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Event: 1193

Key Event Title

A descriptive phrase which defines a discrete biological change that can be measured. More help

N/A, Breast Cancer

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. More help
N/A, Breast Cancer
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Biological Context

Structured terms, selected from a drop-down menu, are used to identify the level of biological organization for each KE. More help
Level of Biological Organization

Key Event Components

The KE, as defined by a set structured ontology terms consisting of a biological process, object, and action with each term originating from one of 14 biological ontologies (Ives, et al., 2017; Biological process describes dynamics of the underlying biological system (e.g., receptor signalling).Biological process describes dynamics of the underlying biological system (e.g., receptor signaling).  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 signaling 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.  Further information on Event Components and Biological Context may be viewed on the attached pdf. More help
Process Object Action
Breast Neoplasms pathological

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 AdverseOutcome Molly M Morgan (send email) Open for adoption
Increased DNA damage leading to breast cancer AdverseOutcome Jessica Helm (send email) Under development: Not open for comment. Do not cite Under Development
RONS leading to breast cancer AdverseOutcome Jessica Helm (send email) Under development: Not open for comment. Do not cite Under Development

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 KE.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
Term Scientific Term Evidence Link
mammals mammals High NCBI
Homo sapiens Homo sapiens High NCBI

Life Stages

An indication of the the relevant life stage(s) for this KE. More help
Life stage Evidence
Adult High

Sex Applicability

An indication of the the relevant sex for this KE. More help
Term Evidence
Mixed High

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. More help

Cancers are thought to arise from a collection of permissive factors which interact within and between different cells of a tissue or tumor to promote tumor growth and invasive characteristics (Sonnenschein and Soto 1999; Hanahan and Weinberg 2011; Floor, Dumont et al. 2012; Goodson, Lowe et al. 2015; Schwarzman, Ackerman et al. 2015; Smith, Guyton et al. 2016; Grashow, De La Rosa et al. 2018). Permissive factors or hallmarks include changes to the cell’s dependence on growth signals, proliferation, metabolism, apoptosis, senescence, angiogenesis, and invasion and metastasis. These hallmarks are modified by other factors including growth factors, inflammation, oxidative stress, changes to the microenvironment, DNA damage, and changes in gene expression.

The mammary gland is a hormone responsive organ with multiple phases of development from embryogenesis into adulthood. Consequently, certain hallmarks and contributing factors including proliferative response to growth signals, growth factors, changes to the microenvironment, and changes in gene expression play a larger role in this organ, and the importance of various factors shifts depending on developmental stage (Rudel, Fenton et al. 2011). Established risk factors of breast cancer extend beyond genetic contributors (principally alterations in DNA damage response genes) and DNA damaging environmental agents to include exposure to pharmaceutical hormones, timing of puberty and first birth, and lifetime exposure to estrogen and progesterone ((IOM) Institute of Medicine 2012). 

Hormonal and other environmental influences during proliferation and differentiation alter the pace and structure of cellular or mammary gland development to leave tissue in the adult gland more susceptible to cancer. In addition, the elevated hormone concentrations associated with the menstrual cycle and pregnancy provide a regular proliferative stimulus to any pre-cancerous cells present in the breast (Rudel, Fenton et al. 2011). A substantial majority of breast cancers express hormone receptors, and these cancers are particularly responsive to hormones (Badowska-Kozakiewicz, Patera et al. 2015).

Consistent with the importance of growth factors and DNA damage in the development of cancer, driver mutations (mutations that favor the success of the nascent cancer cells and are therefore selected) commonly appear in the growth factor related signaling pathways (BRAF, EGRF, RAS, PI3K, STK11) and in DNA damage response and cell cycle checkpoint signal pathways (ATM, TP53, CHEK2, CDKN2B (P15), CDK4) (Greenman, Stephens et al. 2007; Croce 2008; Kaufmann, Nevis et al. 2008; Stratton, Campbell et al. 2009; Vandin, Upfal et al. 2012). These and other mutations are acquired over the development of a cancer and contribute to the evolution of the cancer (Wang, Waters et al. 2014; Yates, Gerstung et al. 2015; Begg, Ostrovnaya et al. 2016).

In breast cancer, TP53, PI3K and GATA3 are each mutated in more than 10% of cancers, amplification or mutation of the RB1 pathway are common, and HER2 (an EGFR receptor) is amplified in HER2 type cancers (CGAN 2012). EGFR, HER2, BRAF, RAS, and PI3K participate in the EGFR (growth factor) signaling pathway. Activating mutations in PI3K generate growth factor independent proliferation of mammary epithelial cells, possibly via the RB1 pathway (Gustin, Karakas et al. 2009). GATA is a transcription factor that maintains luminal epithelial cell differentiation and suppresses proliferation, and mutation results in the proliferation of undifferentiated cells (Kouros-Mehr, Slorach et al. 2006; Shahi, Wang et al. 2017).

Environmental factors contribute significantly to the total number of breast cancers. Women exposed to the synthetic hormone DES or the pesticide DDT in utero are up to two to four times more likely to be diagnosed with breast cancer in their fifties (Palmer, Wise et al. 2006; Cohn, La Merrill et al. 2015). A study in 2002 found that recipients of hormone replacement therapy (HRT) around menopause are 26% more likely to be diagnosed with breast cancer (Narod 2011). When prescriptions of HRT began to fall in response to the study, so did cancer diagnoses. Over the next few years, approximately 5% fewer cancers were diagnosed in women over 45 (Glass, Lacey et al. 2007) with an estimated 126,000 fewer cases of breast cancer over the next ten years (Roth, Etzioni et al. 2014).

How It Is Measured or Detected

A description of the type(s) of measurements that can be employed to evaluate the KE and the relative level of scientific confidence in those measurements.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). Do not provide detailed protocols. More help

In rodent bioassays, tumors can be detected via visual observation or palpation of live animals, necropsy of dead animals, and via microscopic examination of tissue. Malignant tumors including carcinomas in situ are distinguishable from benign tumors on the basis of the thickness or shape of the epithelial cell layer, regularity of the lumen or the presence of cribiform luminae, inflammation or desmoplastic reaction of the stroma, dominance of a less differentiated cell type, and larger nuclei, while diagnosis of invasiveness depends on the identification of metastases or invasion of neoplastic cells into surrounding tissue (Russo and Russo 2000).

In humans, lumps are commonly detected by palpation or mammogram. Further imaging, biopsy, and/or surgical excision of the affected tissue are used to differentiate benign, cancerous, and invasive tumors (McDonald, Clark et al. 2016).

Domain of Applicability

A description of the scientific basis for the indicated domains of applicability and the WoE calls (if provided).  More help

This can be applied to adult women and men and mice.

Regulatory Significance of the Adverse Outcome

An AO is a specialised KE that represents the end (an adverse outcome of regulatory significance) of an AOP. More help

Because of the long latency of mammary tumors, the two-year rodent carcinogenicity bioassay is the primary assay for this adverse outcome. The assay is included in the OECD Test No. 451 and 453 for carcinogenicity and combined toxicity and carcinogenicity (OECD 2009; OECD 2009), and is also used by the US National Toxicology program (Chhabra, Huff et al. 1990), and the FDA (FDA (Food and Drug Administration) 2007), and referenced by the EPA (EPA (Environmental Protection Agency) 2005) in guidelines for risk assessments. Other assays from short term (2-4 weeks) and subchronic (90 day) to chronic (1 year) toxicity also call for the documentation of mammary tumors (FDA (Food and Drug Administration) 2007; OECD (Organisation for Economic Cooperation and Development) 2018), so these assays could capture the early onset of tumors, and could be modified to report earlier key events like proliferation and inflammation.

Several characteristics of classic cancer bioassays limit the sensitivity of these assays to mammary gland carcinogens. First, no assays require prenatal or early post-natal exposures for carcinogenicity testing. The US NIH’s National Toxicology Program assays start exposures at five to six weeks of age and OECD regulatory assay exposures suggest (but do not require) exposures beginning after weaning and before eight weeks of age. Assays initiating exposures at later ages have diminished sensitivity to agents that affect breast development and increase future susceptibility to cancer, such as estrogenic hormones, DDT and dioxins (EPA (Environmental Protection Agency) 2005; Rudel, Fenton et al. 2011). Agents with similar activity to ionizing radiation and DNA damaging chemicals may not be fully captured in some of these assays, since sensitivity appears to peak around or before week seven for these agents (around puberty) (Imaoka, Nishimura et al. 2013). Second, carcinogenicity assay guidelines do not require the best methods for detecting tumors in mammary gland: whole mount preparations of mammary gland coupled with longitudinal sections (dorsoventral sections parallel to the body) of mammary gland for histology (Tucker, Foley et al. 2017). Palpation and transverse sections of mammary gland can easily miss tumors or lesions of interest. Interestingly the NTP reproductive toxicity guidelines do specify these preferable methods for mammary gland analysis.

Two additional factors affect the sensitivity of standard carcinogenicity assays. First, benign tumors are not always considered to be an indicator of carcinogenicity, leading to a possible underestimation of risk.  NTP and EPA guidance suggest that benign tumors provide additional weight of evidence if malignant tumors are also present or if studies suggest benign tumors can progress to carcinogenicity. In a short-term study, benign tumors may indicate a need for a longer-term study. However, benign mammary tumors (fibroadenomas) almost always coincide with carcinogenic tumors in mammary gland or other organs, and carcinomas sometimes grow from fibroadnomas (Rudel, Attfield et al. 2007; Russo 2015) suggesting that benign tumors may be an underutilized indicator of carcinogenicity.

Finally, the dose selection guidance in carcinogenicity testing typically calls for a high dose that is sufficiently toxic to suppress body weight (OECD 2009). However, body weight interacts with risk of breast cancer (Haseman, Young et al. 1997; Rudel, Attfield et al. 2007), reducing the sensitivity of the upper end of the dose range and the likelihood of a positive dose-response.


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

(IOM) Institute of Medicine (2012). Breast Cancer and the Environment: A Life Course Approach. Washington, DC, The National Academies Press.

Badowska-Kozakiewicz, A. M., J. Patera, et al. (2015). "The role of oestrogen and progesterone receptors in breast cancer - immunohistochemical evaluation of oestrogen and progesterone receptor expression in invasive breast cancer in women." Contemp Oncol (Pozn) 19(3): 220-225.

Begg, C. B., I. Ostrovnaya, et al. (2016). "Clonal relationships between lobular carcinoma in situ and other breast malignancies." Breast cancer research : BCR 18(1): 66.

CGAN (Cancer Genome Atlas Network) (2012). "Comprehensive molecular portraits of human breast tumours." Nature 490(7418): 61-70.

Chhabra, R. S., J. E. Huff, et al. (1990). "An overview of prechronic and chronic toxicity/carcinogenicity experimental study designs and criteria used by the National Toxicology Program." Environmental health perspectives 86: 313-321.

Cohn, B. A., M. La Merrill, et al. (2015). "DDT Exposure in Utero and Breast Cancer." J Clin Endocrinol Metab 100(8): 2865-2872.

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

EPA (Environmental Protection Agency) (2005). Guidelines for carcinogen risk assessment. Washington, DC, U.S. Environmental Protection Agency, Risk Assessment Forum: 1-166.

FDA (Food and Drug Administration) (2007). Redbook 2000: Guidance for industry and other stakeholders. Toxicological principles for the safety assessment of food ingredients. Silver Spring, MD, U.S. Department of Health and Human Services, Food and Drug Administration.

Floor, S. L., J. E. Dumont, et al. (2012). "Hallmarks of cancer: of all cancer cells, all the time?" Trends Mol Med 18(9): 509-515.

Glass, A. G., J. V. Lacey, Jr., et al. (2007). "Breast cancer incidence, 1980-2006: combined roles of menopausal hormone therapy, screening mammography, and estrogen receptor status." Journal of the National Cancer Institute 99(15): 1152-1161.

Goodson, W. H., 3rd, L. Lowe, et al. (2015). "Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the environment: the challenge ahead." Carcinogenesis 36 Suppl 1: S254-296.

Grashow, R. G., V. Y. De La Rosa, et al. (2018). "BCScreen: A gene panel to test for breast carcinogenesis in chemical safety screening." Computational Toxicology 5: 16-24.

Greenman, C., P. Stephens, et al. (2007). "Patterns of somatic mutation in human cancer genomes." Nature 446(7132): 153-158.

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.

Haseman, J. K., E. Young, et al. (1997). "Body weight-tumor incidence correlations in long-term rodent carcinogenicity studies." Toxicologic pathology 25(3): 256-263.

Imaoka, T., M. Nishimura, et al. (2013). "Influence of age on the relative biological effectiveness of carbon ion radiation for induction of rat mammary carcinoma." International journal of radiation oncology, biology, physics 85(4): 1134-1140.

Kaufmann, W. K., K. R. Nevis, et al. (2008). "Defective cell cycle checkpoint functions in melanoma are associated with altered patterns of gene expression." J Invest Dermatol 128(1): 175-187.

Kouros-Mehr, H., E. M. Slorach, et al. (2006). "GATA-3 maintains the differentiation of the luminal cell fate in the mammary gland." Cell 127(5): 1041-1055.

McDonald, E. S., A. S. Clark, et al. (2016). "Clinical Diagnosis and Management of Breast Cancer." J Nucl Med 57 Suppl 1: 9S-16S.

Narod, S. A. (2011). "Hormone replacement therapy and the risk of breast cancer." Nature reviews. Clinical oncology 8(11): 669-676.

OECD (2009). Test No. 451: Carcinogenicity Studies.

OECD (2009). Test No. 453: Combined Chronic Toxicity/Carcinogenicity Studies.

OECD (Organisation for Economic Cooperation and Development) (2018). OECD guidelines for the testing of chemicals Section 4. Paris, OECD.

Palmer, J. R., L. A. Wise, et al. (2006). "Prenatal diethylstilbestrol exposure and risk of breast cancer." Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 15(8): 1509-1514.

Roth, J. A., R. Etzioni, et al. (2014). "Economic return from the Women's Health Initiative estrogen plus progestin clinical trial: a modeling study." Ann Intern Med 160(9): 594-602.

Rudel, R. A., K. R. Attfield, et al. (2007). "Chemicals causing mammary gland tumors in animals signal new directions for epidemiology, chemicals testing, and risk assessment for breast cancer prevention." Cancer 109(12 Suppl): 2635-2666.

Rudel, R. A., S. E. Fenton, et al. (2011). "Environmental exposures and mammary gland development: state of the science, public health implications, and research recommendations." Environmental health perspectives 119(8): 1053-1061.

Russo, J. (2015). "Significance of rat mammary tumors for human risk assessment." Toxicologic pathology 43(2): 145-170.

Russo, J. and I. H. Russo (2000). "Atlas and histologic classification of tumors of the rat mammary gland." J Mammary Gland Biol Neoplasia 5(2): 187-200.

Schwarzman, M. R., J. M. Ackerman, et al. (2015). "Screening for Chemical Contributions to Breast Cancer Risk: A Case Study for Chemical Safety Evaluation." Environmental health perspectives 123(12): 1255-1264.

Shahi, P., C. Y. Wang, et al. (2017). "GATA3 targets semaphorin 3B in mammary epithelial cells to suppress breast cancer progression and metastasis." Oncogene 36(40): 5567-5575.

Smith, M. T., K. Z. Guyton, et al. (2016). "Key Characteristics of Carcinogens as a Basis for Organizing Data on Mechanisms of Carcinogenesis." Environmental health perspectives 124(6): 713-721.

Sonnenschein, C. and A. M. Soto (1999). The society of cells : cancer control of cell proliferation. Oxford New York, Bios Scientific Publishers ;Springer.

Stratton, M. R., P. J. Campbell, et al. (2009). "The cancer genome." Nature 458(7239): 719-724.

Tucker, D. K., J. F. Foley, et al. (2017). "Sectioning Mammary Gland Whole Mounts for Lesion Identification." Journal of visualized experiments : JoVE(125).

Vandin, F., E. Upfal, et al. (2012). "De novo discovery of mutated driver pathways in cancer." Genome research 22(2): 375-385.

Wang, Y., J. Waters, et al. (2014). "Clonal evolution in breast cancer revealed by single nucleus genome sequencing." Nature 512(7513): 155-160.

Yates, L. R., M. Gerstung, et al. (2015). "Subclonal diversification of primary breast cancer revealed by multiregion sequencing." Nat Med 21(7): 751-759.

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