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Relationship: 2609

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,miRNA levels

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
Alcohol Induced DNA damage and mutations leading to Metastatic Breast Cancer adjacent Moderate Moderate Agnes Aggy (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 Do not cite Under Development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
Term Scientific Term Evidence Link
human and other cells in culture human and other cells in culture High NCBI
mice Mus sp. High NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Female High

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help
Term Evidence
Not Otherwise Specified Not Specified

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

Upstream event: increased, mutations

Downstream event: increased miRNA

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 Map 2.0

ID Experimental Design Species Upstream Observation Downstream Observation Citation (first author, year) Notes

Evidence Map

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help
Title First Author
Biological Plausibility
Dose Concordance
Temporal Concordance
Incidence Concordance
Biological Plausibility
Dose Concordance Evidence
Temporal Concordance Evidence
Incidence Concordance Evidence
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

In response to stressors like as ionising radiation, miRNAs are differently regulated. When exposed to IR, miRNA expression is frequently disrupted. Some miRNAs are induced by IR, while others are suppressed, a decision that is likely based on the target genes implicated. This figure summarises the miRNAs mentioned in this review whose expression changes in response to IR. Lists of miRNAs whose induction or repression has been detected are on the left and right, respectively. MiRNAs are in the middle, and both induction and repression have been found in many cell types. The centre contains the biggest group of miRNAs, demonstrating how diverse the miRNA profile can be from one cell type to the next. Bold miRNAs play a role in several parts of the DDR.

Induced miRNAs were reported by some studies (Cha et al.,2009;Chaudhary et al 201; Chaudhary et al 2012; Chaudhary et al 2013;Kwon et al.,2013;Mueller et al.,2013;Shin et al.,2009;Sokolov et al.,2012;Wagner et al.,2010),whereas repressed miRNAs are observed in some(Cha et al., 2009,Chaudhari et al.,2010).Both induction and repression of some miRNA were seen in different cell types and results are inconclusive (Cha et al.,2009;Chaudhary et al 201; Chaudhary et al 2012; Chaudhary et al 2013;Kwon et al.,2013;Mueller et al.,2013;Shin et al.,2009;Sokolov et al.,2012;Wagner et al.,2010; Kraemer et al., 2011; Moskwa et al.,2011;Niemoeller et al.,2011;Sokolov et al., 2012;Wagner et al.,2010).This inconsistency could be due to different doses of stressor.

DNA damage response influences miRNA expression, at the same time miRNA can also influence DDR, cell cycle etc.The miR-34 family produces a cell-cycle arrest in the G1 phase and slows cell-cycle progression by targeting multiple cell cycle regulators when ectopically produced, implying tumor-suppressing potential. The miR-34 family, for example, specifically targets and inhibits cyclin-dependent kinase 4 (CDK4), CDK6, E2F3, Myc, and NMYC (Chang  et al.,2007,He et al., 2007).

MiRNA expression can be influenced by DNA damage and mutation, but miRNA can also regulate DNA damage response and cell cycle.By suppressing the transcripts of numerous genes that govern cell-cycle checkpoints or metabolism, these p53-induced miRNAs contribute to cell-cycle arrest (Su et al.,2010;Georges et al.,2008;Hermeking et al.,2012;Klein et al., 2010; Liu et al.,2011; Suh et al.,2011). Wip1 phosphatase, a master inhibitor in the DDR that inhibits the activation and stability of p53, is targeted and repressed by miR-16 and miR-29, resulting in p53 induction (Ugalde et al.,2011; Zhang et al.,2010). Cellcycle arrest is induced by ectopic expression of miR-192/215, which targets a number of genes that regulate the G1/S and G2/M checkpoints (Bulavin et al.,2004).

The oncogene c-Myc is directly targeted by miR-145, implying that p53 suppresses cMyc activities through regulating miRNA expression (Sachdeva et al.,2009, Suh et al.,2011). p53-induced miRNAs, interestingly, influence p53 activity in a positive feedback loop (Han et al.,2012, Hermeking et al.,2012). SIRT1 acetylation and activation are increased when miR-34 inhibits it (Yamakuchi et al., 2008). Mdm2 expression is directly inhibited by miR-192, miR-194, miR-215, and MiR-605, while Wip1 is inhibited by miR-29, resulting in higher p53 levels and activity. (Braun et al.,2008, Pichiorri et al.,2010, Xiao et al., 2011).

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

miRNA expression profiles are influenced by a variety of DNA damaging stressors. Pothof et al. were the first to notice differences in miRNA expression in cell-cycle checkpoints and DNA repair in UV-treated cells (Pothof et al., 2009). Other DNA damaging agents, such as cisplatin, doxorubicin, IR, and NCS, were used to examine miRNA expression profiles in cells (Galluzzi et al., 2010, Saleh et al.,2011;Suzuki et al.,2009). Different levels of DNA damage appear to activate different groups of miRNAs, implying that miRNAs regulate the DDR through a mechanism that is dependent on the type and severity of the DNA damage.

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

Not specific through any particular life stage or gender.