Page 118 - 2022_01-Haematologica-web

P. Kerbs et al.
esis. In the present study, NRIP1-MIR99AHG was found in eight AML patients, as well as in one CMML patient, all of whom had poor survival and were mostly refractory to intensive induction treatment. However, this might also be related to the complex karyotype in several patients. Of note, a recent whole-transcriptome study of 572 patients with AML and 630 with myelodysplastic syndromes did not find any NRIP1-MIR99AHG fusions.38 An extended analysis by the same authors39 of overlapping cohorts, pre- sented at the recent Annual Meeting of the American Society of Hematology, identified recurring NRIP1- MIR99AHG in AML and myelodysplastic syndromes but not in lymphoid malignancies (with MIR99AHG referred to as LINC00478). Further studies are needed to gain more insight into the pathogenic, diagnostic and prognostic sig- nificance of the NRIP1-MIR99AHG fusion in AML and other hematologic malignancies.
In conclusion, RNA-sequencing allows for accurate and more exhaustive identification of fusion transcripts as com- pared to classical cytogenetics or molecular diagnostics alone. We demonstrated that crucial AML-related fusions can be reliably identified by RNA-sequencing, but low sequence coverage limited sensitivity in a subset of sam- ples. These findings underscore the need for stringent qual- ity metrics in diagnostic RNA-sequencing applications. Nevertheless, we found several AML-related fusions that are difficult to detect by clinical routine. Furthermore, our workflow allowed for the identification of novel recurrent fusion transcripts such as NRIP1-MIR99AHG, which results from the chromosomal rearrangement inv(21)(q11.2;q21.1).
This study presents RNA-sequencing as a valuable comple- mentary method to current standard techniques for the detection of fusion genes and we recommend the integra- tion of RNA-sequencing applications into clinical routine for more comprehensive and precise diagnostics of hemato- logic malignancies.
Disclosures
No conflicts of interest to disclose.
Contributions
PK, SV, SK and AS performed research and analyzed data. AMNB and AG provided computational support. CH, PAG and TH provided RNA-sequencing data and clinical annotations. SV, HB, UM, DM and PAG supervised the research. PK, SV and PAG wrote the manuscript. All authors approved the final manu- script.
Acknowledgments
We thank all participants and recruiting centers of the AMLCG and Beat AML trials. We also thank Bianka Ksienzyk and William Keay for technical support.
Funding
This study was supported by the Deutsche Forschungsgemeinschaft (DFG) within the Collaborative Research Center (SFB) 1243 "Cancer Evolution" (projects A08 and A16). PAG acknowledges support from the Munich Clinician Scientist Program (MCSP). SV was supported by the Deutsche José Carreras Leukämie-Stiftung.
References
1. Gao Q, Liang W-W, Foltz SM, et al. Driver fusions and their implications in the devel- opment and treatment of human cancers. Cell Rep. 2018;23(1):227-238.
2. Grimwade D, Hills RK, Moorman AV, et al. Refinement of cytogenetic classification in acute myeloid leukemia: determination of prognostic significance of rare recurring chromosomal abnormalities among 5876 younger adult patients treated in the United Kingdom Medical Research Council trials. Blood. 2010;116(3):354-365.
3. Döhner H, Estey EH, Amadori S, et al. Diagnosis and management of acute myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet. Blood. 2010;115(3):453-474.
4. Arber DA, Orazi A, Hasserjian R, et al. The 2016 revision to the World Health Organization classification of myeloid neo- plasms and acute leukemia. Blood 2016;127(20):2391-405.
5. Wang Y, Wu N, Liu D, Jin Y. Recurrent fusion genes in leukemia: an attractive target for diagnosis and treatment. Curr Genomics. 2017;18(5):378-384.
6.Döhner H, Estey E, Grimwade D, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2017;129(4):424-447.
7.Mack E, Langer D, Marquardt A, et al. Comprehensive genetic diagnostics of acute myeloid leukemia by next generation sequencing. Blood. 2016;128(22):1665.
8. Bacher U, Shumilov E, Flach J, et al. Challenges in the introduction of next-gener-
ation sequencing (NGS) for diagnostics of myeloid malignancies into clinical routine use. Blood Cancer J. 2018;8(11):113.
9. Liu S, Tsai W-H, Ding Y, et al. Comprehensive evaluation of fusion tran- script detection algorithms and a meta-caller to combine top performing methods in paired-end RNA-seq data. Nucleic Acids Res. 2016;44(5):e47.
10. Arindrarto W, Borràs DM, de Groen RAL, et al. Comprehensive diagnostics of acute myeloid leukemia by whole transcriptome RNA sequencing. Leukemia. 2020;35(1):47- 61.
11. Kumar S, Vo AD, Qin F, Li H. Comparative assessment of methods for the fusion tran- scripts detection from RNA-seq data. Sci Rep. 2016;6:21597.
12. Haas BJ, Dobin A, Li B, Stransky N, Pochet N, Regev A. Accuracy assessment of fusion tran- script detection via read-mapping and de novo fusion transcript assembly-based meth- ods. Genome Biol. 2019;20(1):213.
13.Braess J, Amler S, Kreuzer KA, et al. Sequential high-dose cytarabine and mitox- antrone (S-HAM) versus standard double induction in acute myeloid leukemia—a phase 3 study. Leukemia. 2018;32(12):2558- 2571.
14.Büchner T, Berdel WE, Schoch C, et al. Double induction containing either two courses or one course of high-dose cytarabine plus mitoxantrone and postremission thera- py by either autologous stem-cell transplan- tation or by prolonged maintenance for acute myeloid leukemia. J Clin Oncol. 2006;24(16):2480-2489.
15. Hartmann L, Dutta S, Opatz S, et al. ZBTB7A mutations in acute myeloid leukaemia with t(8;21) translocation. Nat Commun.
2016;7(1):1-7.
16.Greif PA, Hartmann L, Vosberg S, et al.
Evolution of cytogenetically normal acute myeloid leukemia during therapy and relapse: An exome sequencing study of 50 patients. Clin Cancer Res. 2018;24(7):1716- 1726.
17. Tyner JW, Tognon CE, Bottomly D, et al. Functional genomic landscape of acute myeloid leukaemia. Nature. 2018;562(7728): 526-531.
18. Pemovska T, Kontro M, Yadav B, et al. Individualized systems medicine strategy to tailor treatments for patients with chemore- fractory acute myeloid leukemia. Cancer Discov. 2013;3(12):1416-1429.
19. Krzywinski M, Schein J, Birol I, et al. Circos: An information aesthetic for comparative genomics. Genome Res. 2009;19(9):1639- 1645.
20. Majumder MM, Kontro M, Edgren H, et al. Genomic and transcriptomic data integration in chronic myelomonocytic leukemia reveals a novel fusion gene involving onco-miR- 125b-2. Cancer Res. 2012;72(8 Suppl):3175.
21.Davis CA, Hitz BC, Sloan CA, et al. The Encyclopedia of DNA Elements (ENCODE): data portal update. Nucleic Acids Res. 2018;46(D1):D794-D801.
22. Gelehrter TD, Collins FS, Ginsburg D. Principles of Medical Genetics. Williams & Wilkins. pp 153-194.
23. De Braekeleer E, Meyer C, Douet-Guilbert N, et al. Complex and cryptic chromosomal rearrangements involving the MLL gene in acute leukemia: a study of 7 patients and review of the literature. Blood Cells Mol Dis. 2010;44(4):268-274.
24. Kivioja JL, Lopez Martí JM, Kumar A, et al. Chimeric NUP98-NSD1 transcripts from the
110
haematologica | 2022; 107(1)