Activation of the AhR leading to metastatic breast cancer

Xavier Coumoul

Robert Barouki

Meriem Koual

Karine Audouze

Celine Tomkiewicz

Breast cancer is the deadliest cancer in women with a poor prognosis in case of metastatic breast cancer. The role of the environments in the formation of metastasis has been suggested. We hypothesized that activation of the AhR (MIE), a xenobiotic receptor, could lead to breast cancer metastasis (AO), through different KEs, constituting a new AOP.

An artificial intelligence tool (AOP-helpfinder), which screens the available literature, was used to collect all existing scientific abstracts to build a novel AOP, using a list of key words. Four hundred and seven abstracts were found containing at least a word from our MIE list and either one word from our AO or KE list. A manual curation retained 113 pertinent articles, which were also screened using PubTator. From these analyses, an AOP was created linking the activation of the AhR to breast cancer related death through decreased apoptosis, inflammation, endothelial cell migration, and increased mortality. These KEs promote an increased tumor growth, angiogenesis and invasion which leads to breast cancer metastasis.

The evidence of the proposed AOP was weighted using the tailored Bradford Hill criteria and the AOP developers’ handbook (https://aopwiki.org/handbooks/). The confidence in our AOP and the biological plausibility was considered strong. Indeed, in vitro and in vivo findings on multiple types of breast cancers (with or without oesrtogen receptors, for instanace) supported our proposed AOP. An in vitro validation must be carried out, but our review proposes a strong relationship between AhR activation and breast cancer metastasis with an innovative use of an artificial intelligence literature search.

This work was published in Envionnmental International: https://doi.org/10.1016/j.envint.2022.107323

Breast cancer is a frequent disease, responsible of 2 262 419 new cases and 684 996 deaths in 2020 in the world, making it the deadliest female cancer (Bray et al., 2018). In 70% of cases, the disease is localized, and the prognosis is favorable with a 5-year survival of 99%. However, once the disease spreads (lymph nodes, metastasis), survival is severely altered with a 5-year survival rate of 26% in case of metastasis (Henley et al., 2020). It is therefore of paramount importance to understand the mechanisms of metastasis in breast cancer.

Amongst risk factors clearly established, including obesity, genetic mutations and hormonal exposure, the importance of the role of the environment is currently emerging (Koual et al., 2020 Nov 17). In an epidemiologic study, we found a positive association between the concentrations of 2.3.7.8-TCDD (2,3,7,8-tetrachlorodibenzo-p-dioxine) in the adipose tissue surrounding the tumors, and breast cancer metastasis in overweight and obese patients (Koual et al., 2019). Moreover, we have shown that, using both in vivo and in vitro models, TCDD exposure could promote an aggressive phenotype to breast cancer cells, thus favoring the formation of metastatic cells (Koual et al., 2021). TCDD is a potent ligand of the aryl hydrocarbon receptor (AhR), a transcriptional factor involved notably in the metabolism of xenobiotics (Larigot et al., 2022). Hence, the impact of the environment on breast cancer aggressiveness could be mediated by the activation of the AhR.

Interest is growing on the role of the AhR in breast cancer. First, the AhR is often overexpressed in different breast cancer cell lines (Zudaire et al., 2008, Kim et al., 2000 Nov 16, Li et al., 2014). Interestingly, the level of expression can be correlated to the stage or the molecular sub-type of the disease (Zudaire et al., 2008, Zhao et al., 2013). Second, the AhR pathway has been associated with different pro-metastatic features in breast cancer, such as resistance to apoptosis, invasiveness, modified cell cycle, migration and proliferation (Zudaire et al., 2008, Goode et al., 2013 Dec 15, Kanno et al., 2006). Triple negative cell lines, breast cancer cell lines with the worse prognosis (not over-expressing Her2 receptor or hormonal receptors), over-expressing the AhR seem to develop stem-like characteristics, favoring epithelial-mesenchymal transition (EMT) and thus metastasis (Stanford et al., 2016). Thirdly, the AhR could be involved in the resistance of breast cancer to treatments (Goode et al., 2013 Dec 15, Goode et al., 2014): after AhR knockout, Goode et al. found enhanced sensitivity of paclitaxel (a drug targeting cancer cells) in triple negative breast cancer, a cancer particularly difficult to treat (Goode et al., 2014). Breast cancer patients expressing estrogen receptors (ER-positive) in their cancer cells, can benefit from an efficient endocrine therapy, which greatly improves their survival. Activation of the AhR can lead to the loss of expression of the ER alpha and therefore to the loss of a potential therapeutic target (Safe et al., 2000 Jul).

The mechanisms linking the activation of the AhR to breast cancer aggressiveness are still unclear. Based on the AOP-wiki database (https://aopwiki.org/, last accessed March 2022), the central repository for AOPs, the AhR has already been proposed in several AOPs, but never in one characterized by the AO breast cancer metastasis. Likewise, an AOP linking an MIE to breast cancer aggressiveness has never been proposed. From our expertise and available knowledge, we hypothesize that the activation of the AhR could be a MIE leading to breast cancer metastasis (AO) through different KEs and KERs.

1. Data input, automatic identification, and extraction of the available knowledge

An artificial intelligence based method, named AOP-helpFinder (https://aop-helpfinder.u-paris-sciences.fr/index.php), was used to scope the available relevant literature (Carvaillo et al., 2019, Zgheib et al., 2021, Rugard et al., 2020 Jan 1, Jornod et al., 2020, Jornod et al., 2022). This tool screens the contents of abstracts from the PubMed database using lists of key words, including stressors, MIEs, KEs and AOs. It then automatically finds, and extracts links co-mentioned in abstracts between pairs of events (MIE/KE/AO) and ranks them using graph theory. In the proposed study, the key words included MIEs (AhR …), KEs (migration, hypoxia, colony…) and an AO (breast cancer, mammary tumor…). All biological events used for the screening were defined using AOP-wiki database and personal keywords. We first scanned the list of KE and KER proposed by AOP wiki and retained words and concepts which concerned cancer aggressivity. Personal keywords were added if necessary (ex: EMT). We reviewed the list of words as a team in order to be as extensive as possible. The key words used can be found in Supplementary Table S1.

The obtained results (i.e., abstracts co-mentioning KE and AO) were manually curated to refine them, and keep the most significant knowledge. First only the abstracts were read and if the article was kept, the full text was reviewed. A manual curation decision tree was created to only include articles that concerned: i) the AhR, ii) breast cancer, iii) cancer progression and not initiation and iv) reviews were excluded (details in results §1 AOP-helpFinder text mining tool).

The newly established version of the AOP-helpFinder tool was applied on the more than 30 million available abstracts from PubMed database, which allowed us to use the two proposed options: i) the refinement filter based on machine learning method (lemmatization process of text) combined with deletion of words of context in order to improve the accuracy of the outputs, and ii) the reduced search option which allow to screen only a part of the abstracts (Jornod et al., 2022). This allows to not screen the introductory part of an abstract which usually refer to a study hypothesis, with the aim to decrease false positives.

In order to cross-check the selected concepts, and to support the evidence in favor of the proposed AOP, all selected articles (after text mining and manual curation) were run through the PubTator Central tool (https://www.ncbi.nlm.nih.gov/research/pubtator/). PubTator is a web-based system that screens PubMed abstracts and PMC full-text articles for biomedical concepts (genes, diseases, mutations, species, cell lines) (Wei et al., 2013, Wei et al., 2019 Jul 2). The PMIDs of the selected articles were used, and PubTator scanned their abstracts. The system overview is detailed by Wei et al. here (Wei et al., 2019 Jul 2). The retrieved chemical, disease, species, cell line and gene concepts were used to support the developed AOP.

2. AOP – Knowledge integration and weight of evidence assessment

The AOP was then developed using all the previously extracted data, using the AOP developers’ handbook (https://aopwiki.org/handbooks/). The graphical linear flow diagram was used to represent our proposed AOP.

The evidence supporting the AOP was organized and evaluated according to the tailored Bradford-Hill criteria, as described by AOP developers’ handbook (https://aopwiki.org/handbooks/) and OECD guidance (OECD, 2018, Hill, 1965). Briefly, these criteria are a group of minimal conditions for providing adequate evidence of a causal relationship between 2 events.

First, the OECD guidelines were used to evaluate the weight of evidence (WoE) between each KE. The biological applicability domain of each KE was assessed for sex, life stage and taxa. Due to the heterogeneity of breast cancer, another category was added, namely whether the KE is present only in certain types of cancer (ER-positive, triple negative, Her2 overexpression). The types of assays used to measure the KE were also recorded. Then, the confidence in the essentiality of each KE was evaluated using the system proposed by the OECD (high, moderate, low) and detailed in the guidebook.

Second, the tailored Bradford-Hill criteria modified to fit the AOP evidence assessment were used as proposed previously to evaluate each KER (Vinken et al., 2013, Becker et al., 2015): i) the concordance of dose–response relationships (ex: is there more migration with higher dosage AhR activators?), ii) the temporal concordance among the KER and AO (ex: is there cell migration before activation of the AhR?), iii) strength, consistency, and specificity of association (ex: use of specific AhR antagonists, silencing or knock out), iv) biological plausibility, coherence, and consistency of the experimental evidence (ex: number of studies finding the association, concordance amongst cell lines), and v) alternative mechanisms that logically present themselves and the extent to which they may distract from the postulated AOP (ex: use of different stressors).

Third, the OECD guidelines were used to evaluate the KERs: i) biological plausibility (mechanistic approach), ii) empirical support (dependent change and the experimental data present), iii) evidence and finally iv) quantitative evidence (closely linked to the tailored Bradford-Hill criteria). These were evaluated using the system proposed by the OECD (high, moderate, low) and detailed in the guidebook.

Finally, the AOP was overall assessed using the three primary considerations: the biological plausibility, the essentiality of each KE and the empirical support of KERs. Since the detail of the evaluation of the overall weight assessment of the AOP is not described in the OECD guidebook, this evaluation was subjective and decided by our team using all the different elements studied before.

3.Results

A total of 17,760 articles related to the MIE, AhR or aryl hydrocarbon receptor, were identified in the PubMed database (as of December 2021). This list of AhR-related abstracts was used to screen the ones concerning the putative AOP. All abstracts had to mention at least one event from the AO list (breast cancer or synonym) and one event from the KE list (KEs leading to metastasis: invasion, stemness…). The list of key words used for searching AOs and KEs can be found in Supplementary Table 1. After merging the identified abstract using their PubMed identifications (PMID), only 407 abstracts were kept from the AhR list with both a key event from our AO list and our KE list A total of 17,760 articles related to the MIE, AhR or aryl hydrocarbon receptor, were identified in the PubMed database (as of December 2021). This list of AhR-related abstracts was used to screen the ones concerning the putative AOP. All abstracts had to mention at least one event from the AO list (breast cancer or synonym) and one event from the KE list (KEs leading to metastasis: invasion, stemness…). The list of key words used for searching AOs and KEs can be found in Supplementary Table 1. After merging the identified abstract using their PubMed identifications (PMID), only 407 abstracts were kept from the AhR list with both a key event from our AO list and our KE list .

Four steps were used for the manual curation, that was performed by several experts. First, all the abstracts were screened to check if it indeed concerned the AhR. One hundred and thirty-four abstracts were excluded mainly because the retrieved “ahr” do not concern the aryl hydrocarbon receptor but the adjusted hazards ratio. Moreover, “ahr” sometimes referred to the last name of an author (Ex: Andre Ahr). Then, only abstracts concerning breast cancer were included. Eighteen abstracts were excluded because they did not directly concern breast cancer. One hundred and nine articles were not selected because they concerned breast cancer initiation and not aggressiveness / metastasis. Finally, 33 articles were reviews and not original works. In total, 113 articles were considered to develop our AOP.

The 113 articles were then classified by category in the metastatic process (migration, invasion…). Each category represented a hallmark of cancer and was associated with the corresponding key words that were used to explore Pubmed using AOP-helpFinder.

The 113 articles were also run through the PubTator Central tool to screen for biomedical concepts. The most frequently found disease was breast cancer, followed by toxicity and concepts concerning metastasis and aggressivity. TCDD (or dioxin, or 2,3,7,8-tetrachlorodibenzo-p-dioxin) was by far the most used chemical followed by estrogen, indole-3-carbinol, alpha-naphthoflavone, polycyclic aromatic hydrocarbons and hexachlorobenzene, mainly ligands of the AhR. Most identified studies concerned humans or mice, except one on zebrafish. The ER-positive cell line MCF-7 was the most frequently studied, followed by the aggressive MDA-MB-231 (triple negative) cell line. Without surprise, the AhR was the “gene concept” the most assessed followed by the estrogen receptor, CYP1A1 and CYP1B1. All results are displayed in Supplementary data S2. These results guided the concepts used in our AOP and the biological applicability domain.

After a careful read of the selected articles by all experts and based on their expertise, an adverse outcome network (AON) using 6 different linear AOPs

The biological plausibility of KERs is defined by the OECD as the « understanding of the fundamental biological processes involved and whether they are consistent with the causal relationship being proposed in the AOP ». The biological plausibility is strong due to the presence of overwhelming evidence present in different studies. A minor setback would be the difficulty to dismiss alternative mechanisms caused by the ligands used for AhR activation. This is detailed in the discussion.

The essentiality of KEs refers to « experimental data for whether or not downstream KEs or the AO are prevented or modified if an upstream event is blocked ». The essentiality of KEs is strong: most works use suppression or inhibition of the AhR (knock out, antagonists and/or silencing) with results coherent with our findings.

Finally, the empirical support of KERs, is often « based on toxicological data derived by one or more reference chemicals where dose–response and temporal concordance for the KE pair can be assessed ». The overall assessment of the empirical support of our KERs is also strong. There is evidence in human cell lines and mice showing a dose–response and temporal concordance for severity of our KE and the presence of metastasis.

We propose a simple and robust AOP associating activation of the AhR and breast cancer related death through migration, invasion, inflammation, and neo-angiogenesis.

One of the main limitations of our AOP is the existence of these diverse ligands and pathways, complexifying the definition of ‘AhR activation’ (6,54). Using PubTator, we found that TCDD was by far the most used chemical followed by I3C, alpha-naphthoflavone, polycyclic aromatic hydrocarbons and hexachlorobenzene, all ligands of the AhR. These ligands can activate different pathways after AhR binding and we therefore assumed that these compounds were AhR agonists. It can be difficult to dismiss alternative mechanisms caused by the ligands used for AhR activation. However, the AhR is the only characterized target of TCDD for example, and studies which use several ligands including TCDD, display similar results using the other modulators. Moreover, the concordance of studies using various ligands and the coherence with the AhR inhibition are in favor of the robustness of the proposed AOP. Indeed, to obtain the most accurate AOP possible, the KEs selected had to be present, no matter the ligand used by the study.

Another minor setback of using the AhR, is that the dose response concordance is a non-monotonous curve for several ligands (122,123). Therefore, the tailored Bradford-Hill criteria could sometimes not be fulfilled.

Moreover, the originality of our work lies in the use of artificial intelligence too such as AOP-helpfinder, which enables a thoroughly search of existing knowledge in the PubMed database and PubTator (19–21). Therefore, our literature review was complete and evidence in favor of our proposed AOP was overwhelming. We plan to validate our proposed AOP in a quantitative in vitro work using Integrated Approaches to Testing and Assessment (IATA).

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