This AOP is licensed under the BY-SA license. This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. If you remix, adapt, or build upon the material, you must license the modified material under identical terms.

AOP: 513


A descriptive phrase which references both the Molecular Initiating Event and Adverse Outcome.It should take the form “MIE leading to AO”. For example, “Aromatase inhibition leading to reproductive dysfunction” where Aromatase inhibition is the MIE and reproductive dysfunction the 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

Reactive Oxygen (ROS) formation leads to cancer via Peroxisome proliferation-activated receptor (PPAR) pathway

Short name
A name that succinctly summarises the information from the title. This name should not exceed 90 characters. More help
ROS formation leads to cancer via PPAR pathway
The current version of the Developer's Handbook will be automatically populated into the Handbook Version field when a new AOP page is created.Authors have the option to switch to a newer (but not older) Handbook version any time thereafter. More help
Handbook Version v2.6

Graphical Representation

A graphical representation of the AOP.This graphic should list all KEs in sequence, including the MIE (if known) and AO, and the pair-wise relationships (links or KERs) between those KEs. More help
Click to download graphical representation template Explore AOP in a Third Party Tool


The names and affiliations of the individual(s)/organisation(s) that created/developed the AOP. More help

Of the originating work:

Jaesong Jeong and Jinhee Choi, School of Environmental Engineering, University of Seoul, Seoul, Republic of Korea

Of the content populated in the AOP-Wiki:

Daniel L. Villeneuve, US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Duluth, MN

Travis Karschnik and John R. Frisch, General Dynamics Information Technology, Duluth, Minnesota

Point of Contact

The user responsible for managing the AOP entry in the AOP-KB and controlling write access to the page by defining the contributors as described in the next section.   More help
John Frisch   (email point of contact)


Users with write access to the AOP page.  Entries in this field are controlled by the Point of Contact. More help
  • John Frisch


This field is used to identify coaches who supported the development of the AOP.Each coach selected must be a registered author. More help

OECD Information Table

Provides users with information concerning how actively the AOP page is being developed and whether it is part of the OECD Workplan and has been reviewed and/or endorsed. OECD Project: Assigned upon acceptance onto OECD workplan. This project ID is managed and updated (if needed) by the OECD. OECD Status: For AOPs included on the OECD workplan, ‘OECD status’ tracks the level of review/endorsement of the AOP . This designation is managed and updated by the OECD. Journal-format Article: The OECD is developing co-operation with Scientific Journals for the review and publication of AOPs, via the signature of a Memorandum of Understanding. When the scientific review of an AOP is conducted by these Journals, the journal review panel will review the content of the Wiki. In addition, the Journal may ask the AOP authors to develop a separate manuscript (i.e. Journal Format Article) using a format determined by the Journal for Journal publication. In that case, the journal review panel will be required to review both the Wiki content and the Journal Format Article. The Journal will publish the AOP reviewed through the Journal Format Article. OECD iLibrary published version: OECD iLibrary is the online library of the OECD. The version of the AOP that is published there has been endorsed by the OECD. The purpose of publication on iLibrary is to provide a stable version over time, i.e. the version which has been reviewed and revised based on the outcome of the review. AOPs are viewed as living documents and may continue to evolve on the AOP-Wiki after their OECD endorsement and publication.   More help
OECD Project # OECD Status Reviewer's Reports Journal-format Article OECD iLibrary Published Version
This AOP was last modified on April 23, 2024 16:25

Revision dates for related pages

Page Revision Date/Time
Increased, Reactive oxygen species April 10, 2024 17:33
Decreased, PPAR-gamma activation October 30, 2023 09:07
Alteration, lipid metabolism October 30, 2023 09:11
General Apoptosis October 18, 2023 12:20
Increase, Cancer August 22, 2023 14:32
Increased, Reactive oxygen species leads to Decreased, PPAR-gamma activation October 19, 2023 10:55
Decreased, PPAR-gamma activation leads to Alteration, lipid metabolism October 19, 2023 11:10
Alteration, lipid metabolism leads to General Apoptosis October 19, 2023 11:25
General Apoptosis leads to Increase, Cancer October 19, 2023 09:46


A concise and informative summation of the AOP under development that can stand-alone from the AOP page. The aim is to capture the highlights of the AOP and its potential scientific and regulatory relevance. More help

Reactive oxygen species (ROS) are derived from oxygen molecules and can occur as free radicals (ex. superoxide, hydroxyl, peroxyl) or non-radicals (ex. ozone, singlet oxygen).  ROS production occurs via a variety of normal cellular process; however, in stress situations (ex. exposure to radiation, chemical or biological stressors) reactive oxygen species levels dramatically increase and cause damage to cellular components.  In this Adverse Outcome Pathway (AOP) we focus on the Peroxisome proliferation-activated receptor (PPAR) response to increases in oxidative stress.  Changes in activation rate of Peroxisome proliferation-activated receptors alter lipid metabolism, and decrease suppression of apoptosis.  In this AOP we focus on the apoptosis response to cellular damage.  Pathways leading to apoptosis, or single cell death, have traditionally been studied as both independent and simultaneous from pathways leading to necrosis, or tissue-wide cell death, with both overlap and distinct mechanisms (Elmore 2007). For the purposes of this AOP, we are characterizing cancer due to widespread cell-death, and recognize the complications in separating the related apoptosis and necrosis pathways.

AOP Development Strategy


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. More help

This Adverse Outcome Pathway focuses on the key pathways in which an established molecular disruption, increased levels of reactive oxygen species (ROS), leads to increased cancer.


Provides a description of the approaches to the identification, screening and quality assessment of the data relevant to identification of the key events and key event relationships included in the AOP or AOP network.This information is important as a basis to support the objective/envisaged application of the AOP by the regulatory community and to facilitate the reuse of its components.  Suggested content includes a rationale for and description of the scope and focus of the data search and identification strategy/ies including the nature of preliminary scoping and/or expert input, the overall literature screening strategy and more focused literature surveys to identify additional information (including e.g., key search terms, databases and time period searched, any tools used). More help

This AOP was developed as part of an Environmental Protection Agency effort to represent putative AOPs from peer-reviewed literature which were heretofore unrepresented in the AOP-Wiki.  Jeong and Choi (2020) and Jeong and Choi (2019) provided initial network analysis from microplastic stressors, guided by weight of evidence from ToxCast assays.  These publications, and the work cited within, were used create and support this AOP and its respective KE and KER pages.

The AOP-wiki authors did a further evaluation of published peer-reviewed literature to provide additional evidence in support of the AOP.  A companion adverse outcome pathways is planned for an additional pathway initiated by reactive oxygen species (ROS), leading to increased cancer: Increased, Reactive oxygen species leads to Increase, Inflammation.

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


Molecular Initiating Events (MIE)
An MIE is a specialised KE that represents the beginning (point of interaction between a prototypical stressor and the biological system) of an AOP. More help
Key Events (KE)
A measurable event within a specific biological level of organisation. More help
Adverse Outcomes (AO)
An AO is a specialized KE that represents the end (an adverse outcome of regulatory significance) of an AOP. More help
Type Event ID Title Short name
MIE 1115 Increased, Reactive oxygen species Increased, Reactive oxygen species
KE 233 Decreased, PPAR-gamma activation Decreased, PPAR-gamma activation
KE 1060 Alteration, lipid metabolism Alteration, lipid metabolism
KE 1513 General Apoptosis General Apoptosis
AO 885 Increase, Cancer Increase, Cancer

Relationships Between Two Key Events (Including MIEs and AOs)

This table summarizes 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. More help
Title Adjacency Evidence Quantitative Understanding

Network View

This network graphic is automatically generated based on the information provided in the MIE(s), KEs, AO(s), KERs and Weight of Evidence (WoE) summary tables. The width of the edges representing the KERs is determined by its WoE confidence level, with thicker lines representing higher degrees of confidence. This network view also shows which KEs are shared with other AOPs. More help

Prototypical Stressors

A structured data field that can be used to identify one or more “prototypical” stressors that act through this AOP. Prototypical stressors are stressors for which responses at multiple key events have been well documented. More help

Life Stage Applicability

The life stage for which the AOP is known to be applicable. More help
Life stage Evidence
All life stages High

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. More help
Term Scientific Term Evidence Link
human Homo sapiens High NCBI
mouse Mus musculus High NCBI
rat Rattus norvegicus High NCBI

Sex Applicability

The sex for which the AOP is known to be applicable. More help
Sex Evidence
Unspecific High

Overall Assessment of the AOP

Addressess the relevant biological domain of applicability (i.e., in terms of taxa, sex, life stage, etc.) and Weight of Evidence (WoE) for the overall AOP as a basis to consider appropriate regulatory application (e.g., priority setting, testing strategies or risk assessment). More help

1. Support for Biological Plausibility of Key Event Relationships: Is there a mechanistic relationship  between KEup and KEdown consistent with established biological knowledge?

Key Event Relationship (KER)


Strong = Extensive understanding of the KER based on extensive previous documentation and broad acceptance.

Relationship 3092: Increased, Reactive oxygen species leads to Decreased, PPAR-gamma activation

Strong support.  Increases in reactive oxygen species (ROS) have been shown to cause a variety of cellular responses including decreased PPARgamma gene expression.  

Relationship 3093: Decreased, PPAR-gamma activation leads to Alteration, lipid metabolism

Strong support. Decreased PPAR gene expression have been shown to cause an alteration of lipid metabolism.  PPAR-gamma acts as a nuclear signaling element that controls the transcription of a variety of genes involved in lipid catabolism and energy production pathways.

Relationship 3094: Alteration, lipid metabolism leads to General Apoptosis

Strong support. Alteration of lipid metabolism have been shown to results in abnormal cell function and activity, leading to apoptosis.  Alteration of lipid metabolism leads to changes in cell lipid levels, structural changes in membranes as lipids are key components, and changes in signaling pathways affecting gene and protein expression.  Loss of plasma membrane integrity due to disruptions to lipid metabolism results in cellular processes identifying cells as damaged, which acts as a signal for apoptosis.

Relationship 2977: General Apoptosis leads to Increase, Cancer

Strong support.  The relationship between failure of apoptosis pathways to initiate cell death pathways and increases in cancer is broadly accepted and consistently supported across taxa.


Strong support.  Extensive understanding of the relationships between events from empirical studies from a variety of taxa.

Domain of Applicability

Addressess the relevant biological domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context. More help

Life Stage: The life stage applicable is all life stages. 

Sex: Applies to both males and females.

Taxonomic: Appears to be present broadly, with representative studies including mammals (humans, lab mice, lab rats), telost fish, and invertebrates (cladocerans, mussels).


Essentiality of the Key Events

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. More help

Support for the essentiality of the key events can be obtained from a wide diversity of taxonomic groups, with mammals (lab ice, lab rats, human cell lines), telost fish, and invertebrates (cladocerans and mussels) particularly well-studied.

2. Essentiality of Key Events: Are downstream KEs and/or the AO prevented if an upstream KE is blocked?

Key Event (KE)


Strong = Direct evidence from specifically designed experimental studies illustrating essentiality and direct relationship between key events.

Moderate = Indirect evidence from experimental studies inferring essentiality of relationship between key events due to difficulty in directly measuring at least one of key events.

MIE 1115: Increased, Reactive oxygen species

Strong support. Increased Reactive oxygen species (ROS) levels are a primary cause of decreases in PPARgamma gene expression.  Evidence is available from studies of stressor exposure and resulting changes in gene expression and protein/enzyme levels.

KE 233: Decreased, PPAR-gamma activation

Strong support. The PPARgamma gene family is important in controlling rate of lipid metabolism.  Evidence is available from studies of stressor exposure and resulting changes in gene expression and protein/enzyme levels.

KE 1060: Alteration, lipid metabolism

Strong support.  Altered lipid metabolism, particularly resulting loss of plasma membrane integrity is a cause of apoptosis.  Evidence is available from studies of stressor exposure and resulting changes in gene expression and protein/enzyme levels.

KE 1513: General Apoptosis

Moderate support. Failure of apoptosis allows cancer cells to proliferate.  Evidence is available from studies of stressor exposure and resulting changes in gene expression, protein/enzyme levels, and histology.

AO 885: Increase, Cancer

Strong support. Cancer proliferates due to a variety of stressors and breakdown of multiple celluar processes.  Evidence is available from studies of stressor exposure and resulting changes in gene expression, protein/enzyme levels, and histology.


Moderate to strong support.  Direct evidence from empirical studies for most key events, with more inferential evidence rather than direct evidence for apoptosis.

Evidence Assessment

Addressess the biological plausibility, empirical support, and quantitative understanding from each KER in an AOP. More help



Increased, Reactive oxygen species leads to Decreased, PPAR-gamma activation

Biological plausibility is high.  Representative studies have been done with mammals (El Midaoui et al. 2006; Blanquicett et al. 2010; Lu et al. 2018; Jeong and Choi 2020) fish (Wang et al. 2022). 

Decreased, Decreased, PPAR-gamma activation leads to Alteration, lipid metabolism

Biological plausibility is high.  Representative studies have been done with mammals (Chamorro-Garcia et al. 2018; Jeong and Choi 2020); fish (Venezia et al. 2021).  For review (Tickner et al. 2001; Berger and Moller 2002; Luquet et al. 2005; Den Broeder et al. 2015).

Alteration, lipid metabolism leads to General Apoptosis

Biological plausibility is high.  Representative studies have been done with mammals (Cadet et al. 2010, Gao et al. 2020); invertebrates (Avio et al. 2015). For review (Huang and Freter 2015).

General Apoptosis leads to Increase, Cancer

Biological plausibility is high.  Representative studies have been done with mammals (Pavet et al. 2014; Jeong and Choi 2020).  For review (Heinlein and Chang 2004; Vihervaara and Sistonen 2014).

3. Empirical Support for Key Event Relationship: Does empirical evidence support that a  change in KEup leads to an appropriate change in KEdown?

Key Event Relationship (KER)


Strong =  Experimental evidence from exposure to toxicant shows consistent change in both events across taxa and study conditions.

Relationship 3092: Increased, Reactive oxygen species leads to Decreased, PPAR-gamma activation

Strong support. Increases in ROS leads to decreases in PPAR gamma gene expression, primarily by examining gene expression levels.

Relationship 3093: Decreased, PPAR-gamma activation leads to Alteration, lipid metabolism

Strong support. Decreases in PPAR gamma expression leads to alteration of lipid metabolism, primarily by assessing lipid content and levels of energy metabolites.

Relationship 3094: Alteration, lipid metabolism leads to General Apoptosis

Strong support. Altered lipid metabolism leads to apoptosis; problems with lipid metabolism lead to abnormal cells, triggering apoptosis pathways.

Relationship 2977: General Apoptosis leads to Increase, Cancer

Strong support. Mechanistic studies show that failure for apoptosis to eliminate cancer cells allows increases in cancer proliferation.


Strong support. Exposure from empirical studies shows consistent change in both events from a variety of taxa.

For overview of the biological mechanisms involved in this AOP, see Liu et al. (2015) and Jeong and Choi (2020); their studies analyzed ToxCast in vitro assays of mammalian acute toxicity data to identify correlations between toxicity pathways and chemical stressors, providing support for the key event relationships represented here.

Known Modulating Factors

Modulating factors (MFs) may alter the shape of the response-response function that describes the quantitative relationship between two KES, thus having an impact on the progression of the pathway or the severity of the AO.The evidence supporting the influence of various modulating factors is assembled within the individual KERs. More help
Modulating Factor (MF) Influence or Outcome KER(s) involved

Quantitative Understanding

Optional field to provide quantitative weight of evidence descriptors.  More help

Considerations for Potential Applications of the AOP (optional)

Addressess 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. More help


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

Avio, C.G., Gorbi, S., Milan, M., Benedetti, M., Fattorini, D., D’Errico, G., Pauletto, M., Bargelloni, L., and Regoli, F.  2015.  Pollutants bioavailability and toxicological risk from microplastics to marine mussels.  Environmental Pollutants 198: 211-222.

Berger, J. and Moller, D.  2002.  The mechanisms of action of PPARS.  Annual Review of Medicine 53: 409-435.

Blanquicett, C., Kang, B-Y., Ritzenthaler, J.D. Jones, D.P., and Hart, C.M.  2010.  Free Radical Biology and Medicine 48: 1618-1625.

Den Broeder, M.J., Kopylova, V.A., Kamminga, L.M. Legler, J.  2015.  Zebrafish as a model to study the role of peroxisome proliferating-activated receptors in adipogenesis and obesity.  PPAR Research 2015: 358029.

Cadet, J.L., Jayanthi, S., McCoy, M.T., Beauvais, G., and Cai, N.S.  2010.  Dopamine D1 receptors, regulation of gene expression in the brain, and neurogeneration.  CNS Neurological Disorders - Drug Targets 9: 526-538.

Chamorro-Garcia, R., Shoucri, B.M., Willner, S., Kach, H., Janesick, A., and Blumberg, B.  2018.  Effect of perinatal exposure to dibutyltin chloride on fat and glucose metabolism in mice, and molecular mechanisms, in vitro.  Environmental Health Perspectives 126: 057006.

El Midaoui, A., Wu, L., Wang, R., and de Champlain, J.  2006.  Modulation of cardiac and aortic peroxisome proliferator-activated receptor-gamma expression by oxidative stress in chronically glucose-fed rats.  American Journal of Hypertension 19: 407-412.

Gao, L., Xu, Z., Huang, Z., Tang, Y., Yang, D., Huang, J., He, L., Liu, M., Chen, Z., and Teng, Y.  2020.  CPI-613 rewires lipid metabolism to enhance pancreatic cancer apoptosis via the AMPK-ACC signaling.  39: 73.

Heinlein, C.A. and Chang, C.  2004.  Androgen receptor in prostate cancer.  Endocrine Reviews 25: 276-308.

Huang, C. and Freter, C.  2015.  Lipid metabolism, apoptosis and cancer therapy.  International Journal of Molecular Sciences 16: 924-949.

Jeong, J. and Choi, J.  2019.  Adverse outcome pathways potentially related to hazard identification of microplastics based on toxicity mechanisms. Chemosphere 231: 249-255.

Jeong, J. and Choi, J.  2020.  Development of AOP relevant to microplastics based on toxicity mechanisms of chemical additives using ToxCast™ and deep learning models combined approach.  Environment International 137:105557.

Liu, J., Mansouri, K., Judson, R.S., Martin, M.T., Hong, H., Chen, M., Xu, X., Thomas, R.S., and Shah, I.  2015.  Predicting hepatoxicity using ToxCast in vitro bioactivity and chemical structure.  Chemical Research in Toxicology 28: 738-751.

Lu, L., Wan, Z., Luo, T., Fu, Z., and Jin, Y.  2018.  Polystyrene microplastics induce microbiota dysbiosis and hepatic lipid metabolism disorder in mice. Science of the Total Environment 631-632: 449-458.

Luquet, S., Gaudel, C., Holst, D., Lopez-Soriano, J., Jehl-Pietri, C., Fredenrich, A., and Grimaldi, P.A.  2005.  Roles of PPAR delta in lipid absorption and metabolism: A new target for the treatment of type 2 diabetes.  Biochimica and Biophysica Acta 1740: 313-317.

Pavet, V., Shlyakhtina, Y., He, T., Ceschin, D.G., Kohonen, P., Perala, M., Kallioniemi, O., and Gronemeyer, H.  2014.  Plasminogen activator urokinase expression reveals TRAIL responsiveness and support fractional survival of cancer cells.  Cell Death and Disease 5: e1043.

Tickner, J.A., Schettler, T., Guidotti, T., Mccally, M., and Rossi, M.  2001.  Health risks posed by used of di-2-ethylhexyl phthalate (DEHP) in PVC medical devices: A critical review.  American Journal of Industrial Medicine 39: 100-111.

Venezia, O., Islam, S., Cho, C., Timme-Laragy, A.R., and Sant, K.E.  2021.  Modulation of PPAR signaling disrupts pancreas development in the zebrafish, Danio rerio.  Toxicology and Applied Pharmacology 426: 115653.

Vihervaara, A. and Sistonen, L.  2014.  HSF1 at a glance.  Journal of Cell Scientce 127: 261-266.

Wang, X., Ma, Q., Chen, L. Wu, H., Chen, L.-Q., Qiao, F., Luo, Y., Zhang, M.-L., and Du, Z.-Y.  2022.  Peroxisome proliferator-activated receptor gamma is essential for stress adaptation by maintaining lipid homeostatis in female fish.  Biochimica et Biophysica Acta – Molecular and Cell Biology of Lipids 1867: 159162.