: 10.1038/sj.bjc.6604977 19277035
62. Au CH, Wa A, Ho DN, Chan TL, Ma ESK. Clinical evaluation of panel testing by next-generation sequencing (NGS) for gene mutations in myeloid neoplasms. Diagn Pathol. 2016;11:11. doi: 10.1186/s13000-016-0456-8 26796102
63. Albitar A, Townsley D, Ma W, De Dios I, Funari V, Young NS, et al. Prevalence of somatic mutations in patients with aplastic anemia using peripheral blood cfDNA as compared with BM. Leukemia. 2018;32: 227–229. doi: 10.1038/leu.2017.271 28832022
64. Taylor J, Xiao W, Abdel-wahab O. Diagnosis and classification of hematologic malignancies on the basis of genetics. Blood. 2017;130: 410–424. doi: 10.1182/blood-2017-02-734541 28600336
65. Hattori K, Sakata-Yanagimoto M, Suehara Y, Yokoyama Y, Kato T, Kurita N, et al. Clinical significance of disease-specific MYD88 mutations in circulating DNA in primary central nervous system lymphoma. Cancer Sci. 2018;109: 225–230. doi: 10.1111/cas.13450 29151258
66. Qin SC, Xia Y, Miao Y, Zhu HY, Wu JZ, Fan L, et al. MYD88 mutations predict unfavorable prognosis in chronic lymphocytic leukemia patients with mutated IGHV gene. Blood Cancer J. 2017;7. doi: 10.1038/s41408-017-0014-y 29242635
67. Varettoni M, Arcaini L, Zibellini S, Boveri E, Rattotti S, Riboni R, et al. Prevalence and clinical significance of the MYD88 (L265P) somatic mutation in Waldenstrom’s macroglobulinemia and related lymphoid neoplasms. Blood. 2013;121: 2522–2528. doi: 10.1182/blood-2012-09-457101 23355535
68. Young AL, Challen GA, Birmann BM, Druley TE. Clonal haematopoiesis harbouring AML-associated mutations is ubiquitous in healthy adults. Nat Commun. 2016;7:12454. doi: 10.1038/ncomms12454
69. Hung SS, Meissner B, Chavez EA, Ben-Neriah S, Ennishi D, Jones MR, et al. Assessment of Capture and Amplicon-Based Approaches for the Development of a Targeted Next-Generation Sequencing Pipeline to Personalize Lymphoma Management. J Mol Diagnostics. 2018;20: 203–214. doi: 10.1016/j.jmoldx.2017.11.010 29429887
70. Kadri S, Zhen CJ, Wurst MN, Long BC, Jiang ZF, Wang YL, et al. Amplicon Indel Hunter Is a Novel Bioinformatics Tool to Detect Large Somatic Insertion/Deletion Mutations in Amplicon-Based Next-Generation Sequencing Data. J Mol Diagnostics. 2015;17: 635–643. doi: 10.1016/j.jmoldx.2015.06.005 26319364
71. Patel KP, Barkoh BA, Chen Z, Ma D, Reddy N, Medeiros LJ, et al. Diagnostic testing for IDH1 and IDH2 variants in acute myeloid leukemia an algorithmic approach using high-resolution melting curve analysis. J Mol Diagnostics. 2011;13: 678–686. doi: 10.1016/j.jmoldx.2011.06.004 21889610
72. Petrova L, Vrbacky F, Lanska M, Zavrelova A, Zak P, Hrochova K. IDH1 and IDH2 mutations in patients with acute myeloid leukemia: Suitable targets for minimal residual disease monitoring? Clin Biochem. 2018;61: 34–39. doi: 10.1016/j.clinbiochem.2018.08.012 30176240
73. Bannon SA, Dinardo CD. Hereditary predispositions to myelodysplastic syndrome. Int J Mol Sci. 2016;17: 838. doi: 10.3390/ijms17060838 27248996
74. Babushok D V, Bessler M, Olson TS. Genetic predisposition to myelodysplastic syndrome and acute myeloid leukemia in children and young adults. Leuk Lymphoma. 2016;57: 520–536. doi: 10.3109/10428194.2015.1115041 26693794
75. Pippucci T, Savoia A, Perrotta S, Pujol-Moix N, Noris P, Castegnaro G, et al. Mutations in the 5′ UTR of ANKRD26, the ankirin repeat domain 26 gene, cause an autosomal-dominant form of inherited thrombocytopenia, THC2. Am J Hum Genet. 2011;88: 115–120. doi: 10.1016/j.ajhg.2010.12.006 21211618
76. Marconi C, Canobbio I, Bozzi V, Pippucci T, Simonetti G, Melazzini F, et al. 5′UTR point substitutions and N-terminal truncating mutations of ANKRD26 in acute myeloid leukemia. J Hematol Oncol. 2017;10: 18. doi: 10.1186/s13045-016-0382-y 28100250
77. Schnittger S, Bacher U, Haferlach C, Alpermann T, Kern W, Haferlach T. Diversity of the Juxtamembrane and TKD I Mutations (Exons 13–15) in the FLT3 Gene with Regards to Mutant Load, Sequence, Length, Localization, and Correlation with Biological Data. Genes Chromosom Cancer. 2012;51: 910–924. doi: 10.1002/gcc.21975 22674490
78. Cabagnols X, Favale F, Pasquier F, Messaoudi K, Defour JP, Ianotto JC, et al. Presence of atypical thrombopoietin receptor (MPL) mutations in triple-negative essential thrombocythemia patients. Blood. 2016;127: 333–342. doi: 10.1182/blood-2015-07-661983 26450985
79. Milosevic Feenstra JD, Nivarthi H, Gisslinger H, Leroy E, Rumi E, Chachoua I, et al. Whole-exome sequencing identifies novel MPL and JAK2 mutations in triple-negative myeloproliferative neoplasms. Blood. 2016;127: 325–332. doi: 10.1182/blood-2015-07-661835 26423830
80. Dohner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, Büchner T, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2017;129: 424–447. doi: 10.1182/blood-2016-08-733196 27895058
81. Alonso CM, Llop M, Sargas C, Pedrola L, Panadero J, Hervás D, et al. Clinical Utility of a Next-Generation Sequencing Panel for Acute Myeloid Leukemia Diagnostics. J Mol Diagnostics. 2019;21: 228–240. doi: 10.1016/j.jmoldx.2018.09.009 30576870
82. Schranz K, Hubmann M, Harin E, Vosberg S, Herold T, Metzeler KH, et al. Clonal heterogeneity of FLT3-ITD detected by high-throughput amplicon sequencing correlates with adverse prognosis in acute myeloid leukemia. Oncotarget. 2018;9: 30128–30145. doi: 10.18632/oncotarget.25729 30046393
83. Bacher U, Shumilov E, Flach J, Porret N, Joncourt R, Wiedemann G, et al. Challenges in the introduction of next-generation sequencing (NGS) for diagnostics of myeloid malignancies into clinical routine use. Blood Cancer J. 2018;8: 113. doi: 10.1038/s41408-018-0148-6 30420667
84. Baker SC. Nex-Generation sequencing challenges. Genet Eng Biotechnol News. 2017;37: accessed on Feb 4, 2019. Available: https//www.genengnews.com/magazine/286/next-generation-sequencing-challenges
Článek vyšel v časopise
PLOS One
2020 Číslo 1
- S diagnostikou Parkinsonovy nemoci může nově pomoci AI nástroj pro hodnocení mrkacího reflexu
- Proč při poslechu některé muziky prostě musíme tančit?
- Je libo čepici místo mozkového implantátu?
- Chůze do schodů pomáhá prodloužit život a vyhnout se srdečním chorobám
- Pomůže v budoucnu s triáží na pohotovostech umělá inteligence?
Nejčtenější v tomto čísle
- Severity of misophonia symptoms is associated with worse cognitive control when exposed to misophonia trigger sounds
- Chemical analysis of snus products from the United States and northern Europe
- Calcium dobesilate reduces VEGF signaling by interfering with heparan sulfate binding site and protects from vascular complications in diabetic mice
- Effect of Lactobacillus acidophilus D2/CSL (CECT 4529) supplementation in drinking water on chicken crop and caeca microbiome
Zvyšte si kvalifikaci online z pohodlí domova
Všechny kurzy