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Relationship: 1896

Title

A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Increase, Mutations leads to Increase, Cell Proliferation (Epithelial Cells)

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). 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

AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Increased reactive oxygen and nitrogen species (RONS) leading to increased risk of breast cancer adjacent Moderate Not Specified Jessica Helm (send email) Under development: Not open for comment. Do not cite Under Development
Increased DNA damage leading to increased risk of breast cancer adjacent Moderate Not Specified 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 Do not cite Under Development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 KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER.  More help

Sex Applicability

An indication of the the relevant sex for this KER. More help

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

Mutations altering gene expression or protein activity can enable cells to escape growth inhibition by increasing resistance to apoptosis, or other inhibitory signals, or by escape of cell cycle checkpoints. Alternatively, mutations can stimulate growth by activating proliferative pathways such as EGFR.

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER.  For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings.  Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

Biological plausibility is High. Multiple mechanisms limit the proliferation of cells in healthy biological systems. Mutations in many of the genes controlling these mechanisms promote proliferation.

Empirical support is Moderate. Mutations that promote proliferation are frequently found in cancers, and both mutation and proliferation occur in response to tumorigenic stressors like ionizing radiation. Mutations appear over the same time frame or prior to the appearance of proliferation. Multiple uncertainties and conflicting evidence weaken this key event relationship. The two key events differ in their dose response- mutation but not proliferation increases with ionizing radiation dose. Furthermore, a single mutation is not necessarily sufficient to increase proliferation- proliferation typically requires multiple mutations or a change in the surrounding environment. In mammary tissue, stromal state – which is modified by hormones - strongly influences the proliferative nature of epithelial cells, and mutated epithelial cells alone appear to be insufficient for tumor growth.

Biological Plausibility
Addresses the biological rationale for a connection between KEupstream and KEdownstream.  This field 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.   More help

High. Multiple mechanisms limit the proliferation of cells in healthy biological systems. Mutations in many of the genes controlling these mechanisms promote proliferation. Biological mechanisms such as contact inhibition, apoptosis, cell cycle checkpoints, and growth factor availability act to restrain proliferation (Sonnenschein and Soto 1999). Under conditions of proliferation such as ductal branching during development of the mammary gland, selected mechanisms are engaged to permit controlled or directed proliferation. In the case of ductal branching, stromal cells respond to estrogen and growth hormone by releasing IGF1, which activates IGF-1R in epithelial cells to promote survival and proliferation (Hinck and Silberstein 2005; Sternlicht, Sunnarborg et al. 2005; Sternlicht 2006). At puberty, epithelial cells respond to estrogen by signaling to the stroma via EGFR to which the stroma replies with proliferative signals via FGFR (Sternlicht, Sunnarborg et al. 2005; Sternlicht 2006). Multiple additional mechanisms of control include proliferation inhibition by TGF-β, which can both directly inhibit proliferation (Francis, Bergsied et al. 2009) and act through stromal cells to stabilize an inhibitory extracellular matrix (Hinck and Silberstein 2005). When mechanisms controlling proliferation are altered, proliferation can occur outside of the normal biological context (Radice, Ferreira-Cornwell et al. 1997; Davies, Platt-Higgins et al. 1999; Ewan, Shyamala et al. 2002; Lanigan, O'Connor et al. 2007; Croce 2008; de Ostrovich, Lambertz et al. 2008).

Uncertainties and Inconsistencies
Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

Mutations are clearly not the only events driving proliferation in mammary gland, particularly in female mammary glands after exposure to a stressor like ionizing radiation where proliferation varies with age and microenvironment (Tang, Fernandez-Garcia et al. 2014). In mammary tissue, stromal state strongly influences the proliferative and metastatic nature of epithelial cells, and mutated epithelial cells alone appear to be insufficient for tumor growth.  Stroma exposed to carcinogens can make transplanted unexposed epithelial cells tumorigenic in rats (Maffini, Soto et al. 2004) and transplanted p53 mutant epithelial cells tumorigenic in BALB/c mice (Barcellos-Hoff and Ravani 2000), while neither epithelia exposed to carcinogens nor p53 mutant cells are tumorigenic when transplanted into unexposed animals (Barcellos-Hoff and Ravani 2000; Maffini, Soto et al. 2004). Similarly, post-lactational stroma can make tumor cells more invasive and metastatic than nulliparous stroma (McDaniel, Rumer et al. 2006), and younger and nulliparous stroma makes tumor cells proliferate more than older and multiparous stroma (Maffini, Calabro et al. 2005). Even proliferating tissue and tumors can regress (Haslam and Bern 1977; Purnell 1980), suggesting that proliferation is insufficient for carcinogenesis in some cases.

While mutations increase linearly in response to ionizing radiation or carcinogens, proliferation (or proliferation of stem cell populations) apparently does not (Beuving, Bern et al. 1967; Mukhopadhyay, Costes et al. 2010; Nguyen, Oketch-Rabah et al. 2011; Tang, Fernandez-Garcia et al. 2014). Because we expect only a subset of mutations to affect cell-cycle or proliferation-related genes and because most cells require multiple mutations for proliferation to commence, only a very small number of cells would be expected to proliferate in response to mutation. It is therefore possible that the proliferation typically observed is actually due to a separate mechanism such as the self-renewal of stem-like or senescent-resistant cells and that a delayed mutation-based proliferation is not being measured.

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references.  More help
Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.  More help
Time-scale
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?). More help
Known Feedforward/Feedback loops influencing this KER
Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Proliferation increases the likelihood that existing DNA damage will result in mutation and creates new mutations through errors in replication.

It is generally accepted that proliferation increases the risk of mutation and cancer (Preston-Martin, Pike et al. 1990). DNA damage that has not been completely or correctly repaired when a cell undergoes mitosis can be fixed in the genome permanently as a mutation, to be propagated to future daughter cells. Incomplete DNA repair can also cause additional DNA damage when encountered by replicative forks. Therefore, in the presence of any DNA damage (and there is a background rate of damage in addition to any other genotoxic stimuli) mutations will increase with cell division (Kiraly, Gong et al. 2015). Mutation-prone double strand breaks can also arise from replicative stress in hyperplastic cells including hyperplasia arising from excess growth factor stimulation (Gorgoulis, Vassiliou et al. 2005). This relationship between proliferation and mutation is thought to drive a significant portion of the risk of cancer from estrogen exposure since breast cells proliferate in response to estrogen or estrogen plus progesterone and risk increases with cumulative estrogen exposure (Preston-Martin, Pike et al. 1990).

Not all proliferating tissue shows replicative stress and DSBs - tissue with a naturally high proliferative index like colon cells don’t show any sign of damage (Halazonetis, Gorgoulis et al. 2008). Additional factors are therefore required beyond replication for damage and mutation from replicative stress, but replication is essential for the expression of these factors.

Gorgoulis, V. G., L. V. Vassiliou, et al. (2005). "Activation of the DNA damage checkpoint and genomic instability in human precancerous lesions." Nature 434(7035): 907-913.

Halazonetis, T. D., V. G. Gorgoulis, et al. (2008). "An oncogene-induced DNA damage model for cancer development." Science 319(5868): 1352-1355.

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

Preston-Martin, S., M. C. Pike, et al. (1990). "Increased cell division as a cause of human cancer." Cancer Res 50(23): 7415-7421.

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

References

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

Alexandrov, L. B., S. Nik-Zainal, et al. (2013). "Signatures of mutational processes in human cancer." Nature 500(7463): 415-421.

Ameziane-El-Hassani, R., M. Boufraqech, et al. (2010). "Role of H2O2 in RET/PTC1 chromosomal rearrangement produced by ionizing radiation in human thyroid cells." Cancer Res 70(10): 4123-4132.

Barcellos-Hoff, M. H. and S. A. Ravani (2000). "Irradiated mammary gland stroma promotes the expression of tumorigenic potential by unirradiated epithelial cells." Cancer Res 60(5): 1254-1260.

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.

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

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.

Davies, B. R., A. M. Platt-Higgins, et al. (1999). "Development of hyperplasias, preneoplasias, and mammary tumors in MMTV-c-erbB-2 and MMTV-TGFalpha transgenic rats." The American journal of pathology 155(1): 303-314.

Davies, H., D. Glodzik, et al. (2017). "HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures." Nat Med 23(4): 517-525.

de Ostrovich, K. K., I. Lambertz, et al. (2008). "Paracrine overexpression of insulin-like growth factor-1 enhances mammary tumorigenesis in vivo." The American journal of pathology 173(3): 824-834.

Ewan, K. B., G. Shyamala, et al. (2002). "Latent transforming growth factor-beta activation in mammary gland: regulation by ovarian hormones affects ductal and alveolar proliferation." Am J Pathol 160(6): 2081-2093.

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.

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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.

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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.

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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.

Lanigan, F., D. O'Connor, et al. (2007). "Molecular links between mammary gland development and breast cancer." Cellular and molecular life sciences : CMLS 64(24): 3159-3184.

Liang, L., L. Deng, et al. (2007). "X-rays induce distinct patterns of somatic mutation in fetal versus adult hematopoietic cells." DNA repair 6(9): 1380-1385.

Maffini, M. V., J. M. Calabro, et al. (2005). "Stromal regulation of neoplastic development: age-dependent normalization of neoplastic mammary cells by mammary stroma." Am J Pathol 167(5): 1405-1410.

Maffini, M. V., A. M. Soto, et al. (2004). "The stroma as a crucial target in rat mammary gland carcinogenesis." J Cell Sci 117(Pt 8): 1495-1502.

McDaniel, S. M., K. K. Rumer, et al. (2006). "Remodeling of the mammary microenvironment after lactation promotes breast tumor cell metastasis." Am J Pathol 168(2): 608-620.

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