To the extent possible under law, AOP-Wiki has waived all copyright and related or neighboring rights to KER:1331

Relationship: 1331

Title

The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

MLL translocation leads to IFL

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
IFL

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

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
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 Agnes Aggy (send email) Open for comment. Do not cite EAGMST Under Review

Taxonomic Applicability

Select one or more structured terms 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. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help
Term Scientific Term Evidence Link
mammals mammals High NCBI

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help
Sex Evidence
Mixed High

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help
Term Evidence
Birth to < 1 month High

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

Propagation of a leukaemic cell clone is based on both blockage of differentiation to more mature cells and ability to expand in an uncontrolled way. Formation of the MLL-rearranged fusion genes and their protein products are intimately involved in both the blocked differentiation of HSPCs and the expansion of the fusion gene-carrying clone. It is believed that the fusion gene product block cell differentiation by inhibiting the normal transcriptional programs and recruiting repressor molecules such as histone deacetylase enzymes (Greaves 2002; Teitell and Pandolfi 2009). Furthermore, the fusion gene product activates other key target genes, which ultimately lead to the propagation of transformed cell lines without normal restrictions (Greaves 2015; Sanjuan-Pla et al 2015). Therefore, the potential of both differentiation blockage and clonal expansion are inherent properties of the MLL-rearranged fusion product, based on the preservation of some original functions, even if in a modified form, and on the gain of some other functions due to the sequences from the new fusion partner gene (Marschalek 2010; Sanjuan-Pla et al 2015).

In principle all MLL fusion genes are potential initiating drivers, although clinical studies have shown a preponderance with infant leukaemia for only a few of these rearrangements. For infants diagnosed with ALL, approximately 60-80% carry an MLL rearrangement (Sam et al 2012; Jansen et al 2007), with predominant fusion partners being AF4 (41%), ENL (18%), AF9 (11%) or another partner gene (10%). In particular, the fusion gene MLL-AF4 shows a specific and consistent relationship with the disease (Menendez et al., 2009): however, it has been difficult to reproduce a manifest disease resulting from this rearrangement in in vivo animal models. For AML, about 30 % of the patients carry an MLL rearrangement.

The occurrence of MLL rearrangements at a very early fetal development is highly probable on the basis of neonatal blood spot analysis and by the high concordance rate of infant leukaemia in monozygotic twins (Ford et al 1993; Gale et al 1997; Sanjuan-Pla 2015). Menendez et al (2009) showed that MLL-AF4 fusion gene is present in bone marrow mesenchymal stem cells in infant leukaemia patients, but not in patients of childhood leukaemia, suggesting that the origin of the fusion gene is probably prehaematopoietic. Consequently, the affected cell, the so called leukaemia-initiating cell, may be an early prehaematopoietic mesodermal precursor, a hematopoietic stem cell or hematopoietic progenitor cell residing mainly in the liver (Greaves 2015; Sanjuan-Pla et al 2015).

MLL translocation sites (breakpoint sequences) in the therapy-related leukaemia fall within a few base pairs of etoposide-induced enzyme-mediated DNA cleavage site. Although rearrangements associated with infant leukaemias are often more complex than those observed in treatment-related leukaemias, many are nevertheless associated with stable TopoII-mediated DNA cut sites. Although all these findings are indirect regarding infant leukaemia, they are nevertheless rather persuasive in this respect.

Growing scientific evidence, including the stable genome of the patients, suggests that infant leukaemia originates from one “big-hit” occurring during a critical developmental window of stem cell vulnerability (Andersson et al 2013; Greaves 2015). Therefore, the totality of evidence suggests the essential role of the formation of MLL-AF4 (and other partner) fusion gene and product in causing pleiotropic effects in the affected cell and directing it to the obligatory pathway to the adverse outcome of leukaemia.

Molecular mechanisms

The MLL is the most common translocation gene in infant leukaemia. The N-terminal part of MLL becomes fused in frame to one of a large number of fusion partners, but in most cases, this fusion occurs between the N-terminal MLL and either AF4, AF6, AF9, AF10, or ENL (Krivtsov and Armstrong 2007). Due to the DNA-binding properties of the N-terminal MLL motif, these fusion proteins are always nuclear and bind to target genes controlled by MLL irrespective of the normal location of the C-terminal partner.

Many fusion proteins have been shown to recruit disruptor of telomeric silencing 1-like (DOT1L or officially KMT4, a histone methyltransferase that methylates lysine 79 located within the globular domain of histone H3, H3K79) to the promoters of MLL target genes. This recruitment seems to be a common feature of many oncogenic MLL fusion proteins and results in abnormal H3K79 methylation and overexpression of several MLL target genes, such as HOXA genes coding for transcription factors involved in body patterning and hematopoiesis (Chen and Armstrong, 2015). Although DOT1L is not genetically altered in the disease per se, its mislocated enzymatic activity is a direct consequence of the chromosomal translocation. Thus, DOT1L has been proposed to be a catalytic driver of leukemogenesis (Chen and Armstrong 2015). The enzymatic activity of DOT1L is critical to the pathogenesis of MLL, because methyltransferase-deficient Dot1L is capable of suppressing growth of MLL-rearranged cells. A small-molecule inhibitor of DOT1L inhibits cellular H3K79 methylation, blocks leukemogenic gene expression, and selectively kills cultured cells bearing MLL translocations (Chen and Armstrong 2015). One of the target gene of DOT1L is BCL-2, belonging to a family of anti-apoptotic genes, which maintains the survival of the MLL-rearranged cells (Benito et al 2015). Expression of BCL-2 is high in human MLL-AF4 leukemia cells from a large number of patients.  A specific BCL-2 inhibitor, ABT-199 is capable of killing MLL-AF4 leukaemia cells and prevents cell proliferation in xenograft mouse leukaemia models (Benito et al 2015). Furthermore, a MLL-AF4 cell line is sensitive to a combination of ABT-199 and DOT1L inhibitors. The figure below provides a schematic representation of the molecular pathway.

 

MLL-rearranged acute lymphoblestic leukemisa activate BCL-2 through H3K79 methylation and are sensitive to the BCL-2 specific antagonist ABT-199 (benito et al, Cell Rep 2015).

Possible facilitating mutated genes

Recurrent activating mutations in the components of the PI3K-RAS signalling pathway have been detected in almost half of the tested MLL-rearranged ALLs in one study (Andersson et al 2015). Prenatal origin of RAS mutations have been demonstrated also in other studies of infant leukaemia with frequencies of about 15-25 % of cases (Driessen et al 2013; Prelle et al 2013; Emerenciano et al 2015).  Emerenciano et al (2015) are of the opinion that RAS mutations seem not to be driver mutations, but may aid disease onset by accelerating the initial expansion of cells.

Overall the activation of the RAS pathway could support the extremely rapid progression of the infant leukaemia. Under this view the mechanism may represent a factor modulating (i.e., increasing) the progression and severity of the adverse outcome, rather than a necessary key event (second hit) for infant leukaemia. In the transgenic MLL-AF4 mouse model, activated K-RAS accelerated disease onset with a short latency (Tamai et al 2011), possibly by augmenting the upregulation of HoxA9. In a recent study of Prieto et al (2016),the activated K-RAS  enhanced extramedullary haematopoiesis of MLL-AF4 expressing cell lines and cord blood-derived CD34+ hematopoietic stem/progenitor cells that was associated with leucocytosis and central nervous system infiltration, both hallmarks of infant MLL-AF4 leukaemia. However, K-RAS activation was insufficient to initiate leukaemia, supporting that the involvement of RAS pathway is an important modifying factor in infant leukemia. It has also been demonstrated that MLL-AF6 fusion product sequesters AF6 into the nucleus to trigger RAS activation in myeloid leukaemia cells and it is possible to attenuate the activation by tipifarnib, a RAS inhibitor (Manara et al 2014).

A possibility that MLL fusions render cells susceptible to additional chromosomal damage upon exposure to etoposide was studied by introducing MLL-AF4 and AF4-MLL via CRISPR/Cas9-genome editing in HEK293 cells as a model to study MLL fusion-mediated DNA-DSB formation/repair (Castano et al 2016). In short, the expression of fusion genes does neither influence DNA signaling nor DNA-DSB repair.

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help

The overall scientific evidence, including the stable genome of patients, suggests that infant leukaemia originates from one “big-hit” occurring during a critical developmental window of stem cell vulnerability (Andersson et al 2013; Greaves 2015). Different from the “two-hit” model of the adult leukemias, the infant leukemia is a developmental disorder where the clonal expansion is a direct consequence of in utero MLL translocation.

There are animal models for infant leukaemia which recapitulate at least some salient aspects of the disease (Sanjuan-Pla et al 2015). However, for example the MLL-AF4 knock-in mice develop leukaemia only after a prolonged latency (Chen et al 2006), thus not recapitulating the ‘pathognomonic’ feature of infant leukaemia.

Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility 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 (see page 40 of the User Handbook for further information).   More help

The biological plausibility linking the MLL translocation to infant leukaemia is strong. Rearrangement in the MLL gene is commonly associated with infant acute leukaemia and the disease has unique clinical and biological feature (Ernest et al. 2002). An in utero initiation, an extremely rapid progression, and a silent mutational landscape of infant leukaemia suggest that the MLL-translocation-associated gene fusion product is itself sufficient to spawn leukaemia and no “second hit” is required. Therapy-related leukaemias following exposure to the topo II poisons such as etoposide are characterized by the MLL chromosomal translocation (Libura et al. 2006, Super et al.1993) and translocations involving MLL are associated with a gain of function and leukemogenic effect (Yu et al. 1998). A critical developmentally early window of stem cell vulnerability, involving perhaps lesions based on epigenetically controlled regulatory factors, has been suggested to explain a rare occurrence and an exceptionally short latency of infant leukaemia (Greaves 2015; Sanjuan-Pla et al 2015).  In primary HSPCs genome engineered for patient specific MLL translocations it was possible to show that this specific ‘artificial’ initiation can induce a selective advantage in survival in extended culturing and a higher clonogenic potential in colony forming assay (Breese et al. 2015).

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

The MLL-AF4 knock-in mice develop leukaemia only after a prolonged latency (Chen et al 2006), thus not recapitulating the ‘pathognomonic’ feature of infant leukaemia. Also other animal models have been developed with similar results. Thus, an adequate experimental model for infant leukaemia is still in need.

The role of a reciprocal fusion gene AF4-MLL in leukemias is controversial: it has a transformation potential in animal model (Bursen et al 2010), but it is not expressed in all MLL-AF4 patients (Andersson et al 2015). The potential role of other reciprocal fusion genes has not been studied.

Beyond MLL rearrangements, activation of cellular proliferation by mutation or other (epi)genetic insults might be necessary for overt leukaemia. Further studies are necessary to fully understand which factors would contribute to convey a proliferative advantage, as observed in cells with MLL translocation, to leukaemia.

The product of MLL and MLL-r fusion genes are histone methyltransferases (HMT), which are the best known epigenetic mechanisms involved in MLL-r infant ALL. The main epigenetic mechanism is that MLL is a HMT with a H3K4me3 genome-wide profile. When MLL breaks and fuses to a partner it recruits DOT1L, the sole HMT H3K79me3 that thus regulates gene expression of the main MLL targets, namely HOX genes, MEIS, etc. Further epigenetic mechanisms recently proposed involved BCL2 activation through H3K70 methylation and H3K27 acetylation. Overall, the gene fusion products disrupt epigenetic pathways.  The MLL-AF4 fusion protein binds to gene targets and is proposed to cause innapropiate gene activation through multiple trancription elongation and epigenetic mechanisms but further investigation is necessary to understand the exact connections between these factors and the enhancer activity. 

Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help
Time-scale
This sub-section should be used to provide 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?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help
Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help
Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help

 Rearrangement in the MLL gene is commonly associated with infant acute leukaemia and the disease has unique clinical and biological feature (Ernest et al. 2002). An in utero initiation, an extremely rapid progression, and a silent mutational landscape of infant leukaemia suggest that the MLL-translocation-associated gene fusion product is itself sufficient to spawn leukaemia and no “second hit” is required. A critical developmentally early window of stem cell vulnerability, involving perhaps lesions based on epigenetically controlled regulatory factors, has been suggested to explain a rare occurrence and an exceptionally short latency of infant leukaemia (Greaves 2015; Sanjuan-Pla et al 2015). These unique characteristics indicate that biological domain for this KER is specific to an early in-utero exposure condition.

References

List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

Andersson AK, Ma J, Wang J, et al.; St. Jude Children's Research Hospital and Washington University Pediatric Cancer Genome Project. The landscape of somatic mutations in infant MLL-rearranged acute lymphoblastic leukemias. Nature Genetics 2015 Apr;47(4):330-337. doi: 10.1038/ng.3230.

Benito JM, Godfrey L, Kojima K, et al. MLL-Rearranged Acute Lymphoblastic Leukemias Activate BCL-2 through H3K79 Methylation and Are Sensitive to the BCL-2-Specific Antagonist ABT-199. Cell Reports 2015 Dec 29;13(12):2715-27. doi: 10.1016/j.celrep.2015.12.003.

Breese EH, Buechele C., Dawson C., Cleary ML, Porteus MH. 2015. Use of genome engineering to create patient specific MLL translocation in primary hematopietic stem and progenitor cells. Public Library of Science (PLoS ONE) 2015; 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.

Bursen A, Schwabe K, Ruster B, et al. The AF4.MLL fusion protein is capable of inducing ALL in mice without requirement of MLL.AF4. Blood Journal 2010;115(17):3570-3579.

Castano J, Herrero AB, Bursen A, Gonzalez F, Marschalek R, Gutierrez NC,Menendez P. Expression of MLL-AF4 or AF4-MLL fusions does not impact the efficiency of DNA damage repair. Oncotarget. 2016 Apr 22. doi: 10.18632/oncotarget.8938.

Chen C-W, Armstrong SA. Targeting DOT1L and HOX gene expression in MLL-rearranged leukemia and beyond. Experimental Hematology 2015; 43: 673-684.

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 2006;108(2): 669-677.

Driessen EM, van Roon EH, Spijkers-Hagelstein JA, Schneider P, de Lorenzo P, Valsecchi MG, Pieters R, Stam RW. Frequencies and prognostic impact of RAS mutations in MLL-rearranged acute lymphoblastic leukemia in infants. Haematologica. 2013 Jun;98(6):937-44. doi: 10.3324/haematol.2012.067983.

Ernest P, Wang J, Korsmeyer SJ. The role of MLL in hematopoiesis and leukemia. Current opinion in hematology 2002; 9: 282-287.

Ernest P, Fisher JK, Avery W, Sade S, Foy D, Korsmeyer SJ. Definitive hematopoiesis requires the mixed-lineage leukemia gene. Developmental Cell 2004; 6: 437-443

Ezoe S. Secondary leukemia associated with the anti-cancer agent, etoposide, a topoisomerase II inhibitor. Int J Environ Res Public Health. 2012 Jul;9(7):2444-53. doi: 10.3390/ijerph9072444

Ford AM, Ridge SA, Cabrera ME, Mahmoud H, Steel CM, Chan LC, et al. In utero rearrangements in the trithorax-related oncogene in infant leukaemias. Nature. 1993; 363(6427):358–60. doi: 10.1038/363358a0

Gale KB, Ford AM, Repp R, Borkhardt A, Keller C, Eden OB, et al. Backtracking leukemia to birth: identification of clonotypic gene fusion sequences in neonatal blood spots. Proc Natl Acad Sci USA. 1997; 94(25):13950–4.

Gole B, Wiesmüller L. Leukemogenic rearrangements at the mixed lineage leukemia gene (MLL)-multiple rather than a single mechanism. Front Cell Dev Biol. 2015 Jun 25;3:41. doi: 10.3389/fcell.2015.00041.

Greaves M. Childhood leukaemia. BRITISH MEDICAL JOURNAL 2002; 324: 283-287

Greaves M. When one mutation is all it takes. Cancer Cell. 2015;27(4):433-434.

Hess JL, Yu BD, Li B, Hanson RD, Korsmeyer SJ. Defect in yolk sac hematopoiesis in mll-null embryos. Blood 1997; 90; 1799-1806.

Jansen MW, Corral L, van der Velden VH, Panzer-Grumayer R, Schrappe M, Schrauder A et al.. Immunobiological diversity in infant acute lymphoblastic leukemiais related to the occurence and type of MLL rearrangment. Leukemia 2007; 21(4): 633-641.

Joannides M, Grimwade D. Molecular biology of therapy-related leukaemias. Clin Transl Oncol 2010 Jan;12(1):8-14. doi: 10.1007/s12094-010-0460-5.

Joannides M, Mays AN, Mistry AR, Hasan SK, Reiter A, Wiemels JL, Felix CA, Coco FL, Osheroff N, Solomon E, Grimwade D. Molecular pathogenesis of secondary acute promyelocytic leukemia. Mediterr J Hematol Infect Dis 2011;3(1):e2011045. doi: 10.4084/MJHID.2011.045. 

Libura JoJ., Slater DJ, Felix C., Richardson C. 2004. T-AML-like MLL rearrangements are induced by etoposide in primary human CD34+ cells and remain stable after clonal expansion. Blood Journal DOI 10.1182/blood-2004-07-2683.

Krivtsov AV, Armstrong SA. MLL translocations, histone modifications and leukaemia stem-cell development. Nature Reviews Cancer. 2007 Nov;7(11):823-33.

Krivtsov AV, Feng Z, Lemieux ME, et al. H3K79 methylation profiles define murine and human MLL-AF4 leukemias. Cancer Cell. 2008;14(5): 355-368.

Manara E, Baron E, Tregnago C, Aveic S, Bisio V, Bresolin S, Masetti R, Locatelli F, Basso G, Pigazzi M. MLL-AF6 fusion oncogene sequesters AF6 into the nucleus to trigger RAS activation in myeloid leukemia. Blood Journal 2014 Jul 10;124(2):263-272. doi: 10.1182/blood-2013-09-525741.

Marschalek R. Mechanisms of leukemogenesis by MLL fusion proteins. British Journal of Haematology 2010; 152: 141-154. doi: 10.1111/j. 1365-2141.2010.08459.x

Menendez P, Catalina P, Rodriguez R, Melen GJ, Bueno C, Arriero M, Garcia-Sanchez F, Lassaletta A, Garcia-Sanz R, Garcia-Castro J. Bone marrow mesenchymal stem cells from infants with MLL-AF4+ acute leukemia harbor and express the MLL-AF4 fusion gene. J Exp Med. 2009 Dec 21;206(13):3131-41. doi: 10.1084/jem.20091050.

Metzler M, Forster A, Pannell R, et al. A conditional model of MLL-AF4 B-cell tumourigenesis using invertor technology. Oncogene. 2006;25(22):3093-3103.

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 M, 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.

Prieto C, Stam RW, Agraz-Doblas A, Ballerini P, Camos M, Castano J, Marschalek R, Bursen A, Varela I, Bueno C, Menendez P. Activated KRAS cooperates with MLLAF4 to promote extramedullary engraftment and migration of cord blood CD34+ HSPC but is insufficient to initiate leukemia. Cancer Researchearchearch. 2016 Feb 2. pii:canres.2769.2015.

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‐18

Sam TN, Kersey JH, Linabery AM, Johnson KJ, Heerema NA, Hilden JM, et al. MLL gene rearrangements in infant leukaemia vary with age at diagnosis and selected demographic factors: a Children’s Oncology Group (COG) study. Pediatric Blood and Cancer 2012; 58 (6): 836-839.

Sanjuan-Pla A, Bueno C, Prieto C, Acha P, Stam RW, Marschalek R, Menendez P. Revisiting the biology of infant t(4;11)/MLL-AF4+ B-cell acute lymphoblastic leukemia. Blood Journal 2015; 126(25): 2676-2685 DOI 10.1182/blood-2015-09-667378.

Super HJ, McCabe NR, Thirman MJ, et al. 1993. Rearrangements of the MLL gene in therap-related acute myeloid leukaemia in patients previously treated with agents targeting DNA-topoisomerase II. Blood; (82) 3705-11.

Tamai H, Inokuchi K. Establishment of MLL/AF4 transgenic mice with the phenotype of lymphoblastic leukemia or lymphoma. Journal of Nippon Medical School 2013;80(5):326-327.

Tamai H, Miyake K, Takatori M, Miyake N, Yamaguchi H, Dan K, Shimada T, Inokuchi K. Activated K-Ras protein accelerates human MLL/AF4-induced leukemo-lymphomogenicity in a transgenic mouse model. Leukemia. 2011 May;25(5):888-91. doi: 10.1038/leu.2011.15.

Teitell MA, Pandolfi PP. Molecular genetics of acute lymphoblastic leukemia.  Annual Review of Pathology 2009; 4: 175-198.

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

Yu BD, Hanson RD, Hess JL, Horning SE, Korsmeyer SJ, 1998. MLL, a mammalian trithorax-group gene, functions as a transcriptional maintenance factor in morphogenesis. Proceedings of the National Academy of SciencesUSA (95) 10632-36.