Blood Res.  2024;59:1. 10.1007/s44313-024-00001-1.

Genomic technologies for detecting structural variations in hematologic malignancies

• Jang M

• KMID: 2552886
• DOI: http://doi.org/10.1007/s44313-024-00001-1

Abstract

Genomic structural variations in myeloid, lymphoid, and plasma cell neoplasms can provide key diagnostic, prog‑ nostic, and therapeutic information while elucidating the underlying disease biology. Several molecular diagnostic approaches play a central role in evaluating hematological malignancies. Traditional cytogenetic diagnostic assays, such as chromosome banding and fluorescence in situ hybridization, are essential components of the current diag‑ nostic workup that guide clinical care for most hematologic malignancies. However, each assay has inherent limita‑ tions, including limited resolution for detecting small structural variations and low coverage, and can only detect alterations in the target regions. Recently, the rapid expansion and increasing availability of novel and comprehensive genomic technologies have led to their use in clinical laboratories for clinical management and translational research. This review aims to describe the clinical relevance of structural variations in hematologic malignancies and introduce genomic technologies that may facilitate personalized tumor characterization and treatment.

Keyword

Molecular diagnostics; Next-generation sequencing; Leukemia; Lymphoma; Myeloma; Myeloid; Lymphoid

Reference

1. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA. 2017. WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues. IARC;Lyon: DOI: 10.53347/rid-9250.

2. Hergott CB, Kim AS. 2022; Molecular diagnostic testing for hematopoietic neoplasms: linking pathogenic drivers to personalized diagnosis. Clin Lab Med. 42:325–47. DOI: 10.1016/j.cll.2022.04.005. PMID: 36150815.

3. Mahmoud M, Gobet N, Cruz-Dávalos DI, Mounier N, Dessimoz C, Sedlazeck FJ. 2019; Structural variant calling: the long and the short of it. Genome Biol. 20:246. DOI: 10.1186/s13059-019-1828-7. PMID: 31747936. PMCID: PMC6868818. PMID: 517825c5aebf44799b3b1892fb3dd17b.

4. Escaramís G, Docampo E, Rabionet R. 2015; A decade of structural variants: description, history and methods to detect structural variation. Brief Funct Genomics. 14:305–14. DOI: 10.1093/bfgp/elv014. PMID: 25877305.

5. Granada I, Palomo L, Ruiz-Xivillé N, Mallo M, Solé F. 2020; Cytogenetics in the genomic era. Best Pract Res Clin Haematol. 33:101196. DOI: 10.1016/j.beha.2020.101196. PMID: 33038985.

6. Akkari YMN, Baughn LB, Dubuc AM, et al. 2022; Guiding the global evolution of cytogenetic testing for hematologic malignancies. Blood. 139:2273–84. DOI: 10.1182/blood.2021014309. PMID: 35167654. PMCID: PMC9710485.

7. Taylor J, Xiao W, Abdel-Wahab O. 2017; Diagnosis and classification of hematologic malignancies on the basis of genetics. Blood. 130:410–23. DOI: 10.1182/blood-2017-02-734541. PMID: 28600336. PMCID: PMC5533199.

8. Mikhail FM, Heerema NA, Rao KW, Burnside RD, Cherry AM, Cooley LD. 2016; Section E6.1-6.4 of the ACMG technical standards and guidelines: chromosome studies of neoplastic blood and bone marrow-acquired chromosomal abnormalities. Genet Med. 18:635–42. DOI: 10.1038/gim.2016.50. PMID: 27124785.

9. Tansatit M. 2017; Applications of fluorescence in situ hybridization technology in malignancies. Methods Mol Biol. 1541:75–90. DOI: 10.1007/978-1-4939-6703-2_8. PMID: 27910016.

10. NCCN. Acute Lymphoblastic Leukemia; National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology Version 3.2023.

11. NCCN. Acute Myeloid Leukemia; National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology Version 3.2023.

12. Peterson JF, Aggarwal N, Smith CA, et al. 2015; Integration of microarray analysis into the clinical diagnosis of hematological malignancies: how much can we improve cytogenetic testing? Oncotarget. 6:18845–62. DOI: 10.18632/oncotarget.4586. PMID: 26299921. PMCID: PMC4662459.

13. Coccaro N, Anelli L, Zagaria A, et al. 2023; Feasibility of optical genome mapping in cytogenetic diagnostics of hematological neoplasms: a new way to look at DNA. Diagnostics (Basel). 13:1841. DOI: 10.3390/diagnostics13111841. PMID: 37296693. PMCID: PMC10252312. PMID: 50243c36f6fe4f5a829cf10b26071654.

14. Smith AC, Neveling K, Kanagal-Shamanna R. 2022; Optical genome mapping for structural variation analysis in hematologic malignancies. Am J Hematol. 97:975–82. DOI: 10.1002/ajh.26587. PMID: 35560245.

15. Neveling K, Mantere T, Vermeulen S, et al. 2021; Next-generation cytogenetics: comprehensive assessment of 52 hematological malignancy genomes by optical genome mapping. Am J Hum Genet. 108:1423–35. DOI: 10.1016/j.ajhg.2021.06.001. PMID: 34237281. PMCID: PMC8387283.

16. Greenberg PL, Tuechler H, Schanz J, et al. 2012; Revised international prognostic scoring system for myelodysplastic syndromes. Blood. 120:2454–65. DOI: 10.1182/blood-2012-03-420489. PMID: 22740453. PMCID: PMC4425443.

17. Wang W, Cortes JE, Tang G, et al. 2016; Risk stratification of chromosomal abnormalities in chronic myelogenous leukemia in the era of tyrosine kinase inhibitor therapy. Blood. 127:2742–50. DOI: 10.1182/blood-2016-01-690230. PMID: 27006386. PMCID: PMC4915795.

18. NCCN. Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma; National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology Version 1.2024. DOI: 10.32388/ftymf7.

19. Palumbo A, Avet-Loiseau H, Oliva S, et al. 2015; Revised international staging system for multiple myeloma: a report from international myeloma working group. J Clin Oncol. 33:2863–9. DOI: 10.1200/JCO.2015.61.2267. PMID: 26240224. PMCID: PMC4846284.

20. NCCN. B-Cell Lymphomas; National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology Version 6.2023.

21. Khoury JD, Solary E, Abla O, et al. 2022; The 5th edition of the World Health Organization classification of haematolymphoid tumours: myeloid and histiocytic/dendritic neoplasms. Leukemia. 36:1703–19. DOI: 10.1038/s41375-022-01613-1. PMID: 35732831. PMCID: PMC9252913.

22. Arber DA, Orazi A, Hasserjian RP, et al. 2022; International consensus classification of myeloid neoplasms and acute leukemias: integrating morphologic, clinical, and genomic data. Blood. 140:1200–28. DOI: 10.1182/blood.2022015850. PMID: 35767897. PMCID: PMC9479031.

23. NCCN. Myelodysplastic Syndromes; National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology Version 2.2023.

24. Alaggio R, Amador C, Anagnostopoulos I, et al. 2022; The 5th edition of the World Health Organization classification of haematolymphoid tumours: lymphoid neoplasms. Leukemia. 36:1720–48. DOI: 10.1038/s41375-022-01620-2. PMID: 35732829. PMCID: PMC9214472.

25. NCCN. Multiple Myeloma; National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology Version 2.2024.

26. Campo E, Jaffe ES, Cook JR, et al. 2022; The international consensus classification of mature lymphoid neoplasms: a report from the clinical advisory committee. Blood. 140:1229–53. DOI: 10.1182/blood.2022015851. PMID: 35653592. PMCID: PMC9479027.

27. Döhner H, Wei AH, Appelbaum FR, et al. 2022; Diagnosis and management of AML in adults: 2022 recommendations from an international expert panel on behalf of the ELN. Blood. 140:1345–77. DOI: 10.1182/blood.2022016867. PMID: 35797463.

28. NCCN. Chronic Myeloid Leukemia; National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology Version 1.2024.

29. Pfeilstöcker M, Tuechler H, Sanz G, et al. 2016; Time-dependent changes in mortality and transformation risk in MDS. Blood. 128:902–10. DOI: 10.1182/blood-2016-02-700054. PMID: 27335276. PMCID: PMC5161006.

30. Virk H, eedharanunni S Sr, Palla S, et al. 2022; Detection of NUP214-ABL1 translocation using BCR-ABL1 dual color FISH probes in T-cell acute lymphoblastic leukemia-an illustrative report and review of literature. Blood Res. 57:278–81. DOI: 10.5045/br.2022.2022134. PMID: 36348635. PMCID: PMC9812733.

31. da Silva FB, Machado-Neto JA, Bertini V, et al. 2017; Single-nucleotide polymorphism array (SNP-A) improves the identification of chromosomal abnormalities by metaphase cytogenetics in myelodysplastic syndrome. J Clin Pathol. 70:435–42. DOI: 10.1136/jclinpath-2016-204023. PMID: 27836923.

32. Xu X, Johnson EB, Leverton L, et al. 2013; The advantage of using SNP array in clinical testing for hematological malignancies-a comparative study of three genetic testing methods. Cancer Genet. 206:317–26. DOI: 10.1016/j.cancergen.2013.09.001. PMID: 24269304.

33. Byun JM, Yoo SJ, Kim HJ, et al. 2022; IDH1/2 mutations in acute myeloid leukemia. Blood Res. 57:13–9. DOI: 10.5045/br.2021.2021152. PMID: 35197370. PMCID: PMC8958365.

34. Singh AK, Olsen MF, Lavik LAS, Vold T, Drabløs F, Sjursen W. 2021; Detecting copy number variation in next generation sequencing data from diagnostic gene panels. BMC Med Genomics. 14:214. DOI: 10.1186/s12920-021-01059-x. PMID: 34465341. PMCID: PMC8406611. PMID: 84d201fa49674f48a6b546f71115b19b.

35. Medvedev P, Stanciu M, Brudno M. 2009; Computational methods for discovering structural variation with next-generation sequencing. Nat Methods. 6:S13–20. DOI: 10.1038/nmeth.1374. PMID: 19844226.

36. Engvall M, Cahill N, Jonsson BI, Höglund M, Hallböök H, Cavelier L. 2020; Detection of leukemia gene fusions by targeted RNA-sequencing in routine diagnostics. BMC Med Genomics. 13:106. DOI: 10.1186/s12920-020-00739-4. PMID: 32727569. PMCID: PMC7388219. PMID: 5e85005c5d9c4e89b00736435ddcd638.

37. Lee YE, Park JH, Lim HJ, Kim HR, Shin JH, Shin MG. 2022; Comparative evaluation of the developed targeted RNA sequencing system and a commercialized test panel. Blood Res. 57:235–8. DOI: 10.5045/br.2022.2022095. PMID: 35880497. PMCID: PMC9492530.

38. Kim B, Lee H, Shin S, Lee ST, Choi JR. 2019; Clinical Evaluation of massively parallel RNA sequencing for detecting recurrent gene fusions in hematologic malignancies. J Mol Diagn. 21:163–70. DOI: 10.1016/j.jmoldx.2018.09.002. PMID: 30347268.

39. Qu X, Yeung C, Coleman I, Nelson PS, Fang M. 2020; Comparison of four next generation sequencing platforms for fusion detection: oncomine by ThermoFisher, AmpliSeq by illumina, FusionPlex by ArcherDX, and QIAseq by QIAGEN. Cancer Genet. 243:11–8. DOI: 10.1016/j.cancergen.2020.02.007. PMID: 32197218. PMCID: PMC9434709.

40. Stengel A, Nadarajah N, Haferlach T, et al. 2018; Detection of recurrent and of novel fusion transcripts in myeloid malignancies by targeted RNA sequencing. Leukemia. 32:1229–38. DOI: 10.1038/s41375-017-0002-z. PMID: 29479069.

41. Jeon MJ, Yu ES, Kim DS, et al. 2023; Performance evaluation and clinical impact of the oncomine myeloid research assay for gene expression analysis in myeloid haematologic malignancies. J Clin Pathol. 76:778–83. DOI: 10.1136/jcp-2022-208425. PMID: 35999034.

42. Zbieranski N, Insuasti-Beltran G. 2024; Analytical validation of an automated semiconductor-based next-generation sequencing assay for detection of DNA and RNA alterations in myeloid neoplasms. J Mol Diagn. 26:29–36. DOI: 10.1016/j.jmoldx.2023.09.011. PMID: 37879438.

43. Bhai P, Hsia CC, Schenkel LC, et al. 2022; Clinical utility of implementing a frontline NGS-based DNA and RNA fusion panel test for patients with suspected myeloid malignancies. Mol Diagn Ther. 26:333–43. DOI: 10.1007/s40291-022-00581-7. PMID: 35381971.

44. Ryan SL, Peden JF, Kingsbury Z, et al. 2023; Whole genome sequencing provides comprehensive genetic testing in childhood B-cell acute lymphoblastic leukaemia. Leukemia. 37:518–28. DOI: 10.1038/s41375-022-01806-8. PMID: 36658389. PMCID: PMC9991920.

45. Roepman P, de Bruijn E, van Lieshout S, et al. 2021; Clinical validation of whole genome sequencing for cancer diagnostics. J Mol Diagn. 23:816–33. DOI: 10.1016/j.jmoldx.2021.04.011. PMID: 33964451.

46. Logsdon GA, Vollger MR, Eichler EE. 2020; Long-read human genome sequencing and its applications. Nat Rev Genet. 21:597–614. DOI: 10.1038/s41576-020-0236-x. PMID: 32504078. PMCID: PMC7877196.

47. Smadbeck J, Peterson JF, Pearce KE, et al. 2019; Mate pair sequencing outperforms fluorescence in situ hybridization in the genomic characterization of multiple myeloma. Blood Cancer J. 9:103. DOI: 10.1038/s41408-019-0255-z. PMID: 31844041. PMCID: PMC6914798.

48. Aypar U, Smoley SA, Pitel BA, et al. 2019; Mate pair sequencing improves detection of genomic abnormalities in acute myeloid leukemia. Eur J Haematol. 102:87–96. DOI: 10.1111/ejh.13179. PMID: 30270457. PMCID: PMC7379948.

49. Tran AN, Taylan F, Zachariadis V, et al. 2018; High-resolution detection of chromosomal rearrangements in leukemias through mate pair whole genome sequencing. PLoS ONE. 13:e0193928. DOI: 10.1371/journal.pone.0193928. PMID: 29529047. PMCID: PMC5846771. PMID: 52616a292e3b4af5a890ca5133b5c220.

50. Duncavage EJ, Schroeder MC, O'Laughlin M, et al. 2021; Genome sequencing as an alternative to cytogenetic analysis in myeloid cancers. N Engl J Med. 384:924–35. DOI: 10.1056/NEJMoa2024534. PMID: 33704937. PMCID: PMC8130455.

51. Lilljebjörn H, Orsmark-Pietras C, Mitelman F, Hagström-Andersson A, Fioretos T. 2022; Transcriptomics paving the way for improved diagnostics and precision medicine of acute leukemia. Semin Cancer Biol. 84:40–9. DOI: 10.1016/j.semcancer.2021.09.013. PMID: 34606984.

52. Brown LM, Lonsdale A, Zhu A, et al. 2020; The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia. Blood Adv. 4:930–42. DOI: 10.1182/bloodadvances.2019001008. PMID: 32150610. PMCID: PMC7065479.

53. Docking TR, Parker JDK, Jädersten M, et al. 2021; A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia. Nat Commun. 12:2474. DOI: 10.1038/s41467-021-22625-y. PMID: 33931648. PMCID: PMC8087683. PMID: b8f2ebaeb4ca47dbbfddf2abb90ffb18.

54. Berglund E, Barbany G, Orsmark-Pietras C, et al. 2022; A Study protocol for validation and implementation of whole-genome and -transcriptome sequencing as a comprehensive precision diagnostic test in acute leukemias. Front Med (Lausanne). 9:842507. DOI: 10.3389/fmed.2022.842507. PMID: 35402448. PMCID: PMC8987911. PMID: 70fbc65187f14244b531f516d55fbc01.

55. Balducci E, Kaltenbach S, Villarese P, et al. 2022; Optical genome mapping refines cytogenetic diagnostics, prognostic stratification and provides new molecular insights in adult MDS/AML patients. Blood Cancer J. 12:126. DOI: 10.1038/s41408-022-00718-1. PMID: 36055992. PMCID: PMC9440217. PMID: 87432a0ce3c84ceea234e0dc50e3058c.

56. Gerding WM, Tembrink M, Nilius-Eliliwi V, et al. 2022; Optical genome mapping reveals additional prognostic information compared to conventional cytogenetics in AML/MDS patients. Int J Cancer. 150:1998–2011. DOI: 10.1002/ijc.33942. PMID: 35064925.

57. Levy B, Baughn LB, Akkari Y, et al. 2023; Optical genome mapping in acute myeloid leukemia: a multicenter evaluation. Blood Adv. 7:1297–307. DOI: 10.1182/bloodadvances.2022007583. PMID: 36417763. PMCID: PMC10119592.

58. Sahajpal NS, Mondal AK, Tvrdik T, et al. 2022; Clinical validation and diagnostic utility of optical genome mapping for enhanced cytogenomic analysis of hematological neoplasms. J Mol Diagn. 24:1279–91. DOI: 10.1016/j.jmoldx.2022.09.009. PMID: 36265723.

59. Nilius-Eliliwi V, Gerding WM, Schroers R, Nguyen HP, Vangala DB. 2023; Optical genome mapping for cytogenetic diagnostics in AML. Cancers (Basel). 15:1684. DOI: 10.3390/cancers15061684. PMID: 36980569. PMCID: PMC10046241. PMID: 8044125cd05145fa8bb2bea74e9670dd.

60. Lestringant V, Duployez N, Penther D, et al. 2021; Optical genome mapping, a promising alternative to gold standard cytogenetic approaches in a series of acute lymphoblastic leukemias. Genes Chromosomes Cancer. 60:657–67. DOI: 10.1002/gcc.22971. PMID: 33982372.