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Relationship: 1635


A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

DSB leads to MLL translocation

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes. Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Inhibitor binding to topoisomerase II leading to infant leukaemia adjacent High Not Specified Andrea Terron (send email) Open for comment. Do not cite WPHA/WNT Endorsed

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER.  More help

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Mixed High

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

There is evidence that the inappropriate joining of ‘hanging ends’ following DSB happens in the same transcriptional factory (hub), and the result is a fusion gene and ultimately protein product (Cowell & Austin 2012; Pendleton et al 2014; Sanjuan-Pla et al 2015). The first part of this description has not been shown in the putative target cell, which is still not unequivocally identified, but for the second part there is ample evidence of formation of MLL-AF4 fusion product that has been a result of a very early chromosomal translocation and rejoining. It is of interest that the simultaneously induced specific DSBs in the MLL gene and two different translocation partners (AF4 and AF9) by engineered nucleases in human HSPCs resulted in specific ‘patient-like’ chromosomal translocations (Breese et al 2016).

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER.  For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings.  Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help
Biological Plausibility
Addresses the biological rationale for a connection between KEupstream and KEdownstream.  This field can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured.   More help

The KER as such is biologically plausible and strong. DNA strand breaks, if not resulting in cell death, may lead to chromosomal translocation in the surviving cell population (McClendon et al. 2007).  DNA breaks and MLL rearrangements by etoposide and bioflavonoids have been demonstrated in human fetal liver haematopoietic stem cells, in human embryonic stem cells and in human prehaematopoietic mesenchymal stem cells as well as in cord blood mononuclear cells (Ishii et al 2002; Blanco et al 2004; Moneypenny et al 2006; Bueno et al 2009; Menendez et al 2009), which shows that DSB (in this specific case due to TopoII poisoning) -associated MLL rearrangements are produced in appropriate human cells in utero.

Uncertainties and Inconsistencies
Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

A target cell, i.e. leukaemia-initiating cell, has not been identified with sufficient confidence and consequently there is no target cell model to recapitulate the linkage between TopoII inhibition (‘poisoning’) and the production of DSB in an appropriate target. Recently, by the expression of engineered nucleases (TALENs) to induce simultaneous patient specific double strand breaks in the MLL gene and two different known translocation partners (AF4 and AF9), Breese et al (2015) were able to produce specific chromosomal translocations in K562 cells and in primary HSPCs.

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references.  More help
Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.  More help
Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). More help
Known Feedforward/Feedback loops influencing this KER
Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

Seminal studies demonstrated an in utero, pre-natal origin of these MLLr in monozygotic twins with concordant B-ALL, in retrospective analysis in Guthrie cards and cord bloods (Ford et al., 1993; Gale et al., 1997). A single-pulse of etoposide induces DSBs measured by g-H2AX staining in all primary cell types tested (hESC, fetal-, neonatal- and adult-derived CD34+ HSPCs)(Rodriguez et al. 2020).


List of the literature that was cited for this KER description. More help

Blanco JG, Edick MJ, Relling MV. Etoposide induces chimeric Mll gene fusions. FEDERATION OF AMERICAN SOCIETIES FOR EXPERIMENTAL BIOLOGY (FASEB) 2004; 18(1):173–5. doi: 10.1096/fj.03-0638fje

Breese EH, Buechele C, Dawson C, Cleary ML, Porteus MH. Use of Genome Engineering to Create Patient Specific MLL Translocations in Primary Human Hematopoietic Stem and Progenitor Cells. Public Library of Science (PLoS ONE) 2015 Sep 9;10(9):e0136644. doi: 10.1371/journal.pone.0136644.

Buechele C, Breese EH, Schneidawind D, Lin CH, Jeong J, Duque-Afonso J, Wong SH, Smith KS, Negrin RS, Porteus M, Cleary ML. MLL leukemia induction by genome editing of human CD34+ hematopoietic cells. Blood 2015 Oct 1;126(14):1683-1694. doi: 10.1182/blood-2015-05-646398.

Chen W, Li Q, Hudson WA, Kumar A, Kirchhof N, Kersey JH. A murine Mll-AF4 knock-in model results in lymphoid and myeloid deregulation and hematologic malignancy. Blood Journal 2006; 108(2):669–77. doi: 10.1182/blood-2005-08-3498

Cowell  IG and AustinInt CA. Mechanism of Generation of Therapy Related Leukemia in Response to Anti-Topoisomerase II Agents. J. Environ. Res. Public Health 2012, 9(6), 2075-2091;

Ford, A. M., Ridge, S. A., Cabrera, M. E., Mahmoud, H., Steel, C. M., Chan, L. C., & Greaves, M. (1993). In utero rearrangements in the trithorax-related oncogene in infant leukaemias. Nature, 363(6427), 358–60.

Gale, K. B., Ford, A. M., Repp, R., Borkhardt, A., Keller, C., Eden, O. B., & Greaves, M. F. (1997). Backtracking leukemia to birth: identification of clonotypic gene fusion sequences in neonatal blood spots. Proceedings of the National Academy of Sciences of the United States of America, 94(25), 13950–4. Retrieved from

Hernandez Jerez AF, Menendez P. Linking pesticide exposure with pediatric leukemia: potential underlying mechanisms. Int J Mol Sci 2016; 17: 461.

Ishii E, Eguchi M, Eguchi-Ishimae M, Yoshida N, Oda M, Zaitsu M, et al. In vitro cleavage of the MLL gene by topoisomerase II inhibitor (etoposide) in normal cord and peripheral blood mononuclear cells. International journal of hematology. 2002; 76(1):74–9.

Li Z, Sun B, Clewell RA, Adeleye Y, Andersen ME, Zhang Q. Dose-response modeling of etoposide-induced DNA damage response. Toxicological Sciences 2014 Feb;137(2):371-84. doi: 10.1093/toxsci/kft259.

Libura J, Slater DJ, Felix CA, Richardson C. Therapy-related acute myeloid leukemia-like MLL rearrangements are induced by etoposide in primary human CD34+ cells and remain stable after clonal expansion. Blood Journal 2005; 105(5):2124–31. doi: 10.1182/blood-2004-07-2683

Libura J, Ward M, Solecka J, Richardson C. Etoposide-initiated MLL rearrangements detected at high frequency in human primitive hematopoietic stem cells with in vitro and in vivo long-term repopulating potential. European Journal of Haematology 2008; 81(3):185–95. doi: 10.1111/j.1600-0609.2008.01103.x

McClendon AK, Osheroff N. DNA Topoisomerase II, Genotoxicity and Cancer. Mutation Research 2007; 623 (1-2): 83-97.

Moneypenny CG, Shao J, Song Y, Gallagher EP. MLL rearrangements are induced by low doses of etoposide in human fetal hematopoietic stem cells. Carcinogenesis. 2006; 27(4):874–81. Epub 2005/12/27. doi: 10.1093/carcin/bgi322

Montecucco A, Zanetta F, Biamonti G. Molecular mechanisms of etoposide. JOURNAL OF EXPERIMENTAL AND CLINICAL SCIENCES. 2015 Jan 19;14:95-108. doi: 10.17179/Journal - Experimental and Clinical Sciences (EXCLI)2015-561.

Nanya M, Sato M, Tanimoto K, Tozuka M, Mizutani S, Takagi M. Dysregulation of the DNA Damage Response and KMT2A Rearrangement in Fetal Liver Hematopoietic Cells. Public Library of Science (PLoS ONE). 2015 Dec 11;10(12):e0144540. doi: 10.1371/journal.pone.0144540.

Pendleton M1, Lindsey RH Jr, Felix CA, Grimwade D, Osheroff N.  Topoisomerase II and leukemia. Ann N Y Acad Sci. 2014 Mar;1310:98-110. doi: 10.1111/nyas.12358. Epub 2014 Feb 3.

Pitz MW, Desai A, Grossman SA, Blakeley JO. Tissue concentration of systemically administered antineoplastic agents in human brain tumors. Journal of Neuro-Oncology 2011 Sep;104(3):629-38. doi: 10.1007/s11060-011-0564-y.

Relling MV, Yanishevski Y, Nemec J, Evans WE, Boyett JM, Behm FG, Pui CH.Etoposide and antimetabolite pharmacology in patients who develop secondary acute myeloid leukemia. Leukemia. 1998 Mar;12(3):346-52.

 Rodríguez‐Cortez, V C, Menéndez, P, 2020. Genotoxicity of permethrin and clorpyriphos on human stem and progenitor cells at different ontogeny stages: implications in leukaemia development. EFSA supporting publication 2020: 17( 5): EN‐1866. 35 pp. doi: 10.2903/sp.efsa.2020.EN‐1866

Stremetzne S, Jaehde U, Kasper R, Beyer J, Siegert W, Schunack W. Considerable plasma levels of a cytotoxic etoposide metabolite in patients undergoing high-dose chemotherapy. European Journal of Cancer 1997 May;33(6):978-9. 

Udroiu I., Sgura A. Genotoxicity sensitivity of the developing hematopoietic system. 2012. Mutation Research 2012; 767: 1-7.