Aop: 41

Title

Each AOP should be given a descriptive title that takes the form “MIE leading to AO”. For example, “Aromatase inhibition [MIE] leading to reproductive dysfunction [AO]” or “Thyroperoxidase inhibition [MIE] leading to decreased cognitive function [AO]”. In cases where the MIE is unknown or undefined, the earliest known KE in the chain (i.e., furthest upstream) should be used in lieu of the MIE and it should be made clear that the stated event is a KE and not the MIE. More help

Sustained AhR Activation leading to Rodent Liver Tumours

Short name
A short name should also be provided that succinctly summarises the information from the title. This name should not exceed 90 characters. More help
Sustained AhR Activation leading to Rodent Liver Tumours

Graphical Representation

A graphical summary of the AOP listing all the KEs in sequence, including the MIE (if known) and AO, and the pair-wise relationships (links or KERs) between those KEs should be provided. This is easily achieved using the standard box and arrow AOP diagram (see this page for example). The graphical summary is prepared and uploaded by the user (templates are available) and is often included as part of the proposal when AOP development projects are submitted to the OECD AOP Development Workplan. The graphical representation or AOP diagram provides a useful and concise overview of the KEs that are included in the AOP, and the sequence in which they are linked together. This can aid both the process of development, as well as review and use of the AOP (for more information please see page 19 of the Users' Handbook).If you already have a graphical representation of your AOP in electronic format, simple save it in a standard image format (e.g. jpeg, png) then click ‘Choose File’ under the “Graphical Representation” heading, which is part of the Summary of the AOP section, to select the file that you have just edited. Files must be in jpeg, jpg, gif, png, or bmp format. Click ‘Upload’ to upload the file. You should see the AOP page with the image displayed under the “Graphical Representation” heading. To remove a graphical representation file, click 'Remove' and then click 'OK.'  Your graphic should no longer be displayed on the AOP page. If you do not have a graphical representation of your AOP in electronic format, a template is available to assist you.  Under “Summary of the AOP”, under the “Graphical Representation” heading click on the link “Click to download template for graphical representation.” A Powerpoint template file should download via the default download mechanism for your browser. Click to open this file; it contains a Powerpoint template for an AOP diagram and instructions for editing and saving the diagram. Be sure to save the diagram as jpeg, jpg, gif, png, or bmp format. Once the diagram is edited to its final state, upload the image file as described above. More help

Authors

List the name and affiliation information of the individual(s)/organisation(s) that created/developed the AOP. In the context of the OECD AOP Development Workplan, this would typically be the individuals and organisation that submitted an AOP development proposal to the EAGMST. Significant contributors to the AOP should also be listed. A corresponding author with contact information may be provided here. This author does not need an account on the AOP-KB and can be distinct from the point of contact below. The list of authors will be included in any snapshot made from an AOP. More help

Richard A Becker, American Chemical Council (ACC) on behalf of the Business Industry Advisory Committee (BIAC) email:Rick_Becker@americanchemistry.com Contributing authors to the development of this AOP are: Ted Simon (Ted Simon LLC), Robert Budinsky, (The Dow Chemical Company), Grace Patlewicz, (DuPont), Craig Rowlands, (The Dow Chemical Company).

Point of Contact

Indicate the point of contact for the AOP-KB entry itself. This person is responsible for managing the AOP entry in the AOP-KB and controls write access to the page by defining the contributors as described below. Clicking on the name will allow any wiki user to correspond with the point of contact via the email address associated with their user profile in the AOP-KB. This person can be the same as the corresponding author listed in the authors section but isn’t required to be. In cases where the individuals are different, the corresponding author would be the appropriate person to contact for scientific issues whereas the point of contact would be the appropriate person to contact about technical issues with the AOP-KB entry itself. Corresponding authors and the point of contact are encouraged to monitor comments on their AOPs and develop or coordinate responses as appropriate.  More help
Rick Becker   (email point of contact)

Contributors

List user names of all  authors contributing to or revising pages in the AOP-KB that are linked to the AOP description. This information is mainly used to control write access to the AOP page and is controlled by the Point of Contact.  More help
  • Rick Becker

Status

The status section is used to provide AOP-KB users with information concerning how actively the AOP page is being developed, what type of use or input the authors feel comfortable with given the current level of development, and whether it is part of the OECD AOP Development Workplan and has been reviewed and/or endorsed. “Author Status” is an author defined field that is designated by selecting one of several options from a drop-down menu (Table 3). The “Author Status” field should be changed by the point of contact, as appropriate, as AOP development proceeds. See page 22 of the User Handbook for definitions of selection options. More help
Author status OECD status OECD project SAAOP status
Open for citation & comment EAGMST Under Review 1.7 Included in OECD Work Plan
This AOP was last modified on December 02, 2016 11:59
The date the AOP was last modified is automatically tracked by the AOP-KB. The date modified field can be used to evaluate how actively the page is under development and how recently the version within the AOP-Wiki has been updated compared to any snapshots that were generated. More help

Revision dates for related pages

Page Revision Date/Time
N/A, Hepatotoxicity, Hepatopathy, including a constellation of observable effects November 29, 2016 18:59
Activation, Long term AHR receptor driven direct and indirect gene expression changes December 02, 2016 11:22
Changes/Inhibition, Cellular Homeostasis and Apoptosis September 16, 2017 10:15
Alterations, Cellular proliferation / hyperplasia September 16, 2017 10:15
Formation, Hepatocellular and Bile duct tumors September 16, 2017 10:15
Activation, Long term AHR receptor driven direct and indirect gene expression changes leads to Changes/Inhibition, Cellular Homeostasis and Apoptosis November 29, 2016 20:41
Activation, Long term AHR receptor driven direct and indirect gene expression changes leads to N/A, Hepatotoxicity, Hepatopathy, including a constellation of observable effects November 29, 2016 19:58
Activation, Long term AHR receptor driven direct and indirect gene expression changes leads to Alterations, Cellular proliferation / hyperplasia November 29, 2016 20:41
Activation, Long term AHR receptor driven direct and indirect gene expression changes leads to Formation, Hepatocellular and Bile duct tumors November 29, 2016 20:41
Changes/Inhibition, Cellular Homeostasis and Apoptosis leads to N/A, Hepatotoxicity, Hepatopathy, including a constellation of observable effects December 02, 2016 11:47
N/A, Hepatotoxicity, Hepatopathy, including a constellation of observable effects leads to Alterations, Cellular proliferation / hyperplasia December 02, 2016 11:49
Alterations, Cellular proliferation / hyperplasia leads to Formation, Hepatocellular and Bile duct tumors December 02, 2016 11:49

Abstract

In the abstract section, authors should provide a concise and informative summation of the AOP under development that can stand-alone from the AOP page. Abstracts should typically be 200-400 words in length (similar to an abstract for a journal article). Suggested content for the abstract includes the following: The background/purpose for initiation of the AOP’s development (if there was a specific intent) A brief description of the MIE, AO, and/or major KEs that define the pathway A short summation of the overall WoE supporting the AOP and identification of major knowledge gaps (if any) If a brief statement about how the AOP may be applied (optional). The aim is to capture the highlights of the AOP and its potential scientific and regulatory relevance More help

An Adverse Outcome Pathway (AOP) represents the existing knowledge of a biological pathway leading from initial molecular interactions of a toxicant and progressing through a series of key events (KEs), culminating with an apical adverse outcome (AO) that has to be of regulatory relevance. An AOP based on the mode of action (MOA) of rodent liver tumor promotion by dioxin-like compounds (DLCs) has been developed and the weight of evidence (WoE) of key event relationships (KERs) evaluated using evolved Bradford Hill considerations. Dioxins and DLCs are potent aryl hydrocarbon receptor (AHR) ligands that cause a range of species-specific adverse outcomes. The occurrence of KEs is necessary for inducing downstream biological responses and KEs may occur at the molecular, cellular, tissue and organ levels. The common convention is that an AOP begins with the toxicant interaction with a biological response element; for this AOP, this initial event is binding of a DLC ligand to the AHR. Data from mechanistic studies, lifetime bioassays and approximately thirty initiation-promotion studies have established a number of substances, including dioxin-like chemicals and indole-3-carbinol from brassica vegetables, as rat liver tumor promoters. Such studies clearly show that sustained AHR activation, weeks or months in duration, is necessary to induce rodent liver tumor promotion; hence, sustained AHR activation is deemed the molecular initiating event (MIE). After this MIE, subsequent KEs are 1) changes in cellular growth homeostasis likely associated with expression changes in a number of genes and observed as development of hepatic foci and decreases in apoptosis within foci; 2) extensive liver toxicity observed as the constellation of effects called toxic hepatopathy; 3) cellular proliferation and hyperplasia in several hepatic cell types. This progression of KEs culminates in the AO, the development of hepatocellular adenomas and carcinomas and cholangiolar carcinomas. A rich data set provides both qualitative and quantitative knowledge of the progression of this AOP through KEs and the KERs. Thus, the WoE for this AOP is judged to be strong. Species-specific effects of dioxins and DLCs are well known -- humans are less responsive than rodents and rodent species differ in sensitivity between strains. Consequently, application of this AOP to evaluate potential human health risks must take these differences into account.

Please also see Becker, R.A., Patlewicz, G., Simon, T.W., Rowlands, J.C., Budinsky, R.A. 2015. The adverse outcome pathway for rodent liver tumor promotion by sustained activation of the aryl hydrocarbon receptor. Regul. Toxicol. Pharmacol. 73, 172-190: PMID: 26145830. The file is open access.

Background (optional)

This optional subsection should be used to provide background information for AOP reviewers and users that is considered helpful in understanding the biology underlying the AOP and the motivation for its development. The background should NOT provide an overview of the AOP, its KEs or KERs, which are captured in more detail below. Examples of potential uses of the optional background section are listed on pages 24-25 of the User Handbook. More help

Summary of the AOP

This section is for information that describes the overall AOP. The information described in section 1 is entered on the upper portion of an AOP page within the AOP-Wiki. This is where some background information may be provided, the structure of the AOP is described, and the KEs and KERs are listed. More help

Events:

Molecular Initiating Events (MIE)
An MIE is a specialised KE that represents the beginning (point of interaction between a stressor and the biological system) of an AOP. More help
Key Events (KE)
This table summarises all of the KEs of the AOP. This table is populated in the AOP-Wiki as KEs are added to the AOP. Each table entry acts as a link to the individual KE description page.  More help
Adverse Outcomes (AO)
An AO is a specialised KE that represents the end (an adverse outcome of regulatory significance) of an AOP.  More help
Sequence Type Event ID Title Short name
1 MIE 165 Activation, Long term AHR receptor driven direct and indirect gene expression changes Activation, Long term AHR receptor driven direct and indirect gene expression changes
2 KE 139 N/A, Hepatotoxicity, Hepatopathy, including a constellation of observable effects N/A, Hepatotoxicity, Hepatopathy, including a constellation of observable effects
3 KE 853 Changes/Inhibition, Cellular Homeostasis and Apoptosis Changes/Inhibition, Cellular Homeostasis and Apoptosis
4 KE 854 Alterations, Cellular proliferation / hyperplasia Alterations, Cellular proliferation / hyperplasia
5 AO 856 Formation, Hepatocellular and Bile duct tumors Formation, Hepatocellular and Bile duct tumors

Relationships Between Two Key Events (Including MIEs and AOs)

This table summarises all of the KERs of the AOP and is populated in the AOP-Wiki as KERs are added to the AOP. Each table entry acts as a link to the individual KER description page.To add a key event relationship click on either Add relationship: events adjacent in sequence or Add relationship: events non-adjacent in sequence.For example, if the intended sequence of KEs for the AOP is [KE1 > KE2 > KE3 > KE4]; relationships between KE1 and KE2; KE2 and KE3; and KE3 and KE4 would be defined using the add relationship: events adjacent in sequence button.  Relationships between KE1 and KE3; KE2 and KE4; or KE1 and KE4, for example, should be created using the add relationship: events non-adjacent button. This helps to both organize the table with regard to which KERs define the main sequence of KEs and those that provide additional supporting evidence and aids computational analysis of AOP networks, where non-adjacent KERs can result in artifacts (see Villeneuve et al. 2018; DOI: 10.1002/etc.4124).After clicking either option, the user will be brought to a new page entitled ‘Add Relationship to AOP.’ To create a new relationship, select an upstream event and a downstream event from the drop down menus. The KER will automatically be designated as either adjacent or non-adjacent depending on the button selected. The fields “Evidence” and “Quantitative understanding” can be selected from the drop-down options at the time of creation of the relationship, or can be added later. See the Users Handbook, page 52 (Assess Evidence Supporting All KERs for guiding questions, etc.).  Click ‘Create [adjacent/non-adjacent] relationship.’  The new relationship should be listed on the AOP page under the heading “Relationships Between Two Key Events (Including MIEs and AOs)”. To edit a key event relationship, click ‘Edit’ next to the name of the relationship you wish to edit. The user will be directed to an Editing Relationship page where they can edit the Evidence, and Quantitative Understanding fields using the drop down menus. Once finished editing, click ‘Update [adjacent/non-adjacent] relationship’ to update these fields and return to the AOP page.To remove a key event relationship to an AOP page, under Summary of the AOP, next to “Relationships Between Two Key Events (Including MIEs and AOs)” click ‘Remove’ The relationship should no longer be listed on the AOP page under the heading “Relationships Between Two Key Events (Including MIEs and AOs)”. More help

Network View

The stressor field is a structured data field that can be used to annotate an AOP with standardised terms identifying stressors known to trigger the MIE/AOP. Most often these are chemical names selected from established chemical ontologies. However, depending on the information available, this could also refer to chemical categories (i.e., groups of chemicals with defined structural features known to trigger the MIE). It can also include non-chemical stressors such as genetic or environmental factors. Although AOPs themselves are not chemical or stressor-specific, linking to stressor terms known to be relevant to different AOPs can aid users in searching for AOPs that may be relevant to a given stressor. More help

Stressors

The stressor field is a structured data field that can be used to annotate an AOP with standardised terms identifying stressors known to trigger the MIE/AOP. Most often these are chemical names selected from established chemical ontologies. However, depending on the information available, this could also refer to chemical categories (i.e., groups of chemicals with defined structural features known to trigger the MIE). It can also include non-chemical stressors such as genetic or environmental factors. Although AOPs themselves are not chemical or stressor-specific, linking to stressor terms known to be relevant to different AOPs can aid users in searching for AOPs that may be relevant to a given stressor. More help

Life Stage Applicability

Identify the life stage for which the KE is known to be applicable. More help

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) can be selected. 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
Rattus sp. ABTC 42503 Rattus sp. ABTC 42503 High NCBI
Mus sp. 2000082 Mus sp. 2000082 High NCBI

Sex Applicability

The authors must select from one of the following: Male, female, mixed, asexual, third gender, hermaphrodite, or unspecific. More help

Overall Assessment of the AOP

This section addresses the relevant biological domain of applicability (i.e., in terms of taxa, sex, life stage, etc.) and WoE for the overall AOP as a basis to consider appropriate regulatory application (e.g., priority setting, testing strategies or risk assessment). The goal of the overall assessment is to provide a high level synthesis and overview of the relative confidence in the AOP and where the significant gaps or weaknesses are (if they exist). Users or readers can drill down into the finer details captured in the KE and KER descriptions, and/or associated summary tables, as appropriate to their needs.Assessment of the AOP is organised into a number of steps. Guidance on pages 59-62 of the User Handbook is available to facilitate assignment of categories of high, moderate, or low confidence for each consideration. While it is not necessary to repeat lengthy text that appears elsewhere in the AOP description (or related KE and KER descriptions), a brief explanation or rationale for the selection of high, moderate, or low confidence should be made. More help

The Bradford Hill considerations, which is an approach consistent with the U.S. Environmental Protection Agency’s Guidelines for Carcinogen Risk Assessment available from: http://www.epa.gov/raf/publications/pdfs/CANCER_GUIDELINES_FINAL_3-25-05.PDF as well as the WHO/IPCS’s human relevance-mode-of-action framework provides the framework for putting the proposed AOP into a weight-of-evidence evaluation. These considerations include dose-response, temporality, strength, consistency, specificity and biological plausibility of the proposed association (the AOP in this case). Alternative AOP propositions must be accounted for and either ruled in or out as part of applying the Bradford Hill considerations. To finalise the Bradford Hill assessment, the AOP template requires an examination of the uncertainties, inconsistencies, data gaps, and the quantitative nature of the KE (as well as the AE and ModFs).

The Bradford Hill (BH) considerations (dose-response, temporality, strength, consistency, specificity and biological plausibility of the proposed association) form the basis for evaluating weight of evidence within the U.S. Environmental Protection Agency's Guidelines for Carcinogen Risk Assessment, the WHO/IPCS human relevance-MOA framework, the key events/dose-response frame- work (KEDRF) (Dellarco and Fenner-Crisp, 2012; Fenner-Crisp, 2012; Julien et al., 2009; Meek et al., 2003; Meek, 2008; OECD, 2013; USEPA, 2005). The BH considerations have recently been updated and additionally tailored for AOPs by the OECD to facilitate evaluations of KEs and KERs as well as the overall AOP (Meek et al., 2013, 2014a, 2014b; OECD, 2014; Becker et al., 2015).

In the tables below, we summarize the weight of evidence evaluation conducted using these AOP-tailored BH considerations of biological plausibility, essentiality and empirical evidence for the sustained AHR activation rodent liver tumor promotion AOP.

Domain of Applicability

The relevant biological domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context are defined in this section. Biological domain of applicability is informed by the “Description” and “Biological Domain of Applicability” sections of each KE and KER description (see sections 2G and 3E for details). In essence the taxa/life-stage/sex applicability is defined based on the groups of organisms for which the measurements represented by the KEs can feasibly be measured and the functional and regulatory relationships represented by the KERs are operative.The relevant biological domain of applicability of the AOP as a whole will nearly always be defined based on the most narrowly restricted of its KEs and KERs. For example, if most of the KEs apply to either sex, but one is relevant to females only, the biological domain of applicability of the AOP as a whole would be limited to females. While much of the detail defining the domain of applicability may be found in the individual KE and KER descriptions, the rationale for defining the relevant biological domain of applicability of the overall AOP should be briefly summarised on the AOP page. More help

Essentiality of the Key Events

An important aspect of assessing an AOP is evaluating the essentiality of its KEs. The essentiality of KEs can only be assessed relative to the impact of manipulation of a given KE (e.g., experimentally blocking or exacerbating the event) on the downstream sequence of KEs defined for the AOP. Consequently evidence supporting essentiality is assembled on the AOP page, rather than on the independent KE pages that are meant to stand-alone as modular units without reference to other KEs in the sequence.The nature of experimental evidence that is relevant to assessing essentiality relates to the impact on downstream KEs and the AO if upstream KEs are prevented or modified. This includes: Direct evidence: directly measured experimental support that blocking or preventing a KE prevents or impacts downstream KEs in the pathway in the expected fashion. Indirect evidence: evidence that modulation or attenuation in the magnitude of impact on a specific KE (increased effect or decreased effect) is associated with corresponding changes (increases or decreases) in the magnitude or frequency of one or more downstream KEs.When assembling the support for essentiality of the KEs, authors should organise relevant data in a tabular format. The objective is to summarise briefly the nature and numbers of investigations in which the essentiality of KEs has been experimentally explored either directly or indirectly. See pages 50-51 in the User Handbook for further definitions and clarifications.  More help

The defining question contained in the OECD AOP guidance (OECD, 2014) for evaluation of essentiality is “are downstream KEs and/or the AO prevented if an upstream KE is blocked?” Overall, the evidence in support of essentiality for sustained AHR activation, the MIE, is strong. There is direct evidence of essentiality from the stop- exposure group in the cancer bioassay; the 100 ng/kg/d dose of TCDD was stopped after 30 weeks and at the 2-year termination, no statistically significant increase in tumor frequency was observed (NTP, 2006a; NTP, 2006b; NTP, 2006c). This observation also in- dicates that the MIE of sustained AHR activation requires more than 30 weeks of continuous exposure and is consistent with the general onset of hepatopathy around the same time (Hailey et al., 2005). Additional support for essentiality comes from studies that show that KEs fail to occur when AHR activity is lost through mutation, polymorphism or knockdown (Gasiewicz et al., 2008). Further- more, the loss of AHR responsivity to ligand-activation has been confirmed in reduction and/or loss of ligand-mediated gene tran- scription and resistance to TCDD-induced toxicity (Harrill et al., 2013). Conversely, constitutive AHR activity in mice increased the incidence of tumors and hepatotoxicity (Andersson et al., 2002; Brunnberg et al., 2006; Chopra and Schrenk, 2011; Moennikes et al., 2004).

Support for Essentiality of KEs Defining Question High (Strong) Moderate Weak
  Are downstream key events and/or the AO prevented if an upstream key event is blocked? [e.g., stop/reversibility studies, antagonism, knock out models, etc.) Multiple lines of experimental evidence illustrating essentiality for several of the key events There is at least one line of experimental evidence indicating essentiality of an important key event Indirect or no experimental evidence of the essentiality of any of the key events
Pre-MIE: Binding of ligands to the AHR Essentiality of the pre-MIE is Strong.

Rationale: Binding to the AHR is a necessary element and downstream KEs do not occur in knock-out animals.

MIE: Sustained AHR Activation Essentiality of the MIE is Strong.

Rationale: Extensive qualitative and quantitative information showing that downstream KEs occur in with increasing time and extent of continued AHR activation

KE#1: Changes in Cellular Homeostasis and Inhibition of Apoptosis Essentiality of the KE1 is Strong

Rationale: Growth of Altered hepatic foci has been explored in many initiation-promotion studies

KE#2: Hepatoxicity, Hepatopathy Essentiality of the KE2 is Strong

Rationale: The regenerative nature of the liver is such that the extensive hepatopathy induced by sustained AHR activation leads to a highly proliferative environment in the liver.

KE#3: Alterations in Cellular Proliferation/Hyperplasia Essentiality of the KE3 is Strong

Rationale: Hyperplasia has been strongly linked to the induction of cancer in many systems.

 

Evidence Assessment

The biological plausibility, empirical support, and quantitative understanding from each KER in an AOP are assessed together.  Biological plausibility of each of the KERs in the AOP is the most influential consideration in assessing WoE or degree of confidence in an overall hypothesised AOP for potential regulatory application (Meek et al., 2014; 2014a). Empirical support entails consideration of experimental data in terms of the associations between KEs – namely dose-response concordance and temporal relationships between and across multiple KEs. It is examined most often in studies of dose-response/incidence and temporal relationships for stressors that impact the pathway. While less influential than biological plausibility of the KERs and essentiality of the KEs, empirical support can increase confidence in the relationships included in an AOP. For clarification on how to rate the given empirical support for a KER, as well as examples, see pages 53- 55 of the User Handbook.  More help

This section provides brief descriptions of the essentiality of each of the KEs and the biological plausibility, empirical support and any uncertainties or inconsistencies in the key event relationships (KERs). These descriptions are consistent with the table presented in the AOP User’s Guide from OECD. Whilst the overall confidence in the AOP as a result of these evaluations is high, the challenge is to apply this knowledge for a regulatory purpose. An additional section is included below on the Application of the AOP. This provides a discussion of the possible regulatory uses of this AOP.

Empirical Evidence

The OECD AOP guidance (OECD, 2014) for evaluation of empirical evidence focuses on dose-response, temporality and incidence concordance. Defining questions include: “Does the empirical evidence support that a change in KEup leads to an appropriate change in KEdown? Does KEup occur at lower doses and earlier time points than KEdown and is the incidence of KEup > than that for KEdown?” Highly consistent dose-response relationships (KERs) along the sequence of KEs in this AOP exhibit dose- and time-concordance. This consistency in the concordance of both temporality and incidence supports a weight of evidence determination of high for the empirical evidence underpinning this AOP.

When the KEs and associative events are placed in sequential order based on dose and temporality, the dose-response slopes from Hill dose-response model fits of the data increase in value. Thus, the later KEs occur with a steeper slope than early KEs and the number of KEs observed increases as a function of dose and time (Simon et al., 2009; Budinsky et al., 2014).

Induction of xenobiotic metabolizing enzymes is one the earliest and most sensitive responses to AHR activation (Budinsky et al., 2010; Silkworth et al., 2005). Xenobiotic metabolizing enzyme induction reflects acute transcriptional and proteomic changes that are more aligned with the concept of a pre-MIE and thus provides an associative event for AHR activation. Since measurable enzyme induction persists for at least one year, we used the AUC of a biomarker for this enzyme induction as a measure of sustained AHR activation. Both Hill equation coefficients and half maximal concentrations increase with increasing values of sustained AHR activation and reflect dose-dependent transitions as KEs occur at the various levels of biological organization (Simon et al., 2009; Budinsky et al., 2014).

The dose-response temporality table above depicts the KEs increasing in frequency in both dose and time (Meek et al., 2013; Simon et al., 2014). This table is an essential requirement of the human relevance MOA framework and is recommended in the OECD AOP guidance (OECD, 2014). Here, the value of the sustained AHR activation index has been provided for each dose-time combination. One can easily see the increase in sustained AHR activation due to the increase in dose going down the table and the increase in duration going across the table.

The need for AHR activation for a sustained period of time, i.e. temporal concordance, is supported by the stop-exposure group in the TCDD cancer bioassay, which showed that when the administration of 100 ng/kg/d TCDD was stopped after 30 weeks, a statistically significant increase in tumor frequency was not observed (NTP, 2006a). This observation also indicates that the AHR activation needs to be sustained for more than 30 weeks for KE#2 to occur (Hailey et al., 2005).

 

Concordance of dose-response relationships

Dose-Time Concordance Table

Empirical evidence: application of the dose and temporal concordance AOP weight of evidence considerations for Key Events (KEs) at dose/time combination. This table is based on NTP (2006a), Teeguarden et al. (1999) and Maronpot et al. (1993). The dose in the left most column shows the range of average liver concentration (ng/kg) from 14 weeks to 2 years from NTP (2006a). The number in parentheses is the administered gavage dose in ng/kg/d. The numerical value of the sustained AHR activation index (ppb-weeks) is shown for each dose/time combination; the calculation of this value is described on the MIE page.

Dose Increasing Time -->
  Weeks to Months (14 wk) Months (31 wk) 1 yr (53 wk) 2 yr (104 wk)
5-20 (0.1)** 0.1 ppb-wk 0.5 ppb-wk 1 ppb-wk 2.4 ppb-wk
100-200 (1)** 1.7 ppb-wk 4.7 ppb-wk 8.8 ppb-wk 19 ppb-wk
450-650 (3)** 4.3 ppb-wk 11 ppb-wk 19 ppb-wk 40 ppb-wk
1500-2000 (10) MIE = 8.3 ppb-wk

Apoptosis Inhibition (KE#1)

MIE = 19 ppb-wk

Apoptosis Inhibition (KE#1)(presumed)

MIE = 34 ppb-wk MIE = 69 ppb-wk

Toxic Hepatopathy (KE#2) Hyperplasia/Proliferation (KE#3)

3500-4200 (22) MIE = 11 ppb-wk

Apoptosis Inhibition (KE#1)(presumed)

MIE = 24 ppb-wk

Apoptosis Inhibition (KE#1)(presumed)

MIE = 42 ppb-wk MIE = 83 ppb-wk

Toxic Hepatopathy (KE#2) Hyperplasia/Proliferation (KE#3)

7000-8000 (46) MIE = 12 ppb-wk

Apoptosis Inhibition (KE#1)(presumed)

MIE = 27 ppb-wk

Apoptosis Inhibition (KE#1)(presumed)

MIE = 47 ppb-wk

Toxic Hepatopathy (KE#2)

MIE = 93 ppb-wk

Toxic Hepatopathy (KE#2) Hyperplasia/Proliferation (KE#3) Cholangiocarcinomas (AO)

15000-17000 (100) MIE = 13 ppb-wk

Apoptosis Inhibition (KE#1)

MIE = 29 ppb-wk

Apoptosis Inhibition (KE#1) Toxic Hepatopathy (KE#2)

MIE = 50 ppb-wk

Toxic Hepatopathy (KE#2) Hyperplasia/Proliferation (KE#3)

MIE = 98 ppb-wk

Toxic Hepatopathy (KE#2) Hyperplasia/Proliferation (KE#3) Cholangiocarcinomas (AO) Hepatic Adenomas (AO)

    • these dose levels are insufficient to induce the degree of sustained AHR activation necessary to exceed the threshold of homeostasis/adaptation; exceeding this threshold is required to trigger the MIE.

When the KEs and associative events are placed in sequential order based on dose and temporality, the dose-response slopes from Hill dose-response model fits of the data increase in value. Thus, the later KEs occur with a steeper slope than early KEs and the number of KEs observed increases as a function of dose and time (Table 2) (Simon et al., 2009; Budinsky et al., 2014).

Induction of xenobiotic metabolizing enzymes is one the earliest and most sensitive responses to AHR activation (Budinsky et al., 2010; Silkworth et al., 2005). Xenobiotic metabolizing enzyme in- duction reflects acute transcriptional and proteomic changes that are more aligned with the concept of a pre-MIE and thus provides an associative event for AHR activation. Since measurable enzyme induction persists for at least one year, we used the AUC of a biomarker for this enzyme induction as a measure of sustained AHR activation. Both Hill equation coefficients and half maximal concentrations increase with increasing values of sustained AHR activation and reflect dose-dependent transitions as KEs occur at the various levels of biological organization (Simon et al., 2009; Budinsky et al., 2014).

The table shown above is the dose-response temporality table and depicts the KEs increasing in both dose and time (Meek et al., 2013; Simon et al., 2014). This table is an essential requirement of the human relevance MOA framework and is recommended in the OECD AOP guidance (OECD, 2014). Here, the value of the sustained AHR activation index has been provided for each dose-time combination. One can easily see the increase in sustained AHR activation due to the increase in dose going down the table and the increase in duration going across the table.

The need for AHR activation for a sustained period of time, i.e. temporal concordance, is supported by the stop-exposure group in the TCDD cancer bioassay, which showed that when the administration of 100 ng/kg/d TCDD was stopped after 30 weeks, a statistically significant increase in tumor frequency was not observed (NTP, 2006a). This observation also indicates that the AHR activation needs to be sustained for more than 30 weeks for KE#2 to occur (Hailey et al., 2005).

Support for the Biological Plausibility of the KERs

The OECD AOP guidance (OECD, 2014) for evaluation of biological plausibility of an AOP provides this defining question for evaluating biological plausibility: “is there a mechanistic (i.e., structural or functional) relationship between KEup and KEdown consistent with established biological knowledge?” Under the OECD guidance, a high degree of confidence is afforded when there is an established mechanistic basis and “extensive understanding of the KER based on extensive previous documentation and broad acceptance.” For biological plausibility, for this AOP, the WoE for each KER is judged to be strong, as is the WoE for the overall AOP.

All the elements in this AOP are strongly associated with the biological steps and elements of carcinogenesis (Hanahan and Weinberg, 2011). First, there is extensive body of mechanistic evi- dence in support the biological plausibility of this MOA (see recent review by Budinsky et al., 2014). Further, the relationships between sustained AHR activation and 1) decreased intrafocal apoptosis (KE#1); 2) increased cell proliferation (KE#2); 3) toxic hepatopathy (KE#3); and 4) eventual tumor formation (AO) are evident from a surfeit of published studies (e.g., Fig. 4). Moreover, overall consistency with knowledge of the pathogenesis of liver tumor promo- tion is supported by replication of events related to tumor promotion across different laboratories and the multiple lines of evidence for sustained AHR activation acting as a mechanism of liver tumor promotion. Thus, the AOP is well supported by the KEs, consistent with the biology of carcinogenesis and the events of tumor promotion (Dietrich and Kaina, 2010; Gasiewicz et al., 2008; Roberts et al., 1997).

The unique sensitivity of the female rat response suggests a possible role for estrogen as a modulating factor in the tumorigenic MOA. Estrogen is an established co-promoter of tumorigenesis and thus may play a role in the MOA (Graham et al., 1988; Hiraku et al., 2001; Lucier et al., 1991; Vickers and Lucier, 1996; Vickers et al., 1989). Crosstalk between the AHR pathway and the estrogen receptor pathway may also be a contributing factor (Matthews and Gustafsson, 2006). Such receptor mediated cross talk is consistent with the sustained AHR MOA.

Support for Biological Plausibility of KERs Defining Question High (Strong) Moderate Weak
  a) Is there a mechanistic (i.e., structural or functional) relationship between KEup and KEdown consistent with established biological knowledge? Extensive understanding of the KER based on extensive previous documentation and broad acceptance (e.g., mutation leading to tumors)

-Established mechanistic basis

The KER is plausible but scientific understanding is not completely established. Only limited or indirect evidence for KER (i.e., based on empirical support, only (See 3.)
Binding of Ligands to the AHR leading to sustained activation of the AHR Biological Plausibility of the pre-MIE => MIE is Strong

Rationale: Long-established knowledge of and extensive research on dioxin-like chemicals and other AHR ligands.

Sustained AHR Activation directly leading to Changes in Cellular Homeostasis and Inhibition of Apoptosis Biological Plausibility of MIE => KE1 is Strong.

Rationale: Direct empirical evidence showing continued application of AHR activators leads to growth alteration of altered hepatic foci.

Sustained AHR Activation indirectly leading to Hepatoxicity and Hepatopathy Biological Plausibility of MIE => KE2 is Strong

Rationale: Long established knowledge : Empirical data from two-year bioassays using AHR activation and sustained administration

Sustained AHR Activation indirectly leading to Alterations in Cellular Proliferation and Hyperplasia Biological Plausibility of MIE => KE3 is Strong

Rationale: Empirical data from two-year bioassays using AHR activation and sustained administration

Sustained AHR Activation indirectly leading to Hepatocellular Adenomas and Cholangiocarcinomas Biological Plausibility of MIE => AO is Strong

Rationale: Empirical data from two-year bioassays using AHR activation and sustained administration

 

Uncertainties, Inconsistencies and Conflicting Evidence for KERs and the AOP

The evidence supporting the KERs and AOP is strong. Alternative MOA(s) or KEs and KE elements can be examined to help ascertain the confidence in the MOA considered most likely (Boobis et al., 2006, 2008, 2009; Cohen et al., 2003; Cohen et al., 2004; Julien et al., 2009; Meek et al., 2003; Meek, 2008; Seed et al., 2005; Sonich-Mullin et al., 2001; USEPA, 2005).

One such alternative MOA would be that DLCs act to produce liver tumors in rodents by a mutagenic mechanism. However, there is substantial evidence that DLCs are neither mutagenic nor genotoxic compounds and thus do not act by a mutagenic MOA (Bock and Kohle, 2005; Dragan and Schrenk, 2000; Knerr et al., 2006; Poland and Glover, 1979; Randerath et al., 1990; Schwarz et al., 2000; Turteltaub et al., 1990; Wassom et al., 1977; Whysner and Williams, 1996).

Effects on gap junctions or induction of oxidative stress are two other potential mechanisms. TCDD disrupts normal gap junction activity and intercellular communication in rat primary hepatocytes and WB-344 cells (Andrysík et al., 2013; Bager et al., 1997; Herrmann et al., 2002; Weiss et al., 2008). Further research is needed to understand the contribution of this mechanism to DLC- induced rodent liver tumor formation. Oxidative stress appears less likely as an alternative MOA and may be a late-occurring associative event due to continued high activity of phase 1 mixed function oxidases and accompanying cytotoxicity.

In summary, the WoE in support of sustained AHR activation leading to changes in cellular growth homeostasis and eventually promotion of liver tumors in rodents is strong. The WoE supporting the alternative MOAs is much weaker.

Uncertainty and Conflicting Evidence for KERs and AOP Defining Question High (Strong) Moderate Weak
  Are there inconsistencies in empirical support across taxa, species which don’t align with appropriate pattern for hypothesized KERs and AOP?

Are there significant knowledge gaps or uncertainties with regard to the relationship between the KEs and overall AOP?

No (or very few) knowledge gaps or inconsistent / conflicting lines of evidence.) Some inconsistent evidence but which can be explained by factors such as experimental design, technical considerations, differences among laboratories, etc.) Contradictory evidence in for which no plausible explanation is known.
Binding of Ligands to the AHR leading to sustained activation of the AHR Inconsistencies / Uncertainties of Pre-MIE => MIE is Strong

Rationale: Highly certain. While a large number of ligands bind to and activate the AHR, only the biologically persistent ligands, such as dioxin-like chemicals produce the MIE, sustained AHR activation

Sustained AHR Activation directly leading to Changes in Cellular Homeostasis and Inhibition of Apoptosis Inconsistencies / Uncertainties of MIE => KE1 is Strong.

Rationale: A large number of initiation-promotion studies with TCDD or other dioxin-like chemicals documented changes in both cell proliferation and inhibition of apoptosis within alterered hepatic foci.

Sustained AHR Activation indirectly leading to Hepatoxicity and Hepatopathy Inconsistencies / Uncertainties of MIE => KE2 is 'Strong

Rationale: Although the exact mechanism is not known, sustained AHR activation often leads to increased concentrations of ROS that may be a factor in generating cytotoxicity. Hepatopathy is common effect of sustained adiministration of AHR activators.

Sustained AHR Activation indirectly leading to Alterations in Cellular Proliferation and Hyperplasia Inconsistencies / Uncertainties of MIE => KE3 is Strong

Rationale: All the biologically persistent AHR activators such as DLCs damage the liver to a sufficient extent that a proliferative/regenerative environment is created in the organ.

Sustained AHR Activation indirectly leading to Hepatocellular Adenomas and Cholangiocarcinomas Inconsistencies / Uncertainties of MIE => AO is Strong

Rationale: These tumors are outcomes of the AHF growth in KE#1 and the increased proliferation in KE#3. Both are induced by the MIE, sustained AHR activation. A large number of bioassays have documented the fact that persistent AHR ligands produce liver tumors in rodents.

 

Quantitative Understanding

Some proof of concept examples to address the WoE considerations for AOPs quantitatively have recently been developed, based on the rank ordering of the relevant Bradford Hill considerations (i.e., biological plausibility, essentiality and empirical support) (Becker et al., 2017; Becker et al, 2015; Collier et al., 2016). Suggested quantitation of the various elements is expert derived, without collective consideration currently of appropriate reporting templates or formal expert engagement. Though not essential, developers may wish to assign comparative quantitative values to the extent of the supporting data based on the three critical Bradford Hill considerations for AOPs, as a basis to contribute to collective experience.Specific attention is also given to how precisely and accurately one can potentially predict an impact on KEdownstream based on some measurement of KEupstream. This is captured in the form of quantitative understanding calls for each KER. See pages 55-56 of the User Handbook for a review of quantitative understanding for KER's. More help

While binding of ligand to the AHR is identified as a pre-MIE, sustained AHR activation by persistent ligands such as DLCs is linked qualitatively and quantitatively to both downstream KEs and the AO. These linkages notwithstanding, additional work is needed to develop and evaluate such a prediction model before the MIE of sustained AHR activation can be used in a quantitative prediction model of the AO. Any prediction model based on this AOP needs to consider the unique aspects of the AHR and its response to DLCs, including the involvement of initiated or partially differentiated stem cells, and such a model would need evaluation/validation for its intended use (Cox et al., 2014; Patlewicz et al., 2015).

Considerations for Potential Applications of the AOP (optional)

At their discretion, the developer may include in this section discussion of the potential applications of an AOP to support regulatory decision-making. This may include, for example, possible utility for test guideline development or refinement, development of integrated testing and assessment approaches, development of (Q)SARs / or chemical profilers to facilitate the grouping of chemicals for subsequent read-across, screening level hazard assessments or even risk assessment. While it is challenging to foresee all potential regulatory application of AOPs and any application will ultimately lie within the purview of regulatory agencies, potential applications may be apparent as the AOP is being developed, particularly if it was initiated with a particular application in mind. This optional section is intended to provide the developer with an opportunity to suggest potential regulatory applications and describe his or her rationale.To edit the “Considerations for Potential Applications of the AOP” section, on an AOP page, in the upper right hand menu, click ‘Edit.’ This brings you to a page entitled, “Editing AOP.” Scroll down to the “Considerations for Potential Applications of the AOP” section, where a text entry box allows you to submit text. In the upper right hand menu, click ‘Update AOP’ to save your changes and return to the AOP page or 'Update and continue' to continue editing AOP text sections.  The new text should appear under the “Considerations for Potential Applications of the AOP” section on the AOP page. More help

The OECD guidance for AOP development (OECD, 2013) suggests a number of potential uses for AOPs. These include 1) category formation for read-across, 2) integrated approaches for testing and assessment 3) development or refinement of test methods such as OECD test guidelines and 4) hazard identification (classification/ labeling) and risk assessment. The use of a specific AOP for any one or more of these applications depends on scientific confidence in the AOP for each specific use. An AOP can offer practical utility in certain applications even if confidence is not sufficient to quantitatively predict the AO from the MIE. Application of the sustained AHR activation AOP for several applications was described in brief in Patlewicz et al. (2015); Below the application of and confidence in this AOP is discussed in more detail.

Which Key Events can be used to predict the AO?

To date, no quantitative models have been developed to predict the adverse outcome from AHR activation by ligand binding. With the exception of DLCs, PCDDs, PCDFs and co-planar PCBs, this predictive capability is highly uncertain for the plethora of AHR ligands. For example, indole 3-carbinol is an AHR ligand occurring in cruciferous vegetables and acts as a cancer chemopreventive agent. In the stomach, indole 3-carbinol forms 3,3- diinolylmethane, a potent AHR ligand that has shown promise for preventing tumor reoccurrence in humans (Banerjee et al., 2011). Dietary administration of indole-3-carbinol for 23 weeks inhibited tumor formation in rats initiated with diethylnitrosamine (Tanaka et al., 1990). However, also in diethylnitrosamine-initiated rats, prolonged indole 3-carbinol administration (>26 weeks) increased the progression of altered hepatic foci to hepatocellular adenomas (Yamamoto et al., 2013). A recent NTP 2-year cancer bioassay failed to demonstrate indole 3-carbinol as a liver tumor promoter in fe- male rats (NTP, 2014). Furthermore, endogenous AHR ligands and naturally occurring exogenous ligands occurring in foods have cancer-preventive properties and likely contribute to a relatively high level of AHR activation activity in human blood (Connor et al., 2008; Navarro et al., 2009, 2011; Peterson et al., 2009; Wincent et al., 2009). These naturally occurring and endogenous ligands induce both their own metabolism and that of other AHR ligands through increased induction of xenobiotic metabolizing enzymes. The transient metabolic increase may be one aspect of the pre- ventive effect against sustained AHR activation that would lead to KEs related to liver tumor promotion.

Neither binding of ligand to the AHR nor short-term transcriptional changes and cellular responses are sufficient to produce liver tumors in rats. Strains of rats that show resistance towards the toxic and carcinogenic effects of DLCs express different genomic profiles outside of the conserved core battery response (Boutros et al., 2011; Yao et al., 2012). Acute genomic changes do not appear to be pre- dictive for the cancer endpoint (Fielden et al., 2011; Ovando et al., 2010). AHR activation-induced transcriptional changes occur within hours of ligand activation; yet the subsequent KEs and AO require months of sustained AHR activation for tumors to occur. Hence, the distinction between short-term and sustained activation of the AHR is an important one and AHR activation must be sus- tained for more than 30% of the rodent lifespan to result in tumor promotion.

While binding of ligand to the AHR is identified as a pre-MIE, sustained AHR activation by persistent ligands such as DLCs is linked qualitatively and quantitatively to both downstream KEs and the AO. These linkages notwithstanding, additional work is needed to develop and evaluate such a prediction model before the MIE of sustained AHR activation can be used in a quantitative prediction model of the AO. Any prediction model based on this AOP needs to consider the unique aspects of the AHR and its response to DLCs, including the involvement of initiated or partially differentiated stem cells, and such a model would need evaluation/validation for its intended use (Cox et al., 2014; Patlewicz et al., 2015).

Using this AOP for grouping chemicals into chemical categories for read-across

Without some measure of sustained activation, the use of pre- MIEs for any purpose other than preliminary screening is problematic as a predictive criteria for liver tumor promotion. Evidence clearly shows it is the combination of sustained AHR activation and the subsequent biological changes involving complex parenchymal and non-parenchymal cell interactions that underlie the hepatotoxicity, the increase in cell proliferation and the apical tumor response. Hence, the MIE is defined as sustained AHR activation, and not simply AHR activation. In addition, the promiscuity of the AHR and the species- and strain-specificity of the initial genomic responses suggest that category development may prove a challenge (Denison, 2011; Dere, 2011).

Using this AOP for integrated approaches to testing and assessment (IATA)

The most straightforward use of this AOP within an integrated testing and assessment approach for hazard evaluation would be to determine the potential for a substance to activate the AHR in a sustained manner with long-term changes in gene transcription involving multiple cell types, which leads to increased liver cell proliferation. An IATA decision-tree approach, for illustrative purposes has been already presented by Patlewicz et al. (2015).

The initial steps in the IATA focus on evaluating molecular and cellular events related to AHR binding and transcriptional activation using rapid and cost effective in silico or in vitro assays. Compounds found to be inactive in such assays would not proceed forward into further testing.

At the present time, there is insufficient understanding to permit the use transcription profiling as a metric of sustained AHR activation to quantitatively predict development of rat liver foci and liver tumors. Therefore, the IATA proposes that substances found to be active in the AHR mechanistic assays be subjected to a decision framework for further evaluating the potential to act as rodent liver tumor promoter. For example, a subchronic study, utilizing an appropriate dosing regimen, may be able to rule-in or rule-out the substance's ability to trigger the critical histological components of hepatopathy (Hailey et al., 2005). Or a rodent liver initiation- promotion assay could be considered, though interpretation can be challenging (Tanaka et al., 1990; Yamamoto et al., 2013; NTP, 2014). Patlewicz et al. (2015) also illustrate how exposure information can be used in conjunction with the AOP to inform IATA decisions.

Using this AOP to inform test method development or refinement

An IATA consisting of a suite of in vitro and in vivo (e.g., sub- chronic) assays to predict hepatopathy, a complex histological response, may be needed to differentiate AHR ligands with and without liver tumor promotion potential. Theoretically, it may be plausible to consider using a combination of AHR-binding, AHR- transcriptional activation and rat liver initiation-promotion assays to develop a prediction model for sustained AHR activation- induced rat liver tumors. Therefore, within the OECD test guidelines program, it may be worthwhile to consider developing performance criteria that could be applied to judge the scientific quality and reliability of in vitro AHR-binding and transactivation assays, liver stem cell assays, as well as a validated test guideline for a rat liver tumor (hepatic foci) initiation-promotion assay.

References

List the bibliographic references to original papers, books or other documents used to support the AOP. More help

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