To the extent possible under law, AOP-Wiki has waived all copyright and related or neighboring rights to KER:2612

Relationship: 2612

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

Increase activation, Nuclear factor kappa B (NF-kB) leads to Antagonism, Estrogen receptor

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

Increase activation, Nuclear factor kappa B (NF-kB)

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

Antagonism, Estrogen receptor

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
DNA damage and mutations leading to Metastatic Breast Cancer	adjacent	Moderate	Moderate	Agnes Aggy (send email)	Under development: Not open for comment. Do not cite

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
human	Homo sapiens	High	NCBI
mice	Mus sp.	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

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

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

Upstream event: Increased, NF kB activity

Downstream event: Estrogen receptor, Reduced

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

Activation NF-κB in breast cancer leads to loss of Estrogen Receptor (ER) expression and Human Epidermal Growth Fac- tor Receptor 2 (HER-2) overexpressed via epidermal growth factor receptor (EGFR) and Mitogen Activated Protein Kinase (MAPK) pathway (Laere et al.,2007). Indeed, the binding of epidermal growth factor (EGF) to its receptor (EGFR) activates NF-B, which most likely contributes to this transcription factor's increased activity in ER negative breast cancer cells (Shostak et al.,2011). Because of constitutive production of cytokines and growth factors, loss of ER function has been linked to constitutive NF-kB activity and hyperactive MAPK, resulting in aggressive, metastatic, hormone-resistant malignancies (Ali et al., 2002). Activation of the progesterone receptor can reduce DNA binding and transcriptional activity by inhibiting NF-B-driven gene expression (Kalkhoven et al., 1996). HER-2 stimulates NF-B via the conventional route, which includes IKK (Merkhofer et al., 2010).

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

-NF-kB activation in breast cancer has been extensively documented in oestrogen receptor negative (ER) breast tumours and ER breast cancer cell lines, implying a significant inhibitory interaction between both signalling pathways (Biswas et al, 2000, 2001, 2004; Zhou et al, 2005). A rise in both NF-kB DNA-binding activity (Nakshatri et al, 1997) and expression of NF-kB target genes such IL8 coincides with a transition from oestrogen dependence to oestrogen independence in breast cancer, indicating inhibitory cross-talk. The fact that some breast tumours that are resistant to the tumoricidal action of anti-estrogens become sensitised to apoptosis and show a drop in NF-kB activity after treatment with oestrogen supports the inverse relationship between ER and NF-kB activity.

-This shows that oestrogen's proapoptotic actions in these tumours are mediated via NF-kB suppression.

Empirical Evidence

In this section authors are encouraged to cite specific evidence that supports the idea that a change in the upstream KE (KEupstream) will lead to, or is associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient. Given the likelihood that new empirical support will be developed over time, particularly as various AOPs are tested and applied, it is most practical to provide empirical support in the form of bulleted lists or tables that include a short description of the nature of the empirical support along with the corresponding reference(s).In particular, it is useful to cite evidence showing that stressors that perturb KEupstream also perturb KEdownstream. Because this section of the KER description cites evidence from specific studies, it is also helpful to provide as much detail about the toxicological and biological context in which the measurements were made, as is feasible, including the stressor(s) tested, the effective doses at each KE, etc. While the KER itself is not intended to be stressor-specific, those details can aid the overall assessment of the individual AOPs that include that KER. These details also help inform the question of consistency of supporting data, consistency across different biological contexts for which the KER is relevant, and the applicability domain of the KER. However, authors are cautioned that this evidence should focus on data that only relate KEupstream to KEdownstream, and should avoid reference to other KEs, KERs and AOPs as much as possible in order to maintain modularity of the KER. Please see pages 40-41 of the User Handbook for more information. More help

In specific subclasses of human breast cancer cells and tumour tissue specimens, an enhanced level of activated NF-kB is found, primarily in erbB2-overexpressing ER-negative breast cancer (Biswas et al 2000;2003).

Singh et al explored a variety of methods to inhibit NF-kB activation in ER-negative breast cancer cells and looked at the effects on cell proliferation, apoptosis, and tumour growth in xenografts(Singh et al.,2007). Several cell lines were utilised as representative cultured cell models for subclasses of human breast cancer, including ER negative and erbB2 positive (SKBr3 and MDA-MB453), ER negative and erbB1 positive (MDA-MB231), and ER positive and erbB1/erbB2 negative (MCF-7). IKK, the primary kinase in NF-nB activation, was disabled using a conditional dominant-negative gene construct and small-molecule inhibitors. Bortezomib, a proteasome inhibitor, was used to prevent NF-kB activation.

-The study compared the results of NF-kB activation patterns in ER-negative and erbB2-positive SKBr3 and MDA-MB453 cell lines as representative functional systems of this subclass of human breast cancer to the ER-positive and erbB2-negative MCF-7 cell line. Growing SKBr3 cells in deficient (minimum) media followed by supplementation with the particular mitogenic growth factor HRG (+HRG) allowed the degree of activated NF-kB to be experimentally controlled. This therapy increased IKK activity in as little as 15 minutes, while also increasing NF-nB DNA-binding activity and NF-nB–driven reporter gene expression. These findings imply that HRG-initiated signalling in erbB2-positive cells is mediated by IKK-induced NF-kB activation. MDA-MB453, a second erbB2-positive and ER-negative breast cancer cell line, showed similar results.

In a prospective cohort study, Sampepajung et al used immunohistochemistry (IHC) to examine NF-B expression and intrinsic subtypes of breast cancer tissue and found a significant correlation between negative ER and overexpression of NF-B (p 0.05), with overexpression of NF-B being higher in negative ER (77.3 percent) compared to positive ER (47.4 percent )( Sampepajung et al., 2021)

Laere et al suggested that activation of NF-kB in inflammatory breast cancer (IBC) is associated with loss of estrogen receptor (ER) expression, indicating a potential crosstalk between NF-kB and ER(Laere et al.,2007).

In this study, the activation of NF-kB in IBC and non-IBC cells was investigated in relation to ER and EGFR expression, ErbB2 expression, and MAPK hyperactivation.The expression of eight NF-kB target genes was associated with the expression of a qRT–PCR-based ER signature in tumours with and without transcriptionally active NF-kB. Hierarchical clustering was performed using a combined ER/NF-kB signature. MAPK hyperactivation was associated to tumour phenotype, ER and EGFR overexpression, and/or ErbB2 overexpression, according to a recently reported MAPK signature.

In breast tumours without transcriptionally active NF-kB, the expression of most ER-modulated genes was much higher. Furthermore, the expression of most ER-modulated genes was highly anticorrelated with that of most NF-kB target genes, demonstrating that ER and NF-kB activity are inversely related.

-The activation of the transcription factors of ER and NF-kB are inversely linked.

Indra et al employed the prospective cohort approach to investigate 62 samples in an observational analysis.The positive and negative expression of NF-B, ER, and HER2 overexpression were among the data used in this investigation(Indra et al.,2021). The cases were separated into two groups: those who responded to neoadjuvant chemotherapy and those who did not. Negative NF-B expression (82.5%), positive HER2 status (85.7%), and negative ER status (85.7%) were all associated with a larger percentage of responding individuals (71.9 percent ).

-NF-B expression, ER status, and HER2 all had a substantial relationship with the response to anthracycline-based neoadjuvant chemotherapy for locally advanced breast cancer, with NF-B expression having the strongest link.

-A higher percentage of responding participants (71.9 percent) had a negative ER status, indicating that ER expression and chemotherapy response have a substantial relationship (p 0.05).

This finding is consistent with alanalysis by Osako et al, of 103 individuals with locally advanced KPD. Neoadjuvant chemotherapy with anthracyclines and taxanes was given to the patients. The pCR chemotherapy results were significantly correlated with negative ER and PR expression results (Osako et al.,2012).

The expression of NF-B, HER2, and ER status has a strong association with chemotherapy response, according to these findings. Multivariate analysis of the specific association between NF-B expression and chemotherapeutic response revealed that NF-B expression and HER2 status were both related with chemotherapy response , whereas ER status had no such relationship.

Sarkar et al assessed NF-B expression in breast cancer tissue and fibroadenoma tissue as test samples and controls, respectively. The Western Blot Technique was used to measure the p65 protein from the NF-kB superfamily of transcription factors. Immunohistochemistry was used to determine the levels of ER, PR, and HER-2/neu(Sarkar et al., 2013).Large tumour size (5 cm), high grade tumours, negative ER, negative PR, and positive HER-2/neu are all related with -NF-B/p65.

-NF-B activation was shown to be more common in ER-negative tumours (81.8%) than in ER-positive cancers (38.5%), a statistically significant difference.

-NF-B expression is linked to ER negative status and is also linked to a higher NPI value, which indicates a poor prognosis.

NF-kB activity is elevated in hormone-independent and ER-negative breast tumors , and hyperactiva- tion of MAPK leads to enhanced NF-kB activity through induction of autocrine factors such as HB- EGF (Norris et l.,1999;Pearson et l.,2001;McCarthy et l.,1995;Troppamair et l.,1998). NF-kB activity is elevated in MCF-7 breast cancer cells with elevated MAPK activity(Holloway et l.,2004).

-NF-kB activity is about 5-fold higher than parental MCF-7 in all of our model cell lines. This elevated NF-kB activity is attributable to hyperactivation of MAPK because NF-kB activity is returned to normal levels (basal levels in co-MCF7 cells) by dnERKs 1 and 2 .

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

No specific uncertainties and inconsistencies reported to the best of our knowledge.

Quantitative Understanding of the Linkage

The quantitative understanding section of the KER description is intended to capture 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. Empirical support addresses whether data between the two KEs are consistent with the patterns that are expected if the upstream event is causing the downstream event to occur, while the quantitative understanding section helps to define the precision with which the state of the downstream KE can be predicted from knowledge of the state of the upstream KE. These quantitative relationships may be defined in terms of correlations, response-response relationships, dose-dependent transitions or points of departure (i.e., a threshold of change in KEupstream needed to elicit a change in KEdownstream), etc. They may take the form of simple mathematical equations or sophisticated biologically-based computational models that consider other modulating factors such as compensatory responses, or interactions with other biological or environmental variables. Regardless of form, the idea is to briefly describe what is known regarding the quantitative relationship between the KEs and cite appropriate literature that defines those relationships and/or provides support for them.Data that confer quantitative understanding of a KER are not necessarily mutually exclusive from those addressing other weight of evidence considerations. In that respect, the quantitative understanding section of the KER description is not intended to be redundant with the other WoE sections. Rather, it is intended to aid application of the AOP by allowing a reader to rapidly identify the relationships that would support a quantitative prediction of the probability or magnitude of change in KEdownstream based on a known state of KEupstream. For transparency, the toxicological and biological context in which the quantitative relationships were defined should be indicated within the description. However, the ultimate goal is to identify quantitative relationships that generalize across the entire applicability domain of the two KEs being linked via the KER. More help

	Method/ measurement reference	Reliability	Strength of evidence	Assay fit for purpose	Repeatability/ reproducibility	Direct measure
Human cell line	qPCR, western blotting, immunoprecipitation, immunofluorescent microscopy, Luciferase reporter assay EMSA, IHC,Cell viability assay	Yes	Strong	Yes	Yes	Yes
Humans	qRT-PCR, immunohistochemistry	Yes	Strong	Yes	Yes	Yes
Mouse(A1)	EMSA,Autoradiography Immunofluorescent microscopy, Westernblotting	Yes	Strong	Yes	Yes	Yes

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

Differential Sensitivity of ER α and ERβ Cells to the NF-kB Inhibitor Go6976. A differential sensitivity to Go6976 by ER α and ERβ breast cancer cells was observed (Holloway et al.,2004). The ER α cells were more sensitive and less viable after treatment with this NF-kB inhibitor. The IC50 (50% killing) by Go6976 was 1 mM for Era of MDA-MB435 and MDA-MB231 breast cancer cells, whereas it was greater than 10 mM for ERa of MCF-7 and T47D or the normal mammary epithelial H16N cells . At 10 mM Go6976, about 80% of the ERa cells were killed, whereas only 15–30% of ERa and normal H16N cells were sensitive to this compound. The relative resistance of the H16N normal human mammary cells indicates a possible high therapeutic index of Go6976 against ERa cancer cells.

This observation is consistent with the previously observed role of NF-kB as an antiapoptotic agent. FACS analysis demonstrated accumulation of sub-G1 population (67%) in Go6976- treated (48 h at 1 mM) ERa vs. only 10–15% in ERa cells, indicating enhanced apoptotic cell death preferentially of ERa cells caused by this low molecular weight compound.

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

Key events connected by this KER occur within hours of exposure.

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

Estradiol has been shown to decrease transcriptional activity and expression of NF-kB in a variety of experimental models (Biswas et al., 2005;Lobanova et al.,2007). Estrogen treatment of MCF-7 or MCF-7/H cells resulted in a significant suppression of NF-kB activity in both cell lines, according to research. The antiestrogen tamoxifen boosted NF-kB activity in the cells, indicating that ER plays a key role in NF-kB down-regulation in both parent and hypoxia-tolerant cells.

-MCF-7/T2H cells were discovered to have a partial tolerance to acute cobalt chloride-induced hypoxia while maintaining their estrogen-independent phenotype. In contrast to the MCF-7/H subline, MCF-7/T2H cells had a non-affected baseline NF-kB level, indicating that estrogens are responsible for NF-kB downregulation (Scherbakov et al., 2009).

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

- Multiple pathways are implicated in the crosstalk between NF-KB and ER. Through many mechanisms, including collaboration with FOXA1 to strengthen latent ER-binding sites and trigger translation of their synergistic genes, NF-KB directly interacts with the DNA-binding activity of ER (Franco et al. 2015). Furthermore, NF-KB affects ER via interacting with its ER co-activator or co-repressor, which changes ER transcriptional activity (Park et al. 2005). Similar to ER, NF-KB has been reported to have a role as a downstream effector for the growth factor pathway, which is recognized to be involved in both ligand-dependent and non-ligand-dependent ER activation, leading to resistance to a wide range of anti- oestrogen drugs (Zhou et al. 2005a, Sas et al. 2012, Frasor et al. 2015).

-NF-KB is also involved in the anti-apoptotic pathway and immune surveillance systems, both of which have been linked to endocrine resistance (Hu et al. 2015; Lim et al. 2016). Furthermore, NF-KB inhibition of ER activity has been observed. The zinc finger repressor B-lymphocyte-induced maturation protein (BLIMP1), which can bind to the ER promoter area and restrict ER transcription, is triggered by the NFB subunit RelB. (Wang et al. 2009). Increasing data suggests that NF-KB plays an important role in the complexities of the endocrine resistance environment in breast cancer.

-NF-KB and ERS1 mutations in breast cancer patients who are resistant to endocrine therapy

TNF needs NF-KB and FOXA1 to change the breast cancer cell transcriptome by modulating latent ER-binding sites.

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

KER has been observed in humans and animals irrespective of the gender and life stage.

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

Ali, S., & Coombes, R. C. (2002). Endocrine-responsive breast cancer and strategies for combating resistance. Nature Reviews Cancer, 2(2), 101-112.

Kalkhoven, E., Wissink, S., van der Saag, P. T., & van der Burg, B. (1996). Negative Interaction between the RelA (p65) Subunit of NF-κB and the Progesterone Receptor (∗). Journal of Biological Chemistry, 271(11), 6217-6224.

Allred, D. C., & Mohsin, S. K. (2000). Biological features of premalignant disease in the human breast. Journal of mammary gland biology and neoplasia, 5(4), 351-364.

Biswas, D. K., Shi, Q., Baily, S., Strickland, I., Ghosh, S., Pardee, A. B., & Iglehart, J. D. (2004). NF-κB activation in human breast cancer specimens and its role in cell proliferation and apoptosis. Proceedings of the National Academy of Sciences, 101(27), 10137-10142.

Biswas, D. K., Martin, K. J., McAlister, C., Cruz, A. P., Graner, E., Dai, S. C., & Pardee, A. B. (2003). Apoptosis caused by chemotherapeutic inhibition of nuclear factor-κB activation. Cancer research, 63(2), 290-295.

Biswas, D. K., Cruz, A. P., Gansberger, E., & Pardee, A. B. (2000). Epidermal growth factor-induced nuclear factor κB activation: a major pathway of cell-cycle progression in estrogen-receptor negative breast cancer cells. Proceedings of the National Academy of Sciences, 97(15), 8542-8547.

Biswas, D. K., Dai, S. C., Cruz, A., Weiser, B., Graner, E., & Pardee, A. B. (2001). The nuclear factor kappa B (NF-κB): a potential therapeutic target for estrogen receptor negative breast cancers. Proceedings of the National Academy of Sciences, 98(18), 10386-10391.

Biswas, D. K., Singh, S., Shi, Q., Pardee, A. B., & Iglehart, J. D. (2005). Crossroads of estrogen receptor and NF-κB signaling. Science's STKE, 2005(288), pe27-pe27.

Franco, H. L., Nagari, A., & Kraus, W. L. (2015). TNFα signaling exposes latent estrogen receptor binding sites to alter the breast cancer cell transcriptome. Molecular cell, 58(1), 21-34.

Frasor, J., El-Shennawy, L., Stender, J. D., & Kastrati, I. (2015). NFκB affects estrogen receptor expression and activity in breast cancer through multiple mechanisms. Molecular and cellular endocrinology, 418, 235-239..

Holloway, J. N., Murthy, S., & El-Ashry, D. (2004). A cytoplasmic substrate of mitogen-activated protein kinase is responsible for estrogen receptor-α down-regulation in breast cancer cells: the role of nuclear factor-κB. Molecular Endocrinology, 18(6), 1396-1410.

Hu, R., Warri, A., Jin, L., Zwart, A., Riggins, R. B., Fang, H. B., & Clarke, R. (2015). NF-κB signaling is required for XBP1 (unspliced and spliced)-mediated effects on antiestrogen responsiveness and cell fate decisions in breast cancer. Molecular and cellular biology, 35(2), 379-390.

Manginstar, C., Islam, A. A., Sampepajung, D., Hamdani, W., Bukhari, A., Syamsu, S. A., ... & Faruk, M. (2021). The relationship between NFKB, HER2, ER expression and anthracycline-based neoadjuvan chemotherapy response in local advanced stadium breast cancer: A cohort study in Eastern Indonesia. Annals of Medicine and Surgery, 63, 102164.

Lim, S. O., Li, C. W., Xia, W., Cha, J. H., Chan, L. C., Wu, Y., ... & Hung, M. C. (2016). Deubiquitination and stabilization of PD-L1 by CSN5. Cancer cell, 30(6), 925-939.

Lobanova, Y. S., Scherbakov, A. M., Shatskaya, V. A., & Krasil’nikov, M. A. (2007). Mechanism of estrogen-induced apoptosis in breast cancer cells: role of the NF-κB signaling pathway. Biochemistry (moscow), 72(3), 320-327.

McCarthy, S. A., Samuels, M. L., Pritchard, C. A., Abraham, J. A., & McMahon, M. (1995). Rapid induction of heparin-binding epidermal growth factor/diphtheria toxin receptor expression by Raf and Ras oncogenes. Genes & development, 9(16), 1953-1964.

Merkhofer, E. C., Cogswell, P., & Baldwin, A. S. (2010). Her2 activates NF-κB and induces invasion through the canonical pathway involving IKKα. Oncogene, 29(8), 1238-1248.

Nakshatri, H., Bhat-Nakshatri, P., Martin, D. A., Goulet Jr, R. J., & Sledge Jr, G. W. (1997). Constitutive activation of NF-kappaB during progression of breast cancer to hormone-independent growth. Molecular and cellular biology, 17(7), 3629-3639.

Norris, J. L., & Baldwin, A. S. (1999). Oncogenic Ras enhances NF-κB transcriptional activity through Raf-dependent and Raf-independent mitogen-activated protein kinase signaling pathways. Journal of Biological Chemistry, 274(20), 13841-13846.

Osako, T., Nishimura, R., Okumura, Y., Toyozumi, Y., & Arima, N. (2012). Predictive significance of the proportion of ER-positive or PgR-positive tumor cells in response to neoadjuvant chemotherapy for operable HER2-negative breast cancer. Experimental and therapeutic medicine, 3(1), 66-71.

Park, K. J., Krishnan, V., O’Malley, B. W., Yamamoto, Y., & Gaynor, R. B. (2005). Formation of an IKKα-dependent transcription complex is required for estrogen receptor-mediated gene activation. Molecular cell, 18(1), 71-82.

Pearson, G., English, J. M., White, M. A., & Cobb, M. H. (2001). ERK5 and ERK2 cooperate to regulate NF-κB and cell transformation. Journal of Biological Chemistry, 276(11), 7927-7931.

Sampepajung, E., Hamdani, W., Sampepajung, D., & Prihantono, P. (2021). Overexpression of NF-kB as a predictor of neoadjuvant chemotherapy response in breast cancer. Breast Disease, (Preprint), 1-9.

Sarkar, D. K., Jana, D., Patil, P. S., Chaudhari, K. S., Chattopadhyay, B. K., Chikkala, B. R., ... & Chowdhary, P. (2013). Role of NF-κB as a prognostic marker in breast cancer: a pilot study in Indian patients. Indian journal of surgical oncology, 4(3), 242-247.

Sas, L., Lardon, F., Vermeulen, P. B., Hauspy, J., Van Dam, P., Pauwels, P., ... & Van Laere, S. J. (2012). The interaction between ER and NFκB in resistance to endocrine therapy. Breast Cancer Research, 14(4), 1-14.

Scherbakov, A. M., Lobanova, Y. S., Shatskaya, V. A., & Krasil’nikov, M. A. (2009). The breast cancer cells response to chronic hypoxia involves the opposite regulation of NF-kB and estrogen receptor signaling. Steroids, 74(6), 535-542.

Shostak, K., & Chariot, A. (2011). NF-κB, stem cells and breast cancer: the links get stronger. Breast Cancer Research, 13(4), 1-7.

Singh, S., Shi, Q., Bailey, S. T., Palczewski, M. J., Pardee, A. B., Iglehart, J. D., & Biswas, D. K. (2007). Nuclear factor-κB activation: a molecular therapeutic target for estrogen receptor–negative and epidermal growth factor receptor family receptor–positive human breast cancer. Molecular cancer therapeutics, 6(7), 1973-1982.

Song, R. D., Zhang, Z., Mor, G., & Santen, R. J. (2005). Down-regulation of Bcl-2 enhances estrogen apoptotic action in long-term estradiol-depleted ER+ breast cancer cells. Apoptosis, 10(3), 667-678.

Troppmair, J., Hartkamp, J., & Rapp, U. R. (1998). Activation of NF-κB by oncogenic Raf in HEK 293 cells occurs through autocrine recruitment of the stress kinase cascade. Oncogene, 17(6), 685-690.

Van Laere, S. J., Van der Auwera, I., Van den Eynden, G. G., Van Dam, P., Van Marck, E. A., Vermeulen, P. B., & Dirix, L. Y. (2007). NF-κB activation in inflammatory breast cancer is associated with oestrogen receptor downregulation, secondary to EGFR and/or ErbB2 overexpression and MAPK hyperactivation. British journal of cancer, 97(5), 659-669.

Wang, X., & Belguise, K. (2009). O’ Neill, CF, Sanchez-Morgan, N. Romagnoli, M., Eddy, SF, Mineva, ND, Yu, Z., Min, C., Trinkaus-Randall, V. et al, 3832-3844.

Zhou, Y., Eppenberger-Castori, S., Eppenberger, U., & Benz, C. C. (2005). The NFkB pathway and endocrine-resistant breast cancer. Endocrine Related Cancer, 12(1), S37.