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Event: 1182

Key Event Title

The KE title should describe a discrete biological change that can be measured. It should generally define the biological object or process being measured and whether it is increased, decreased, or otherwise definably altered relative to a control state. For example “enzyme activity, decreased”, “hormone concentration, increased”, or “growth rate, decreased”, where the specific enzyme or hormone being measured is defined. More help

Increase, Cell Proliferation (Epithelial Cells)

Short name
The KE short name should be a reasonable abbreviation of the KE title and is used in labelling this object throughout the AOP-Wiki. The short name should be less than 80 characters in length. More help
Increase, Cell Proliferation (Epithelial Cells)

Biological Context

Structured terms, selected from a drop-down menu, are used to identify the level of biological organization for each KE. Note, KEs should be defined within a particular level of biological organization. Only KERs should be used to transition from one level of organization to another. Selection of the level of biological organization defines which structured terms will be available to select when defining the Event Components (below). More help
Level of Biological Organization

Cell term

Further information on Event Components and Biological Context may be viewed on the attached pdf.The biological context describes the location/biological environment in which the event takes place.  For molecular/cellular events this would include the cellular context (if known), organ context, and species/life stage/sex for which the event is relevant. For tissue/organ events cellular context is not applicable.  For individual/population events, the organ context is not applicable. More help
Cell term
epithelial cell

Organ term

Further information on Event Components and Biological Context may be viewed on the attached pdf.The biological context describes the location/biological environment in which the event takes place.  For molecular/cellular events this would include the cellular context (if known), organ context, and species/life stage/sex for which the event is relevant. For tissue/organ events cellular context is not applicable.  For individual/population events, the organ context is not applicable. More help

Key Event Components

Further information on Event Components and Biological Context may be viewed on the attached pdf.Because one of the aims of the AOP-KB is to facilitate de facto construction of AOP networks through the use of shared KE and KER elements, authors are also asked to define their KEs using a set of structured ontology terms (Event Components). In the absence of structured terms, the same KE can readily be defined using a number of synonymous titles (read by a computer as character strings). In order to make these synonymous KEs more machine-readable, KEs should also be defined by one or more “event components” consisting of a biological process, object, and action with each term originating from one of 22 biological ontologies (Ives, et al., 2017; See List). Biological process describes dynamics of the underlying biological system (e.g., receptor signalling). The biological object is the subject of the perturbation (e.g., a specific biological receptor that is activated or inhibited). Action represents the direction of perturbation of this system (generally increased or decreased; e.g., ‘decreased’ in the case of a receptor that is inhibited to indicate a decrease in the signalling by that receptor).Note that when editing Event Components, clicking an existing Event Component from the Suggestions menu will autopopulate these fields, along with their source ID and description. To clear any fields before submitting the event component, use the 'Clear process,' 'Clear object,' or 'Clear action' buttons. If a desired term does not exist, a new term request may be made via Term Requests. Event components may not be edited; to edit an event component, remove the existing event component and create a new one using the terms that you wish to add. More help
Process Object Action
cell proliferation increased

Key Event Overview

AOPs Including This Key Event

All of the AOPs that are linked to this KE will automatically be listed in this subsection. This table can be particularly useful for derivation of AOP networks including the KE. Clicking on the name of the AOP will bring you to the individual page for that AOP. More help
AOP Name Role of event in AOP Point of Contact Author Status OECD Status
ER activation to breast cancer KeyEvent Brendan Ferreri-Hanberry (send email) Open for adoption
RONS leading to breast cancer KeyEvent Evgeniia Kazymova (send email) Under development: Not open for comment. Do not cite Under Development
Increased DNA damage leading to breast cancer KeyEvent Allie Always (send email) Under development: Not open for comment. Do not cite Under Development


This is a structured field used to identify specific agents (generally chemicals) that can trigger the KE. Stressors identified in this field will be linked to the KE in a machine-readable manner, such that, for example, a stressor search would identify this as an event the stressor can trigger. NOTE: intermediate or downstream KEs in one AOP may function as MIEs in other AOPs, meaning that stressor information may be added to the KE description, even if it is a downstream KE in the pathway currently under development.Information concerning the stressors that may trigger an MIE can be defined using a combination of structured and unstructured (free-text) fields. For example, structured fields may be used to indicate specific chemicals for which there is evidence of an interaction relevant to this MIE. By linking the KE description to a structured chemical name, it will be increasingly possible to link the MIE to other sources of chemical data and information, enhancing searchability and inter-operability among different data-sources and knowledgebases. The free-text section “Evidence for perturbation of this MIE by stressor” can be used both to identify the supporting evidence for specific stressors triggering the MIE as well as to define broad chemical categories or other properties that classify the stressors able to trigger the MIE for which specific structured terms may not exist. More help

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) can be selected from an ontology. In many cases, individual species identified in these structured fields will be those for which the strongest evidence used in constructing the AOP was available in relation to this KE. More help

Life Stages

The structured ontology terms for life-stage are more comprehensive than those for taxa, but may still require further description/development and explanation in the free text section. More help

Sex Applicability

The authors must select from one of the following: Male, female, mixed, asexual, third gender, hermaphrodite, or unspecific. More help

Key Event Description

A description of the biological state being observed or measured, the biological compartment in which it is measured, and its general role in the biology should be provided. For example, the biological state being measured could be the activity of an enzyme, the expression of a gene or abundance of an mRNA transcript, the concentration of a hormone or protein, neuronal activity, heart rate, etc. The biological compartment may be a particular cell type, tissue, organ, fluid (e.g., plasma, cerebrospinal fluid), etc. The role in the biology could describe the reaction that an enzyme catalyses and the role of that reaction within a given metabolic pathway; the protein that a gene or mRNA transcript codes for and the function of that protein; the function of a hormone in a given target tissue, physiological function of an organ, etc. Careful attention should be taken to avoid reference to other KEs, KERs or AOPs. Only describe this KE as a single isolated measurable event/state. This will ensure that the KE is modular and can be used by other AOPs, thereby facilitating construction of AOP networks. More help

Proliferation occurs when changes in external signals release inhibitory controls limiting entry into the cell cycle, and oncogenic mutations act via these same pathways to generate abnormal proliferation (Hanahan and Weinberg 2011; Weber, Desai et al. 2017). Inhibitory signals such as contact inhibition or TGF-β (Polyak, Kato et al. 1994; Francis, Bergsied et al. 2009) stabilize the mechanisms limiting entry into the cell cycle. Proliferative signals such as those following progesterone or estrogen (Croce 2008; Weber, Desai et al. 2017) or compensatory proliferation after apoptosis (Fogarty and Bergmann 2017) relieve inhibition and enable cells to enter the cell cycle. Mutations that inactivate inhibitory signals (tumor suppressors) or activate proliferative signals (oncogenes) promote proliferation outside of the normal biological context (Gustin, Karakas et al. 2009; Francis, Chakrabarti et al. 2011; Hanahan and Weinberg 2011; Weber, Desai et al. 2017). Abnormal proliferation is typically met with apoptosis or senescence, so additional mutations or other mechanisms are required to escape these additional levels of control for proliferation to continue indefinitely (Garbe, Bhattacharya et al. 2009; Shay and Wright 2011; Fernald and Kurokawa 2013).

Proliferation increases mutations as DNA damage and replication errors become integrated into the genome (Kiraly, Gong et al. 2015). Proliferation can also promote the expansion of existing cells with proliferative mutations. Genomic mutations favoring further proliferation are positively selected from among the expanded cells, resulting in the accumulation of mutational errors and moving the organism further towards cancer. Different clonal populations can also collaborate to promote growth (Marusyk, Tabassum et al. 2014; Franco, Tyson et al. 2016).

How It Is Measured or Detected

One of the primary considerations in evaluating AOPs is the relevance and reliability of the methods with which the KEs can be measured. The aim of this section of the KE description is not to provide detailed protocols, but rather to capture, in a sentence or two, per method, the type(s) of measurements that can be employed to evaluate the KE and the relative level of scientific confidence in those measurements. Methods that can be used to detect or measure the biological state represented in the KE should be briefly described and/or cited. These can range from citation of specific validated test guidelines, citation of specific methods published in the peer reviewed literature, or outlines of a general protocol or approach (e.g., a protein may be measured by ELISA).Key considerations regarding scientific confidence in the measurement approach include whether the assay is fit for purpose, whether it provides a direct or indirect measure of the biological state in question, whether it is repeatable and reproducible, and the extent to which it is accepted in the scientific and/or regulatory community. Information can be obtained from the OECD Test Guidelines website and the EURL ECVAM Database Service on Alternative Methods to Animal Experimentation (DB-ALM). ?

Past cellular proliferation can be measured directly using labels that are incorporated into cells upon cell division (BRDU or cytoplasmic proliferation dyes) or indirectly by measuring a change in population size. Ongoing current proliferation can be quantified by labeling a protein associated with the cell cycle (e.g. Ki67). Methods for measuring proliferation were reviewed in (Romar, Kupper et al. 2016) and summarized in Table 1.

Table 1. Common methods for detecting proliferation





Past proliferation

Nucleoside analog incorporation (BRDU)


Stable, so can see proliferation from a specific time point onward. Can be used in vivo. BRDU must be labeled with a secondary fluorescent or other label for visualization, so it cannot be measured in living cells.

Past proliferation

Cytoplasmic proliferation dyes:  carboxyfluorescein diacetate succinimidyl ester (CFSE).


Enables quantification of successive cell divisions and differentiation between slowly and rapidly cycling cells. Cells survive analysis, so these dyes can be used as part of ongoing experiments. The dyes are better suited to in vitro experiments.

Past proliferation

Cell counting


An increase in cell numbers over time could represent proliferation or a decrease in apoptosis. Better suited to in vitro experiments, unless a label can be used to uniquely label a population of cells.

Ongoing proliferation rate

Ki67 probe


Labels all non-G0 phase proliferating cells. Labeling requires permeabilization so examination terminates the experiment.

Domain of Applicability

This free text section should be used to elaborate on the scientific basis for the indicated domains of applicability and the WoE calls (if provided). While structured terms may be selected to define the taxonomic, life stage and sex applicability (see structured applicability terms, above) of the KE, the structured terms may not adequately reflect or capture the overall biological applicability domain (particularly with regard to taxa). Likewise, the structured terms do not provide an explanation or rationale for the selection. The free-text section on evidence for taxonomic, life stage, and sex applicability can be used to elaborate on why the specific structured terms were selected, and provide supporting references and background information.  More help

Evidence for Perturbation by Stressor

Ionizing Radiation

While higher doses of ionizing radiation cause cell death in the short term (especially of dividing cells), IR is associated with delayed proliferation in vitro and in vivo. In vitro, IR can promote the proliferation/expansion in p16-suppressed and immortal epithelial populations as well as in bystander CHO cells co-cultured with IR-exposed cells (Han, Chen et al. 2010; Mukhopadhyay, Costes et al. 2010; Tang, Fernandez-Garcia et al. 2014). In vivo, IR increases apoptosis and compensatory proliferation in adult rats (Loree, Koturbash et al. 2006), and long term expression of proliferation in adolescent but not adult mammary gland (Datta, Hyduke et al. 2012; Snijders, Marchetti et al. 2012; Suman, Johnson et al. 2012), possibly via the expansion of a population of stem-like cells in vivo (Nguyen, Oketch-Rabah et al. 2011; Tang, Fernandez-Garcia et al. 2014). This proliferation appears to be associated with TGF-β/Notch activity (Tang, Fernandez-Garcia et al. 2014) and nitric oxide (Han, Chen et al. 2010). IR also increases mammary hyperplasia (Faulkin, Shellabarger et al. 1967; Imaoka, Nishimura et al. 2006). While IR can induce senescence in epithelial cells, IR selects for a post-senescent variant of epithelial cell which would be more conducive to tumorigenesis (Mukhopadhyay, Costes et al. 2010).

Datta, K., D. R. Hyduke, et al. (2012). "Exposure to ionizing radiation induced persistent gene expression changes in mouse mammary gland." Radiat Oncol 7: 205.

Faulkin, J. L. J., C. J. Shellabarger, et al. (1967). "Hyperplastic Lesions of Sprague-Dawley Rat Mammary Glands After X Irradiation2." JNCI: Journal of the National Cancer Institute 39(3): 449-459.

Han, W., S. Chen, et al. (2010). "Nitric oxide mediated DNA double strand breaks induced in proliferating bystander cells after alpha-particle irradiation." Mutation research 684(1-2): 81-89.

Imaoka, T., M. Nishimura, et al. (2006). "Persistent cell proliferation of terminal end buds precedes radiation-induced rat mammary carcinogenesis." In Vivo 20(3): 353-358.

Loree, J., I. Koturbash, et al. (2006). "Radiation-induced molecular changes in rat mammary tissue: possible implications for radiation-induced carcinogenesis." International journal of radiation biology 82(11): 805-815.

Mukhopadhyay, R., S. V. Costes, et al. (2010). "Promotion of variant human mammary epithelial cell outgrowth by ionizing radiation: an agent-based model supported by in vitro studies." Breast cancer research : BCR 12(1): R11.

Nguyen, D. H., H. A. Oketch-Rabah, et al. (2011). "Radiation acts on the microenvironment to affect breast carcinogenesis by distinct mechanisms that decrease cancer latency and affect tumor type." Cancer Cell 19(5): 640-651.

Snijders, A. M., F. Marchetti, et al. (2012). "Genetic differences in transcript responses to low-dose ionizing radiation identify tissue functions associated with breast cancer susceptibility." PLoS One 7(10): e45394.

Suman, S., M. D. Johnson, et al. (2012). "Exposure to ionizing radiation causes long-term increase in serum estradiol and activation of PI3K-Akt signaling pathway in mouse mammary gland." International journal of radiation oncology, biology, physics 84(2): 500-507.

Tang, J., I. Fernandez-Garcia, et al. (2014). "Irradiation of juvenile, but not adult, mammary gland increases stem cell self-renewal and estrogen receptor negative tumors." Stem Cells 32(3): 649-661.


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

Croce, C. M. (2008). "Oncogenes and cancer." The New England journal of medicine 358(5): 502-511.

Fernald, K. and M. Kurokawa (2013). "Evading apoptosis in cancer." Trends in cell biology 23(12): 620-633.

Fogarty, C. E. and A. Bergmann (2017). "Killers creating new life: caspases drive apoptosis-induced proliferation in tissue repair and disease." Cell death and differentiation 24(8): 1390-1400.

Francis, S. M., J. Bergsied, et al. (2009). "A functional connection between pRB and transforming growth factor beta in growth inhibition and mammary gland development." Molecular and cellular biology 29(16): 4455-4466.

Francis, S. M., S. Chakrabarti, et al. (2011). "A context-specific role for retinoblastoma protein-dependent negative growth control in suppressing mammary tumorigenesis." PLoS One 6(2): e16434.

Franco, O. E., D. R. Tyson, et al. (2016). "Altered TGF-alpha/beta signaling drives cooperation between breast cancer cell populations." FASEB journal : official publication of the Federation of American Societies for Experimental Biology 30(10): 3441-3452.

Garbe, J. C., S. Bhattacharya, et al. (2009). "Molecular distinctions between stasis and telomere attrition senescence barriers shown by long-term culture of normal human mammary epithelial cells." Cancer research 69(19): 7557-7568.

Gustin, J. P., B. Karakas, et al. (2009). "Knockin of mutant PIK3CA activates multiple oncogenic pathways." Proceedings of the National Academy of Sciences of the United States of America 106(8): 2835-2840.

Hanahan, D. and R. A. Weinberg (2011). "Hallmarks of cancer: the next generation." Cell 144(5): 646-674.

Kiraly, O., G. Gong, et al. (2015). "Inflammation-induced cell proliferation potentiates DNA damage-induced mutations in vivo." PLoS Genet 11(2): e1004901.

Marusyk, A., D. P. Tabassum, et al. (2014). "Non-cell-autonomous driving of tumour growth supports sub-clonal heterogeneity." Nature 514(7520): 54-58.

Polyak, K., J. Y. Kato, et al. (1994). "p27Kip1, a cyclin-Cdk inhibitor, links transforming growth factor-beta and contact inhibition to cell cycle arrest." Genes & development 8(1): 9-22.

Romar, G. A., T. S. Kupper, et al. (2016). "Research Techniques Made Simple: Techniques to Assess Cell Proliferation." The Journal of investigative dermatology 136(1): e1-7.

Shay, J. W. and W. E. Wright (2011). "Role of telomeres and telomerase in cancer." Seminars in cancer biology 21(6): 349-353.

Weber, R. J., T. A. Desai, et al. (2017). "Non-autonomous cell proliferation in the mammary gland and cancer." Current opinion in cell biology 45: 55-61.