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Relationship: 1939


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

Increase, DNA strand breaks leads to Increase, Chromosomal aberrations

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

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
Oxidative DNA damage leading to chromosomal aberrations and mutations non-adjacent High Low Brendan Ferreri-Hanberry (send email) Open for comment. Do not cite EAGMST Under Review
Direct deposition of ionizing energy leading to lung cancer non-adjacent High Low Brendan Ferreri-Hanberry (send email) Under development: Not 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 Do not cite EAGMST Under Review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
human Homo sapiens High NCBI
rat Rattus norvegicus High NCBI
mouse Mus musculus 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
Unspecific 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
All life stages 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

DNA strand breaks (single and double) can arise from endogenous processes (e.g., topoisomerase reaction, excision repair, and VDJ recombination) and exogenous insults (e.g., replications stressors, ionizing radiation, and reactive oxygen species). Single strand breaks (SSBs) are generally repaired rapidly without error. However, multiple SSBs in close proximity to each other and interference of replication by unrepaired SSBs can lead to double strand breaks (DSB). DSB are more difficult to repair and are more toxic than SSB (Kuzminov, 2001). DSBs may lead to chromosomal breakages that may permanently alter the structure of chromosomes (i.e., chromosomal aberrations) and cause loss of DNA segments.

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
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

DNA strand breaks are a necessity for chromosomal aberrations to occur. However, not all strand breaks lead to clastogenic events as most of them is repaired rapidly by a variety of different repair mechanisms. DNA DSBs are the critical damage because they lead to chromosome breakage. It is well-understood that unrepaired DSBs can lead to chromosomal aberrations. Studies have demonstrated DSBs leading to irreversible structural damage; for example, treatment of cultured cells with replication stress-inducing agents such as hydroxyurea induced micronuclei that are positive for gamma-H2AX, a marker of DSBs (Xu et al., 2010). The link between DSBs and the importance of DSB repair in preventing chromosomal aberrations/genomic instability is extensively discussed in literature and many reviews are available (van Gent et al., 2001; Ferguson and Alt, 2001; Hoeijmakers, 2001; Iliakis et al., 2004; Povirk, 2006; Weinstock et al., 2006; Natarajan and Palitti, 2008; Lieber et al., 2010; Mehta and Haber, 2014; Ceccaldi et al., 2016; Chang et al., 2017; Sishc and Davis, 2017; Brunet and Jasin, 2018).

In addition, attempted repair of DSBs can lead to chromosomal aberrations such as translocations; NHEJ is a recognized source of oncogenic translocations in human cancers (Ferguson and Alt, 2001; Weinstock et al., 2006; Byrne et al., 2014; Brunet and Jasin, 2018), and a contributor to the carcinogenic process (Hoeijmakers, 2001; Sishc and Davis, 2017).

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

As described above, statistically significant increases in MN occur, in some cases, at lower concentrations than strand breaks measured with the comet assay (Platel et al., 2001; Watters et al., 2009; Kawaguchi et al., 2010). The two assays measure different endpoints at different time points; the MN test may appear to be more sensitive than the comet assay but it is difficult to directly compare these two assays.

Mughal et al. (2010) study compared different parameters of comet assay (tail moment, length, and % tail DNA) to MN frequency. Depending on the parameter, the observation of increase in strand breaks varied. For example, % tail DNA would show a visible increase in strand breaks at one concentration; however, no change would be observed in the tail moment calculated using the same data. Use of different parameters in presenting comet assay data may add subjectivity to the results that are reported in certain papers.

Rossner Jr. et al. exposed human embryonic lung fibroblasts (HEL12469) to 1, 10, and 25 µM of benzo[a]pyrene (B[a]P) for 24 hours and measured DSB (γH2AX immunodetection by Western blotting) and translocations (by fluorescence in situ hybridization of chromosomes 1, 2, 4, 5, 7, 17) (Rossner Jr. et al., 2014).

  • Increases in γH2AX were observed only at 25 µM B[a]P (~2.5 fold increase) after the 24h exposure.
  • Translocations were quantified and expressed as the genomic frequency of translocations per 100 cells (FG/100)
    • All concentrations of B[a]P induced an elevated frequency of translocations compared to the DMSO control (DMSO: ~0.19/100; 1 µM: ~0.53/100 cells; 10 µM: ~0.33/100; 25 µM: ~0.39/100)

In this study, the increase in translocations was detected at concentrations that did not induce an increase in γH2AX signal. This observation of the discordant relationship between γH2AX and translocations may be due to the differences in assay sensitivity. In addition, immunodetection by Western blotting cannot precisely measure small changes in protein content.

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
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

DNA strand breaks and subsequent chromosomal aberrations can occur in any eukaryotic and prokaryotic cell.


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

Brunet, E. & M. Jasin (2018), "Induction of chromosomal translocations with CRISPR-Cas9 and other nucleases: Understanding the repair mechanisms that give rise to translocations.", Adv. Exp. Med. Biol. 1044:15-25.

Byrne, M. et al. (2014), "Mechanisms of oncogenic chromosomal translocations.", Ann. N.Y. Acad. Sci., 1310:89-97.

Ceccaldi, R., B. Rondinelli & A.D. D'Andrea (2016), "Repair Pathway Choices and Consequences at the Double-Strand Break.", Trends Cell Biol. 26(1):52-64.

Chang, H. et al. (2017), "Non-homologous DNA end joining and alternative pathways to double‑strand break repair.", Nature Rev. Mol. Cell. Biol., 18:495-506.

Chernikova, S.B., R.L. Wells & M. Elkind (1999), "Wortmannin Sensitizes Mammalian Cells to Radiation by Inhibiting the DNA-Dependent Protein Kinase-Mediated Rejoining of Double-Strand Breaks.", Radiat. Res., 151:159-166.

Collins, A.R. et al. (2008), "The comet assay: topical issues.", Mutagenesis, 23:143-151.

Dertinger, S.D. et al. (2019), "Predictions of genotoxic potential, mode of action, molecular targets, and potency via a tiered multiflow® assay data analysis strategy.", Environ. Mol. Mutagen., 60(6):513-533

Ensminger, M. et al. (2014), "DNA breaks and chromosomal aberrations arise when replication meets base excision repair.", J. Cell Biol.,  206:29.

Ferguson, D.O. & F.W. Alt (2001), "DNA double strand break repair and chromosomal translocation: Lessons from animal models.", Oncogene 20(40):5572–5579.

Hoeijmakers, J.H. (2001), "Genome maintenance mechanisms for preventing cancer.", Nature, 411:366-374.

Iliakis, G. et al. (2019), "Defined Biological Models of High-LET Radiation Lesions.", Radiat. Protect Dosimet., 183:60-68.

Iliakis, G. et al. (2004), "Mechanisms of DNA double strand break repair and chromosome aberration formation.", Cytogenet. Genome Res. 104:14-20.

Kawaguchi, S. et al. (2010), "Is the comet assay a sensitive procedure for detecting genotoxicity?.", J. Nucleic Acids, 2010:541050.

Kuzminov, A. (2001), "Single-strand interruptions in replicating chromosomes cause double-strand breaks.", Proc. Natl. Acad. Sci. USA 95:8241-8246.

Lieber, M. et al. (2010), "Nonhomologous DNA End Joining (NHEJ) and Chromosomal Translocations in Humans.", Subcell Biochem., 50:279-296.

Mehta, A. & J. Haber (2014), "Sources of DNA Double-Strand Breaks and Models of Recombinational DNA Repair.", Cold Spring Harb. Perspect Biol., 6:a016428.

Mughal, A. et al. (2010), "Micronucleus and comet assay in the peripheral blood of juvenile rat: Establishment of assay feasibility, time of sampling and the induction of DNA damage.", Mutat. Res. Gen. Tox. En., 700:86-94.

Natarajan, A.T & F. Palitti (2008), "DNA repair and chromosomal alterations.", Mutat. Res., 657:3-7.

Platel, A. et al. (2011), "Study of oxidative DNA damage in TK6 human lymphoblastoid cells by use of the thymidine kinase gene-mutation assay and the in vitro modified comet assay: Determination of No-Observed-Genotoxic-Effect-Levels.", Mutat. Res., 726:151-159.

Platel, A. et al. (2009), "Study of oxidative DNA damage in TK6 human lymphoblastoid cells by use of the in vitro micronucleus test: Determination of No-Observed-Effect Levels.", Mutat. Res., 678:30-37.

Povirk, L. (2006), "Biochemical mechanisms of chromosomal translocations resulting from DNA double-strand breaks.", DNA Repair 5:1199-1212.

Rogakou, E.P. et al. (1999), "Megabase chromatin domains involved in DNA double-strand breaks in vivo.", J. Cell Biol., 146:905-916.

Rossner, Jr. P et al. (2014), "Nonhomologous DNA end joining and chromosome aberrations in human embryonic lung fibroblasts treated with environmental pollutants.", Mutat. Res., 763-764:28-38.

Rothfuss, A. et al. (1999), "Evaluation of mutagenic effects of hyperbaric oxygen (HBO) in vitro.", Environ. Mol. Mutagen., 34:291-296.

Sishc, B.J. & A.J. Davis (2017), "The Role of the Core Non-Homologous End Joining Factors in Carcinogenesis and Cancer.", Cancers (Basel), 9(7): pii E82.

Sudprasert, W., P. Navasumrit & M. Ruchirawat (2006), "Effects of low-dose gamma radiation on DNA damage, chromosomal aberration and expression of repair genes in human blood cells.", Int. J. Hyg. Environ.-Health, 206:503-511.

Trenz, K., J. Landgraf & G. Speit (2003), "Mutagen sensitivity of human lymphoblastoid cells with a BRCA1 mutation.", Breast Cancer Res. Treat., 78:69-79.

Trenz, K., P. Schutz & G. Speit (2005), "Radiosensitivity of lymphoblastoid cell lines with a heterozygous BRCA1 mutation is not detected by the comet assay and pulsed field gel electrophoresis.", Mutagenesis, 20:131-137.

Turner, H.C. et al. (2015), "Effect of Dose Rate on Residual c-H2AX Levels and Frequency of Micronuclei in X-Irradiated Mouse Lymphocytes.", Radiat. Res., 183:315-324.

van Gent, D., J.H. Hoeijmakers & R. Kanaar (2001), "Chromosomal Stability and the DNA Double-Stranded Break Connection.", Nature 2:196-206.

Watters, G.P. et al. (2009), "H2AX phosphorylation as a genotoxicity endpoint.", Mutat. Res., 670:50-58.

Weinstock, D. et al. (2006), "Modeling oncogenic translocations: Distinct roles for double-strand break repair pathways in translocation formation in mammalian cells.", DNA Repair 5:1065-1074.

Xu, B. et al. (2010), "Replication Stress Induces Micronuclei Comprising of Aggregated DNA Double-Strand Breaks.", PLoS One, 6:e18618.