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Relationship: 1929

Title

A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Epithelial-mesenchymal transition leads to Resistant gastric cancer

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Epithelial-mesenchymal transition

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

Resistant gastric cancer

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
Increases in cellular reactive oxygen species and chronic reactive oxygen species leading to human treatment-resistant gastric cancer	adjacent	Moderate	Moderate	Shihori Tanabe (send email)	Open for comment. Do not cite	EAGMST Under Review

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
Unspecific	High

Life Stage Applicability

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

Term	Evidence
All life stages	High

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

Some population of the cells exhibiting EMT demonstrates the feature of cancer stem cells (CSCs), which are related to cancer malignancy (Shibue & Weinberg, 2017; Shihori Tanabe, 2015a, 2015b; Tanabe, Aoyagi, Yokozaki, & Sasaki, 2015).

EMT phenomenon is related to cancer metastasis and cancer therapy resistance (Smith & Bhowmick, 2016; Tanabe, 2013). The increased expression of enzymes that degrade the extracellular matrix components and the decrease in adhesion to the basement membrane in EMT induces the cell to escape from the basement membrane and metastasis (Smith & Bhowmick, 2016). Morphological changes observed during EMT are associated with therapy resistance (Smith & Bhowmick, 2016).

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

The morphological and physiological changes associated with EMT are involved in invasiveness and drug resistance (Shibue & Weinberg, 2017). The EMT-activated particular carcinoma cells in primary tumors invade the surrounding stroma (Shibue & Weinberg, 2017). The EMT –activated carcinoma cells interact with the surrounding extracellular matrix protein to induce focal adhesion kinase and extracellular signal-related kinase activation, followed by the transforming growth factor-beta (TGFbeta) and canonical and/or noncanonical Wnt pathways to induce cancer stem cell (CSC) properties which contribute to the drug resistance (Shibue & Weinberg, 2017).

EMT-associated down-regulation of multiple apoptotic signaling pathways induces drug efflux and slows cell proliferation to induce the general resistance of carcinoma cells to anti-cancer drugs (Shibue & Weinberg, 2017).

Snail, an EMT-related transcription factor, induces the expression of the AXL receptor tyrosine kinase, which enables the cancer cells to survive by the activation of AXL signaling triggered by the binding of its ligand growth arrest-specific protein 6 (GAS6)(Shibue & Weinberg, 2017).

The EMT-activated cells evade the lethal effect of cytotoxic T cells, which include the elevated expression of programmed cell death 1 ligand (PD-L1) which binds to the programmed cell death protein 1 (PD-1) inhibitory immune-checkpoint receptor on the cell surface of cytotoxic T cells (Shibue & Weinberg, 2017).

Empirical Evidence

Provides specific (citable) evidence that supports the idea of a change in the upstream KE (KEupstream) leading to, or being associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient. More help

Incidence concordance

Slug/Snai2, a ces-1-related zinc finger transcription factor gene, confers resistance to p53-mediated apoptosis of hematopoietic progenitors by repressing PUMA (also known as BBC3, encoding Bcl-2-binding component 3) (Inukai et al., 1999; Shibue & Weinberg, 2017; W.-S. Wu et al., 2005).

EMT activation induces the expression of multiple members of the ATP-binding cassette (ABC) transporter family, which results in the resistance to doxorubicin (Saxena, Stephens, Pathak, & Rangarajan, 2011; Shibue & Weinberg, 2017)

TGFbeta-1 induced EMT results in the acquisition of cancer stem cell (CSC) like properties (Pirozzi et al., 2011; Shibue & Weinberg, 2017).

Snail-induced EMT induces cancer metastasis and resistance to dendritic cell-mediated immunotherapy (Kudo-Saito, Shirako, Takeuchi, & Kawakami, 2009).

Zinc finger E-box-binding homeobox (ZEB1)-induced EMT results in the relief of miR-200-mediated repression of programmed cell death 1 ligand (PD-L1) expression, a major inhibitory ligand for the programmed cell death protein (PD-1) immune-checkpoint protein on CD8+ cytotoxic T lymphocyte (CTL), subsequently the CD8⁺ T cell immunosuppression and metastasis (Chen et al., 2014).

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

The reversing process of EMT, which names as a mesenchymal-epithelial transition (MET), maybe one of the candidates for the anti-cancer therapy, where the plasticity of the cell phenotype is of importance and under investigation (Shibue & Weinberg, 2017).

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

ABC transporters that are related to drug resistance are overexpressed in the EMT-activated cells (Saxena et al., 2011). The expression of PD-L1, which binds to the PD-1 on the cytotoxic T cells, is up-regulated in EMT-activated cells, which results in the inhibition of cancer immunity and the resistance to cancer therapy (Shibue & Weinberg, 2017).

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. More help

Response-response Relationship

Provides sources of data that define the response-response relationships between the KEs. More help

Induction of EMT by TGFbeta and Twist increases the gene expression of EMT markers such as Snail, Vimentin, N-cadherin, and ABC transporters including ABCA3, ABCC1, ABCC3, and ABCC10 (Saxena et al., 2011).

Human mammary epithelial cells (HMLE) stably expressing Twist, FOXC2 or Snail demonstrates the increased cell viability compared to control HMLE in the treatment with about 0.3, 3, 30 mM of doxorubicin, dose-dependently (Saxena et al., 2011).

Time-scale

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

The treatment with doxorubicin for 48 hours demonstrates the increase in the cell viability in Twist/FOXC2/Snail overexpressed HMLE compared to control HMLE (Saxena et al., 2011).

The inhibition of Twist or Zeb1 with small interference RNA (siRNA) induced the inhibition of cell viability compared to control MDAMB231 cells treated with doxorubicin for 48 hours (Saxena et al., 2011).

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

The investigation of EMT-CSC relations is important to understand the relationship between EMT and cancer malignancy. Non-CSCs in cancer can spontaneously undergo EMT and dedifferentiate into new CSC, subsequently induce the regeneration of tumorigenic potential (Marjanovic, Weinberg, & Chaffer, 2013; Shibue & Weinberg, 2017).

The plastic CSC theory demonstrates the bidirectional conversions between non-CSCs and CSCs, which may contribute to the acquisition of cancer malignancy in EMT-activated cells (Marjanovic et al., 2013).

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

EMT induces cancer invasion, metastasis (Homo sapiens)(P. Zhang et al., 2015).

EMT is related to cancer drug resistance in MCF-7 human breast cancer cells (Homo sapiens)(B. Du & Shim, 2016).

References

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

Chen, L., Gibbons, D. L., Goswami, S., Cortez, M. A., Ahn, Y.-H., Byers, L. A., . . . Qin, F. X.-F. (2014). Metastasis is regulated via microRNA-200/ZEB1 axis control of tumour cell PD-L1 expression and intratumoral immunosuppression. Nature communications, 5, 5241-5241. doi:10.1038/ncomms6241

Du, B., & Shim, J. S. (2016). Targeting Epithelial-Mesenchymal Transition (EMT) to Overcome Drug Resistance in Cancer. Molecules, 21(7). doi:10.3390/molecules21070965

Inukai, T., Inoue, A., Kurosawa, H., Goi, K., Shinjyo, T., Ozawa, K., . . . Look, A. T. (1999). SLUG, a ces-1-Related Zinc Finger Transcription Factor Gene with Antiapoptotic Activity, Is a Downstream Target of the E2A-HLF Oncoprotein. Molecular Cell, 4(3), 343-352. doi:https://doi.org/10.1016/S1097-2765(00)80336-6

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:https://doi.org/10.1016/j.ccr.2009.01.023

Marjanovic, N. D., Weinberg, R. A., & Chaffer, C. L. (2013). Cell plasticity and heterogeneity in cancer. Clinical chemistry, 59(1), 168-179. doi:10.1373/clinchem.2012.184655

Pirozzi, G., Tirino, V., Camerlingo, R., Franco, R., La Rocca, A., Liguori, E., . . . Rocco, G. (2011). Epithelial to mesenchymal transition by TGFβ-1 induction increases stemness characteristics in primary non small cell lung cancer cell line. PLoS One, 6(6), e21548-e21548. doi:10.1371/journal.pone.0021548

Saxena, M., Stephens, M. A., Pathak, H., & Rangarajan, A. (2011). Transcription factors that mediate epithelial-mesenchymal transition lead to multidrug resistance by upregulating ABC transporters. Cell death & disease, 2(7), e179-e179. doi:10.1038/cddis.2011.61

Shibue, T., & Weinberg, R. A. (2017). EMT, CSCs, and drug resistance: the mechanistic link and clinical implications. Nat Rev Clin Oncol, 14(10), 611-629. doi:10.1038/nrclinonc.2017.44

Smith, B. N., & Bhowmick, N. A. (2016). Role of EMT in Metastasis and Therapy Resistance. J Clin Med, 5(2). doi:10.3390/jcm5020017

Tanabe, S. (2013). Perspectives of gene combinations in phenotype presentation. World journal of stem cells, 5(3), 61-67. doi:10.4252/wjsc.v5.i3.61

Tanabe, S. (2015a). Origin of cells and network information. World journal of stem cells, 7(3), 535-540. doi:10.4252/wjsc.v7.i3.535

Tanabe, S. (2015b). Signaling involved in stem cell reprogramming and differentiation. World journal of stem cells, 7(7), 992-998. doi:10.4252/wjsc.v7.i7.992

Tanabe, S., Aoyagi, K., Yokozaki, H., & Sasaki, H. (2015). Regulated genes in mesenchymal stem cells and gastric cancer. World journal of stem cells, 7(1), 208-222. doi:10.4252/wjsc.v7.i1.208

Wu, W.-S., Heinrichs, S., Xu, D., Garrison, S. P., Zambetti, G. P., Adams, J. M., & Look, A. T. (2005). Slug Antagonizes p53-Mediated Apoptosis of Hematopoietic Progenitors by Repressing puma. Cell, 123(4), 641-653. doi:https://doi.org/10.1016/j.cell.2005.09.029

Zhang, P., Sun, Y., & Ma, L. (2015). ZEB1: at the crossroads of epithelial-mesenchymal transition, metastasis and therapy resistance. Cell Cycle, 14(4), 481-487. doi:10.1080/15384101.2015.1006048