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Relationship: 3363

Title

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

Cell cycle disruption leads to Decrease, Cell proliferation

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Cell cycle disruption

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

Decrease, Cell proliferation

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
DBDPE-induced DNA damage increase in liver leading to Non-alcoholic fatty liver disease via liver steatosis and inhibition of regeneration	adjacent	Not Specified	Not Specified	Cataia Ives (send email)	Under development: Not open for comment. Do not cite
Excessive reactive oxygen species leading to growth inhibition via oxidative DNA damage	adjacent			Evgeniia Kazymova (send email)	Under development: Not open for comment. Do not cite
Excessive reactive oxygen species leading to growth inhibition via protein oxidation and cell cycle disruption	adjacent			Cataia Ives (send email)	Under development: Not open for comment. Do not cite
Reactive oxygen species leading to growth inhibition via oxidative DNA damage and cell cycle disruption	adjacent	High	Moderate	Agnes Aggy (send email)	Under development: Not open for comment. Do not cite

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

Term	Scientific Term	Evidence	Link
humans	Homo sapiens	High	NCBI
mammals	mammals	High	NCBI
fish	fish	High	NCBI
crustaceans	Daphnia magna	Moderate	NCBI
green algae	Ulva compressa	Moderate	NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help

Sex	Evidence
Unspecific	Moderate

Life Stage Applicability

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

Term	Evidence
All life stages	Moderate

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

This KER describes the causal and predictive relationship by which disruption of the cell cycle leads to decreased cell proliferation. Cell proliferation requires cells to progress through an ordered series of phases, including G1, S, G2 and M phase, with checkpoints that monitor cell size, DNA replication, DNA damage, spindle assembly and other conditions necessary for successful division. When these processes are disrupted, cells may arrest at a checkpoint, delay progression, fail to replicate DNA, fail mitosis, enter senescence, or undergo cell death. Any of these outcomes reduces the fraction of cells completing successful division and therefore decreases the net rate of cell proliferation (Hartwell and Weinert, 1989; Nurse, 2000; Malumbres and Barbacid, 2009).

The upstream KE is deliberately defined broadly as "cell cycle, disrupted" to preserve modularity across AOPs. It can include G0/G1 arrest, S-phase arrest, G2/M delay, mitotic arrest, checkpoint activation, failure of DNA synthesis, altered cyclin/CDK regulation, spindle checkpoint disruption or permanent cell-cycle exit. The downstream KE, "Decrease, Cell proliferation", refers to a reduction in the rate of increase in cell number or proliferative capacity, measured by cell counts, DNA synthesis, EdU/BrdU incorporation, Ki-67 or PCNA markers, colony formation, growth rate of unicellular organisms, or similar proliferation endpoints.

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

The evidence base for this KER was assembled as part of the ROS-growth AOP development workflow. The starting point was the AOP-Wiki Relationship 3363 page and the corresponding KE pages for Event 1505 and Event 1821. Existing AOP-Wiki content was used to confirm the upstream and downstream KE definitions and to ensure compatibility with other ROS-growth AOPs in which cell-cycle disruption and reduced proliferation are reused as modular components (AOP-Wiki, 2026a, 2026b).

Literature evidence was identified using a hybrid strategy combining targeted searching, AOP-helpFinder style term development, and manual expert curation. Search terms included combinations of "cell cycle disruption", "cell cycle arrest", "G1 arrest", "G2/M arrest", "DNA damage checkpoint", "p21", "cyclin-dependent kinase", "cell proliferation", "BrdU", "EdU", "Ki-67", "PCNA", "cell density", "colony formation", "oxidative stress", "DNA strand breaks", "zebrafish", "Chlamydomonas", "algae", "silver nanoparticles", and "cadmium". Studies were prioritized when they measured both upstream cell-cycle endpoints and downstream proliferation, cell-number, colony formation or growth endpoints in the same biological system.

During screening, studies were categorized according to whether they supported biological plausibility, empirical concordance or essentiality. The most informative studies were those that provided dose-response or temporal evidence showing that cell-cycle disruption occurred together with, or before, reduced proliferation. Mechanistic reviews and established cell-cycle biology references were used to support biological plausibility, whereas primary studies in algae, fish or mammalian/human cells were used for empirical support. Final inclusion and interpretation of evidence were based on expert curation rather than automated screening alone.

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

Biological plausibility of this KER is high. Cell proliferation requires successful completion of the cell cycle. Checkpoints that delay or block progression are conserved control mechanisms that prevent cells from dividing when DNA is damaged, DNA replication is incomplete, chromosomes are not correctly attached to the spindle, or other cellular conditions are incompatible with successful division (Hartwell and Weinert, 1989; O'Connell et al., 2000; Nurse, 2000). If disruption persists, cells fail to complete mitosis, enter senescence, or activate cell death pathways, resulting in reduced net cell accumulation. The AOP-Wiki Event 1505 page similarly describes cell-cycle disruption as a disruption of G1, S, G2, M or G0 progression that can lead to decreased cell number (AOP-Wiki, 2026b).

The structural and functional relationship between the KEs is direct: the upstream KE alters the process required to generate daughter cells, while the downstream KE represents the measurable decrease in cell proliferation. Cyclins, cyclin-dependent kinases, checkpoint kinases, p53/p21 signaling, DNA damage response pathways and spindle checkpoint mechanisms all provide mechanistic links through which upstream cell-cycle disruption can reduce proliferation (Malumbres and Barbacid, 2009; Cuddihy and O'Connell, 2003).

Empirical Evidence

Provides specific (citable) evidence that supports the idea of a change in the upstream KE (KEupstream) leading to, or being associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient. More help

Empirical support for this KER is moderate to high. The relationship is supported by many studies across cell biology and toxicology showing that stressor-induced cell-cycle arrest or disruption is accompanied by decreased cell number, colony formation, DNA synthesis or population growth. Within the ROS-growth evidence set, the most relevant evidence comes from systems in which genotoxic or oxidative stress is associated with cell-cycle responses and reduced proliferation or cell accumulation. However, not every study measures the two KEs in the same time course, so the empirical call is not uniformly high across all taxa and stressor classes.

Empirical Evidence Table

Biological system	Stressor or perturbation	Evidence relevant to KER	Interpretation
Green algae	DNA-damaging agents such as zeocin or N-OH-2-AAF	DNA damage-induced changes in cell-cycle progression and division outcomes were reported in green algal systems, demonstrating that damage-associated cell-cycle responses can alter cell division behavior (David et al., 2009; Hlavová et al., 2011).	Supports relevance of cell-cycle disruption to algal cell division/proliferation, although responses can be species- and phase-specific.
Green algae, Chlamydomonas reinhardtii	Isoproturon and cadmium	The combined exposure reduced chlorophyll and photosynthetic performance, increased oxidative damage markers, and reduced algal fitness endpoints; this provides supporting context for stressor-induced disruption of growth-related cellular processes in algae (Qiu et al., 2024).	Supportive but indirect for this specific KER; strongest for stressor effects on growth and oxidative damage rather than a direct cell-cycle-to-proliferation linkage.
Embryonic zebrafish cells	Silver nanoparticles and ionic silver	Silver exposure triggered DNA damage/repair responses in embryonic zebrafish cells, with endpoints relevant to damage response and cell-cycle control (Quevedo et al., 2021).	Supports relevance of the DNA damage response/cell-cycle context in fish cell systems.
Human Jurkat T cells	Silver nanoparticles	AgNP exposure activated stress signaling and induced DNA damage, cell-cycle arrest and apoptosis; the study also reported cytotoxicity/viability effects (Eom and Choi, 2010).	Supports co-occurrence of cell-cycle arrest with impaired cell survival/proliferation in a human cell model.
Human and mammalian cells	Genotoxic and cell-cycle regulatory perturbations	Large mechanistic literature shows that checkpoint activation, CDK inhibition and cell-cycle arrest reduce DNA synthesis, mitotic entry and cell accumulation (Hartwell and Weinert, 1989; Cuddihy and O'Connell, 2003; Malumbres and Barbacid, 2009).	Provides broad empirical and mechanistic support for the general KER.

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

The main uncertainty is that cell-cycle disruption is a broad upstream KE and can represent different biological states. Transient checkpoint activation may delay proliferation without causing a sustained decrease in cell number, whereas persistent arrest, mitotic failure or permanent cell-cycle exit has a stronger effect on proliferation. The magnitude of the downstream response therefore depends on the duration and reversibility of the upstream cell-cycle perturbation.

Another uncertainty is that decreased cell proliferation can be measured by multiple endpoints, including cell counts, DNA synthesis, colony formation or metabolic activity. Some assays, such as MTT or resazurin, may reflect both proliferation and viability/metabolic state, which can complicate interpretation. Additionally, cell-cycle disruption may lead to cell death in some contexts rather than simply decreased proliferation, so the downstream response may diverge depending on severity and cell type. In algal and early developmental systems, reduced population growth can result from both proliferation effects and other processes such as photosynthetic inhibition, energy depletion or cell death.

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

Modulating factor	Details	Influence on KER	Supporting evidence
Cell type and proliferative state	Rapidly dividing, quiescent, differentiated, stem-like or senescent cells.	Rapidly dividing cells are more sensitive to cell-cycle disruption; quiescent or terminally differentiated cells may show little proliferation effect.	Nurse, 2000; Malumbres and Barbacid, 2009.
Cell-cycle phase at exposure	G1, S, G2 or M phase when the stressor occurs.	Phase determines whether disruption blocks DNA synthesis, mitotic entry, mitosis, or return to cycle; this affects time course and magnitude of proliferation decrease.	Hartwell and Weinert, 1989; Hlavová et al., 2011.
DNA damage response and checkpoint capacity	p53, p21, ATM/ATR, Chk1/Chk2 and related checkpoint pathways.	Strong checkpoint activation can increase arrest and decrease proliferation; impaired checkpoints may permit division with damage or shift outcome toward cell death.	O'Connell et al., 2000; Cuddihy and O'Connell, 2003.
Repair capacity and stressor severity	Extent and persistence of DNA damage, oxidative stress or spindle disturbance.	Mild, reversible disruption may delay proliferation; severe or persistent disruption can cause permanent arrest, senescence or cell death.	Cuddihy and O'Connell, 2003; Eom and Choi, 2010.
Compensatory growth and recovery	Post-exposure recovery, tissue repair and regenerative proliferation.	Recovery mechanisms can reduce the apparent downstream effect on proliferation if the upstream disruption is transient.	Malumbres and Barbacid, 2009.

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. More help

Quantitative understanding of this KER is moderate. The qualitative relationship is well established: cells that cannot progress through the cell cycle cannot complete division, and sustained arrest therefore reduces proliferation. However, a general quantitative model that predicts the magnitude of decreased proliferation from a given measure of cell-cycle disruption has not been established across species, cell types, stressors and assay platforms.

Response-response Relationship

Provides sources of data that define the response-response relationships between the KEs. More help

The relationship can be quantified in specific experimental systems by relating the fraction of cells in each cell-cycle phase, the proportion of cells positive for DNA synthesis markers such as BrdU or EdU, mitotic index, checkpoint marker intensity, or duration of arrest to subsequent changes in cell number, population doubling time or colony-forming ability. The time scale varies from hours for checkpoint activation and DNA synthesis inhibition to days for measurable reductions in population growth or colony formation. The relationship is expected to be nonlinear: a transient delay may produce limited or reversible effects, whereas persistent arrest or permanent cell-cycle exit can sharply reduce proliferation.

Quantitative prediction is complicated by several factors, including baseline growth rate, synchronization state of the cell population, cell-cycle phase at exposure, checkpoint competence, repair capacity, cell death, and assay choice. Therefore, quantitative interpretation should be made within a defined biological system and ideally with paired upstream and downstream measurements collected across multiple time points and exposure concentrations.

Time-scale

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

This KER is applicable to proliferating eukaryotic cells and tissues in which cell-cycle progression is required for cell number increase. It is broadly relevant across algae, invertebrates, fish, mammals and human-derived cell systems when the cells or tissues under study are actively proliferating or can be stimulated to proliferate. Applicability is strongest for developmental, regenerative, immune, epithelial, tumor, algal growth or cell culture contexts, where decreased cell proliferation is readily measured.

The KER is less directly applicable to terminally differentiated non-dividing cells or tissues in which proliferation is not a meaningful endpoint. It should also be interpreted carefully when decreased proliferation is inferred from metabolic viability assays alone, because changes in ATP, mitochondrial activity or cytotoxicity may confound proliferation measurements. Species, sex and life stage are best viewed as modifiers of sensitivity rather than determinants of whether the relationship can occur.

References

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

AOP-Wiki. 2026a. Relationship 3363: Cell cycle, disrupted leads to Decrease, Cell proliferation. AOP-Wiki. Accessed 14 May 2026.

AOP-Wiki. 2026b. Event 1505: Cell cycle, disrupted. AOP-Wiki. Accessed 14 May 2026.

Cuddihy AR, O'Connell MJ. 2003. Cell-cycle responses to DNA damage in G2. International Review of Cytology 222:99-140. https://doi.org/10.1016/S0074-7696(02)22013-6.

Eom HJ, Choi J. 2010. p38 MAPK activation, DNA damage, cell cycle arrest and apoptosis as mechanisms of toxicity of silver nanoparticles in Jurkat T cells. Environmental Science & Technology 44(21):8337-8342. https://doi.org/10.1021/es1020668.

Hartwell LH, Weinert TA. 1989. Checkpoints: controls that ensure the order of cell cycle events. Science 246(4930):629-634. https://doi.org/10.1126/science.2683079.

Hlavová M, Čížková M, Vítová M, Bišová K, Zachleder V. 2011. DNA damage during G2 phase does not affect cell cycle progression of the green alga Scenedesmus quadricauda. PLoS ONE 6(5):e19626. https://doi.org/10.1371/journal.pone.0019626.

Malumbres M, Barbacid M. 2009. Cell cycle, CDKs and cancer: a changing paradigm. Nature Reviews Cancer 9(3):153-166. https://doi.org/10.1038/nrc2602.

Nurse P. 2000. A long twentieth century of the cell cycle and beyond. Cell 100(1):71-78. https://doi.org/10.1016/S0092-8674(00)81684-0.

O'Connell MJ, Walworth NC, Carr AM. 2000. The G2-phase DNA-damage checkpoint. Trends in Cell Biology 10(7):296-303. https://doi.org/10.1016/S0962-8924(00)01773-6.

Qiu CB, Tang J, Chen G, Yang H, Liu J. 2024. Single and joint bioaccumulation and toxicity of isoproturon and cadmium in green algae (Chlamydomonas reinhardtii). Chemical and Biological Technologies in Agriculture 11:97. https://doi.org/10.1186/s40538-024-00628-3.

Quevedo AC, Lynch I, Valsami-Jones E. 2021. Cellular repair mechanisms triggered by exposure to silver nanoparticles and ionic silver in embryonic zebrafish cells. Environmental Science: Nano 8(9):2507-2522. https://doi.org/10.1039/D1EN00422K.