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Relationship: 962


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

Activation, EGFR leads to Decreased ciliated cell 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
EGFR Activation Leading to Decreased Lung Function adjacent Moderate Low Karsta Luettich (send email) Under development: Not open for comment. Do not cite Under Development

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 Moderate NCBI
mouse Mus musculus Moderate NCBI
rat Rattus norvegicus 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
Mixed Moderate

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
Adult Low

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

Exposure to airborne toxicants and pathogens causing oxidative stress as well as oxidative stress induced by inflammatory responses to environmental exposures mediate proteolytic cleavage of membrane-bound EGFR ligand precursors (Burgel and Nadel, 2004; Gao et al., 2015; Øvrevik et al., 2015). Subsequent ligand binding then activates the receptor tyrosine kinase in an autocrine fashion. Downstream of EGFR activation, phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signaling elicits an anti-apoptotic response in ciliated cells favoring their survival (Tyner et al., 2006).

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

Tyner et al. (2006) reported that ciliated cell survival in a mouse airway infection model is promoted via EGFR-dependent PI3K/Akt signaling. Oxidative stress following inhalation exposure increased Bcl-2 mRNA and protein levels in human and rat airway epithelial cells (Casalino-Matsuda et al., 2006; Foster et al., 2003; Lee et al., 2011; Tesfaigzi et al., 1998; Tesfaigzi et al., 2000; Petecchia et al., 2009). Neutralization of Bcl-2 expression in rat nasal epithelium reduced goblet cell metaplasia (Harris et al., 2005), and treatment of OVA-sensitized Balb/c mice with the EGFR inhibitor gefitinib decreased Bcl-2 expression and increased apoptosis (Song et al., 2016).

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

Downstream EGFR signaling involving the PI3K/AKT pathway regulating cell survival is well-documented, in particular in cancer cells where this pathway is often deregulated (e.g. Hennessey et al., 2005). However, to date, very few studies reported on the direct link between EGFR activation and the identity of airway epithelial cells undergoing apoptosis, so biological plausibility is only moderate. 

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

Some evidence available to date is correlative, demonstrating increased ciliated cell numbers following EGFR or EGFR/PI3K blockade. Other studies provide indirect support of a variety of stressors known to activate EGFR causing apoptosis of airway epithelial cells, although the identity of the affected cells is not always specified (Tesfaigzi et al., 2000; Tesfaigzi et al., 1998; Song et al., 2016; Sydlik et al., 2006). Other studies make no reference to the airway epithelial cell type that is affected by apoptosis. 

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

In primary bronchial epithelial cells, treatment with 0.6 mM xanthine and 0.05 units xanthine oxidase (X/XO) for 30 min doubled the pEGFR/EGFR ratio and increased the Bcl-2/actin mRNA ratio by ca. 5-fold. Both effects could be at least partially suppressed by pretreatment of cells with anti-EGFR neutralizing antibodies. Of note, this study was focused on goblet cells; however, the described mechanism may also apply to ciliated cells (Casalino-Matsuda et al., 2006).

Sendai virus, delivered at 2 × 105 PFUs intranasally to C57Bl/6J mice, caused EGFR activation (not quantified) in ciliated cells 21 days after inoculation, which was accompanied by an approx. 40-fold increase in ciliated cell number in the absence of proliferation as evidenced by the lack of BrdU staining. Complementary experiments in mouse tracheal epithelial cells grown at the air-liquid interface stimulated with 1 or 10 ng/mL EGF also demonstrated EGFR activation (not quantified), and EGFR blockade with PD153035 caused a dose-dependent decrease in ciliated cell numbers, with a maximum decrease (50%) seen at 0.3 µM inhibitor, while the number of TUNEL- and caspase 3-positive cells nearly tripled and quadrupled, respectively (Tyner et al., 2006).

EGFR phosphorylation was increased approx. 3-fold in rat alveolar epithelial cells (RLE-6TN) exposed to 10 µg/cm2 ultrafine carbon black particles for as little as 2 min. After an 8-h exposure, DNA fragmentation had doubled and caspase 3 activity tripled, but the latter could be almost completely suppressed by pretreatment with the EGFR inhibitor AG1478 (Sydlik et al., 2006).

Treatment of NCI-H292 lung cancer cells with 10 ng/mL the EGFR ligand TGFa for 24 h increased Bcl-2 protein expression by 50%, which was prevented by pretreatment with AG1478 (Takeyama et al., 2008).

Treatment of immortalized human bronchial epithelial BEAS-2B cells with 0.1 mM Ni2+ for 24 h significantly increased EGFR mRNA expression (1.59 ± 0.04-fold compared to untreated), EGFR phosphorylation and Bcl-2 protein expression levels (Giunta et al., 2012).

Treatment of primary human airway epithelial cells, grown as a monolayer, with 10 µg/mL cigarette smoke extract for 48 h increased EGFR phosphorylation by approx. 50%, Bcl-2 mRNA expression ca. 2.5-fold and Bcl-2 protein expression ca. 4.5-fold (Hussain et al., 2018).

In the small airways of male Sprague-Dawley rats that were exposed to cigarette smoke generated from 5 unfiltered cigarettes for 30 min twice daily for 4 weeks, the rate of apoptosis, as assessed by TUNEL staining, increased by 50%, and phosphorylation of EGFR at Tyr1068 increased 5.1-fold  (Ning et al., 2013).

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

EGFR was persistently activated in ciliated cells in C57Bl/6J mouse lungs at day 21, but not day 12, post-inoculation with Sendai virus, which coincided with an increased number of ciliated cells (approx. 10% increase in ß-tubulin-positive cells), a decreased number of goblet cells (approx. 10% decrease in Muc5ac-positive cells), but not with the expression of the proliferation markers BrdU, Ki67 or PCNA (Tyner et al., 2006).

In rat alevolar epithelial cells, treatment with ultrafine carbon black particles resulted in phosphorylation of EGFR after 2 minutes and a second, more persistent activation of the receptor from 120 to 480 min. Caspase 3 activity increased in a time-dependent manner, starting at 4 h and reaching a maximum after 8 h (Sydlik et al., 2006).

Intranasal influenza virus infection (7.5 PFU of H1N1) led to the loss of ciliated epithelial cells (acetylated tubulin–positive) by day 3, with recovery of the epithelial barrier by day 14 (Fujino et al., 2019). EGFR promotes uptake of influenza viruses and is activated (ca. 2-fold increase in phosphorylated EGFR) at 10 min following infection of immortalized human bronchial epithelial BEAS-2B cells (Ueki et al., 2013).

Chronic, 6-month exposure of immortalized human bronchial epithelial BEAS-2B cells to 0.25 μm Cr(VI) activated EGFR constitutively, beginning from month 2, and permanently elevated Bcl-2 protein levels (Kim et al., 2015).

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 studies that support epithelial cell apoptosis induced by EGFR activation include rat and mouse in vivo experiments and in vitro experiments in human and rat cells.


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

Burgel, P., and Nadel, J. (2004). Roles of epidermal growth factor receptor activation in epithelial cell repair and mucin production in airway epithelium. Thorax 59, 992-996.

Casalino-Matsuda, S., Monzón, M., and Forteza, R. (2006). Epidermal Growth Factor Receptor Activation by Epidermal Growth Factor Mediates Oxidant-Induced Goblet Cell Metaplasia in Human Airway Epithelium. Am. J. Respir. Cell Mol. Biol. 34, 581–591.

Curran, D., and Cohn, L. (2010). Advances in mucous cell metaplasia: a plug for mucus as a therapeutic focus in chronic airway disease. Am. J. Respir. Cell Mol. Biol. 42, 268–275.

Fujino, N., Brand, O.J., Morgan, D.J., Fujimori, T., Grabiec, A.M., Jagger, C.P., et al. (2019). Sensing of apoptotic cells through Axl causes lung basal cell proliferation in inflammatory diseases. J. Exp. Med. 216, 2184-2201.

Gao, W., Li, L., Wang, Y., Zhang, S., Adcock, I.M., Barnes, P.J., Huang, M., and Yao, X. (2015). Bronchial epithelial cells: The key effector cells in the pathogenesis of chronic obstructive pulmonary disease? Respirol. 20, 722-729.

Giunta, S., Castorina, A., Scuderi, S., Patti, C., and D’agata, V. (2012). Epidermal growth factor receptor (EGFR) and neuregulin (Neu) activation in human airway epithelial cells exposed to nickel acetate. Toxicol. In Vitro 26, 280-287.

Hennessy, B.T., Smith, D.L., Ram, P.T., Lu, Y. and Mills, G.B., 2005. Exploiting the PI3K/AKT pathway for cancer drug discovery. Nat. Rev. Drug Discov. 4, 988-1004.

Hussain, S.S., George, S., Singh, S., Jayant, R., Hu, C.-A., Sopori, M., et al. (2018). A Small Molecule BH3-mimetic Suppresses Cigarette Smoke-Induced Mucous Expression in Airway Epithelial Cells. Sci. Rep. 8(1), 13796-13796. 

Kim, D., Dai, J., Fai, L.Y., Yao, H., Son, Y.-O., Wang, L., et al. (2015). Constitutive activation of epidermal growth factor receptor promotes tumorigenesis of Cr(VI)-transformed cells through decreased reactive oxygen species and apoptosis resistance development. J. Biol. Chem. 290, 2213-2224. 

Ning, Y., Shang, Y., Huang, H., Zhang, J., Dong, Y., Xu, W., et al. (2013). Attenuation of cigarette smoke-induced airway mucus production by hydrogen-rich saline in rats. PLoS One 8, e83429.

Øvrevik, J., Refsnes, M., Låg, M., Holme, J.A., and Schwarze, P.E. (2015). Activation of proinflammatory responses in cells of the airway mucosa by particulate matter: Oxidant- and non-oxidant-mediated triggering mechanisms. Biomolecules 5, 1399-1440.

Petecchia, L., Sabatini, F., Varesio, L., Camoirano, A., Usai, C., Pezzolo, A., et al. (2009). Bronchial airway epithelial cell damage following exposure to cigarette smoke includes disassembly of tight junction components mediated by the extracellular signal-regulated kinase 1/2 pathway. Chest 135, 1502-1512. 

Song, L., Tang, H., Liu, D., Song, J., Wu, Y., Qu, S., et al. (2016). The chronic and short-term effects of gefinitib on airway remodeling and inflammation in a mouse model of asthma. Cell. Physiol. Biochem. 38, 194-206.

Sydlik, U., Bierhals, K., Soufi, M., Abel, J., Schins, R.P.F., and Unfried, K. (2006). Ultrafine carbon particles induce apoptosis and proliferation in rat lung epithelial cells via specific signaling pathways both using EGF-R. Am. J. Physiol. Lung Cell. Mol. Physiol. 291, L725–L733.

Tesfaigzi, J., Hotchkiss, J.A., and Harkema, J.R. (1998). Expression of the Bcl-2 protein in nasal epithelia of F344/N rats during mucous cell metaplasia and remodeling. Am. J. Resp. Cell Mol. Biol. 18, 794-799.

Tesfaigzi, Y., Fischer, M.J., Martin, A.J., and Seagrave, J. (2000). Bcl-2 in LPS- and allergen-induced hyperplastic mucous cells in airway epithelia of Brown Norway rats. Am. J. Physiol. Lung Cell. Mol. Physiol. 279, L1210-L1217.

Tyner, J., Tyner, E., Ide, K., Pelletier, M., Roswit, W., Morton, J., Battaile, J., Patel, A., Patterson, G., Castro, M., et al. (2006). Blocking airway mucous cell metaplasia by inhibiting EGFR antiapoptosis and IL-13 transdifferentiation signals. J. Clin. Invest. 116, 309–321.

Ueki, I.F., Min-Oo, G., Kalinowski, A., Ballon-Landa, E., Lanier, L.L., Nadel, J.A., et al. (2013). Respiratory virus-induced EGFR activation suppresses IRF1-dependent interferon λ and antiviral defense in airway epithelium. J. Exp. Med. 210, 1929-1936.