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Relationship: 1985

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, Chromosomal aberrations leads to Increase, lung cancer

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
Deposition of energy leading to lung cancer non-adjacent Moderate Moderate Brendan Ferreri-Hanberry (send email) Open for citation & comment EAGMST Approved

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 Homo sapiens High NCBI
rat Rattus norvegicus High NCBI
mouse Mus musculus High NCBI

Sex Applicability

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

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help
Term Evidence
All life stages High

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

Chromosomal aberrations (CAs) are described as irregularities in chromosome structure due to segments of the chromosome that have been lost, gained, or rearranged. This can lead to two categories of chromosomal exchanges: balanced, which do not impact the overall frame of chromosome structure, and unbalanced, which refers to CAs that do alter the frame of chromosome structure (Genetic Alliance 2010) . Specific categories of CAs include chromosome-type aberrations (CSAs) such as chromosome-type breaks, ring chromosomes, marker chromosomes, and dicentric aberrations; chromatid-type aberrations (CTAs) such as chromatid breaks and chromatid exchanges (Hagmar et al. 2004; Bonassi et al. 2008); micronuclei (MN); nucleoplasmic bridges (NPBs); and copy number variants (CNVs). When CAs affect genes related to tumourigenesis or their regulatory regions (Shlien and Malkin 2009; Liu et al. 2013), this may lead to an abnormal accumulation of malignant cells and ultimately may result in cancer. Lung cancer in particular may occur if these tumourigenesis-related CAs (which are more often unbalanced than balanced in lung cancer (Mitelman et al. 1997) occur in cells of the lung. 

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

Uncertainties and inconsistencies in this KER are as follows:

  1. CNVs are often difficult to detect in cancer cells, even with current advances in next generation sequencing. This is due to the sheer number of CNVs that could possibly be present within one tumour; the unknown ratio of cancer cells and healthy cells within a tumour sample; the unknown ploidy of tumours; and the possible presence of multiple clones in one tumour, including possible low-number subclones that may be difficult to detect (Liu et al. 2013).  
  2. In some studies, smoking does not affect the CA-cancer relationship (Bonassi et al. 2000; Bonassi et al. 2008; El-zein et al. 2014; Vodenkova et al. 2015; El-zein et al. 2017), but it does have a significant effect in other studies (Paik et al. 2012; Lloyd et al. 2013; Minina et al. 2017).
  3. In a study examining MN in lung fibroblasts isolated from Wistar rats and Syrian hamsters exposed to radon, Syrian hamsters were found to have a significantly increased rate of MN per 1000 bincleated cells per Gy relative to rats. According to the literature however, Wistar rats have a higher documented sensitivity to radon-induced lung cancer than Syrian hamsters (Khan et al. 1995).

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

Some studies have documented modulating factors that affect CAs in lung cancer, including age, ethnicity (Lloyd et al. 2013), smoking (Feder et al. 1998; Paik et al. 2012; Lloyd et al. 2013; Minina et al. 2017), sex (Feder et al. 1998), and genotype (Kim et al. 2012; Minina et al. 2017). In NSCLC patients, ALK and EML4 rearrangements have reportedly been influenced by confounding variables such as age (Shaw et al. 2009; Wong et al. 2009; Sasaki et al. 2010), sex (Shaw et al. 2009), and smoking history (Koivunen et al. 2008; Shaw et al. 2009; Wong et al. 2009; Sasaki et al. 2010).

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

The domain of applicability applies to mammals such as mice, rats, hamsters and humans.