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Relationship: 1252

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

Increased, Ductal Hyperplasia leads to N/A, Breast Cancer

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
Estrogen receptor activation leading to breast cancer adjacent High High Brendan Ferreri-Hanberry (send email) Open for adoption
Increased DNA damage leading to increased risk of breast cancer adjacent High Not Specified Allie Always (send email) Under development: Not open for comment. Do not cite Under Development
Increased reactive oxygen and nitrogen species (RONS) leading to increased risk of breast cancer adjacent High Not Specified Evgeniia Kazymova (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

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

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

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

Proliferative lesions are believed to evolve over time and with successive cell divisions to take on the hallmarks of carcinogenesis, either directly or via other cell types recruited to the site such as fibroblasts and macrophages.

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 is High. It is generally accepted that proliferation contributes to cancer. Proliferation increases mutations, which can further promote proliferation and/or changes to the local microenvironment.

Empirical support is High. Carcinogenic agents increase proliferation and hyperplasia as well as tumors. Proliferation and hyperplasia appears prior to or at the same time as tumors, grow into carcinomas, and are more effective at forming mammary tumors than non-proliferating tissue. Disruption of proliferation is associated with decreased tumor growth, and tumor resistant rats do not show proliferation. However, the discrepancy between the non-linear proliferative and linear mammary tumor response to carcinogen dose coupled with evidence of independent occurrences of proliferation and tumorigenesis suggests that while proliferation and hyperplasia likely promote carcinogenesis, additional factors also contribute.

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
 Biological Plausibility is High. It is generally accepted that proliferation contributes to cancer. Proliferation increases mutations, which can further promote proliferation and/or changes to the local microenvironment. For example, cells that become insensitive to certain TGF-β signaling pathways would be resistant to contact or TGF-β inhibition (Polyak, Kato et al. 1994) or apoptosis (Chapman, Lourenco et al. 1999), and cells that release or promote the stromal release of MMPs remodel the stroma and promote tumorigenesis and invasiveness (Sternlicht, Lochter et al. 1999; Ha, Moon et al. 2001).
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

In the relatively small number of studies that examine the dose-dependence of proliferation and hyperplasia in models of carcinogenesis, proliferation does not appear to increase linearly with dose (Han, Chen et al. 2010; Mukhopadhyay, Costes et al. 2010; Nguyen, Oketch-Rabah et al. 2011; Tang, Fernandez-Garcia et al. 2014) while tumor formation and carcinogenesis does increase linearly with dose.

Some studies report carcinogenesis in the absence of hyperplasia (Middleton 1965; Sinha and Dao 1974) and others do not find increased tumorigenesis from transplanted hyperplasia (Haslam and Bern 1977; Sinha and Dao 1977). In Copenhagen rats resistant to tumors from MNU treatment, hyperplasia appear after MNU treatment but do not progress into carcinomas in situ, instead disappearing over time (Korkola and Archer 1999). Similarly, Fisher rats are less sensitive to tumor induction by DMBA, and hyperplasia from these rats do not go on to form tumors when transplanted (Beuving, Bern et al. 1967).

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
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
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

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

Beuving, L. J. (1968). "Mammary tumor formation within outgrowths of transplanted hyperplastic nodules from carcinogen-treated rats." Journal of the National Cancer Institute 40(6): 1287-1291.

Beuving, L. J., H. A. Bern, et al. (1967). "Occurrence and Transplantation of Carcinogen-Induced Hyperplastic Nodules in Fischer Rats2." JNCI: Journal of the National Cancer Institute 39(3): 431-447.

Beuving, L. J., J. L. J. Faulkin, et al. (1967). "Hyperplastic Lesions in the Mammary Glands of Sprague-Dawley Rats After 7,12-Dimethylbenz[a]anthracene Treatment2." JNCI: Journal of the National Cancer Institute 39(3): 423-429.

Chapman, R. S., P. C. Lourenco, et al. (1999). "Suppression of epithelial apoptosis and delayed mammary gland involution in mice with a conditional knockout of Stat3." Genes & development 13(19): 2604-2616.

Connelly, L., W. Barham, et al. (2011). "Inhibition of NF-kappa B activity in mammary epithelium increases tumor latency and decreases tumor burden." Oncogene 30(12): 1402-1412.

Deome, K. B., L. J. Faulkin, Jr., et al. (1959). "Development of mammary tumors from hyperplastic alveolar nodules transplanted into gland-free mammary fat pads of female C3H mice." Cancer Res 19(5): 515-520.

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.

Ha, H. Y., H. B. Moon, et al. (2001). "Overexpression of membrane-type matrix metalloproteinase-1 gene induces mammary gland abnormalities and adenocarcinoma in transgenic mice." Cancer research 61(3): 984-990.

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.

Haslam, S. Z. and H. A. Bern (1977). "Histopathogenesis of 7,12-diemthylbenz(a)anthracene-induced rat mammary tumors." Proceedings of the National Academy of Sciences of the United States of America 74(9): 4020-4024.

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.

Imaoka, T., M. Nishimura, et al. (2005). "Cooperative induction of rat mammary cancer by radiation and 1-methyl-1-nitrosourea via the oncogenic pathways involving c-Myc activation and H-ras mutation." Int J Cancer 115(2): 187-193.

Korkola, J. E. and M. C. Archer (1999). "Resistance to mammary tumorigenesis in Copenhagen rats is associated with the loss of preneoplastic lesions." Carcinogenesis 20(2): 221-227.

Kutanzi, K. R., I. Koturbash, et al. (2010). "Imbalance between apoptosis and cell proliferation during early stages of mammary gland carcinogenesis in ACI rats." Mutation research 694(1-2): 1-6.

Luo, M., H. Fan, et al. (2009). "Mammary epithelial-specific ablation of the focal adhesion kinase suppresses mammary tumorigenesis by affecting mammary cancer stem/progenitor cells." Cancer research 69(2): 466-474.

Medina, D. and H. J. Thompson (2000). A Comparison of the Salient Features of Mouse, Rat, and Human Mammary Tumorigenesis. Methods in Mammary Gland Biology and Breast Cancer Research. M. M. Ip and B. B. Asch. Boston, MA, Springer US: 31-36.

Middleton, P. J. (1965). "The histogenesis of mammary tumours induced in the rat by chemical carcinogens." British journal of cancer 19(4): 830-839.

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.

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.

Purnell, D. M. (1980). "The relationship of terminal duct hyperplasia to mammary carcinoma in 7,12-dimethylbenz(alpha)anthracene-treated LEW/Mai rats." The American journal of pathology 98(2): 311-324.

Rivera, E. M., S. D. Hill, et al. (1981). "Organ culture passage enhances the oncogenicity of carcinogen-induced hyperplastic mammary nodules." In vitro 17(2): 159-166.

Russo, J., J. Saby, et al. (1977). "Pathogenesis of Mammary Carcinomas Induced in Rats by 7, 12-Dimethylbenz[a]anthracene2." JNCI: Journal of the National Cancer Institute 59(2): 435-445.

Shellabarger, C. J., J. P. Stone, et al. (1976). "Synergism between neutron radiation and diethylstilbestrol in the production of mammary adenocarcinomas in the rat." Cancer research 36(3): 1019-1022.

Sinha, D. and T. L. Dao (1974). "A Direct Mechanism of Mammary Carcinogenesis Induced by 7,12-Dimethylbenz[a]anthracene2." JNCI: Journal of the National Cancer Institute 53(3): 841-846.

Sinha, D. and T. L. Dao (1977). "Hyperplastic alveolar nodules of the rat mammary gland: tumor-producing capability in vivo and in vitro." Cancer letters 2(3): 153-160.

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.

Sternlicht, M. D., A. Lochter, et al. (1999). "The stromal proteinase MMP3/stromelysin-1 promotes mammary carcinogenesis." Cell 98(2): 137-146.

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.

Ullrich, R. L. and R. J. Preston (1991). "Radiation induced mammary cancer." Journal of radiation research 32 Suppl 2: 104-109.