Claus Meyer1, Bruno A Lopes1,2, Aurélie Caye-Eude3, Hélène Cavé3, Chloé Arfeuille3, Wendy Cuccuini4, Rosemary Sutton5, Nicola C Venn5, Seung Hwan Oh1,6, Grigory Tsaur7, Gabriele Escherich8, Tobias Feuchtinger9, Hansen J Kosasih10, Seong L Khaw10, Paul G Ekert5,10, Maria S Pombo-de-Oliveira11, Audrey Bidet12, Bardya Djahanschiri13, Ingo Ebersberger13,14, Marketa Zaliova15, Jan Zuna15, Zuzana Zermanova16, Vesa Juvonen17, Renate Panzer Grümayer18, Grazia Fazio19, Gianni Cazzaniga19, Patrizia Larghero1, Mariana Emerenciano2, Rolf Marschalek20. 1. DCAL/Institute of Pharmaceutical Biology, Goethe-University Frankfurt, Frankfurt am Main, Germany. 2. Division of Clinical Research, Research Center, Instituto Nacional de Cancer, Rio de Janeiro, Brazil. 3. Department of Genetics, AP-HP Robert Debré, Paris Diderot University, Paris, France. 4. Department of Cytogenetics, Saint Louis Hospital, Paris, France. 5. Children's Cancer Institute Australia, University of NSW Sydney, Sydney, Australia. 6. Department of Laboratory Medicine, Inje University College of Medicine, Busan, Korea. 7. Regional Children Hospital 1, Research Institute of Medical Cell Technologies, Pediatric Oncology and Hematology Center, Ural Federal University named after the first President of Russia BN Yeltsin, Ekaterinburg, Russia. 8. Clinic of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 9. Department of Pediatric Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Dr. von Hauner University Children's Hospital, Ludwig Maximilian University Munich, Munich, Germany. 10. Murdoch Children's Research Institute, The Royal Children's Hospital, Flemington Road Parkville, 3052, Victoria, Australia. 11. Pediatric Hematology-Oncology Program-Research Center, Instituto Nacional de Cancer Rio de Janeiro, Rio de Janeiro, Brazil. 12. Laboratoire d'Hématologie, University Hospital, Brest, CHU de Bordeaux, Bordeaux, France. 13. Department of Applied Bioinformatics, Institute of Cell Biology and Neuroscience, Goethe-Universität Frankfurt, Frankfurt am Main, 60438, Germany. 14. Senckenberg Climate and Research Centre (BIK-F), Frankfurt am Main, 60325, Germany. 15. CLIP, Department of Paediatric Haematology/Oncology, Charles University Prague, 2nd Faculty of Medicine, Prague, Czech Republic. 16. Center of Oncocytogenetics, Institute of Medical Biochemistry and Laboratory Diagnostics, General University Hospital and First Faculty of Medicine, Charles University, Prague, Czech Republic. 17. Department of Clinical Chemistry and Laboratory Division, Turku University Hospital, Turku, Finland. 18. Children's Cancer Research Institute, Medical University of Vienna, Vienna, Austria. 19. Centro Ricerca Tettamanti, Clinica Pediatrica University of Milano-Bicocca, Monza, Italy. 20. DCAL/Institute of Pharmaceutical Biology, Goethe-University Frankfurt, Frankfurt am Main, Germany. rolf.marschalek@em.uni-frankfurt.de.
To the Editor,For nearly 3 decades, the humanMLL (KMT2A) gene and its rearrangements have been investigated in many different laboratories around the world. At our diagnostic center (DCAL Frankfurt), our standard strategy for the identification of MLL-r is based on two independent approaches, namely “Multiplex” (MP)-polymerase chain reaction (PCR) and “Long distance inverse” (LDI)-PCR approach [1]. The MP-PCR approach is used to rapidly identify the eight most frequent MLL fusions (AF4, AF6, AF9, AF10, ENL, ELL, EPS15, and PTDs) which encompass ~90% of all diagnosed MLL-r leukemiapatients, while LDI-PCR is used for all other patients (~10%). By applying both technologies, we have accumulated 94 direct MLL-gene fusions and 247 reciprocal fusion partner genes [2]. Nearly, all breakpoints have been identified in the major breakpoint cluster region (BCR) of the MLL gene (MLL exons 8–14). However, some of the patients remained negative, although they were positively prescreened by various methods.In order to diagnose MLL breakpoints in every patient, a total of 2688 overlapping Illumina capture probes covering the whole-MLL gene were designed and used to analyze a cohort of ALpatients (n = 109) where we had either limited (n = 4; PCR positive but not sequenced) or no information (n = 105) on their molecular status. As depicted in Fig. 1a, we identified chromosomal rearrangements in 93 out of 109 patient cases. Sixteen patients remained MLL-r negative and were therefore assigned as patients with “unknown status”. The data analyses of the remaining 93 patients revealed the following distribution: for 67 patients (72%) a breakpoint could be analyzed in the major BCR; 5 patients (5%) displayed only the reciprocal der(TP) with breakpoints in exon 11 (putative CEP83-MLL spliced fusion), intron 11 (n = 3; putative FKBP8-MLL spliced fusion, AF9-MLL, RELA-MLL) and intron 27 (IFT46-MLL), respectively. Surprisingly, an additional 21 patients (23%) had their breakpoints outside of the major BCR, but inside a novel, minor BCR. This novel BCR is localizing between MLL intron 19 and exon 24 (with a clear preference for MLL intron 21–23).
Fig. 1
Overview about all analyzed patients, their molecular information and breakpoint distribution. a Data from 109 patients which were analyzed with NGS in percentages. Their breakpoint distribution is displayed left (major BCR; n = 67) and right (minor BCR; n = 21). Five patients displayed only a reciprocal fusion, while 16 cases displayed no MLL rearrangement. b Top: chromosome 11 is depicted with highlighting of the MLL (red) and USP2 (green) genes. Below: all the genes between MLL and USP; blue marked genes: additional genes found in this study to be rearranged with MLL; orange marked genes: genes that have been earlier described to be rearranged with MLL. Recombinations between MLL and USP2 are caused by an inversion, with reciprocal alleles that carry additional deletions or complex rearrangements
Overview about all analyzed patients, their molecular information and breakpoint distribution. a Data from 109 patients which were analyzed with NGS in percentages. Their breakpoint distribution is displayed left (major BCR; n = 67) and right (minor BCR; n = 21). Five patients displayed only a reciprocal fusion, while 16 cases displayed no MLL rearrangement. b Top: chromosome 11 is depicted with highlighting of the MLL (red) and USP2 (green) genes. Below: all the genes between MLL and USP; blue marked genes: additional genes found in this study to be rearranged with MLL; orange marked genes: genes that have been earlier described to be rearranged with MLL. Recombinations between MLL and USP2 are caused by an inversion, with reciprocal alleles that carry additional deletions or complex rearrangementsMost of the new BCR cases represented MLL–USP2 gene fusions (n = 17). USP2 is localized about 1 Mbp telomer to MLL at 11q23.3 and transcriptionally orientated in direction of the centromere of chromosome 11, classifying all these fusions as intrachromosomal inversions (see Fig. 1b). In addition, we identified four balanced translocations in the minor BCR: one patient with an USP8 fusion (see Fig. 2 and Suppl. Figure S1), two with AF4 and one with AF9.
Fig. 2
Detailed distribution of all breakpoints in both BCRs of MLL. The MLL gene is depicted from exon 4 to the end. The major BCR is marked in green, the minor BCR in red. Main breakpoint regions are depicted in dark green/red while regions with fewer breakpoints are depicted in light green/red. The fusions sites and the fusion partners are shown. Information about the 5 cases with no der(11) or the 23 cases with 3′-MLL deletions are given in the box at the right bottom
Detailed distribution of all breakpoints in both BCRs of MLL. The MLL gene is depicted from exon 4 to the end. The major BCR is marked in green, the minor BCR in red. Main breakpoint regions are depicted in dark green/red while regions with fewer breakpoints are depicted in light green/red. The fusions sites and the fusion partners are shown. Information about the 5 cases with no der(11) or the 23 cases with 3′-MLL deletions are given in the box at the right bottomMLL–USP2 and MLL–USP8 alleles seem to be restricted to the minor BCR (see Fig. 2), because they were never diagnosed in association with the major BCR. Most of the reciprocal USP2–MLL fusions were scattered over a larger region at 11q23.3 (see Fig. 2), involving also upstream (C2CD2L) and downstream genes (USP2-AS1). Our analysis revealed also five patients with 3′-MLL deletions that were caused by microdeletions (<200 bp), larger deletions (up to 34 kbp), or complex rearrangements including other chromosomes as well (n = 4; chromosome regions 2p21, 4q13.1, 12p13.33, and 18p11.32). A detailed picture of the investigated MLL–USP2 and MLL–USP8 and their reciprocal fusions is shown in the Suppl. Fig. S2A–D.All patients with a rearrangement of USP2 or USP8 fused the conserved “UCH-domain” to an extended 5′-MLL portion (see Suppl. Fig. S1A). This may indicate that the UCH domain has a functional importance for the resulting MLL fusion protein. USP genes belong to a large group of deubiquitinating proteins binding to specific target proteins [3-5]. The USP family exhibits a ubiquitin-specific protease (UCH domain) that is characterized by several conserved amino acids that are summarized as CYS- and ASP-box (see Suppl. Fig. 1B). USP2 protein deubiquinates and stabilizes MDM2, leading to an enhanced degradation of p53 [6]. This in turn activates MYC, because active p53 induces the transcription of several microRNAs that target MYC mRNA.MLL fusions with the conserved 3′-UCH domain of USP2 and USP8 may change profoundly the functions of these novel MLL fusion proteins. It has already been shown that PHD2 [7] and PHD3/BD [8] both bind to proteins (CDC34 and ESCASB2) that mediate the destruction of MLL by poly-ubiquitination and proteasomal degradation. Fusing single or all PHD domains to a der(11) product (MLL-AF9 and MLL-ENL) caused even a strong drop of their transforming potential [9, 10]. This well-described degradation mechanism of MLL may now be counteracted by the UCH domain of MLL–USP2 or MLL–USP8, and thus, restoring their oncogenic transformation capacity.In our cohort, we also identified new MLL fusion partner genes (n = 3). These novel fusion genes were SNX9 (6q25.3), USP8 (15q21.2), and SEPT3 (22q13.2). SNX9 encodes a protein known to be a member of the sorting nexin family which contain a phosphoinositide binding domain and are involved in intracellular trafficking. The SNX9 protein has a variety of interaction partners, including an adapter protein 2, dynamin, tyrosine kinase nonreceptor 2, Wiskott–Aldrich syndrome-like, and ARP3 actin-related protein 3. USP8 has diverse functions, being required for the internalization of liganded receptor tyrosine kinases and stabilization of ESCRT components. The USP8 protein is thought to regulate the morphology of the endosome by ubiquitination of proteins on this organelle and is involved in cargo sorting and membrane trafficking at the early endosome stage. SEPT3 is the seventh member of the septin family of GTPases that is fused to MLL. Members of this family are required for cytokinesis.A few cases of MLL–USP2 fusions have already been described. However, these were single patient cases and they were classified as exceptional rearrangements [11-13]. Our NGS approach allowed for the first time the recurrent characterization of breakpoints in this novel minor BCR region of the MLL gene. Moreover, our targeted NGS approach enabled us to overcome the technical limitations associated with LDI-PCR and MP-PCR approaches.Another advantage of the targeted NGS approach is the simultaneous identification of 3′ MLL deletions or copy number variations. In the current study, 23 of the patients (out of 88: 26%) had a 3′ MLL deletion. According to our data, 3′-MLL deletions were present in both breakpoint groups (major and minor) to a similar extent with 26.9% and 23.8%, respectively. This seems to be much higher than previously described (Andersson et al. [12]: 13%; Peterson et al. [14]: 7%).In diagnostic fluorescence in situ hybridization analyses, these MLL–USP2 cases revealed two major patterns: (1) loss of the 3′-MLL probe signal, and (2) a normal pattern typical for MLL wild-type (Suppl. Table S1b, Suppl. Fig. S3). Considering the clinical data (Suppl. Table S1a–c), our 17 patients with MLL–USP2 were divided into 8 males and 9 females. All of them were children, and the median age at diagnosis was 17 months (range: 3–120 months). The median leukocyte count was 30.4 × 109/L (range: 3.4–324.0 × 109/L), and the disease phenotype was predominantly B-ALL (n = 12), followed by mixed-phenotype acute leukemia (MPAL) (n = 4) and acute myeloid leukemia (n = 1). The MPAL cases all had mixed myeloid and B-cell phenotype. The patients were treated with diverse therapy protocols. Five patients (29%) presented with central nervous system disease, and 13 patients (76%) had positive-minimal residual disease (MRD) levels at day 33. Prednisone response was measured in 12 patients with a poor response in 5 patients (42%). The median follow-up of the patients was 1.2 years (range: 0.1–11.1 years), and 2 cases died after 5 and 9 months following diagnosis. The remaining patients are still at first clinical remission.In conclusion, we have identified a minor BCR within the humanMLL gene that is recurrently associated in acute leukemiapatients with MLL–USP2 fusion alleles as well as MLL fusion partnerships with USP8, AF4, and AF9. However, with 17 cases out of ~2500 analyzed patients the incidence is less than 1% while still ranking fourteenth of our updated fusion gene list (see Table 1 of reference 1). The discovery of a second, minor BCR extends our knowledge of the MLL-recombinome and MLL-r oncogenesis. Moreover, these findings will enable many labs to make changes in their diagnostic set-up for MLL-MRD diagnostics to ensure the best medical treatment for a group of patients that is still very hard to cure.Supplementary data file
Authors: Michael J Clague; Igor Barsukov; Judy M Coulson; Han Liu; Daniel J Rigden; Sylvie Urbé Journal: Physiol Rev Date: 2013-07 Impact factor: 37.312
Authors: Kathryn G Roberts; Yongjin Li; Debbie Payne-Turner; Richard C Harvey; Yung-Li Yang; Deqing Pei; Kelly McCastlain; Li Ding; Charles Lu; Guangchun Song; Jing Ma; Jared Becksfort; Michael Rusch; Shann-Ching Chen; John Easton; Jinjun Cheng; Kristy Boggs; Natalia Santiago-Morales; Ilaria Iacobucci; Robert S Fulton; Ji Wen; Marcus Valentine; Cheng Cheng; Steven W Paugh; Meenakshi Devidas; I-Ming Chen; Shalini Reshmi; Amy Smith; Erin Hedlund; Pankaj Gupta; Panduka Nagahawatte; Gang Wu; Xiang Chen; Donald Yergeau; Bhavin Vadodaria; Heather Mulder; Naomi J Winick; Eric C Larsen; William L Carroll; Nyla A Heerema; Andrew J Carroll; Guy Grayson; Sarah K Tasian; Andrew S Moore; Frank Keller; Melissa Frei-Jones; James A Whitlock; Elizabeth A Raetz; Deborah L White; Timothy P Hughes; Jaime M Guidry Auvil; Malcolm A Smith; Guido Marcucci; Clara D Bloomfield; Krzysztof Mrózek; Jessica Kohlschmidt; Wendy Stock; Steven M Kornblau; Marina Konopleva; Elisabeth Paietta; Ching-Hon Pui; Sima Jeha; Mary V Relling; William E Evans; Daniela S Gerhard; Julie M Gastier-Foster; Elaine Mardis; Richard K Wilson; Mignon L Loh; James R Downing; Stephen P Hunger; Cheryl L Willman; Jinghui Zhang; Charles G Mullighan Journal: N Engl J Med Date: 2014-09-11 Impact factor: 91.245
Authors: Jess F Peterson; Linda B Baughn; Kathryn E Pearce; Cynthia M Williamson; Jonna C Benevides Demasi; Renee M Olson; Tony A Goble; Reid G Meyer; Patricia T Greipp; Rhett P Ketterling Journal: Genes Chromosomes Cancer Date: 2018-09-10 Impact factor: 5.006
Authors: Thomas B Alexander; Zhaohui Gu; Ilaria Iacobucci; Kirsten Dickerson; John K Choi; Beisi Xu; Debbie Payne-Turner; Hiroki Yoshihara; Mignon L Loh; John Horan; Barbara Buldini; Giuseppe Basso; Sarah Elitzur; Valerie de Haas; C Michel Zwaan; Allen Yeoh; Dirk Reinhardt; Daisuke Tomizawa; Nobutaka Kiyokawa; Tim Lammens; Barbara De Moerloose; Daniel Catchpoole; Hiroki Hori; Anthony Moorman; Andrew S Moore; Ondrej Hrusak; Soheil Meshinchi; Etan Orgel; Meenakshi Devidas; Michael Borowitz; Brent Wood; Nyla A Heerema; Andrew Carrol; Yung-Li Yang; Malcolm A Smith; Tanja M Davidsen; Leandro C Hermida; Patee Gesuwan; Marco A Marra; Yussanne Ma; Andrew J Mungall; Richard A Moore; Steven J M Jones; Marcus Valentine; Laura J Janke; Jeffrey E Rubnitz; Ching-Hon Pui; Liang Ding; Yu Liu; Jinghui Zhang; Kim E Nichols; James R Downing; Xueyuan Cao; Lei Shi; Stanley Pounds; Scott Newman; Deqing Pei; Jaime M Guidry Auvil; Daniela S Gerhard; Stephen P Hunger; Hiroto Inaba; Charles G Mullighan Journal: Nature Date: 2018-09-12 Impact factor: 49.962
Authors: Anna K Andersson; Jing Ma; Jianmin Wang; Xiang Chen; Amanda Larson Gedman; Jinjun Dang; Joy Nakitandwe; Linda Holmfeldt; Matthew Parker; John Easton; Robert Huether; Richard Kriwacki; Michael Rusch; Gang Wu; Yongjin Li; Heather Mulder; Susana Raimondi; Stanley Pounds; Guolian Kang; Lei Shi; Jared Becksfort; Pankaj Gupta; Debbie Payne-Turner; Bhavin Vadodaria; Kristy Boggs; Donald Yergeau; Jayanthi Manne; Guangchun Song; Michael Edmonson; Panduka Nagahawatte; Lei Wei; Cheng Cheng; Deqing Pei; Rosemary Sutton; Nicola C Venn; Albert Chetcuti; Amanda Rush; Daniel Catchpoole; Jesper Heldrup; Thoas Fioretos; Charles Lu; Li Ding; Ching-Hon Pui; Sheila Shurtleff; Charles G Mullighan; Elaine R Mardis; Richard K Wilson; Tanja A Gruber; Jinghui Zhang; James R Downing Journal: Nat Genet Date: 2015-03-02 Impact factor: 38.330
Authors: C Meyer; T Burmeister; D Gröger; G Tsaur; L Fechina; A Renneville; R Sutton; N C Venn; M Emerenciano; M S Pombo-de-Oliveira; C Barbieri Blunck; B Almeida Lopes; J Zuna; J Trka; P Ballerini; H Lapillonne; M De Braekeleer; G Cazzaniga; L Corral Abascal; V H J van der Velden; E Delabesse; T S Park; S H Oh; M L M Silva; T Lund-Aho; V Juvonen; A S Moore; O Heidenreich; J Vormoor; E Zerkalenkova; Y Olshanskaya; C Bueno; P Menendez; A Teigler-Schlegel; U Zur Stadt; J Lentes; G Göhring; A Kustanovich; O Aleinikova; B W Schäfer; S Kubetzko; H O Madsen; B Gruhn; X Duarte; P Gameiro; E Lippert; A Bidet; J M Cayuela; E Clappier; C N Alonso; C M Zwaan; M M van den Heuvel-Eibrink; S Izraeli; L Trakhtenbrot; P Archer; J Hancock; A Möricke; J Alten; M Schrappe; M Stanulla; S Strehl; A Attarbaschi; M Dworzak; O A Haas; R Panzer-Grümayer; L Sedék; T Szczepański; A Caye; L Suarez; H Cavé; R Marschalek Journal: Leukemia Date: 2017-07-13 Impact factor: 11.528
Authors: Ryotaro Nishi; Paul Wijnhoven; Carlos le Sage; Jorrit Tjeertes; Yaron Galanty; Josep V Forment; Michael J Clague; Sylvie Urbé; Stephen P Jackson Journal: Nat Cell Biol Date: 2014-09-07 Impact factor: 28.824
Authors: Lauren M Brown; Andrew Lonsdale; Andrea Zhu; Nadia M Davidson; Breon Schmidt; Anthony Hawkins; Elise Wallach; Michelle Martin; Francoise M Mechinaud; Seong Lin Khaw; Ray C Bartolo; Louise E A Ludlow; Jackie Challis; Ian Brooks; Vida Petrovic; Nicola C Venn; Rosemary Sutton; Ian J Majewski; Alicia Oshlack; Paul G Ekert Journal: Blood Adv Date: 2020-03-10
Authors: Hansen J Kosasih; Nadia M Davidson; Stefan Bjelosevic; Emma Morrish; Margs S Brennan; Alicia Oshlack; Ricky W Johnstone; Gabriela Brumatti; Seong L Khaw; Paul G Ekert Journal: Blood Adv Date: 2020-10-13