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Relationship: 1711


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

p21 (CDKN1A) expression, increase leads to Cell cycle, disrupted

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

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
Rattus norvegicus Rattus norvegicus High NCBI
Mus musculus 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
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 regulation through p21 (cyclin dependent kinase inhibitor 1A; CDKN1A) activation is demonstrated by the interactions of p21 with cyclins [Dotto, 2000]. p21 interacts directly with cyclins through a conserved region in close to its N-terminus (amino acids 17-24; Cy1) [Dotto, 2000]. The cyclin dependent kinase inhibitor, p21 has the secondary weak cyclin binding domain near its C-terminus region (amino acids 153-159), which overlaps with its proliferating cell nuclear antigen (PCNA) binding domain [Dotto, 2000]. Kinase activity of cyclin-dependent kinase (Cdk) was inhibited by Cy1 site of p21 that is important for the interaction of p21 with cyclin-Cdk complexes [Chen, 1996]. The p21 inhibits Cdk complexes such as cyclin A/E-Cdk2 or cyclin D-Cdk4 complexes, leading to the cell cycle disruption as G1/S arrest [Chen, 1996].

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

p21 has a separate cyclin-dependent kinase 2 (CDK2) binding site in its N-terminus region (amino acids 53-58) and optimal cyclin/CDK inhibition requires binding by this site as well as one of the cyclin binding sites [Dotto, 2000]. The peptide containing Cy1 site inhibited the kinase activity of cyclin E-Cdk2 and cyclin A-Cdk2 [Chen, 1996]. The p21WAF1/CIP1/sdi1 gene product inhibits the cyclin D/cdk4/6 and the cyclin E/cdk2 complexes in response to DNA-damage, resulting in G1/S arrest [Moussa, 2015, Ogryzko, 1997]. p21 inhibits cyclin-dependent kinases and regulates cell cycle to promote cell cycle arrest. Deletion of either cyclin binding site in N-terminus or C-terminus of p21, or CDK binding domain was sufficient for the kinase activity inhibition [Chen, 1996].

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

TSA promotes apoptosis via HDAC inhibition and p53 signaling pathway activation [Deng, 2016a]. It is suggested that furazolidone induces reactive oxygen species leading to suppression of p-AKT and p21, and induction of apoptosis [Deng, 2016b]. The dual roles of p21 in cell cycle arrest and anti-apoptotic effect in the testicular germ cells of diabetic rats are suggested [Kilarkaje, 2015]. The anti-apoptotic effect of p21 is mediated by caspase-3 inhibition, which demonstrates the possibility of cell-cycle independent effect on apoptosis [Deng, 2016b]. It has been demonstrated that p21 induces apoptosis in human cervical cancer cell lines [Tsao, 1999], whereas p21 is implicated in apoptosis inhibition by blocking activation of caspase-3 or interacting with ASK1 [Gartel, 2002, Zhan, 2007]. Up-regulation of p21 is implicated in the activation of DNA damage pathways, and deletion of p21 improved stem cell function and lifespan without accelerating chromosomal instability, which indicates that p21-dependent checkpoint induction affects the longevity limit [Choudhury, 2007].

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

The peptide containing cyclin-binding domain of p21 in N-terminus inhibited the kinase activity of cyclin E-Cdk2 with 296 nM of the concentration in which kinase activity is inhibited in 50% (Ki) [Chen, 1996].

The peptide containing cyclin-binding domain of p21 in C-terminus showed 32,000, 800, or >300,000 nM of Ki for inhibition of the kinase activity of cyclin E-Cdk2, cyclin A-Cdk2 or cyclin D1-Cdk4, respectively [Chen, 1996].

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 replication in Xenopus was suppressed by the GST fusion protein of p21 without amino acids 17-24 or the peptide containing cyclin binding site in N-terminus of p21 protein [Chen, 1996]. P21 regulates the E2F transcriptional activity to control cell cycle in human U2OS osteosarcoma cells (Homo sapiens) [Delavaine, 1999]. Cell cycle is regulated by p21 through cyclins and CDKs in mice (Mus musculus) [Sherr CJ, 2004].  


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

Dotto GP (2000) p21WAF1/Cip1: more than a break to the cell cycle? Biochim Biophys Acta 1471: M43-M56

Chen J et al (1996) Cyclin-binding motifs are essential for the function of p21CIP1. Mol Cell Biol 16: 4673-4682

Moussa RS et al. (2015) Differential targeting of the cyclin-dependent kinase inhibitor, p21CIP/WAF1, by chelators with anti-proliferative activity in a range of tumor cell-types. Oncotarget 6:29694-29711

Ogryzko VV et al. (1997) WAF1 retards S-phase progression primarily by inhibition of cyclin-dependent kinases. Mol Cell Biol 17:4877-4882

Gartel AL and Tyner AL (2002) The role of the cyclin-dependent kinase inhibitor p21 in apoptosis. Mol Cancer Ther 1: 639-649

Kilarkaje N and Al-Bader MM. (2015) Diabetes-Induced Oxidative DNA Damage Alters p53-p21CIP1/Waf1 Signaling in the Rat Testis. Reproductive Sciences 22: 102–112

Kang MR et al (2016) miR-6734 up-regulates p21 gene expression and induces cell cycle arrest and apoptosis in colon cancer cells. PLoS One 11: e0160961

Aix E et al (2016) Postnatal telomere dysfunction induces cardiomyocyte cell-cycle arrest through p21 activation. J Cell Biol 213: 571-583

Deng Z et al. (2016a) Histone deacetylase inhibitor trichostatin A promotes the apoptosis of osteosarcoma cells through p53 signaling pathway activation. Int J Biol Sci 12:1298-1308

Deng S et al (2016b) P21Waf1/Cip1 plays a critical role in furazolidone-induced apoptosis in HepG2 cells through influencing the caspase-3 activation and ROS generation. Food Chem Toxicol 88: 1-12

Tsao YP et al (1999) Adenovirus-mediated p21WAF1/SDII/CIP1 gene transfer induces apoptosis of human cervical cancer cell lines. J Virology 73: 4983-4990

Zhan J et al (2007) Negative regulation of ASK1 by p21Cip1 involves a small domain that includes serine 98 that is phosphorylated by ASK1 in vivo. Mol Cell Biol 27: 3530-3541

Choudhury AR et al (2007) Cdkn1a deletion improves stem cell function and lifespan of mice with dysfunctional telomeres without accelerating cancer formation. Nat Genet 39: 99-105

Delavaine L and La Thangue NB (1999) Control of E2F activity by p21Waf1/Cip1. Oncogene 18: 5381-5392

Sherr CJ and Roberts JM (2004) Living with or without cyclins and cyclin-dependent kinases. Gene Dev 18: 2699-2711