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Relationship: 1908

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

Increased pro-inflammatory mediators leads to Increase, Cell Proliferation (Epithelial Cells)

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Increased pro-inflammatory mediators

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

Increase, Cell Proliferation (Epithelial Cells)

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 Do not cite	Under Development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 Do not cite	Under Development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

Pro-inflammatory factors increase proliferation.

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. Inflammation is generally understood to lead to proliferation during recovery from inflammation.

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

Biological Plausibility is High. Inflammation is generally understood to lead to proliferation during recovery from inflammation. Major inflammation-related transcription factors NF-kB, AP1, and STAT3 mediate proliferation and survival (Grivennikov, Greten et al. 2010). Inflammation enhances compensatory proliferation during wound healing including following inflammation-associated cell killing (Landen, Li et al. 2016), and contributes to proliferation via growth enhancing signals including changes to the microenvironment and promotion of stem-like characteristics (Grivennikov, Greten et al. 2010; Hanahan and Weinberg 2011; Kiraly, Gong et al. 2015). These effects can vary between tissues and in different contexts in ways that are not well understood (Grivennikov, Greten et al. 2010). In mammary gland and in mammary epithelial cells, inflammation-related transcription factor NF-kB and multiple cytokines promote proliferation and tumorigenesis (Connelly, Barham et al. 2011; Esquivel-Velazquez, Ostoa-Saloma et al. 2015).

Empirical Evidence

Provides specific (citable) evidence that supports the idea of a change in the upstream KE (KEupstream) leading to, or being associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient. More help

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

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

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. 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

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

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.

Esquivel-Velazquez, M., P. Ostoa-Saloma, et al. (2015). "The role of cytokines in breast cancer development and progression." J Interferon Cytokine Res 35(1): 1-16.

Grivennikov, S. I., F. R. Greten, et al. (2010). "Immunity, inflammation, and cancer." Cell 140(6): 883-899.

Hanahan, D. and R. A. Weinberg (2011). "Hallmarks of cancer: the next generation." Cell 144(5): 646-674.

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

Landen, N. X., D. Li, et al. (2016). "Transition from inflammation to proliferation: a critical step during wound healing." Cellular and molecular life sciences : CMLS 73(20): 3861-3885.