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Relationship: 1712

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

Cell cycle, disrupted leads to Apoptosis

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
Histone deacetylase inhibition leading to testicular atrophy adjacent Moderate Moderate Shihori Tanabe (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 Do not cite EAGMST Under Review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
Homo sapiens Homo sapiens High NCBI
Mus musculus Mus musculus High NCBI
Oryctolagus cuniculus Oryctolagus cuniculus Moderate 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
Not Otherwise Specified 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

Cell cycle dysregulation may leads to apoptosis. Cell cycles characterized by the DNA content changes regulate cell death and cell proliferation [Lynch et al., 1986].

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

microRNA-497, potentially targeting Bcl2 and Cyclin D2 (CCND2), induced apoptosis via the Bcl-2/Bax - caspase 9 - caspase 3 pathway and CCND2 protein in human umbilical vein endothelial cells (HUVECs) [Wu, 2016]. The microRNA-497 activated caspases 9 and 3, and decreased Bcl2 and CCND2 [Wu et al., 2016]. CCND2 is an important cell cycle gene that induces G1 arrest [Li et al., 2012], and deregulated CCND2 is implicated in cell proliferation inhibition [Wu et al., 2016; Mermelstein et al., 2005; Dong et al., 2010].

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 incidence of apoptosis was increased in vincristine-treated cells, in which metaphases were arrested, compared to untreated cells, which indicates that cell cycle dysregulation leads to apoptosis [Sarraf and Bowen, 1986]. Cell gain and loss are balanced with mitosis and apoptosis [Cree et al., 1987]. Apoptosis is mediated by caspase activation [Porter and Janicke, 1999]. Caspase-3 is activated in the programmed cell death, and the pathways to caspase-3 activation include caspase-9 and mitochondrial cytochrome c release [Porter and Janicke, 1999]. The activation of caspase-3 leads to apoptotic chromatin condensation and DNA fragmentation [Porter and Janicke, 1999]. Sinularin, a marine natural compound, exhibited DNA damage and induced G2/M cell cycle arrest, followed by apoptosis in human hepatocellular carcinoma HepG2 cells [Chung et al., 2017]. Sinularin induced caspases 8, 9, and 3, and pro-apoptotic protein Bax, whereas it decrease the anti-apoptotic Bcl-2 protein expression level [Chung et al., 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

MAA induces CDK4 and CDK2 decreases, cell cycle arrest and apoptosis, which may be regulated by several pathways [Parajuli et al., 2014].

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

Treatment with sinularin, a natural product isolated from cultured soft coral posessing antineoplastic activity, at 12.5, 25, 50 microM resulted in cell cycle disrubtion and apoptosis in dose-dependent manner in hepatocellular carcinoma cells [Chun et al., 2017]. The cell cycle disruption and apoptosis are induced by 30 micromol/L curcumin, a major component extracted from turmeric plants which have anti-cancer effect [Liu et al., 2018].

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

MAA (5 mM) decreases CDK4, CDK2 expression in 48 hrs after the treatment, which indicates the G1 arrest [Parajuli et al., 2014]. MAA (5 mM) decreases the protein expression of procaspase 7 and 3 in 24 to 72 hrs after the treatment, indicating the activation of caspases 7 and 3 [Parajuli et al., 2014].

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

The relationship between disrupted cell cycle and apoptosis is likely well conserved between species.

  • MicroRNA let-7a induced cell cycle arrest, inhibited CCND2 and proliferation of human prostate cancer cells (Homo sapiens) [Dong et al., 2010].
  • microRNA-497 down-regulated CCND2 and induced apoptosis via the Bcl-2/Bax-caspase 9- caspase 3 pathway in HUVECs (Homo sapiens) [Wu et al., 2016].
  • micoRNA-26a regulated p53-mediated apoptosis and CCND2 and CCNE2 in mouse hepatocyte (Mus musculus) [Zhou et al., 2016].

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

Chung, T.W. et al. (2017), "Sinularin induces DNA damage, G2/M phase arrest, and apoptosis in human hepatocellular carcinoma cells", BMC Complement Altern Med 17:62

Cree, I.A. et al. (1987), "Cell death in granulomata: the role of apoptosis", J Clin Pathol 40:1314-1319

Dong, Q. et al. (2010), "microRNA let-7a inhibits proliferation of human prostate cancer cells in vitro and in vivo by targeting E2F2 and CCND2", PLoS One 5:e10147

Kerr, J.F.R. et al. (1972), "Apoptosis: a basic biological phenomenon with wide-ranging implications in tissue kinetics", Br J Cancer 26:239-257

Li, L. et al. (2012), "Downregulation of microRNAs miR-1, -206 and -29 stabilizes PAX3 and CCND2 expression in rhabdomyosarcoma", Lab Invest 92:571-583

Liu, W. et al. (2018), "Curcumin suppresses gastric cancer biological activity by regulation of miRNA-21: an in vitro study", Int J Clin Exp Pathol 11:5820-5289

Lynch, M.P. et al. (1986), "Evidence for soluble factors regulating cell death and cell proliferation in primary cultures of rabbit endometrial cells grown on collagen", Proc Natl Acad Sci USA 83:4784-4788

Mermelshtein, A. et al. (2005), "Expression of F-type cyclins in colon cancer and in cell lines from colon carcinomas", Br J Cancer 93:338-345

Parajuli, K.R. et al. (2014), "Methoxyacetic acid suppresses prostate cancer cell growth by inducing growth arrest and apoptosis", Am J Clin Exp Urol 2:300-313

Porter, A.G. and Janicke, R.U. (1999), "Emerging roles of caspase-3 in apoptosis", Cell Death Differ 6:99-104

Sarraf, C.E. and Bowen, I.D. (1986), "Kinetic studies on a murine sarcoma and an analysis of apoptosis", Br J Cancer 54:989-998

Wu, R. et al. (2016), "microRNA-497 induces apoptosis and suppressed proliferation via the Bcl-2/Bax-caspase9-caspase 3 pathway and cyclin D2 protein in HUVECs", PLoS One 11:e0167052

Zhou, J. et al. (2016), "miR-26a regulates mouse hepatocyte proliferation via directly targeting the 3’ untranslated region of CCND2 and CCNE2", Hepatobiliary Pancreat Dis Int 15:65-72