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Event: 1193

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

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. The short name should be less than 80 characters in length. More help
N/A, Breast Cancer

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

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
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

Stressors

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
Term Scientific Term Evidence Link
mammals mammals High NCBI

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

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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

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

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). ?

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

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

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. For KEs that are designated as an AO, one additional field of information (regulatory significance of the AO) should be completed, to the extent feasible. If the KE is being described is not an AO, simply indicate “not an AO” in this section.A key criterion for defining an AO is its relevance for regulatory decision-making (i.e., it corresponds to an accepted protection goal or common apical endpoint in an established regulatory guideline study). For example, in humans this may constitute increased risk of disease-related pathology in a particular organ or organ system in an individual or in either the entire or a specified subset of the population. In wildlife, this will most often be an outcome of demographic significance that has meaning in terms of estimates of population sustainability. Given this consideration, in addition to describing the biological state associated with the AO, how it can be measured, and its taxonomic, life stage, and sex applicability, it is useful to describe regulatory examples using this AO. 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.

References

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 (https://www.oecd.org/about/publishing/OECD-Style-Guide-Third-Edition.pdf) (OECD, 2015). 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.