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Relationship: 2577


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

Apoptosis leads to tumor growth

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
Activation of the AhR leading to metastatic breast cancer adjacent High Evgeniia Kazymova (send email) Under Development: Contributions and Comments Welcome 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
Homo sapiens Homo sapiens High NCBI

Sex Applicability

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

Life Stage Applicability

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

Apoptosis, also known as programmed cell death, is a natural and tightly regulated process that plays a crucial role in maintaining tissue homeostasis by eliminating damaged, aged, or unnecessary cells. When apoptosis is impaired or decreased, it can contribute to tumor growth and the progression of cancer. It is one of the hallmarks of cancer (Hanahan) :

  • Accumulation of Mutated or Damaged Cells: Apoptosis is a mechanism for eliminating cells with DNA damage or mutations. When apoptosis is reduced, cells with genetic abnormalities or mutations that might have led to their destruction can persist and accumulate. The accumulation of these abnormal cells provides a foundation for the development of tumors, as they may carry oncogenic mutations that promote uncontrolled cell proliferation (Schmitt)
  • Resistance to Cell Death Signals: Cancer cells often develop resistance to signals that would normally induce apoptosis. This resistance can be acquired through various mechanisms, including mutations in apoptotic pathway components or the overexpression of anti-apoptotic proteins. Decreased sensitivity to apoptotic signals allows cancer cells to evade elimination, contributing to their survival and uncontrolled proliferation. Some cancers overexpress proteins like Bcl-2 and FLIP, which inhibit the apoptotic machinery and promote cell survival. This allows cancer cells to evade cell death signals and continue proliferating (Fulda).
  • Enhanced Survival of Cancer Cells: Apoptosis acts as a natural mechanism to eliminate cells that are no longer needed or pose a threat to the organism. When apoptosis is suppressed, cancer cells gain a survival advantage, allowing them to resist death signals and persist in the tissue. This enhanced survival capability contributes to the prolonged existence and growth of cancer cells within the tumor microenvironment. p53 plays a critical role in triggering apoptosis in response to DNA damage or other stresses. Mutations inactivating p53 are common in many cancers and contribute to uncontrolled cell proliferation and resistance to apoptosis.
  • Uncontrolled Cell Proliferation: Apoptosis and cell proliferation are intricately linked processes that help maintain tissue homeostasis. A decrease in apoptosis disrupts the balance between cell death and cell division. Cancer cells, with reduced susceptibility to apoptosis, can undergo uncontrolled and sustained proliferation, leading to the formation of a tumor mass. Many cancers harbor mutations that activate pro-proliferative signaling pathways like Ras or PI3K/Akt (Fulda, Luo). These pathways normally promote cell growth and division, but when dysregulated, they can contribute to uncontrolled proliferation even in the absence of proper growth signals.

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings.  Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help
Biological Plausibility
Addresses the biological rationale for a connection between KEupstream and KEdownstream.  This field can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured.   More help
  • Unchecked Cell Proliferation: Healthy tissues maintain homeostasis through a finely tuned balance between cell proliferation and apoptosis. When apoptosis is compromised, cells that would normally undergo programmed cell death survive and continue to divide, leading to an uncontrolled increase in cell number and contributing to the initial mass of a tumor.
  •  Sustained Proliferative Signaling: Many cancers harbor mutations that activate pro-proliferative signaling pathways like Ras or PI3K/Akt. These pathways normally promote cell growth and division, but when dysregulated due to mutations, they can continue to signal proliferation even in the absence of proper growth signals or when apoptosis should occur. Additionally, a decrease in apoptosis can prevent the activation of pro-apoptotic pathways that would normally act as brakes on cell division.
  • Evasion of Growth-Inhibitory Signals: Healthy cells respond to various cues, including density-dependent inhibition and nutrient limitations, by activating apoptosis. When apoptosis is compromised, cells can evade these growth-inhibitory signals and continue dividing even when resources are limited or cell density is high. This allows the tumor to expand beyond its normal boundaries and invade surrounding tissues.
  • Selection for Favorable Traits: Tumor development is often described as a process of clonal selection. Cells harboring mutations that grant them a growth advantage, including those that escape apoptosis, will have a higher chance of surviving and proliferating. This selection pressure over time can lead to a tumor population with a decreased overall apoptotic response, further accelerating tumor growth.
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
  • Establishing Direct Causation: While various studies support the association, proving a direct and definitive cause-and-effect relationship between decreased apoptosis and tumor development in vivo remains challenging. Tumorigenesis is a complex process with multiple contributing factors, making it difficult to isolate the sole effect of reduced apoptosis in a living organism.
  • Heterogeneity of Cancers: Different types of cancers may have varying levels of dependence on reduced apoptosis for their growth and progression. This heterogeneity presents a challenge in understanding the universal impact of apoptosis across all cancers.
  • Role of Other Cell Death Mechanisms: Apoptosis is not the only form of cell death. Other mechanisms like necrosis and autophagy also play roles in tumor development and can interact with apoptosis in complex ways. The relative contribution of each type of cell death to tumorigenesis in different contexts remains an active area of research.
  • Limitations of Experimental Models: In vitro studies using isolated cells provide valuable insights on specific aspects of apoptosis, but they often lack the complex cellular and environmental context present in vivo. This can limit the generalizability of findings to real-world scenarios.
  • Challenges in Therapeutic Targeting: While targeting the apoptotic pathway holds promise for cancer treatment, effectively manipulating these processes in vivo without unintended consequences remains a significant challenge. Additionally, tumors may develop resistance mechanisms to therapies targeting apoptosis, hindering their long-term effectiveness.

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
Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.  More help
Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). More help
Known Feedforward/Feedback loops influencing this KER
Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help




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

Schmitt, C. A., et al. (2000). Senescence and apoptosis. Oncogene, 19(56), 6207-6210.

Schottenfeld, D., & Beebe-Wood, L. (2012). Chronic inflammation and cancer prevention: A bird's-eye view. Nature Reviews Cancer, 12(3), 189-201.

Zhang, J., et al. (2008). The role of the BCL-2 family in the development of transgenic mouse models of cancer. Current Molecular Medicine, 8(1), 70-82.

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

Fulda, S., & Debatin, K. M. (2007). Apoptosis signaling in cancer. Experimental Cell Research, 313(9), 1503-1515.

Luo, X., & Heng, H. H. (2003). Apoptosis and cancer therapy: lessons from the past and new directions. Current Pharmaceutical Design, 9(21), 1803-1816.

Schmitt, C. A., et al. (2000. Senescence and apoptosis. Oncogene, 19(56), 6207-6210.