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Relationship: 2071

Title

The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

Proliferation/ beta-catenin activation leads to Epithelial-mesenchymal transition

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. 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

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Chronic reactive oxygen species leading to human treatment-resistant gastric cancer adjacent Moderate Moderate Shihori Tanabe (send email) Under Development: Contributions and Comments Welcome Under Development

Taxonomic Applicability

Select one or more structured terms 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. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help
Term Scientific Term Evidence Link
Homo sapiens Homo sapiens High NCBI

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help
Sex Evidence
Unspecific High

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help
Term Evidence
All life stages High

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

Beta-catenin activation, of which mechanism include the stabilization of the dephosphorylated beta-catenin and translocation of beta-catenin into the nucleus, induce the formation of beta-catenin-TCF complex and transcription of transcription factors such as Snail, Zeb and Twist (Clevers & Nusse, 2012) (Ahmad et al., 2012; Pearlman, Montes de Oca, Pal, & Afaq, 2017; Sohn et al., 2019; Yang et al., 2019).

EMT-related transcription factors including Snail, ZEB and Twist are up-regulated in cancer cells (Diaz, Vinas-Castells, & Garcia de Herreros, 2014). The transcription factors such as Snail, ZEB and Twist bind to E-cadherin (CDH1) promoter and inhibit the CDH1 transcription via the consensus E-boxes (5’-CACCTG-3’ or 5’-CAGGTG-3’), which leads to EMT (Diaz et al., 2014).

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help
Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility 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 (see page 40 of the User Handbook for further information).   More help

The treatment of human gastric cancer cells with INC280, which inhibits c-MET overexpressed in diffuse-type gastric cancer with poor prognosis, shows downregulation in beta-catenin and Snail expression,(Sohn et al., 2019).

The treatment with garcinol, a polyisoprenylated benzophenone derivative that is obtained from Garcinia indica extract, induced ZEB1 and ZEB2 down-regulation, increase in phosphorylated beta-catenin and decrease in nuclear beta-catenin in human breast cancer cells (Ahmad et al., 2012).

Sortilin, a member of the Vps10p sorting receptor family which is highly expressed in high-glade malignant glioma, positively regulates GSK-3beta/beta-catenin/Twist signaling pathway in glioblastoma (Yang et al., 2019).

The transcription factors such as Snail, Zeb and Twist inhibit the CDH1 expression through their binding towards the promoter of CDH1, which leads to inhibition of cell adhesion and EMT (Diaz et al., 2014)

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

It is possible that the inhibition of ZEB1 and ZEB2 by garcinol treatment is caused by down-regulation of NFkappaB and Wnt/beta catenin signaling (Ahmad et al., 2012).

The EMT is induced different transcription factors other than Zeb, Twist and Snail, which includes E47 and KLF8 (Diaz et al., 2014).

Zeb, Twist and Snail may activate or inactivate different genes or molecules to induce phenomena related to EMT and other phenomena other than EMT (Li & Balazsi, 2018).

Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help

The treatment with AF38469, a sortilin inhibitor, in 0, 100, 200, 400, 800, and 1600 nM concentration inhibited beta-catenin and Twist expression dose-dependently in human glioblastoma cells (Yang et al., 2019).

Snail (SNAI1) mRNA is methylated and N6-methyladenosine (m6A) in its coding region (CDS) and 3’ untranslated region (3’UTR) are significantly enriched during EMT progression (Lin et al., 2019). The m6A enrichment fold of SNAI1 mRNA in EMT cells is about 2.3-fold greater than in control cells (Lin et al., 2019).

Time-scale
This sub-section should be used to provide 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?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help

The treatment with 25 uM of garcinol for 48 hours induced increase in phosphorylated beta-catenin and decreased nuclear beta-catenin protein and ZEB1/ZEB2 mRNA in human breast cancer cells (Ahmad et al., 2012).

The treatment with AF38469, a sortilin inhibitor, for 0, 2, 4, 8, 16, or 24 hours shows that the expression of beta-catenin and Twist decrease in 8 hours followed by the subsequent decrease in 16 and 24 hours in human gliobastoma cells (Yang et al., 2019).

Snail (SNAI1) transfection for 48 hours induce the repression of E-cadherin (CDH1) protein expression (Lin et al., 2019).

SNAI1 mRNA in polysome is up-regulated in EMT-undergoing HeLa cells treated with 10 ng/ml of TGF-beta for 3 days compared with control cells (Lin et al., 2019).

Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help

The proto-oncogene MET regulates beta-catenin and Snail expression (Sohn et al., 2019).

The inhibition of GSK3beta by SB216763 induced expression of beta-catenin and Twist, as well as mesenchymal markers such as N-cadherin, vimentin and MMP9 (Yang et al., 2019).

The decrease in E-cadherin (CDH1), a cell adhesion molecule, is related to EMT (Diaz et al., 2014).

Methyltransferase-like 3 (METTL3) modulates methylation of Snail (SNAI1) mRNA and EMT (Lin et al., 2019).

Binding of beta-catenin to members of the TCF/LEF family transcription factors increase gene expression related to EMT such as Twist and decrease E-cadherin protein expression (Qualtrough, Rees, Speight, Williams, & Paraskeva, 2015).

Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

The inhibited expression of phosphorylated GSK3beta, beta-catenin and Twist by sortilin inhibition is reversed by GSK3beta inhibition. Furthermore, twist overexpression by lentivirus increased the inhibited expression of N-cadherin, MMP9 and vimentin and reverses the inhibitory effect of AF38469 on sortilin, which suggests that sortilin induces glioblastoma invasion mainly via GSK3beta/beta-catenin/Twist induced mesenchymal transition (Yang et al., 2019).

The inhibition of Hedgehog signaling pathway with cyclopamine reduces beta-catenin-TCF transcriptional activity, decreases the Twist expression, induces E-cadherin expression and inhibits EMT (Qualtrough et al., 2015).

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help
  • The inhibition of c-MET decreases the expression of beta-catenin and Snail in human diffuse-type gastric cancer (Homo sapiens) (Sohn et al., 2019).
  • The treatment with garcinol decreases the expression of beta-catenin and ZEB1/ZEB2 in human breast cancer cells (Homo sapiens) (Ahmad et al., 2012).
  • Zeb1 activation leads to EMT via Prex1 activation in NCH421k, NCH441, and NCH644 human glioblastoma model cells (Homo sapiens) (Rosmaninho et al., 2018).
  • Zeb1 siRNA induced the suppression of EMT in SGC-7901 human gastric cancer cell line (Homo sapiens) (Xue et al., 2019). Snail induces EMT in SAS and HSC-4 human head and neck squamous cancer cells (Homo sapiens) (Ota et al., 2016).
  • Snail induces EMT in B16-F10 murine melanoma cells (Mus musculus) (Kudo-Saito, Shirako, Takeuchi, & Kawakami, 2009; Wang, Shi, Chai, Ying, & Zhou, 2013).
  • Twist1 is related to EMT in MCF-7 and MDA-MB-231 human breast cancer cell lines (Homo sapiens) (Menendez-Menendez et al., 2019).
  • Twist induces EMT in Huh7 human hepatocellular carcinoma cell lines (Homo sapiens) (Hu et al., 2019).

References

List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

Ahmad, A., Sarkar, S. H., Bitar, B., Ali, S., Aboukameel, A., Sethi, S., . . . Sarkar, F. H. (2012). Garcinol regulates EMT and Wnt signaling pathways in vitro and in vivo, leading to anticancer activity against breast cancer cells. Mol Cancer Ther, 11(10), 2193-2201. doi:10.1158/1535-7163.MCT-12-0232-T

Batlle, E., Sancho, E., Francí, C., Domínguez, D., Monfar, M., Baulida, J., & García de Herreros, A. (2000). The transcription factor Snail is a repressor of E-cadherin gene expression in epithelial tumour cells. Nature Cell Biology, 2(2), 84-89. doi:10.1038/35000034

Clevers, H., & Nusse, R. (2012). Wnt/beta-catenin signaling and disease. Cell, 149(6), 1192-1205. doi:10.1016/j.cell.2012.05.012

Diaz, V. M., Vinas-Castells, R., & Garcia de Herreros, A. (2014). Regulation of the protein stability of EMT transcription factors. Cell Adh Migr, 8(4), 418-428. doi:10.4161/19336918.2014.969998

Hu, B., Cheng, J. W., Hu, J. W., Li, H., Ma, X. L., Tang, W. G., . . . Yang, X. R. (2019). KPNA3 Confers Sorafenib Resistance to Advanced Hepatocellular Carcinoma via TWIST Regulated Epithelial-Mesenchymal Transition. Journal of Cancer, 10(17), 3914-3925. doi:10.7150/jca.31448

Kudo-Saito, C., Shirako, H., Takeuchi, T., & Kawakami, Y. (2009). Cancer Metastasis Is Accelerated through Immunosuppression during Snail-Induced EMT of Cancer Cells. Cancer Cell, 15(3), 195-206. doi:10.1016/j.ccr.2009.01.023

Li, C., & Balazsi, G. (2018). A landscape view on the interplay between EMT and cancer metastasis. NPJ Syst Biol Appl, 4, 34. doi:10.1038/s41540-018-0068-x

Lin, X., Chai, G., Wu, Y., Li, J., Chen, F., Liu, J., . . . Wang, H. (2019). RNA m(6)A methylation regulates the epithelial mesenchymal transition of cancer cells and translation of Snail. Nat Commun, 10(1), 2065. doi:10.1038/s41467-019-09865-9

Menendez-Menendez, J., Hermida-Prado, F., Granda-Diaz, R., Gonzalez, A., Garcia-Pedrero, J. M., Del-Rio-Ibisate, N., . . . Martinez-Campa, C. (2019). Deciphering the Molecular Basis of Melatonin Protective Effects on Breast Cells Treated with Doxorubicin: TWIST1 a Transcription Factor Involved in EMT and Metastasis, a Novel Target of Melatonin. Cancers (Basel), 11(7). doi:10.3390/cancers11071011

Ota, I., Masui, T., Kurihara, M., Yook, J. I., Mikami, S., Kimura, T., . . . Kitahara, T. (2016). Snail-induced EMT promotes cancer stem cell-like properties in head and neck cancer cells. Oncol Rep, 35(1), 261-266. doi:10.3892/or.2015.4348

Pearlman, R. L., Montes de Oca, M. K., Pal, H. C., & Afaq, F. (2017). Potential therapeutic targets of epithelial-mesenchymal transition in melanoma. Cancer Lett, 391, 125-140. doi:10.1016/j.canlet.2017.01.029

Peinado, H., Olmeda, D., & Cano, A. (2007). Snail, Zeb and bHLH factors in tumour progression: an alliance against the epithelial phenotype? Nat Rev Cancer, 7(6), 415-428. doi:10.1038/nrc2131

Qualtrough, D., Rees, P., Speight, B., Williams, A. C., & Paraskeva, C. (2015). The Hedgehog Inhibitor Cyclopamine Reduces beta-Catenin-Tcf Transcriptional Activity, Induces E-Cadherin Expression, and Reduces Invasion in Colorectal Cancer Cells. Cancers (Basel), 7(3), 1885-1899. doi:10.3390/cancers7030867

Rosmaninho, P., Mükusch, S., Piscopo, V., Teixeira, V., Raposo, A. A., Warta, R., . . . Castro, D. S. (2018). Zeb1 potentiates genome-wide gene transcription with Lef1 to promote glioblastoma cell invasion. The EMBO Journal, 37(15), e97115. doi:10.15252/embj.201797115

Sohn, S. H., Kim, B., Sul, H. J., Kim, Y. J., Kim, H. S., Kim, H., . . . Zang, D. Y. (2019). INC280 inhibits Wnt/beta-catenin and EMT signaling pathways and its induce apoptosis in diffuse gastric cancer positive for c-MET amplification. BMC Res Notes, 12(1), 125. doi:10.1186/s13104-019-4163-x

Wang, Y., Shi, J., Chai, K., Ying, X., & Zhou, B. P. (2013). The Role of Snail in EMT and Tumorigenesis. Current cancer drug targets, 13(9), 963-972. doi: 10.2174/15680096113136660102

Wawruszak, A., Kalafut, J., Okon, E., Czapinski, J., Halasa, M., Przybyszewska, A., . . . Stepulak, A. (2019). Histone Deacetylase Inhibitors and Phenotypical Transformation of Cancer Cells. Cancers (Basel), 11(2). doi:10.3390/cancers11020148

Xue, Y., Zhang, L., Zhu, Y., Ke, X., Wang, Q., & Min, H. (2019). Regulation of Proliferation and Epithelial-to-Mesenchymal Transition (EMT) of Gastric Cancer by ZEB1 via Modulating Wnt5a and Related Mechanisms. Medical science monitor : international medical journal of experimental and clinical research, 25, 1663-1670. doi:10.12659/MSM.912338

Yang, W., Wu, P. F., Ma, J. X., Liao, M. J., Wang, X. H., Xu, L. S., . . . Yi, L. (2019). Sortilin promotes glioblastoma invasion and mesenchymal transition through GSK-3beta/beta-catenin/twist pathway. Cell Death Dis, 10(3), 208. doi:10.1038/s41419-019-1449-9