# International regulatory needs for development of an IATA for non-genotoxic carcinogenic chemical substances

Miriam Jacobs, Annamaria Colacci, Kimmo Louekari, Mirjam Luijten, Betty

C. Hakkert, Martin Paparella, Paule Vasseur

► To cite this version:

Miriam Jacobs, Annamaria Colacci, Kimmo Louekari, Mirjam Luijten, Betty C. Hakkert, et al. International regulatory needs for development of an IATA for non-genotoxic carcinogenic chemical substances. Altex -Heidelberg-, 2016, 33 (4), pp.359-392. 10.14573/altex.1601201 . hal-03208956

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Distributed under a Creative Commons Attribution 4.0 International License
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**Concept Article**

**International Regulatory Needs for
Development of an IATA for Non-Genotoxic
Carcinogenic Chemical Substances**

Miriam N. Jacobs¹, Annamaria Colacci², Kimmo Louekari³, Mirjam Luijten⁴, Betty C. Hakkert⁵,
Martin Paparella⁶ and Paule Vasseur⁷

¹Department of Toxicology, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Oxfordshire, UK; ²Center for Environmental Toxicology and Risk Assessment, Environmental Protection and Health Prevention Agency, Emilia Romagna Region, Italy; ³European Chemicals Agency, Helsinki, Finland; ⁴Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands; ⁵Bureau REACH, Department for Industrial Chemicals, Centre for Safety of Substances and Products (VSP), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands; ⁶Chemicals & Biocides, Environment Agency Austria, Vienna, Austria; ⁷CNRS UMR 7360, University of Lorraine, Metz, France

**Summary**

Although regulatory requirements for carcinogenicity testing of chemicals vary according to product sector and regulatory jurisdiction, the standard approach starts with a battery of genotoxicity tests. If any of the *in vivo* genotoxicity tests are positive, a lifetime rodent cancer bioassay may be requested, which allows the detection of non-genotoxic carcinogens (NGTxC). However, under most chemical regulations the cancer bioassay is rarely requested, specific requests to obtain information on non-genotoxic mechanisms of carcinogenicity are few, and there are no OECD approved screening methods. When the *in vitro* genotoxicity battery is negative, usually no further carcinogenicity testing is requested. Consequently NGTxC might remain unidentified and therefore the risks they may pose to human health will not be managed. In contrast to genotoxic carcinogens NGTxC act through a large variety of specific mechanisms, and a panel of tests covering multiple biological traits will be needed.

The development of an integrated approach to testing and assessment (IATA) of NGTxC could assist regulatory decision makers. We examine what NGTxC are and discuss chemical regulatory requirements and limitations. With a strong drive to reduce animal testing and costs in mind, it is essential that proper and robust alternatives for animal testing methods (3Rs) for addressing non-genotoxic modes of action are developed and used. Therefore relevant *in vitro* mechanisms and assays are described and tentatively organized in levels of information, indicating both a possible structure of the future IATA for NGTxC and associated OECD Test Guideline development priorities.

Keywords: non-genotoxic carcinogens, integrated approaches to testing and assessment of chemicals

# 1 Introduction

The current thinking is that there are three main stages of carcinogenicity: initiation, promotion and progression, and that the mechanisms by which chemicals cause carcinogenicity can fall into two broad categories: genotoxic (a mechanism causing ini-

tiation) and non-genotoxic (including both initiation and propa- gation phases). Both categories are comprised of several more specific modes of action (MoA).

Over the last two decades there has been much debate about the “Hallmarks of Cancer”, highlighting the need to better un- derstand the biological mechanisms underlying cancer onset and

**Abbreviations**

AhR, aryl-hydrocarbon receptor; APC, adenomatous polyposis coli; AR, androgen receptor; AOP, adverse outcome pathway; BMD, bench mark dose; CAR, constitutive androstane receptor; CTA, cell transformation assay; CYP P450, cytochrome P450; DEHP, di(2-ethylhexyl)phthalate; DEN, N-nitrosodiethylamine; ER, estrogen receptor; FAP, familial adenomatous polyposis; GTx, genotoxic; HTP, high-throughput; IATA, Integrated Approach to Testing and Assessment; IARC, International Agency for Research on Cancer; KE, key event; KER, key event relationship; GHS, Globally Harmonized System; MIE, molecular initiating event; miRNA, microRNA; MoA, mode of action; NGTx, non-genotoxic; NGTxC, non-genotoxic carcinogen(s); OECD, Organisation for Economic Cooperation and Development; PPAR, peroxisome proliferator-activated receptor; (Q)SAR, (Quantitative) Structure Activity Relationship; REACH, Registration, Evaluation and Authorization and Restriction of Chemicals; WoE Weight of Evidence

Received January 20, 2016
Accepted April 14, 2016;
Epub April 27, 2016;
http://dx.doi.org/10.14573/altex.1601201

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This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is appropriately cited.
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progression (reviewed in Hanahan and Weinberg, 2000, 2011; Smith et al., 2015). Initially six hallmarks were described in 2000: sustained proliferative signaling; evasion of growth suppression; resisting cell death; replicative immortality; induced angiogenesis; and activated invasive metastasis (Hanahan and Weinberg, 2000). To this set, further hallmarks have been added, including dysregulation of cell metabolism and avoidance of immune destruction. Genetic instability and chronic inflammation underlie these hallmarks, as do epigenetic perturbation mechanisms, particularly changes in DNA methylation (Moggs et al., 2004; Thomson et al., 2012, 2014; Miousse et al., 2015), see Figure 1. Whilst this evolving somatic mutation theory of cancer is widely but not universally accepted (Sonnenschein and Soto, 2013), it provides a useful grouping format to assist with the clustering of relevant assays for the biological processes associated with cancer initiation, promotion/progression, and tumor formation for regulatory test method development and integrated approaches to testing and assessment (IATA) purposes. It also accommodates the growing body of information about the biological processes underlying each of the hallmarks; clearly there are a number of different pathways underlying each.

Here we examine what non-genotoxic carcinogens (NGTxC) are, the current European and also international chemical regulatory requirements and difficulties with respect to NGTxC, and how an IATA could be explored and a framework ultimately be developed to assist regulators in their assessments of NGTxC.

Relevant *in vitro* assays are briefly described such that, with respect to the 3Rs test methods and assessment strategies, relevant *in vitro* Organisation for Economic Cooperation and Development (OECD) Test Guideline (TG) development for chemical hazard assessment will be stimulated.

## 2 What are non-genotoxic carcinogens?

Carcinogens can be categorized as either predominantly genotoxic or non-genotoxic according to their specific pathogenic mechanism. Genotoxic carcinogens, also known as DNA-reactive carcinogens, interact directly with DNA through the formation of covalent bonds, resulting in DNA-carcinogen complexes.

NGTxC are substances that act through secondary mechanisms that do not involve direct interaction with DNA; they do not induce mutation in (short term) eukaryotic and prokaryotic mutation assays nor do they induce direct DNA damage in the target organ. They also include “epigenetic” carcinogens, where the term “epigenetic” is sometimes used to encompass the full spectrum of transcriptional regulatory processes that appear to mediate environmental influences and change a cellular state to reflect past and current (chemical) exposures (Greally and Jacobs, 2013). Here we consider that epigenetic changes comprise changes in chromatin (DNA methylation and/or histone modifications) and non-coding RNAs, including microRNAs.

<figure><img src="image_5.png" /><figcaption>Fig. 1: Hallmarks of cancer with associated modes of action (MoA) and existing assays that address particular aspects of certain hallmarks</figcaption></figure>

(adapted and modified from Goodson et al., 2015)
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NGTxC can act via epigenetic mechanisms, as reviewed by Thomson et al (2014). Additionally, NGTxC can also act via other well-known mechanisms, many of which underlie the hallmarks shown in Figure 1, such as: peroxisome proliferation; immune suppression; receptor-mediated endocrine modulation; inhibition of intercellular communication; induction of tissue-specific toxicity; inflammatory responses; disruption of cellular signaling or structures by changing the rate of either cell proliferation or of processes that increase the risk of genetic error; disruption of certain negative cell feedback signals that can enhance proliferative signaling (e.g., the oncogenic effect of mutations in the Ras gene stem from disruption of its negative feedback system) (Hanahan and Weinberg, 2011); and mutations in tumor suppressor genes that allow cells to evade growth suppression and contact inhibition.

Thus, NGTxC act through a large and diverse variety of different and in some cases specific mechanisms. An overview of the major mechanisms is provided in Table 1 and Figure 1. This is a living list of NGTxC mechanism examples. With the recent rapid elucidation of epigenetic mechanisms in the NGTxC process, specific epigenetic mechanisms of relevance are increasingly being identified. While genetic modifications in tumor cells may initiate and drive malignancy, exposure to NGTxC may affect one or more of the biological traits underlying the hallmarks of cancer. NGTxC in this paper therefore refer to carcinogens that are negative (or produce ambiguous results) in genotoxicity assays performed to measure biological endpoints, including gene mutations and chromosomal damage (chromosomal aberrations, micronuclei formation).

There are a large number of pathways and intervention points for NGTxC to contribute to cancer initiation and cancer progression. In addition, there is evidence to support the theory that NGTxC can cause alterations that increase the likelihood of genetic instability, which would promote the acquisition of a fully malignant and invasive phenotype (Ellinger-Ziegelbauer et al., 2009). NGTxC exhibit thresholds and may be reversible at some early stages; they are strain, species and tissue specific and function often at the tumor promotion stage, while they are also able to be tumorigenic alone (such as asbestos).

From the overview of NGTxC mechanisms presented in Table 1, it should be noted that assays with endpoints capturing early key event mechanisms may provide an individual contribution to the Weight of Evidence (WoE) – where multiple sources of information are assessed in relation to each other – that is relatively poor. For example, measurement of proliferation alone does not necessary mean that there will be further downstream pathway perturbation leading to angiogenesis.

In other cases, the mechanism may not be purely non-genotoxic. A relevant example of a non-genotoxic mechanism is oxidative stress as it is considered to be one of the best documented mechanisms for carcinogenesis together with impacts upon cell cycle regression. Oxidative stress is one of the mechanisms through which environmental pollutants may induce cell damage, triggering an inflammatory response which may evolve into chronic inflammation as a consequence of enduring exposure.

Both non-genotoxic and genotoxic substances can trigger oxidative stress (Ellinger-Ziegelbauer et al., 2005), see also Table 1, which can also lead to adverse outcomes other than cancer. One of the main pathways related to oxidative stress is orchestrated by p53. The modulation of p53-downstream genes controls cell cycle and apoptosis. These two endpoints may or may not be related to cancer onset and progression. However, a string of p53-signaling pathway-dependent genes are directly related to angiogenesis and metastasis, including the master gene TSP1, which plays an important role in bladder cancer (Mitra et al., 2006). The modulation of different genes in the p53-signaling pathway can also lead to different fates of cells affected by oxidative stress damage, which may proceed through apoptosis or to steps leading to DNA damage (Filomeni et al., 2015). Oxidative DNA damage may be critical in carcinogenesis if it results in extensive enough changes to induce gene mutations. However, the induction of oxidative stress may also regulate gene expression either directly through activation of gene transcriptional pathways or indirectly through hypomethylation (Nishida and Kudo, 2013; Casey et al., 2015; Vaccari et al., 2015; Wu and Ni, 2015). Epigenetic mechanisms in relation to regulatory needs are reviewed by Greally and Jacobs (2013) and Marczylo et al. (2016), and International Agency for Research on Cancer (IARC) cancer classification by Herceg et al. (2013). Taken together, these reviews demonstrate the major roles that such epigenetic mechanisms can play in tumor formation, often in combination with other mechanisms, and how this understanding can start to be applied for OECD and IARC purposes. A mechanism-based approach provides valuable insights with respect to the test method combinations that could be developed, also employing current OECD TGs (as Tab. 1 suggests), in order to obtain an IATA for NGTxC. Table 2 provides examples of molecular regulators of the vertebrate epigenome and Table 3 provides molecular epigenomic choices (Greally and Jacobs, 2013).

Of these, the three principle mechanisms DNA methylation, histone modification and miRNA are particularly promising with respect to assay development and augmentation for detecting NGTxC, as they are often key elements of many of the cancer hallmarks (as indicated on the right side of Fig. 2). Relevant information about DNA methylation, RNA and miRNA expression studies and chromatin structure and modification data can already start to be derived from the literature, together with analyses to identify markers for detection of NGTxC with epigenetic activity. This information can be used in combination with the key event assay blocks identified in Table 1, specific examples being endocrine receptor (Zhang and Ho, 2011, reviewed in Greally and Jacobs, 2013) and xenobiotic receptor activation (Lempiainen et al., 2011). One of the major challenges when studying epigenetic changes inferred by NGTxC is to link these epigenetic changes to adverse outcomes. Preliminary review suggests that association of NGTxC exposure with miRNA's may contribute to the WoE for downstream adverse outcome pathway (AOP) linkages, but specific epigenetic machinery may differ between adverse outcomes. Taking the male germline as an example, we can relate an MIE such as androgen receptor (AR) activation with a negative correlation to
<figure><img src="image_7.png" /><figcaption>Tab. 1: Major mechanisms of non-genotoxic carcinogenicity, and suggested organization for IATA development</figcaption></figure>

Level 1: basic molecular information: Molecular initiating event (MIE) and of lower priority

Level 2: MIE + additional level of complexity: higher priority (See the chapter on "Levels of information" below)

<table><thead><tr><th>Level of information: Early key events</th><th>AOP: Assay block: Key mechanism</th><th>Relevance of key mechanism(s)/ endpoints</th><th>Level of readiness for TG development/ AOP inclusion</th><th>Main relevant pathways and important genes involved: utility of key event relationships (KERS)</th><th>Related pathways/ cross-interactions</th><th>Endpoint/ hallmark affected cross-reactions</th><th>Examples of major genes of the pathways involved</th><th>Prototype substances associated with early key events</th><th>Prototype substances associated with adverse outcome</th></tr></thead><tbody><tr><td>1</td><td>Receptor binding and activation also as part of hormone mediated processes</td><td>Angiogenesis receptors such as VEGF would be relevant, as the tyrosine phosphorylation patters and the activation of major downstream signaling pathways are comparable (Nieminen et al., 2014)</td><td>Receptor assays available (some validated (OECD, 2012a)). Could be used in combination with gene expression profiles for related pathways Potential for adaptation of the Seroigenogenesis TG 456 (OECD, 2011) to address the KE of aromatase MoA for an aromatase dependent breast cancer AOP Combine with TG 473 but leave out the use of methaphase-attesting substances in exposed cells; this could then be used to screen for epigenetic effects</td><td>Wnt/catenin signaling pathway, i.e.: DNA modifications (cytosine methylation) miRNA and RNA expression studies Studies of chromatin components and structure</td><td>ER, AR, PPARs, RXR, RAR, VDR, GR, FXR, AhR and ARNT (see e.g., Schaap et al., 2015) Also see below re: VEGF</td><td>Gene expression Metabolic enzyme induction Genetic instability Tumor micro-environment Cell cycle Invasion and metastasis</td><td>AhR: Modulation of Hsp (very early KE) (Corton et al., 2014) PPARs: β-catenin (Lin et al., 2014)</td><td>DES (Gibson and Saunders, 2014) TCDD (Murray et al., 2014) DEHP (Corton et al., 2014)</td><td>DES (Gibson and Saunders, 2014) TCDD (Murray et al., 2014) DEHP (Corton et al., 2014)</td></tr><tr><td>1</td><td>Cell proliferation assay</td><td>A very early downstream KE</td><td>Assays available</td><td>p13k-Akt signaling pathway</td><td>VEGF signaling pathway plus specific relevant miRNA MAPK signaling pathway</td><td>Cell proliferation Angiogenesis DNA repair</td><td>Ras-Raf-1-MEK-ERK</td><td>BPA (Song et al., 2015)</td><td>Nitric oxide (Choudhari et al., 2013) DES (Wong and Walker, 2013)</td></tr><tr><td>1/2</td><td>Gap junctional intercellular communication</td><td>Endpoint: block of dye transfer Markers: connexin inhibition</td><td>Assays available and in regulatory use (Swierenga, 1992), e.g., clonogenic soft</td><td>Gap junction Possibly (chemical specific) connected with</td><td>MAPK signaling pathway</td><td>Apoptosis Differentiation Tissue homeostasis</td><td>Ras-Raf-1-MEK-ERK, connexins</td><td>TPA (Skeberdis et al., 2001)</td><td></td></tr></tbody></table>
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<table><thead><tr><th>Level of information: Early key events</th><th>AOP: Assay block: Key mechanism</th><th>Relevance of key mechanism(s) / endpoints</th><th>Level of readiness for TG development/ AOP inclusion</th><th>Main relevant pathways and important genes involved: utility of key event relationships (KERs)</th><th>Related pathways/ cross-interactions</th><th>Endpoint/ hallmark affected cross-reactions</th><th>Examples of major genes of the pathways involved</th><th>Prototype substances associated with early key events</th><th>Prototype substances associated with adverse outcome</th></tr></thead><tbody><tr><td rowspan="2">2</td><td rowspan="2">CYP P450 induction</td><td rowspan="2">or decrease of connexin expression</td><td rowspan="2">agar assay included in some pharmaceutical regulatory requirements (also a cell proliferation assay)</td><td>apoptosis and cell morphological transformation</td><td>Calcium signaling pathway</td><td>Sustained proliferative signaling</td><td>PLC, PKC</td><td>TPA (Skeberdis et al., 2001)</td><td></td></tr><tr><td>CYP 2E1 and 2B induction as predictive marker of potential chemical carcinogenesis due to increased reactive oxygen species production</td><td>Oxidative stress Hepatic inflammation Xenobiotic metabolism</td><td>NADPH oxidase activity Oxidative stress</td><td>Deregulated metabolism</td><td>Phospho-Akt (Nakanishi et al., 2005)</td><td>Ethanol (Ekstrom and Ingelman-Sundberg, 1989; Kukielka and Cederbaum, 1992; Parke, 1994; Lewis, 1996)</td><td>Ethanol</td></tr><tr><td>2</td><td></td><td>CYP 1A1 AhR mediated transduction</td><td>Assays available</td><td>Mitochondrial transcription and mitochondrial stress signaling (Biswas et al., 2008)</td><td>ER pathway cross talk (Go et al., 2015) MMP1, MMP2, MMP9</td><td>Correlation with migratory processes and metastasis potential</td><td>Induction of alterations in gene expression: Decrease in E-cadherin Activation of JNK, increased HEF1, also known as NEDD9 and CAS-L</td><td>Dioxins Dioxin-like PCBs PAH in mixtures</td><td>Dioxins Dioxin-like PCBs</td></tr><tr><td>2</td><td>Induction of oxidative stress</td><td>ROS triggered mitochondrial pathway inducing apoptosis (Lucas and Kolodziej, 2015)</td><td>Assays available Can be combined with P450 induction and DNA methylation</td><td>p53 signaling pathway: Induction of oxidative stress; association with regulation of gene expression either directly through activation of gene transcriptional pathways or indirectly through</td><td>Mitochondrial malignancy</td><td>MDM onco-protein family of p53-proteins (p21 and bcl-2)</td><td></td><td>Paraquat (Yang and Tiffany-Castiglioni, 2008; Black et al., 2008; Chang et al., 2013)</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>AhR</td><td></td><td>HMOX</td><td>PAH (Ferecatu et al., 2010)</td><td></td></tr></tbody></table>
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<table><thead><tr><th>Level of information: Early key events</th><th>AOP: Assay block: Key mechanism</th><th>Relevance of key mechanism(s) / endpoints</th><th>Level of readiness for TG development/ AOP inclusion</th><th>Main relevant pathways and important genes involved: utility of key event relationships (KERs)</th><th>Related pathways/ cross-interactions</th><th>Endpoint/ hallmark affected cross-reactions</th><th>Examples of major genes of the pathways involved</th><th>Prototype substances associated with early key events</th><th>Prototype substances associated with adverse outcome</th></tr></thead><tbody><tr><td rowspan="2">2 (cont.)</td><td rowspan="2">Induction of oxidative stress (cont.)</td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2">hypomethylation; specific relevant miRNA<br>ROS plus anti angiogenic stimuli</td><td>Casp-3-dependent PKC-δ</td><td>Apoptosis</td><td>CASP-3</td><td>Nitric oxide (Choudhari et al., 2013)</td><td></td></tr><tr><td>HIF-signaling pathway; Erb-2 signaling pathway</td><td>Angiogenesis HIF-1α</td><td>VEGF-MMPs-IL-8</td><td>Nitric oxide (Choudhari et al., 2013)</td><td></td></tr><tr><td rowspan="2">2</td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2">NADH dependent signaling pathway</td><td>Deregulated metabolism Senescence</td><td>MAP kinase, apoptosis</td><td>CXCL 10, CXCL11</td><td>Paraquat (Paolillo et al., 2011)</td><td>Ethanol</td></tr><tr><td>Cell trans- formation and stabilization Microtubules Cell-cell and cell matrix adhesion Organelle transport Transcription and signal transduction</td><td>Gap junctional intercellular communication (Cruciani et al., 1997, 1999) c-myc (Maire et al., 2007) Ornithine decarboxylase induction (Dhalluin et al., 1997, 1998)</td><td>Cell trans- formation Connexins Cadherins β-catenin Coronines Cell adhesion</td><td>c-myc cdh3 Ctnnbip1 Calmi3 Coro1 (Landkocz et al., 2011)</td><td>SIRT family (Huang et al., 2015) hTERT (Rathmell et al., 2015)</td><td>Ethanol (Dicker and Cederbaum, 1992)</td><td>Ethanol</td></tr><tr><td>2/3</td><td>Morphological transformation</td><td>Markers of cytoskeleton remodeling</td><td>Cell trans- formation assays available SHE CTA (OECD, 2007) available in OECD (2015a). However mechan- anistic under- standing is cur- rently considered insufficient by the OECD (OECD, 2015a)</td><td>Actin polymeriza- tion and stabilization Microtubules Cell-cell and cell matrix adhesion Organelle trans- port Transcription and signal transduction</td><td>TGF-β signaling pathway</td><td>Transcription fac- tors</td><td>Immunosuppres- sion Angiogenesis</td><td>DEHP (Cruciani et al., 1999; Landkocz et al., 2011) 2,4-D (Maire et al., 2007) Chlordane (Bessi et al., 1995)</td><td>DEHP (Cruciani et al., 1999; Landkocz et al., 2011) 2,4-D (Maire et al., 2007) Chlordane (Bessi et al., 1995)</td></tr><tr><td>2/3</td><td>Immunosup- pression</td><td>Markers of chemokine signaling pathway</td><td>No available assay for regulatory purposes, but could the local lymph node assay (LLNA- TG 429- level 3/4) be modified, e.g. using the nude mouse model (which would represent</td><td></td><td></td><td></td><td>IL-6 (Kravchenko et al., 2015)</td><td>DEHP (Ma et al., 2012)</td><td></td></tr></tbody></table>
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<table><thead><tr><th>Level of information: Early key events</th><th>AOP: Assay block: Key mechanism</th><th>Relevance of key mechanism(s) / endpoints</th><th>Level of readiness for TG development/ AOP inclusion</th><th>Main relevant pathways and important genes involved: utility of key event relationships (KERs)</th><th>Related pathways/ cross-interactions</th><th>Endpoint/ hallmark affected cross-reactions</th><th>Examples of major genes of the pathways involved</th><th>Prototype associated with early key events</th><th>Prototype substances associated with adverse outcome</th></tr></thead><tbody><tr><td rowspan="2">2</td><td rowspan="2">Gene expression and cell signaling pathways</td><td rowspan="2">These modifications may result in either increased cell proliferation or selective cell death (apoptosis or necrosis). The release of calcium may result in the activation of kinases, such as PKC</td><td rowspan="2">Assays available Can also be combined with epigenetic DNA methylation tests</td><td>Protein kinase A; a cAMP-mediated cascade (Serezani et al., 2008)</td><td rowspan="2">Calcium-calcium-odulin activated pathway P13K-Akt Intracellular signal transducers such as nitric oxide</td><td rowspan="2">Cytoskeleton restructuring (tumor micro-environment) Apoptosis, necrosis</td><td rowspan="2">PKC NFkB AP-1</td><td rowspan="2">Nitric oxide</td><td rowspan="2"></td></tr><tr><td>Transcription factors, e.g., NFkB and AP-1. NFkB appears to be involved in the mediation of cell proliferation and apoptosis. Changes in DNA methylation and hydroxymethylation patterns</td></tr><tr><td rowspan="2">1/2</td><td rowspan="2">Increased resistance to apoptotic cell death</td><td rowspan="2">Regulation of apoptosis mainly by BCL-2 family of mitochondria, death receptors and caspase network</td><td rowspan="2">Assays available, e.g., Rieger et al. (2011)</td><td>ER, P53, ErbB-/ HER-2 tyrosine kinase, ERK, MAPK P16/P53, BCL-2/P53, PPARα, gap junction intracellular communication, hypersecrection of LH</td><td rowspan="2">A KE with many downstream pathways. Cross reaction with almost all the pathways indicated in this table</td><td rowspan="2">Annexin V (Rieger et al., 2011)</td><td rowspan="2">Lindane BPA DBP and DEHP</td><td rowspan="2">Lindane</td></tr><tr><td>Also ALK, VEGF, HER receptors, BRAF, Rho-associated protein kinase, fibroblast growth factor-9, cathepsins, cyclooxygenases, prostaglandins (Narayanan et al., 2015)</td></tr></tbody></table>
<figure><img src="image_11.png" /></figure>

<table><thead><tr><th>Level of information: Early key events</th><th>AOP: Assay block: Key mechanism</th><th>Relevance of key mechanism(s) / endpoints</th><th>Level of readiness for TG development/ AOP inclusion</th><th>Main relevant pathways and important genes involved: utility of key event relationships (KERs)</th><th>Related pathways/ cross-interactions</th><th>Endpoint/ hallmark affected cross-reactions</th><th>Examples of major genes of the pathways involved</th><th>Prototype substances associated with early key events</th><th>Prototype substances associated with adverse outcome</th></tr></thead><tbody><tr><td rowspan="2">2/3</td><td rowspan="2">Metastasis (migration, intra- and extravasation, survival outside of original tissue)</td><td>reverse transcriptase (hTERT).</td><td rowspan="2">no specific assay available</td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td></tr><tr><td>Related to genetic instability (telomere-mediated chromosomal instability)</td></tr><tr><td rowspan="2"></td><td rowspan="2"></td><td>The only hallmark definitively related to cancer.</td><td rowspan="2">Assays available (Albini and Noonan, 2010).</td><td rowspan="2">Leukocyte transendothelial pathway</td><td rowspan="2">p53 signaling, MAP kinases, VEGF signaling</td><td rowspan="2">Migration</td><td rowspan="2">CAMs</td><td rowspan="2">DES (Gibson and Saunders, 2014) TCDD (Murray et al., 2014)</td><td rowspan="2">DES (Gibson and Saunders, 2014) TCDD (Murray et al., 2014)</td></tr><tr><td>Ability of cells to grow in semisolid medium</td></tr><tr><td></td><td></td><td>Ability of cells to cross membrane barriers</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

AhR, Aryl-hydrocarbon receptor; ALK, anaplastic lymphoma kinase; ARNT, AhR nuclear translocator; AP-1, activator protein 1; AR, androgen receptor; BAD, Bcl-2-associated death promoter protein; BCL-2, B-cell lymphoma 2 (oncogene); bFGF, basic fibroblast growth factor; BPA, bisphenol A; BRAF, proto-oncogene B-Raf or v-Raf murine sarcoma viral oncogene homolog B; Calm13, calmodulin 3; CAMs, cell adhesion molecules; CASP, Caspase; cdn3, cadherin3; CCL2, chemokine (C-C motif) ligand 2; c-myc, myelocytomatosis oncogene; ctnbp1, catenin beta interacting protein 1; col-111, an ortholog of human ADIPOQ (adiponectin, C1Q and collagen domain containing); CXL-10, C-X-C motif chemokine 10; CXCL, chemokine (C-X-C motif) ligand; CYP-P450, cytochrome P450 enzymes; DCC, deleted in colon carcinoma; DEHP, di(2-ethylhexyl)phthalate; DES, Diethylstilbestrol; DNMT1, DNA maintenance methyltransferase; ER, Estrogen Receptor; ERG, ETS-related gene; ETS, erythroblast transformation-specific family of transcription factors; ERK, Extra signal-regulated kinases; FAK, focal adhesion kinase; FXR, farnesoid x receptor; GR, glucocorticoid receptor; HATs, histone acetyltransferases; HDAC, histone deacetylases; HEF 1, human enhancer of filamentation 1; HER, human epidermal growth factor receptor; HER 2, v-erb-b2 erythroblastic leukemia viral oncogene homolog 2; HIF-1α, hypoxia-inducible factor 1; HMOX, heme oxygenase; Hsp, heat shock proteins, hTERT, human telomerase reverse transcriptase; IL, interleukin; ICAM1, intercellular adhesion molecule 1; JNK, c-Jun N-terminal kinases; LH, luteinizing hormone; MAPK, mitogen-activated protein kinase; MMP, matrix metalloproteinase; NF-κB, nuclear factor-κB; P13K/Akt, Phosphatidylinositol-3 kinases (P13K)/ serine/threonine kinase Akt (also known as protein kinase B or PKB); PAH, polyaromatic hydrocarbon; PCBs, Polychlorinated biphenyls; PDGF, Platelet derived growth factor; PFOS, perfluorooctane sulfonate; Phospho-Akt, phosphorylated Akt; PLC, phospholipase C; PKC, protein kinase C; PPAR, peroxisome proliferator-activated receptor; RAR, retinoic acid receptor; Ras/Rat/MEK/ERK, Ras/Rat/Mitogen-activated protein kinase/ERK kinase (MEK)/extracellular-signal-regulated kinase (ERK); ROS, reactive oxygen species; RXR, retinoid X receptor; SIRT, sirtuin; TERT, telomerase reverse transcriptase; TCDD, 2,3,7,8-tetrachlorodibenzo-p-dioxin; THBD, thrombomodulin; TGF-β, transforming growth factor-β; TPA, 12-O-tetradecanoylphorbol-13-acetate; uPAR, urokinase-type plasminogen activator receptor; VCAM1, vascular cell-adhesion molecule 1; VDR, Vitamin D receptor; VEGF/VEGFR, vascular endothelial growth factor/receptor.
<figure><img src="image_12.png" /><figcaption>**Tab. 2: Examples of molecular regulators of the vertebrate epigenome**
(from Greally and Jacobs, 2013)</figcaption></figure>

<table><caption>**Tab. 3: Molecular epigenomic assay choices**
 updated from Greally and Jacobs, 2013)</caption><thead><tr><td>Molecular mediator</td><td>Example</td><td>References</td></tr></thead><tbody><tr><td>Histone post-translational modifications</td><td>Histone H3 lysine 9 trimethylation (H3K9me3), a repressive mark</td><td>Hiragami-Hamada et al., 2009</td></tr><tr><td>Histone variants</td><td>Histone Macro H2A.1</td><td>Bernstein et al., 2008</td></tr><tr><td>Nucleosome positioning</td><td>Nucleosome-free regions at gene promoters</td><td>Hartley and Madhani, 2009</td></tr><tr><td>Chromatin looping</td><td>Kit regulation by Gata1/Gata2</td><td>Jing et al., 2008</td></tr><tr><td>DNA modifications</td><td>Cytosine methylation</td><td>Klose and Bird, 2006</td></tr><tr><td>DNA structural variation</td><td>R-loop formation</td><td>Roy et al., 2008</td></tr><tr><td>RNA-mediated</td><td>Antisense RNA transcription</td><td>Beiter et al., 2009</td></tr></tbody></table>

<table><thead><tr><th>Molecular mediator</th><th colspan="2">Detection method</th><th>Strengths and limitations of method</th></tr></thead><tbody><tr><td rowspan="5">DNA methylation</td><td colspan="2">Primary (recommended)</td><td></td></tr><tr><td rowspan="2">Bisulfite mutagenesis-based</td><td>MethylC-seq (Lister et al., 2009)</td><td>Nucleotide resolution, can interrogate most cytosines in genome. Expensive.</td></tr><tr><td>RRBS (Meissner et al., 2008)</td><td>Nucleotide resolution, relatively inexpensive. Interrogates limited number of cytosines, focused on CpG-dense regions.</td></tr><tr><td rowspan="2">Restriction enzyme-based</td><td>HELP-tagging (Suzuki et al., 2010) MSCC (Ball et al., 2009)</td><td>Relatively inexpensive, tests CpG-dense and depleted contexts. Interrogates limited number of cytosines.</td></tr><tr><td>meDIP-seq (Down et al., 2008)</td><td>Can test throughout genome. Quantitative capacity limited in CpG-depleted regions, interrogates contiguous groups of CpGs.</td></tr><tr><td>Microarray-based</td><td>450K Infinium Methylation BeadChip (Illumina) (Bibikova et al., 2011)</td><td>Inexpensive, design targeted to regions of presumed function. Interrogates limited number of cytosines, informativeness depends on design choices.</td></tr><tr><td>miRNA</td><td>miRNA-seq</td><td></td><td>Quantitative, can identify previously undiscovered miRNAs. Library preparation becoming cheaper and easier.</td></tr><tr><td>RNA</td><td>RNA-seq (Nagalakshmi et al., 2008)</td><td></td><td>Quantitative, can also generate qualitative data about transcription such as alternative splicing. Data analysis approaches still being optimized.</td></tr><tr><td colspan="4" style="text-align: center;">Secondary (alternative)</td></tr><tr><td>Chromatin post-translational modifications, chromatin constituents</td><td>ChIP-seq (Mikkelsen et al., 2007)</td><td></td><td>Tests entire sequenced genome. Resolution limited, not shown to be quantitative.</td></tr><tr><td>Chromatin structure</td><td>DNase-seq (Song and Crawford, 2010)</td><td></td><td>Identifies important regulatory regions not located at annotated promoters. Not shown to be quantitative.</td></tr></tbody></table>
<figure><img src="image_13.png" /></figure>

miRNA-34c (Ostling et al., 2011), altered regulation is noted in infertile men (Wang et al., 2011), and it is known that miRNA plays a critical role in cleavage in mammalian spermatogenesis (Liu et al., 2012), but neither have been reported so far to be associated with adverse clinical outcomes in prostate cancer. However, there is an adverse association with the downregulation of miRNA-4723 and miRNA 338-3p in prostate cancer (Arora et al., 2013; Bakkar et al., 2016).

A recent review of IARC monograph Volume 100 found that this volume identified specific epigenetic substances with non-genotoxic carcinogenic potential and a recommendation is made to identify a priority set of potential epigenetic, non-genotoxic carcinogens (Herceg et al., 2013; see also Tab. 4). These examples illustrate the complexity of the processes leading to carcinogenicity, such that chemicals acting through one mechanism can trigger another, as well as the complex interaction of cancer

pathways with other toxicity or AOPs. It will therefore be important to consider the paradigm of pathway-based responses in the discrimination between genotoxic and non-genotoxic chemicals, together with understanding the causality of exposures in inducing cancer versus other possible outcomes.

### 3 Current regulatory requirements and difficulties with respect to non-genotoxic carcinogens

Regulatory requirements for carcinogenicity testing of chemicals vary from legislation to legislation and region to region; however, a standard approach starts with a battery of genotoxicity tests. Positive *in vitro* genotoxicity assays trigger *in vivo* genotoxicity assays, and if these are also positive, they can trigger further more involved mammalian testing. Positive *in vitro* genotoxicity assays

<figure><img src="image_14.png" /><figcaption>Fig. 2: Preliminary conceptual overview of an IATA for NGTxC</figcaption></figure>

The upper left side of this figure shows the chemical independent AOP and existing information source factors (in blue) that can feed the NGTxC IATA, whilst the lower left side shows the chemical dependent factors, which include (Q)SARS, read-across and chemical categorization, exposure considerations, Absorption, Distribution, Metabolism and Excretion (ADME) factors, TG generated data and other possible factors (in purple).

The right hand side of the figure depicts the suggested levels of organization for the NGTxC IATA, with increasing levels of complexity that the hallmarks of NGTxC, shown in Figure 1, sit within, underpinned in many cases by epigenetic machinery, as indicated in the epicenter of the NGTxC hallmark wheel.

The underlying blue lines with connecting nodes are symbolic of the NGTxC AOP causality network, where key events (KE) and key event relationships (KER) can be identified on the basis of the mechanisms and MoA identified in Table 1. As work on the IATA progresses, these nodes will be completed as KE, KER and relevant *in vitro* assays for both the IATA and as potential OECD TGs are identified and assessed for relevance and readiness.
<figure><img src="image_15.png" /><figcaption>**Tab. 4:** Epigenetic mechanisms and other recognized mechanism(s) of human chemical carcinogens and lifestyle factors
(adapted from Herceg et al., 2013; IARC, 2012)</figcaption></figure>

<table><thead><tr><th rowspan="2">Human chemical carcinogens and lifestyle factors</th><th colspan="3">Epigenetic mechanisms</th><th rowspan="2">Main recognized mechanism(s)</th></tr><tr><th>DNA methylation</th><th>Histone marks</th><th>miRNA</th></tr></thead><tbody><tr><td>Arsenic</td><td>X</td><td>X</td><td>X</td><td>DNA repair inhibition, oxidative damage, aneu-/polyploidy</td></tr><tr><td>Asbestos</td><td>X</td><td></td><td>X</td><td>Free radicals-induced genotoxicity, aneu-/polyploidy, inflammation</td></tr><tr><td>Beryllium</td><td>X</td><td></td><td></td><td>Genotoxicity, oxidative stress</td></tr><tr><td>Cadmium</td><td>X</td><td></td><td>X</td><td>Disturbance of DNA repair and tumor-suppressor protein</td></tr><tr><td>Chromium VI</td><td></td><td>X</td><td></td><td>Genotoxicity</td></tr><tr><td>Cyclophosphamide</td><td></td><td></td><td>X</td><td>Genotoxicity</td></tr><tr><td>Diethylstilbestrol (DES)</td><td>X</td><td>X</td><td>X</td><td>Estrogen receptor-dependent pathway</td></tr><tr><td>Nickel</td><td>X</td><td>X</td><td></td><td>Disturbance of DNA repair, genotoxicity, inflammation</td></tr><tr><td>Tobacco smoking</td><td>X</td><td>X</td><td></td><td>Mutagenicity, genotoxicity inflammation, oxidative damage</td></tr><tr><td>Alcohol consumption</td><td>X</td><td>X</td><td>X</td><td>Oxidative stress, estrogen and androgen increased level, folate deficiency</td></tr></tbody></table>

can also trigger Globally Harmonized System (GHS) 2 classification for mutagenicity. If any of the *in vivo* genotoxicity tests are positive, then under several regulatory schemes a lifetime rodent cancer bioassay (RCB) may (or may not) follow. The RCB is the standard comprehensive *in vivo* test for the detection of carcinogens, including detection of NGTxC, but the bioassay will seldom be performed for chemicals.

Whilst it has been estimated that 10-20% of recognized human carcinogens classified as Class 1 by IARC act by NGTx mechanisms (Hernandez et al., 2009) there are no specific requests to obtain information on NGTx mechanisms of carcinogenicity in several chemical regulatory frameworks in OECD member countries. As already noted, the current approach to classification of carcinogens is based on the results of the *in vivo* RCB. For example, with respect to chemicals entering the European Registration, Evaluation and Authorization and Restriction of Chemicals (REACH)<fnref n="1" /> registration process, there is a general requirement that all available information on the registered substance needs to be submitted in the REACH registration dossier. Moreover, the legislation does indicate that when hyperplasia and/or pre-neoplastic lesions are observed in repeated dose studies and the substance has a widespread use or there is frequent or long-term human exposure, further carcinogenicity studies could be considered. However, the requirement to perform a carcinogenicity study is conditional (see Annex X of REACH Regulation for details). In practice, new carcinogenicity bioassays are seldom proposed by the registrants, and ECHA rarely requests such data. ECHA reports that only two proposals to conduct the RCB have been submitted to ECHA (ECHA, 2014). At the REACH registration deadlines of 2010 and 2013 substances that are manufactured at more than 100 tons per annum (tpa), have been registered, and only two carcinogenicity

studies were actually performed, as from the 2010 deadline. As they are rarely performed, few NGTxC might be identified via the assessment of these *in vivo* studies.

Published final decisions of ECHA can be found at http://echa.europa.eu/information-on-chemicals/dossier-evaluation-decisions. The REACH regulation permits registrants to adapt the standard testing regime to fill data gaps using existing data, weight of evidence, (Quantitative) Structure Activity Relationships ((Q)SAR), *in vitro* methods, and grouping of substances and read-across (ECHA, 2008, 2014). The issues regarding existing models and approaches with respect to the acceptance of *in silico* data for NGTxC chemical regulatory purposes are discussed in more detail in Section 5.4.

As there are no (OECD approved) *in vitro* screening methods for NGTxC, it appears likely that many NGTxC remain unidentified. Consequently the risks they may pose to human health will not be managed.

The situation appears to be similar in other regulatory frameworks in OECD member countries, i.e., that there is no specific chemicals legislation in place to address the NGTxC mode of action directly. As part of the regulatory evaluation process, further carcinogenicity studies can be requested if deemed necessary. In the United States, guidance is given on how to use MoA data (US EPA, 2005; Corton et al., 2014), as available, to determine if the substance is genotoxic or not, and inform the dose response relationship characterization. Similarly in the US, Canada and Japan, for cancer risk assessment, examination of the various indicators that can be seen within an OECD TG study that may alert to a potential NGTxC (e.g., estrogen agonists, overt cytotoxicity or cellular proliferation, etc.) is conducted, but there is no specific structured guidance for NGTxC

<footnote n="1">¹ https://echa.europa.eu/regulations/reach/</footnote>
<figure><img src="image_16.png" /></figure>

identification. Consequently, NGTxC is not well covered/addressed under the different OECD regulatory jurisdictions.

For GHS purposes, information regarding the type of le-
sion and species affected is an important element to forming
the conclusions regarding classification for sufficient or limited
evidence for carcinogenicity. The GHS classification is mainly
based on the evaluation of complex *in vivo* long term and carci-
nogenicity data, and the GHS criteria indicate that information
in two species is often needed to conclude as to whether a sub-
stance is a category 2 or category 1B carcinogen. In this regard,
it is important to note that several retrospective analyses of car-
cinogenicity data generated in rats and mice have raised doubts
about the need for two-species testing and revealed that mouse
studies have not been of substantial added value in regulatory
decision-making (Billington et al., 2010; Annys et al., 2014).
Therefore systematic analysis of the GHS category 1 criteria
for multi-species carcinogenicity will be needed to adequately
identify NGTxC (Gray et al., 1995), whilst also some uncer-
tainties of this test method in terms of reliability and relevance
are recognized (Gottmann et al., 2001; Alden et al., 2011). Ad-
ditionally, critical MoA information providing insights into the
human relevance may be missing (Meek et al., 2014; WHO,
2007), and this is discussed further below.

As with REACH, there are no formal NGTxC regulation
procedures to follow in several other chemical regulatory
frameworks, whilst information on the effect level and/or dose
response curve and information on the Classification and Label-
ling form an essential step in the risk management of chemicals.
With a strong international drive to reduce animals testing and
costs, it is essential that proper and robust methods for address-
ing NGTxC modes of action are developed and put in place.
This is particularly stimulated by recent discussions between
OECD member countries on difficulties as to how to meaning-
fully apply individual *in vitro* tests, such as the Cell Transforma-
tion Assay(s) (CTA), for NGTxC assessment.

At a meeting of the Working Group of the National Coordina-
tors of the OECD Test Guidelines Programme (WNT) in April
2014, the CTA using Syrian Hamster Embryo (SHE) cells was
not accepted as a Test Guideline (TG) but was proposed and
then accepted as a Guidance Document (GD) (OECD, 2015a).
Therefore, it does not fall under the Mutual Acceptance of
Data (MAD) Decision, under which data generated in the test-
ing of chemicals in an OECD member country, or a partner
country having adhered to the Decision, in accordance with
TGs and Principles of Good Laboratory Practice (GLP), can be
accepted in other OECD countries (and partner counties hav-
ing adhered to the Decision), for the purposes of assessment
and the protection of human health and the environment. This
greatly reduces the testing that needs to be done for different
regulatory jurisdictions. A GD only provides guidance as to
how to use a test.

At the WNT April 2014 meeting, it was also again recognized
that no single test can currently demonstrate and predict NGTxC
(OECD, 2012b). So, appropriate integrated approaches to detect
and manage these NGTxC are not yet in place. The construction
of an IATA could be a primary way to address this crucial gap.

4 Examples of the role of NGTxC events
in the tumor development process

In rodents the liver is the target organ that is most commonly
affected by carcinogens, thus one of the first experimental can-
cer models to highlight the role of non-genotoxic events in the
tumor multistep process was hepatocarcinogenesis. Hepatocar-
cinogenesis is a progressive process, starting with focal lesions
of inflamed liver. The neoplastic transformation of hepatocytes
is a consequence of the accumulation of genetic damage in hy-
perproliferative cells such that inflammation and cell prolifera-
tion are then considered among the initial steps in the liver tu-
mor process.

The sequence of these events is considered to be mimicked
in experimental carcinogenesis models. However, tumor forma-
tion in treated animals depends on dose, which should be suf-
ficiently high, and time span, which should be sufficiently long.
Moreover, the induction of cell proliferation is often required.
This can be achieved by performing hepatectomy, or by repeat-
edly administering a “tumor-promoting” agent, such as pheno-
barbital, which serves as an inducer of both chemical bioacti-
vation, by stimulating Phase-1 enzymes, and clonal expansion
of pre-neoplastic cells. A single administration of a genotoxic
chemical, such as N-nitrosodiethylamine (DEN), often requires
a very long time to induce the tumor. Tumor formation is also
strain, sex and age-dependent and it is poorly reproducible. For
this reason, several experimental models have been developed
to improve the sensitivity and reproducibility of the *in vivo* as-
say to study hepatocarcinogenesis in order to highlight the key
steps leading to the adverse outcome. The experimental models,
ranging from two-stage studies to xenograft models, however,
show several limitations. Even if the sequence of events in ex-
perimental models can be considered similar to the tumor pro-
cess in humans, the molecular changes are often of no or low
significance in humans. As an example, H-Ras mutations in-
duced by the treatment of DEN as a key event leading to tumor
formation, is a late event in humans, related to the formation of
metastasis and poor prognosis (Heindryckx et al., 2009). Based
on the accumulated evidence from data reported in the literature
over the last 40 years, NGTxC may trigger hepatocarcinogen-
esis through different mechanisms, including the activation of
Phase-1 enzymes via binding the Constitutive Androstane Re-
ceptor (CAR) (e.g., phenobarbital and some polychlorinated
biphenyl congeners), binding the Aryl-hydrocarbon Receptor
(AhR) (dioxin and dioxin-like compounds), or by inducing
peroxisome proliferation via the Peroxisome Proliferator-Ac-
tivated Receptor (PPARα) (e.g., hexachlorobenzene) (see Fig.
3). Peroxisome proliferation, however, is another example of
a species-specific event, whose role in human carcinogenesis
is debated and generally considered not relevant to humans in
regulatory evaluations.

On the basis of these mechanisms together with results from *in vitro* assays and two-stage *in vivo* studies, IARC provided a first list of non-genotoxic hepatocarcinogens in 1992, which was expanded in the IARC evaluations reported in 2013. The lists are included in Tables 5.1-5.4. These substances are known
<figure><img src="image_17.png" /></figure>

<figure><img src="image_18.png" /><figcaption>Fig. 3: Liver multistep carcinogenesis with liver nuclear receptor -P450 transcription factors</figcaption></figure>

(with modification from Jacobs et al., 2003)

Hepatocellular carcinoma is strongly associated with chronic liver diseases, including chronic hepatitis and cirrhosis, which are characterized by a prolonged inflammatory condition. The P450 transcription factors can be MIEs that may ultimately contribute to liver tumor development in vivo shown in Figure 3.

to modulate cell growth and cell death and exhibit dose response relationships between the initial stages of exposure and the latter stages of tumor formation. While the exact MoAs of these substances on the process of neoplastic cell formation have not been established, changes in gene expression and cell growth parameters appear to be paramount.

## 5 IATA for NGTxC

The OECD working definition of an IATA is as follows: “a structured approach used for hazard identification (potential), hazard characterization (potency) and/or safety assessment (potential/potency and exposure) of a chemical or group of chemicals, which strategically integrates and weights all relevant data

to inform regulatory decision regarding potential hazard and/or risk and/or the need for further targeted testing and therefore optimising and potentially reducing the number of tests that need to be conducted” (OECD, 2015b). When applying IATA, the hazard information together with the exposure information would be used to determine which data gaps exist, and what testing if any would be most appropriate to undertake in order to elucidate the hazard profile of that substance for a given use context. Thus the extent to which testing approaches are needed depends on the problem formulation, which in turn is defined by the end purpose under consideration and the scientific confidence needed (OECD, 2015b). The IATA should be as simple as possible but as complex as necessary, and it is necessary to provide regulators with the understanding of the assumptions on which the IATA is based (OECD, 2015b).
<figure><img src="image_19.png" /></figure>

An IATA therefore represents an approach to integrate and weigh all available data for hazard and risk purposes. This includes a wide variety of regulatory needs that range from simple hazard identification for priority setting or support for category formation and read-across to complex quantitative-based risk/safety assessments. An IATA is usually comprised of several elements, and the selection of these can be based on an AOP, where an AOP describes existing knowledge on the toxicity mechanisms at different levels of biological organization that lead to an adverse human and/or environmental health effect (Ankley et al., 2010; OECD, 2013; Tollefesen et al., 2014; Villeneuve et al., 2014). It depicts biological changes, defined as key events (KEs), at cellular, tissue,

organ and individual organism levels that occur in response to a molecular initiating event (MIE; a direct interaction of a chemical with its molecular target) leading to an adverse outcome (AO). Linkages between adjacent MIEs, KEs and AOs are described in key event relationships (KERs). For further information on OECD activities in relation to AOPs please see http://www.oecd.org/env/ehs/testing/adverse-outcome-pathways-molecular-screening-and-toxicogenomics.htm (accessed 5 April 2016).

With respect to AOP information quality, an IATA can be graded as follows:

- Correlative: a simple format, where the AOPs / MoAs have only qualitative or limited quantitative understanding of one or two

<caption>**Tab. 5: Examples of groups of chemicals that may trigger mechanisms involved in non-genotoxic carcinogenesis**</caption>

The current approach to classification of carcinogens is based on the results of the rodent bioassay. As already noted, most of the chemicals target the liver in these models.

<table><caption>**Tab. 5.1: Pesticides classified as non-genotoxic hepatocarcinogens* by IARC**</caption><thead><tr><th rowspan="2">CAS no</th><th rowspan="2">Name</th><th rowspan="2">IARC source</th><th colspan="6">Classification of carcinogenesis</th></tr><tr><th>IARC</th><th>Dir 67/548/EEC¹</th><th>Reg 1272/2008¹,²<br>(this replaces Dir<br>67/548/EEC from<br>1 June 2015)</th><th>US-EPA³</th><th>NIH Report<br>(NTP, 2014)</th></tr></thead><tbody><tr><td>15972-60-8</td><td>Alachlor</td><td>(Vainio, 1992)</td><td>—</td><td>Carc Cat 3, R40</td><td>C2 (not approved)</td><td>NA</td><td>—</td></tr><tr><td>309-00-2</td><td>Aldrin</td><td>(Vainio, 1992)</td><td>3</td><td>Carc Cat 3, R40</td><td>C2 (banned)</td><td>B2</td><td>Reasonably**</td></tr><tr><td>2425-06-1</td><td>Captafol</td><td>(Vainio, 1992)</td><td>2A</td><td>Carc Cat 2, R45</td><td>C1B (banned)</td><td>B2</td><td>—</td></tr><tr><td>86-74-8</td><td>Carbazole</td><td>(Vainio, 1992)</td><td>2B</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>57-74-9</td><td>Chlordane</td><td>(Vainio, 1992)</td><td>2B</td><td>Carc Cat 3, R40</td><td>C2 (banned)</td><td>B2</td><td>—</td></tr><tr><td>50-29-3</td><td>p,p'-DDT</td><td>(Vainio, 1992)</td><td>2B</td><td>Carc Cat 3, R40</td><td>C2 (banned)</td><td>B2</td><td>Reasonably**</td></tr><tr><td>60-57-1</td><td>Dieldrin</td><td>(Vainio, 1992)</td><td>3</td><td>Carc Cat 3, R40</td><td>C2 (banned)</td><td>B2</td><td>—</td></tr><tr><td></td><td>Hexachlorocyclohexanes</td><td>(Vainio, 1992)</td><td>2B</td><td>—</td><td>—</td><td>Not assessed</td><td>—</td></tr><tr><td>67747-09-5</td><td>Prochloraz</td><td>(Vainio, 1992)</td><td>—</td><td>—</td><td>Declassified and<br>approved 2011</td><td>—</td><td>—</td></tr><tr><td>60207-90-1</td><td>Propiconazole</td><td>(Vainio, 1992)</td><td>—</td><td>—</td><td>Included in Annex 1</td><td>Not assessed</td><td>—</td></tr><tr><td>55219-65-3</td><td>Triadimelon</td><td>(Vainio, 1992)</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>1582-09-8</td><td>Trifluralin</td><td>(Vainio, 1992)</td><td>3</td><td>—</td><td>C2 (not authorized)</td><td>Not assessed</td><td>—</td></tr></tbody></table>

<table><caption>**Tab. 5.2: Drugs and dyes classified as non-genotoxic hepatocarcinogens* by IARC**</caption><thead><tr><th rowspan="2">CAS no</th><th rowspan="2">Name</th><th rowspan="2">IARC source</th><th colspan="6">Classification of carcinogenesis</th></tr><tr><th>IARC</th><th>Dir 67/548/EEC¹</th><th>Reg 1272/2008¹,²</th><th>US-EPA³</th><th>NIH Report<br>(NTP, 2014)</th></tr></thead><tbody><tr><td>492-80-8</td><td>Auramine (4,4'-carbonimidoyl-bis[N,N-dimeth-hylaniline])</td><td>(Vainio, 1992)</td><td>2B</td><td>Cat 3, R40</td><td>C2</td><td>—</td><td>—</td></tr><tr><td>144-02-5</td><td>Barbital</td><td>(Vainio, 1992)</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>637-07-0</td><td>Clofibrate</td><td>(IARC, 1996)</td><td>3</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>68-89-3</td><td>Dipyrone</td><td>(Vainio, 1992)</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>97-77-8</td><td>Disulfiram</td><td>(Vainio, 1992)</td><td>3</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>938-73-8</td><td>Ethenzamide</td><td>(Vainio, 1992)</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>50-06-6</td><td>Phenobarbital</td><td>(Vainio, 1992)</td><td>2B</td><td>—</td><td>—</td><td>—</td><td>—</td></tr></tbody></table>
<figure><img src="image_20.png" /><figcaption>Tab. 5.3: Hormone, hormone-like and endogenous metabolites classified as non-genotoxic hepatocarcinogens* by IARC</figcaption></figure>

<table><caption>Tab. 5.4: Miscellaneous compounds classified as non-genotoxic hepatocarcinogens* by IARC</caption><thead><tr><th rowspan="2">CAS no</th><th rowspan="2">Name</th><th rowspan="2">IARC source</th><th colspan="5">Classification of carcinogenesis</th></tr><tr><th>IARC</th><th>Dir 67/548/EEC<fnref n="1" /></th><th>Reg 1272/200¹,</th><th>US-EPA<fnref n="3" /></th><th>NIH Report (NTP, 2014)</th></tr></thead><tbody><tr><td>57-63-6</td><td>17α Ethinyl oestradiol</td><td>(Vainio, 1992)</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>117-81-7</td><td>DEHP</td><td>(IARC, 2013)</td><td>2B</td><td>Repr Cat 2, R60-61</td><td>R1B</td><td>B2</td><td>Reasonably**</td></tr></tbody></table>

<table><thead><tr><th rowspan="2">CAS no</th><th rowspan="2">Name</th><th rowspan="2">IARC source</th><th colspan="5">Classification of carcinogenesis</th></tr><tr><th>IARC</th><th>Dir 67/548/EEC</th><th>Reg 1272/2008</th><th>US-EPA<fnref n="3" /></th><th>NIH Report (NTP, 2014)</th></tr></thead><tbody><tr><td>94-59-7</td><td>Safrole</td><td>(Vainio, 1992)</td><td>2B</td><td>Carc Cat 2- R45 Mut Cat 3-R68</td><td>C1B - M1</td><td>–</td><td>Reasonably**</td></tr><tr><td>62-55-5</td><td>Thioacetamide</td><td>(Vainio, 1992)</td><td>2B</td><td>Carc Cat 2 R45</td><td>C1B</td><td>–</td><td>Reasonably**</td></tr><tr><td>51-79-6</td><td>Urethane</td><td>(Vainio, 1992)</td><td>2A</td><td>Carc Cat 2 R45</td><td>C1B</td><td>Not assessed</td><td>Reasonably**</td></tr><tr><td>111-42-2</td><td>Diethanolamine</td><td>(IARC, 2013)</td><td>2B</td><td>Carc NC</td><td></td><td></td><td>Inadequate</td></tr><tr><td>1746-01-6.</td><td>2,3,7,8 TCDD</td><td>(IARC, 2012)</td><td>1</td><td>–</td><td>–</td><td>–</td><td>Known carcinogen*** Clear evidence (NTP, 2006)</td></tr></tbody></table>

cause and effect linkages between KEs or a KE and the AO. These pathways are often based on a few stressors tested in a limited number of assays with a low level of confidence in the AOP.

- Qualitative: where AOPs / MoAs have qualitative understanding of critical components of the AOP / MoA. Pathways are often based on one or a few well-studied stressors where there is experimental evidence for the most critical KEs and the AO. The level of confidence in the AOP is moderate.

- Semi-Quantitative: where AOPs / MoAs have, in addition to qualitative understanding of the entire AOP / MoA, semi-quantitative understanding of some of the KEs. Pathways are based on multiple compounds and/or stressors evaluated at several KEs and the AO. The level of confidence in the AOP is moderate to high.

- Quantitative: where AOPs / MoAs have, in addition to quantitative understanding of critical components of the AOP, empirical data across the spectrum of KEs and AO. These pathways are based on many compounds evaluated for all KEs and the AO, so *in vitro* effects can be scaled to *in vivo* effects for risk assessment. The level of confidence in the AOP is high (OECD, 2015b).

Much of the available information about AOPs, MIEs, KEs, AOs and chemical initiators is being collected and will be linked in the AOP Knowledge Base (AOP-KB, https://aopkb.org), an ongoing OECD initiative. The number of AOPs being developed by the scientific community internationally, both for human health and ecological effects, is steadily increasing. As more AOPs are developed and successfully peer reviewed, networks of AOPs will arise that are interlinked by sharing one or more KEs and/or KERs. In this way the AOP concept provides a framework to organize and communicate scientific knowledge on toxicological mechanisms that may be highly informative for regulatory decision-making and IATA construction. An IATA can also be developed in an empirical manner, based upon predictivity and reproducibility, as expected from a TG, and can so also contain elements that are not informed by an AOP, particularly intended use and exposure, toxicokinetics and -dynamics, etc.

Depending on the purpose of the risk assessment, the exposure assessment may need to emphasize certain areas in addition to quantification of exposure and dose, for example, the number of people exposed and the duration and frequency of exposure(s). However, the methodology and guidance for exposure assessment considerations are not being included at this

<footnote>* Note that carcinogenicity endpoints other than hepatocarcinogenicity may have also been included in some of these classifications.</footnote>

<footnote>** Reasonably anticipated to be human carcinogen according to NTP classification</footnote>

<footnote>*** Known to be human carcinogen</footnote>

<footnote n="1">¹ Annex I of Directive 67/548/EEC by Dir ENV. This was repealed from 1 June 2015, and replaced by Regulation (EC) No 1272/2008, with substantial modifications, including the introduction of the Globally Harmonised System of Classification and Labelling of Chemicals (GHS)</footnote>

<footnote n="2">² according to Classification, Labelling and Packaging (CLP) Regulation (CE) 1272/2008 (extract from Table 3.1 of annex VI), 6th ATP</footnote>

<footnote n="3">³ Chemicals known to the state to cause cancer or reproductive toxicity February 3, 2006 (State of California Environmental Protection Agency)</footnote>
<figure><img src="image_21.png" /></figure>

early stage, since these are outside the scope of the intrinsic haz-
ard profile. The reader is referred to more authoritative sources
for the conduct of an exposure assessment, e.g., Embry et al.
(2014).

The governance of IATA activities is in development under
the auspices of the OECD. The intention is that at least core
elements of IATAs can be developed that will also fall under the
Mutual Acceptance of Data (MAD) principle that underpins the
OECD Test Guideline Programme (Section 3), such that they
are mutually accepted in member countries.

Here, we explore the basis for the development of an IATA for
NGTxC, aiming first to address hazard identification and how
this can start to be approached internationally in a harmonized
manner (and under the auspices of the OECD). There might be
a need for several “purpose” levels within an IATA for NGTxC,
or there might be a need to develop different and separate pur-
pose driven IATAs for NGTxC. These ideas and concepts are in
very early development, and here we are not able to make con-
crete and definitive suggestions as to a final IATA for NGTxC,
but we do examine how to start synthesizing the approaches
that would be acceptable at the OECD level. Figure 2 provides
a conceptual bird’s eye view and provisional structure in which
to synthesize the elements that can inform an IATA for NGTxC,
as described within this paper.

5.1 Thresholds

NGTxC chemical substances exhibit temporal and threshold
characteristics frequently requiring repeated treatment to pro-
duce carcinogenicity. While NGTxC are carcinogenic alone,
they are generally considered to impact upon the promotion
stage of the cancer process. As such, they synergize with geno-
toxic agents and/or DNA damaging events, triggering the mul-
tistep carcinogenic process. Co-exposure and interactions occur
constantly in real life, and promoting effects might be worth
considering in the regulation of chemicals for cancer preven-
tion. The AOP construct can be very useful to discriminate
between the adaptive response and the adverse responses, so
identifying the reference dose that is the point of departure (i.e.,
benchmark dose (BMD)) for the calculation of the acceptable
exposure levels (Chepelev et al., 2015).

Within current regulatory frameworks up to now the existence
of thresholds for NGTxC has been generally accepted. However,
due to the possible interactions with GTxC, and in the context
of probabilistic, population-based limit value derivation (WHO,
2014), the concept may need refinement for the purpose of plan-
ning, design and interpretation of an NGTxC IATA, and therefore
a brief consideration on the threshold issues is presented here.

The variability of data points within each experimental data
set could be used to derive a no adverse effect level including its
confidence interval, i.e., a BMD approach. In other words, there
is a probability that at concentrations much below the BMD the
effect size should still be considered as adverse. In addition to
“within experimental uncertainty”, there is extrapolation un-
certainty – from animals to humans and between humans. Dif-
ferences between animals and humans, and furthermore differ-
ences between humans vary for each individual chemical, and

the use of safety assessment factors varies according to differ-
ent regulatory frameworks. Assessment factors may be better
formulated scientifically as probability distributions (mean ±
SD) (e.g., Jaworska et al., 2011; WHO, 2014) rather than de-
terministic (e.g., factor 100), in which case on a human popula-
tion level no deterministic threshold for whatever type of effect
can be defined, be it GTx or NGTx (see e.g., Vermeire et al.,
1999). The current common regulatory practice is to use large
assessment factors or probabilistic thresholds for GTx carcino-
gens (e.g., residual tumor probability of 10⁻⁶), but standard as-
sessment factors and deterministic thresholds for NGTx effects.
This perhaps reflects the differing confidence in the reliability
and relevance of the GTx and NGTx testing methods rather than
a biological concept, and as such could be a useful consideration
in the WoE analysis within an NGTxC IATA.

5.2 Requirement of consistent evidence
of adversity

When we consider the possible mechanisms through which
NGTxC affect the carcinogenesis process, it is important to
appreciate that not all of these mechanisms are always related
to adversity. For example, oxidative stress, cell death and im-
mune system evasion are three strictly interconnected cancer
hallmarks (they share several molecular targets and pathways).
However, cell death is also a mechanism of cell defense, and the
immune system has a counterbalancing role to play that recent-
ly has been described as a yin/yang response (Khatami, 2008;
Biswas and Mantovani, 2010), depending upon the affected
pathway, as the body attempts to recover from a toxic insult
and tries to restore balance. Among these three mechanisms,
oxidative stress is directly linked to adversity, but for the other
mechanisms, disturbance of the immune system could also lead
to serious adverse effects, depending upon whether the balance
is disturbed and equilibrium is not quickly restored. Since it is
possible to measure only the endpoint (molecular target, bio-
marker) that is related to the mechanisms, but not necessarily
to adversity, a substance cannot be considered to be a positive
NGTxC simply on the basis of a single mechanistic *in vitro* test,
or only one mechanism, particularly if this mechanism cannot
be unequivocally related to adversity.

5.3 One IATA NGTxC cancer model or many?

When it comes to building an IATA for NGTxC, it is very like-
ly that while there may be mechanistic blocks or common KE
elements and KERs that occur in many different types of can-
cers, there can also often be specific influences and signaling
pathways as first indicated in Table 1 that are more relevant to a
particular tissue and organ. It is therefore unlikely that a global
“one size fits all” model will be sufficient. Here we suggest
three initial examples of the natural history of tumor progres-
sion scheme: liver (Fig. 3), colon (Fig. 4) and lung (Fig. 5),
utilizing the AOP format that might provide the basis for IATA
approaches for NGTxC to prioritize testing regimes. These first
examples are developed to highlight the role of inflammation
and related oxidative stress as steps that trigger NGTxC in
the multistep carcinogenesis process. Inflammation is a major
<figure><img src="image_22.png" /></figure>

<figure><img src="image_23.png" /><figcaption>**Fig. 4: Colon multistep carcinogenesis**</figcaption></figure>

Colon cancer can be initiated by inherited damage or mutated APC in FAP families, as a sporadic form, where APC is hypermethylated as a consequence of environmental exposures (diet, alcohol consumption) and as a consequence of inflammation in chronic diseases or inflammation stimulated by pathogenic bacteria. Inflammation plays the main role also in the early steps of sporadic tumors.

pathological condition that provides suitable conditions for fur-
ther evolution of the multistep process.

Whilst there are for NGTxC many mechanisms and modes of
action leading to an adverse outcome, one can start to map the
AOP utilizing current understanding of tumor natural histories,
and therefore elucidate the key assay blocks that would be re-
quired for an organ specific IATA for example.

These may therefore form a basis for the IATA specific com-
partments from which an IATA framework for NGTxC will be
able to draw out mechanistic KE commonalties for assay selec-
tion and development, and the KE differences that would need
specific attention.

The first example is that for hepatocarcinogenesis. Figure 3
shows major nuclear receptor -P450 transcription factors in-
volved in xenobiotic metabolism that can be MIE, which may
ultimately lead to liver tumor development *in vivo*. This figure
depicts the natural history of tumor development and progres-
sion leading to the adverse outcome of liver cancer.

A second example is that for colon cancer. Figure 4 shows
such a scheme for colon cancer. It is known that colon cancer
can be initiated by inherited damage, e.g., an encoding large
multidomain protein that antagonizes the Wnt signaling path-
way, called mutated adenomatous polyposis coli (APC), is
known to be the main causative gene responsible for familial
adenomatous polyposis (FAP). This is an autosomal dominant
disorder characterized by the development of many hundreds to
thousands of colonic adenomas, and thus an increased risk of

colorectal cancer (Liu et al., 2016). It can also occur as a spo-
radic form where APC is hypermethylated as a consequence of
environmental exposures (i.e., diet, alcohol consumption) and
also as a consequence of inflammation in chronic diseases or
due to pathogenic bacteria (Viljoen et al., 2015). Inflammation
also plays the main role also in the early steps of sporadic colon
tumors.

The third example is lung cancer. For lung cancer, inflam-
mation is the first adverse effect following the exposure to
environmental oxidative stressors (such as smoking and air-
borne environmental pollutants). Inflammation is supported
by the immediate immune response, through the production of
chemokines and activation of alveolar macrophages. Figure 5
maps the key events in the natural history of tumor develop-
ment and progression leading to the adverse outcome of lung
cancer.

**5.4 Acceptance of *in silico* data for regulatory purposes**

Generally, *in silico* approaches have been utilized for many
years by regulatory organizations such as the US EPA, but the
routine use of such tools has not been consistent (Lo Piparo et
al., 2011), often due of a lack of in-house expertise but also, with
respect to carcinogenicity, due to a lack of appropriate models.
However, the implementation of REACH, which aims to fill in-
formation gaps for a large number of chemicals and strongly
encourages the minimization of animal testing, has provided an
<figure><img src="image_24.png" /></figure>

<figure><img src="image_25.png" /><figcaption>Fig. 5: Lung multistep carcinogenesis</figcaption></figure>

Inflammation is the first adverse effect following exposure to environmental oxidative stressors (smoking, environmental pollutants). Inflammation is supported by the immediate immune response through the production of chemokines and activation of alveolar macrophages.

impetus to employ *in silico* models for the safety assessment of chemicals (EC, 2008). Non-testing methods to assess genotoxic or carcinogenic hazard to humans encompass (Q)SARs as well as chemical grouping for read-across approaches. The principle of the latter is that endpoint or test information for one or more chemicals is used to predict the same endpoint or test for another chemical, which is considered to be similar by robust scientific justification (Wu et al., 2010; OECD, 2014). Crucial for this approach are the quality of the existing data and definitions of the similarity, and with a drive to improve the transparency and consistency in the utilization and evaluation of read-across, ECHA have recently developed a Read-Across Assessment Framework (ECHA, 2015). Read-across approaches are more frequently applied for cancer hazard assessment than (Q)SAR methods (ECHA, 2014). (Q)SAR models predict the biological activity of a given chemical using quantitative parameters describing structure but also physico-chemical and/or reactivity

properties of substances. SAR models only use (sub)structure information and can therefore be seen as a more formal way of performing read-across with a given reference set of data, as the property of one or more substances is directly used to predict the property of the substance of interest. It is noted that conceptually (Q)SARs should be developed utilizing a large, good quality database using robust scientific and statistical concepts and as such should represent the most formalized non-testing approach. In contrast, read-across has the disadvantage of representing a much less formalized and therefore more subjective non-testing approach, but it may provide more specific information. In the future a combination of (Q)SARs with read-across, i.e., a local validity analysis of the models, may be of greater reliability for decision making. VEGA², for example, explicitly supports this. Such an approach may improve possibilities to yield robust information on the type of effect (tumor) and the dose levels at which effects occur. This information is crucial
<figure><img src="image_26.png" /></figure>

in risk assessment and will not be delivered by the use of, e.g., alert models such as DEREK-Nexus<fnref n="3" />, or ToxTree<fnref n="4" /> (Patlewicz et al., 2008). Application of such alert models will be more relevant in screening large numbers of substances, and subsequent priority setting. A good example of such an approach is the ICH M7 guideline for assessment of potentially genotoxic impurities in pharmaceuticals (ICH, 2014). According to this guideline, a negative result obtained from *in vitro* bacterial mutagenicity (e.g., Ames test) is sufficient to assume lack of genotoxic potential of the impurities under study, and no further testing is conducted.

Indeed the examples for *in silico* genotoxicity tools are far stronger than those for NGTxC mechanisms and MoA. Multiple computational models have been established for identifying a chemical's genotoxic potential, triggered over 25 years ago by the publication of the Ashby-Tennant alerts in 1991 (Ashby and Tennant, 1991), followed by software such as VEGA (Fjodorova et al., 2010), ToxTree (Patlewicz et al., 2008), the OECD QSAR Toolbox (OECD, 2015c) and LAZAR (Maunz et al., 2013; Lo Piparo et al., 2014), which are all available free of charge. Other, (semi)commercial, models include MultiCASE<fnref n="5" />, TOPKAT<fnref n="6" />, HazardExpert<fnref n="7" />, LeadScope<fnref n="8" /> and DEREK-Nexus<fnref n="3" />. In general, it can be stated that these models, in contrast to those developed for predicting NGTxC, are more developed, and cover broader chemical space. The knowledge embedded in the various free-of-charge models, as well as in the commercial models, often largely overlaps, as most models derive their knowledge from the same set of experimental data, although there are differences in the details. Caution is warranted when using multiple theoretical models in a WoE approach, as the same outcome from different models does not necessarily increase the confidence in that prediction. A further distinction should be made between models that are “only” alert models, such as the DEREK-Nexus expert system, ToxTree, or the profilers in the OECD QSAR Toolbox, versus models that also try to correlate the absence of genotoxicity or carcinogenicity to specific chemical and/or physicochemical properties. The first are considered to give only a valid positive prediction, i.e., the absence of an alert is not a prediction of the absence of genotoxicity and/or carcinogenicity. In contrast, models such as VEGA, TOPKAT and MultiCASE give valid predictions of the presence and absence of genotoxicity or carcinogenicity, the latter being based on the similarity of a substance with the negative (non-carcinogenic) substances in their training datasets.

With the large diversity of chemicals that might interfere with the NGTxC mechanisms and the many potential molecular targets, the establishment of a single (Q)SAR for NGTxC is an unrealistic goal and the diversity makes development of (Q)SAR models for identifying NGTxC a challenging process. Furthermore, NGTxC typical characteristics, such as receptor binding,

are considered more important than structural alerts (Silva Lima and Van der Laan, 2000), but these can be combined. A few models describing a number of structural alerts and/or characteristics of several types of NGTxC, such as PPARα activators and inducers of oxidative stress, have been developed (Woo and Lai, 2003; Benigni et al., 2013).

Thus, for structural alerts for receptor mediated interactions (e.g., ER, AR, PXR, CAR, PPAR, GR and AhR, where the receptors are considered MIEs that may induce cancer indirectly via hormonal imbalance), (Jacobs et al., 2003; Jacobs, 2004; EFSA, 2013, 2014, and references therein; OECD 2015c and references therein), oxidative stress and DNA methylation (Benigni, 2012; OECD 2015c), application of *in silico* methods in sequential/ step-wise approaches (combining relevant and reliable expert systems or (Q)SAR models), can contribute to the WoE. Overall, for MIE endpoints, such as receptor binding and activation, the quality and reliability of the tools are relatively high, but reliability for more complex endpoints has been noted to be far less certain (Benigni, 2014; EFSA, 2013, 2014; OECD, 2015c). With respect to models built upon the CTA for example, as already discussed, regulatory confidence needs to be improved, but this is possible when used in a tiered testing strategy with the inclusion of relevant new structural alerts for NGTxC.

The OECD has recently published new guidance principles for (Q)SAR analysis of chemical carcinogens with mechanistic considerations (OECD, 2015c), which include some NGTxC mechanisms, though these will need further assessment, whilst the US EPA have developed and published a new pathway-based approach with performance based metrics, using the ER signaling pathway as the first example. The approach consists in an integrated model of chemical perturbations of a biological pathway using 18 *in vitro* high throughput screening assays for the ER, with data generated from the Toxcast/Tox21 program (Browne et al., 2015). Kleinstreuer et al. (2013) developed a model trained on 232 pesticides from the phase 1 study of the Toxcast project for the prediction of rodent carcinogenicity including some of the cancer hallmark processes, identified in Figure 1. However, there were several false negatives of concern, and the data used to build this model is noted to be limited, but the phase 2 study, may overcome some of these data quality problems.

For both predictions (positive and negative), the similarity of the substance of interest to the substances used in the training datasets of the models (the so-called *applicability domain* of the models) is crucial. Although a (Q)SAR model might be able to give a prediction for any (organic) substance, if this prediction is far outside of the applicability domain, the reliability of the prediction will be low. Amongst the model builders there are also different interpretations of the definition of the term

<footnote n="2">² http://www.vega-qsar.eu//</footnote>

<footnote n="3">³ http://www.lhasalimited.org/products/derek-nexus.htm</footnote>

<footnote n="4">⁴ https://eurl.ecvam.jrc.ec.europa.eu/laboratories-research/predictive_toxicology/qsar_tools/toxtree</footnote>

<footnote n="5">⁵ http://multicase.com/</footnote>

<footnote n="6">⁶ http://accelrys.com/products/datasheets/qsar-admet-and-predictive-toxicology-with-ds.pdf</footnote>

<footnote n="7">⁷ http://www.compudrug.com/hazardexpertpro, accessed 5 April 2016.</footnote>

<footnote n="8">⁸ http://www.leadscope.com/product_info.php?products_id=66</footnote>
<figure><img src="image_27.png" /></figure>

"applicability domain" (VEGA, TOPKAT and MultiCASE all have their own definitions), which is confusing for the inexperienced user. However, in principle, deciding on the applicability domain for a (Q)SAR model represents the same challenge as deciding on sufficient similarity of substances within read-across approaches. As outlined below, further improvements are expected in future with the integration of such non-testing approaches with *in vitro* approaches.

A thorough analysis of the use of *in silico* information in a regulatory setting shows that the number of REACH dossiers for which read-across and/or (Q)SAR was used to replace experimental evidence hovers around 30% (ECHA, 2014). Furthermore, read across/(Q)SAR information was more frequently used for substances with lower information requirements in comparison to substances with higher information requirements (higher production volume) (ECHA, 2014). This could, in part, be explained by the fact that more (Q)SARs are available for the mechanistically more simple endpoints (irritation, sensitization, mutagenicity), which are required to be assessed at lower tonnage levels. A similar trend in the use of Q(SAR) predictions can be noted for pharmaceuticals, as the ICH has adopted the M7 guideline for assessment of potentially DNA-reactive/mutagenic impurities in pharmaceuticals (ICH, 2014). The use of WoE approaches should further enhance both the application and acceptance of *in silico* information in chemical safety assessment.

## 5.5 Acceptance of *in vitro* data for regulatory purposes

Current GHS criteria will not consider *in vitro* data on their own as adequate to classify a substance as a carcinogen, as the definition indicates it needs to be established in an intact organism, as is also the case for many regulatory frameworks with respect to endocrine disruptors, but there are signs of improvements in flexibility with respect to the term “intact organism.” This is also valid for the conclusion as to whether a substance is not an NGTxC. Thus NGTxC determination for a chemical can as yet not be concluded solely on basis of a single mechanistic *in vitro* test.

In the development of an IATA for NGTxC, it therefore will be important to integrate more than one “adversity” endpoint, so that there is more consistent evidence of adversity. For example, if a chemical triggers senescence by modulating telomerase, it should be tested for genetic instability. In this context, the CTA also could be considered to provide the endpoint related to morphological transformation. And another example, if a chemical blocks the gap junctions or induces oxidative stress, is this mechanism related to morphological transformation? Or does it occur independently? If both morphological transformation and oxidative stress are observed, the level of concentrations that are effective on each criterion may inform as to a possible link, or not.

The development of test case study examples may help in assisting with such evaluations for practical purposes and application to real life risk assessment scenarios. Particular attention will need to be paid to how this will be used by stakeholders in

practice. Will they indicate their substance as being an NGTxC on the basis of an IATA primarily based on *in silico* and *in vitro* data? Or will it still be necessary for regulators to ask for more (*in vivo*) information to come to definite conclusions that are essential for risk management measures? In the spirit of *Toxicity Testing in the 21st Century* (NAS, 2007), an additional ultimate goal will be for the IATA to eventually move away from animal testing altogether, as the KE, KERs and test methods that could address those KEs are increasingly identified, confirmed and validated.

It will be essential that the IATA is developed in such a way that in most cases regulatory decisions can be taken without the need of additional animal testing. Otherwise regulatory acceptance will be limited due to concern for false negatives on one hand or concern for false positives on the other hand, such that gains in the 3Rs as well as gains in regulatory testing and assessment throughput will be minimal. Expectations for the time frame necessary to develop such an IATA vary between experts and in the end depend upon resources that are made available. The time frame will also be influenced by how far the IATA can accommodate defined testing approaches for specified chemical spaces (the “chemical applicability domains” referred to in the previous section), for more robustly characterized mechanisms of action compared to less well characterized mechanisms, and for categorization and read-across based on a larger database including other animal data or for specific regulatory areas, e.g., those without legal animal data requirements. In any case, scrutinizing the reliability and the relevance and potential added value of the *in vivo* testing standards (Gottmann et al., 2001; Alden et al., 2011; Basketter et al., 2012; Marone et al., 2014) should contribute to the development of robust testing strategies (Paparella et al., 2013, 2016).

## 5.6 Levels of test information as a preliminary step towards the IATA

A structured approach to building an IATA for NGTxC could be usefully organized into different levels of information, and the AOP concept provides a suitable starting point for creating such an information level framework. Table 6 provides a summary overview of such a structure, as described below, and Figure 2 illustrates how such levels could fit conceptually into an IATA for NGTxC.

Level 0 would cover pre-screening of existing information, category formation, read-across and (Q)SARs, also indicated in Figure 2 as part of the AOP information. Subsequent levels would continue to incorporate AOP level concepts, such that: Level 1 would be at a subcellular level of very early KE and include for example *in vitro* assays such as receptor binding assays that indicate the MIE; Level 2 would be at the cellular level, also *in vitro*, and include both MIEs such as receptor binding and initial KE such as DNA activation, enzyme activation and other further downstream KE (such as disturbance of metabolism and key event relationships); Level 3 would be at the organ level, and so include *ex vivo* assays and *in vivo* screening assays, developing KER further, whilst Level 4 would include the whole organism level, but be kept to a minimum, in keeping
<figure><img src="image_28.png" /><figcaption>Tab. 6: Overview of levels of test information as a preliminary step towards the IATA</figcaption></figure>

<table><thead><tr><td>Level</td><td>Description</td></tr></thead><tbody><tr><td>0</td><td><strong>Existing data and non-test information</strong><br>pre-screening of existing information, category formation, read across and (Q)SARs</td></tr><tr><td>1</td><td><strong>Subcellular level: in vitro</strong><br>very early KEs including for example in vitro assays such as receptor binding assays that indicate the MIE</td></tr><tr><td>2</td><td><strong>Cellular level: in vitro</strong><br>includes both MIEs such as receptor binding and initial KEs such as DNA activation; enzyme activation and other further downstream key events (e.g., disturbance of metabolism, and KERs)</td></tr><tr><td>3</td><td><strong>Multicellular tissue and organ level</strong><br>includes in vitro, ex vivo assays and in vivo screening assays, developing KERs further</td></tr><tr><td>4</td><td><strong>Whole organism level</strong><br>only to be performed if the earlier levels did not provide a sufficiently strong weight of evidence required by a regulator/ regulatory jurisdiction</td></tr></tbody></table>

with *Toxicity Testing in the 21st Century* (NAS, 2007) and only be performed if the earlier levels did not provide sufficiently strong weight of evidence as required by a regulator/regulatory jurisdiction.

In some cases an assay or diagnostic tool might straddle two levels, for example docking studies with chemicals and receptors/P450 can provide very specific molecular mechanisms for an MIE and belong in Level 0 ((Q)SAR information) and Level 1. The CTA's also might belong to two levels: Level 2 and Level 3. This is because while the cytoskeleton changes are strictly related to the acquisition of the malignant phenotype in the CTA, cloning of embryonic Syrian hamster cells leads to colonies that may acquire a transformed phenotype when exposed to chemical carcinogens. The morphologically transformed colonies are characterized by disorganized growth patterns which mimic early stages in the carcinogenic process (OECD, 2015a). Thus, in combination with toxicogenomics profiling highlighting the CTA mechanisms, the assay could in the future be considered a Level 3 assay, as the change in cytoskeleton may be used as a hallmark of the cancer microenvironment. This would be in keeping with the OECD recommendation (OECD, 2015a) that "When SHE CTA results are used as part of a testing strategy (not as results from a stand-alone assay) and/or in a weight of evidence approach, they may contribute to the assessment of carcinogenic potential of test chemicals (Creton et al., 2012)."

The resolution of the different levels (molecular /subcellular – cellular – tissue/organ – organism) may need to be higher, depending upon the purpose of the IATA, and this will need more discussion.

Such a structured approach for the scoping of the IATA is necessary, whether it is being developed for prioritization purposes for further testing or the purpose is for hazard identification/ characterization to indicate whether a substance is an NGTxC or not, for subsequent quantitative risk assessment purposes, or both.

The structure can then also assist in the grouping of different types of tests and assays that can be used in identification of NGTxC. At each level the decision on the next required test to be done would depend on the available information and test

results already obtained. This involves an integrative assessment before each level is considered completed. Probabilistic approaches are increasingly considered to reflect more realistic data interpretation (Jaworska and Hoffmann, 2010; Jaworska et al., 2011; Paparella et al., 2013; Rovida et al., 2015).

To further ensure that the key MoA(s) are identified, and not missed, all MoAs would need to be tested when one moves from one block of MoA tests to the next, if negative in the first block tested. That is, testing one MoA will not exclude all other MoAs.

## 6 Chemical examples

From the list of chemicals that are considered as NGTxC hepatocarcinogens by IARC (Tab. 5), with the Table 1 overview of key NGTxC mechanisms and the liver tumor model shown in Figure 3, it may be helpful to consider actual chemical examples that demonstrate how the results from *in vitro* tests at different levels may contribute to overcome the uncertainties related to *in vivo* results.

These examples all have their limitations and are given here not to draw any conclusions but to emphasize the limitations of the current approaches in the evaluation of the carcinogenic potential of NGTxC (including the role of peroxisome proliferation), and to provide a starting point for discussion and evolution of the concept.

A good first chemical example, DEHP, can be given to start to suggest minimum information requirements for each level. This example is also interesting in that it highlights the fact that carcinogenic information generated *in vivo* can in some cases be considered equivocal, species specific and may be better detected with key event based testing. This is because the earlier levels, before Level 4, provide the key MOA information, whilst the key MOA information often is obscured in Level 4 *in vivo* data.

DEHP, is negative in GTxC assays, but is an initiator in initiation/promotion studies and is considered to be a hepatocarcinogen in rodents (IARC, 2013). However, the carcinogenic effect in rodents is recognized to be species specific and strictly
<figure><img src="image_29.png" /></figure>

related to the peroxisome proliferation in the liver of treated animals (Melnick, 2001), and this is not considered relevant to humans. Recently, it has been reported to induce liver tumors in PPARα-null mice and a different mechanism has been hypothesized, which includes the activation of the human CAR, a constitutively expressed xenobiotic receptor that plays a role in liver cancer induced by phenobarbital, in structure activity relationships (Zhang et al., 2015) and *in vivo* (Lv et al., 2015). The potential for ER dependent and ER independent modulations also has been shown recently in two cell lines (Tanay Das et al., 2014).

DEHP can be shown to have the following succession of key events: Level 1, MIE/KEs: Receptor binding with PPARα and CAR (see Tab. 1), thus two MIEs, followed by KEs also at sub cellular level: induction of CYP 4A and CYP 2B, respectively (see also Fig. 3); Level 2, KEs: inhibition of apoptosis, peroxisome proliferation, inhibition of gap junctional intracellular communication; Level 3 KEs: enlarged liver due to peroxisome proliferation; and Level 4, AO adverse outcome: hepatocarcinoma (see Tab. 7).

Another example, atrazine is the prototype of a class of chemicals (triazines) sharing the same MoA supporting NGTxC. Triazines represent the first example for which combinations of structure-activity considerations and relevant biological and molecular events were used to support a MoA regulatory approach to assess adverse effects (US EPA, 2002). In the following years,

however, this mechanism was considered not relevant to humans, and the carcinogenic activity of atrazine was questioned on the basis of biological plausibility. More recent reports highlight the transgenerational effect of atrazine exposure (Hovey et al., 2011), resembling the next generational behavior of endocrine disruptors, such as diethylstilbestrol (DES), via a mechanism that could be of relevance to humans, but for which there is no evidence in the standard cancer bioassay. Atrazine and atrazine metabolites have MIEs acting via early KEs that include steroidogenesis/aromatase, CYP 1A2 induction and binding to G protein-coupled estrogen receptor 1 (GPER). Level 2 KEs include ERK (extra signal-regulated kinases) activation, at Level 3 the effect observed is delayed mammary gland development (initiated *in utero*), and at Level 4 in rats, mammary gland tumors are reported (Tab. 7). The MoA for mammary gland tumors in the rat is species and strain specific (Simpkins et al., 2011) due to differences in the modulation of gonadotrophin releasing hormone (GnRH) pulse and impact upon the release of luteinizing hormone with alteration of ovulatory cycles – which are markedly different and not of human relevance, as recently concluded by the Risk Assessment Committee at ECHA (ECHA, 2015).

The third example, captafol, a pesticide, is not considered genotoxic, but displays both hepatic and renal carcinogenicity (Rakitsky et al., 2000; IARC, 1991). However, most NGTxC that are renal carcinogens are negative in a standard cancer bioassay, and thus captafol is an example of a NGTx carcinogen

<table><caption>Tab. 7: Minimum information currently available per level from existing data: Three chemical examples</caption><thead><tr><td>Chemical</td><td>Level 0</td><td>Level 1</td><td>Level 2/3</td><td>Level 3</td><td>Level 4*</td></tr></thead><tbody><tr><td>DEHP</td><td>(Q)SAR and structure activity information (Benigni, 2012; Serafimova et al., 2007; Zhang et al., 2015)</td><td>Induction of CYP 2B10 associated with CAR activation (Ren et al., 2010)</td><td>Inhibition of apoptosis in cultured human hepatocytes (Goll et al., 1999) and SHE cells (Maire et al., 2005; Pant et al., 2010)</td><td>3D liver models (Soldatow et al., 2013), peroxisome proliferation in liver of exposed animal in standard toxicity assays (Doull et al., 1999), inhibition of gap junctional intercellular communication in liver of exposed rats and mice (McKee, 2000), ex vivo assays</td><td>Hepatocarcinoma, cholangiocellular tumors in male rats (standard bioassay male rats and PPARα-null mice), cholangiocellular carcinoma (PPARα-null mice), hepatocarcinoma in female rats (standard bioassay), increased incidence of kidney tumors in rats (initiation/promotion protocol) (Garvey et al., 1987; IARC, 2013)</td></tr><tr><td>Atrazine</td><td>SAR and grouping based upon mammary gland tumor induction by various triazine compounds in rats (US EPA, 2002)</td><td>In vitro liver microsomal CYP 1A2 induction (Lang et al., 1996, 1997)</td><td>ERK activation as the consequence of atrazine binding to GPER (Albanito et al., 2015), aromatase induction (Albanito et al., 2015; Quignot et al., 2012; Sanderson et al., 2000)</td><td>Delayed mammary gland development (initiated *in utero*) (Hovey et al., 2011)</td><td>Mammary gland tumors in Sprague-Dawley rats (US EPA, 2002)</td></tr><tr><td>Captafol</td><td>Existing literature data (Rakitsky et al., 2000; NTP, 2008, 2011; IARC, 1991)</td><td>Assessment of effects on CYP 1A1 and CYP 2B (Rahden-Staron et al., 2001)</td><td>In vitro cell transformation assays (Perocco et al., 1995)</td><td>Liver/nuclear pleomorphism, oval-cell proliferation, and foci of cellular alteration, cortical tubular cyst lesions (renal system) (NTP, 2011)</td><td>Hemangiosarcoma in B6C3F1 and CD-1 mice (NTP, 2014), hepatocarcinoma and renal carcinoma in rodent bioassay (NTP, 2011)</td></tr></tbody></table>

<footnote>*Note that with the building of the IATA it may be possible that Level 4 *in vivo* assay information will no longer need to be generated.</footnote>
<figure><img src="image_30.png" /></figure>

that can potentially be classified as a false negative under cur-
rent regulatory testing paradigms. Furthermore, it is clearly car-
cinogenic only to mouse, inducing liver hepatocarcinomas in
B6C3F1 mice, hemangiosarcomas in male CD-1 mice, lympho-
sarcoma in both sexes, and harderian gland adenoma in males
(NTP, 2011, 2014). In rats, captafol also induces renal adeno-
mas and carcinomas, but the incidence is statistically significant
in males only when the adenomas and carcinomas are combined
and when considering the positive trend at the highest assayed
dose after applying the Cochran Armitage test (or equivalent)
for the trends to the combination. In this example, the carci-
nogenic endpoint effect therefore exists, but the standard RCB
method is not sensitive enough, on its own, to detect it, prob-
ably due to the NGTxC mechanism. Captafol also induces cell
transformation *in vitro*. Most recent reports consider captafol as
both GTx and NGTxC (NTP, 2008, 2011). The NGTxC activity
was revealed in initiation/promotion studies, but the possible
NGTxC mechanisms have not been fully explained.

**7 How could an IATA for NGTxC start
to take shape?**

Both quantitative and qualitative AOP/MoA IATA elements will
be required and can be based upon the essential conceptual steps
of the carcinogenic process, which include initiation (such as the
early KE in Tab. 1), promotion (differential stimulation, inhibi-
tion or toxicity (as for example with cell proliferation, gap junc-
tion intercellular communication), transformation (from benign
to malignancy), neoangiogenesis and progression with patho-
genic angiogenesis and neoangiogenesis, shown in the steps in
Figures 3, 4 and 5 and presented conceptually in Figure 2.

As already briefly indicated in Section 5.6, to further ensure
that the key MoA is identified and not missed, all MoAs would
need to be tested for, when one moves from one block of MoA
tests to the next, if negative in the first block tested. When we
consider the possible mechanisms through which NGTxC affect
the carcinogenesis process, it is important to appreciate that not
all of these mechanisms are always related to adversity. For ex-
ample, receptor binding and transactivation may not lead to con-
sequential adverse effects at all. As these early MIE/KE often do
not result in downstream adverse outcomes, an IATA will need to
examine the specific initiating events for each receptor, and then
look at the downstream KE that is/are related to all receptors
with a pivotal role in the adverse tissue/target organ outcome.

When we can see that several mechanisms are interconnected
and are being affected adversely, then we will start to be in a
position to make IATA based decisions. For example, oxidative
stress, cell death and immune system evasion are three cancer
hallmarks that are strictly interconnected (they share several
molecular targets and pathways). Three examples of chemical
case studies specific to tumor models are given in Table 7.

In this way, the intention would be to overcome current issues
of insufficient applicability, scope and downstream relevance. It
will be important to have a conservative approach to such tiered
test information, and while keeping false positives to a minimum

is important, also low probability of false negatives is critical.

In this context it will be essential to characterize qualitatively
and, as far as possible, quantitatively the reliability and rele-
vance of the established animal testing methods as well as the in
vitro/in silico test methods. We need to take stock of the perfor-
mance of the actual methods in order to define a benchmark that
new approaches should overcome. Furthermore the animal test
data often serve as reference for the validation of new methods.
The weight these animal test data should have within a valida-
tion compared to human data and mechanistic information shall
depend on the reliability and relevance of all these sources of
information for the target of evaluation, i.e., human health. It
will be important to conduct thorough and step by step trans-
parent uncertainty analyses as part of the WoE approach within
the IATA, particularly for potentially sensitive conclusions on
positively and negatively identified substances. In this way it is
possible to reduce uncertainty and remove controversy, so that
a scientifically robust decision that is acceptable to regulatory
authorities can be made.

In any case, Level 1, 2 and 3 assays (see below) will require
validation to the extent that definitive decisions including the
derivation of acceptable exposure levels can be made.

**7.1 Level 0: Existing information and
*in silico* approaches**

Literature and *in silico* MoA review information (using for ex-
ample chemical structure information and prior published in-
formation) would guide the selection of the most relevant test
block in which to first initiate testing the substance. Whilst it
is too early to devise any precise decision rules at this stage, it
is recognized that in a final IATA, decision rules or workflows
would be necessary, together with the considerations described
in the earlier Section 5.4. In summary, when selecting and in-
terrogating such computational tools, a high level of attention
needs to be paid to chemistry and biological endpoint data qual-
ity and data cleaning considerations, appropriate selection and
use of descriptors and statistics. The use of (Q)SAR models,
expert systems, category formation tools, as well as the inter-
pretation of the results, require expert knowledge, because each
of these tools have their own level of reliability and chemical
applicability domain limitations.

**7.2 Level 1: Subcellular level and**
**Level 2: Cellular level**

A number of mechanisms have been linked to NGTxC. For
some of these mechanisms there is an assay that can in principle
be taken to the OECD Test Guideline Programme and be devel-
oped into an internationally accepted test method. So far this has
only taken place for endocrine MIEs, such as estrogen receptor
binding and transactivation, and steroidogenesis. In addition,
the ToxCast program offers a plethora of high-throughput tests
that may be very useful as Level 1/2 tests (Judson et al., 2014),
although the readiness of these assays to be developed into an
internationally accepted test method needs assessment.

As already noted, many of these mechanisms may be initial
steps in the NGTxC processes, but their initiation does not mean
<figure><img src="image_31.png" /></figure>

that there are automatically relevant downstream carcinogenic events, unless this has been clearly demonstrated in the literature. Moreover, not all the mechanisms may be related unequivocally (or to the same extent) to adversity (as described above in Section 5.2).

Furthermore, with exception of “inhibition of gap junction intercellular communication” and “inhibition of senescence through activation of telomerase,” a number of the mechanisms/ endpoints listed are not specific to NGTxC: oxidative stress, increased mitogenesis, interference with tubulin polymerization and so on, are also mechanisms for genotoxic carcinogens, and where negative results are recorded in the mutagenicity/genotoxicity assays, these are acceptable for mutagenesis/genotoxicity regulatory purposes. For NGTxC mechanisms, the IATA will need to both address and be negative for each principal mechanism, should the IATA be required to indicate that a substance is not a NGTxC. However if the IATA is being used solely for prioritization for *in vivo* testing, it will not need to be so rigorous in this regard.

A more holistic way to approaching the creation of relevant testing sequences or batteries would mean reducing the focus on the MIEs in Levels 1 and 2, and concentrating instead on the cellular and tissue events that are pivotal for NGTx cancer outcomes. There are several examples of such test developments in medical research that could be considered for adaptation. Key cellular properties that indicate that tumor cells are successively accumulating to be included in such test developments are as follows:

- Disturbed regulation of growth (balance between cell replication and cell death)

- Genetic instability (disturbed DNA repair, quick establishment of mutations = “mutator phenotype”)

- Control of micro-environment (establishment of tumor-tissue, angiogenesis)

- Cellular senescence (immortality of tumor cells, expression of telomerase)

- Metastases (migration, intra- and extravasation, survival outside of original tissue)

This approach could be complemented by toxicogenomic approaches using *in vitro* test systems to recognize and group chemicals according to specific MoA, as demonstrated by Schaap et al. (2012, 2015).

## 7.3 Potential regulatory use of Level 1 and 2 assays

From today's perspective, once relevant methods are developed for NGTxC, the mechanistically based *in vitro* assays may be used for detecting positives. At Level 1 (subcellular), it has been proposed to use sequential testing on the basis of mechanistic and toxicokinetic understanding for the chemical structure for initial hazard identification (OECD, 2015a) (note this is not referring to formal REACH Classification and Labelling), and sequential testing is clearly preferred to battery testing by industry for pragmatic reasons such as time and cost.

Assays can be grouped together as key stages of the particular NGTx MoA. If a substance is positive for one MoA group, then

it may still need to be tested in others before that substance can move to Level 3 and then 4, i.e., definitive *in vivo* testing. This is because NGTxC may have multiple MoAs, as indicated in Table 1 and references therein. With multiple MoAs, testing only one MoA group is not sufficient, not least because it may not necessarily be the most sensitive one, and so a battery of *in silico* /vitro assays or *in vitro* assays covering the entire spectrum would be preferable. A high-throughput (HTP) setting could potentially expedite this. Moreover, testing a wide range of MoAs will be preferable to making the decision as to whether or not additional testing is required. An additional advantage is that it will yield knowledge on adverse outcome and toxicological pathways in general, not only on NGTx carcinogenesis. It is important to note that quantitative information, such as dose response relationships and points of departure (POD), will be required in order to know whether a particular KE will trigger the next KE, and not single dose data points, which cannot contribute at the qualitative level of a more comprehensive IATA format.

## 7.4 Level 3: Multicellular tissue and organ level

This is the pivotal level at which the cellular changes are sufficient to trigger cytoskeletal, tissue and organ changes, and angiogenesis. This level includes *in vitro* tests such as the CTAs, which may also be at Level 2: The SHE assay can be utilized for the first steps of the multistep carcinogenic process, whilst the Balb 3T3 and C3H10T1/2 CTA assays are designed to address the later steps of a carcinogenic process. At this level, also 3D liver cell models (Hengstler et al., 2015; Prestigiacomo and Suter-Dick, 2015; Ramachandran et al., 2015; van Grunsven, 2015) and isolated organ studies, such as tissue perfusion and histopathology from *in vivo* repeated dose studies would be relevant.

Pathogenic angiogenesis and neoangiogenesis are the later multistep cancer processes following on from endothelial cell activation in response to angiogenic factors. This leads to the re-organization of endothelial cells to form tubules, which interconnect to form a network by way of:

1. Degradation of the capillary wall by extracellular proteinases;

2. Migratory signals;

3. Interconnection of the new tubules to form a network (anastomosis).

Some assays at level 2 will be highly supportive in addressing these three network aspects and HTP assays for primary angiogenic pathway molecular targets are available (Tab. 1).

Currently organ-on-chip technologies are also being explored for applicability in this respect (Marx et al., 2012) but are currently being developed more for drug discovery applications (Bhatia and Ingber, 2014), and the translation from pharmaceutical research and safety assessment to applied chemical hazard assessment has often taken longer and been more problematic than initially envisaged.

## 7.5 Potential regulatory use of Level 2/3 assays

Positive histopathology findings such as hyperplasia or neoplasia, and neoangiogenesis studies do not have a clear mechanistic basis. While they provide useful descriptive data, they are not
<figure><img src="image_32.png" /></figure>

sufficient in the evaluation of the carcinogenicity of a substance. However, taken together with other, more mechanistically based data and in a WoE approach, this information may be useful and increase the relevance in the evaluation of carcinogenicity. For data rich pharmaceuticals, the absence of histopathological data combined with information on mutagenicity and hormonal activity has been shown to correlate well with non-carcinogens (Sistare et al., 2011), and this could also be the case for chemicals.

Under the REACH Regulation, the sub-chronic toxicity study is a standard information requirement above 100 tonnes per annum (tpa) and therefore relevant histopathological findings can be observed, when present, and used in the evaluation of carcinogenicity. In the development of the individual test methods and IATA, the aim is to cover the hazard characterization with Level 1, 2 and *in vitro* Level 3 tests as often as possible. Note that the concept of this testing does not imply that only *in vivo* Level 3/4 tests can give definitive or conclusive test results for regulatory purposes. At present, Level 2 and *in vitro* Level 3 assays, as shown in Table 1, may be able to meet regulatory information requirements from the information available from the MIE together with additional WoE information, e.g., also in the context of category formation and read-across according to REACH Annex XI, whereas *in vivo* Level 3 studies would be considered sufficient for Classification and Labelling purposes. Thus, *in vivo* Level 3 information may not be necessarily needed to complete the decision making process.

## 7.6 Level 4: Organism level

Examples of Level 4 assays from which information relevant for an IATA for NGTxC may be derived include:

- assays with transgenic rodents

- the rodent carcinogenicity bioassay

- chronic toxicity studies (provided that the histopathology findings give sufficient evidence of carcinogenicity of human relevance)

## 7.7 Actual regulatory use of Level 4 assays

Currently, information needs to be obtained from whole organisms if insight is required regarding the adverse effects level, dose response curve and the type of tumors in the tested species (which is essential for the GHS/Classification, Labelling and Packaging (CLP) regulatory requirements for chemicals).

Positive evidence from a definitive *in vivo* study, with no controversy about human relevance, can normally be used for risk assessment and for CLP, and is dependent upon the regulatory context and process. For instance for REACH it is essential that a substance is classified before certain risk management procedures come in to effect. However, Level 4 data will often not be available for the industrial chemicals. Therefore, the IATA should advise the registrants and authorities on making an informed decision as to when Level 4 studies should be conducted. Some non-conclusive evidence ranging from mechanistic/MoA *in vitro* tests (Tab. 1) to repeated dose studies might lead to testing the substance at Level 4. The REACH Substance Evaluation, for example, enables the request for this

type of information, if it is not already in a regulatory decision. On the basis of this new information a member state could propose classification and labelling for the substance and/or could start other processes but, as already indicated, such requests are rare. It is therefore anticipated that use of this type of IATA will not increase the number of *in vivo* studies. In any case, e.g., in the REACH Substance Evaluation, any additional standard and non-standard methods may be required if they appear to be critical for a decision.

Human epidemiological evidence should be utilized where available for existing chemicals/substances, but of course this is unlikely to be the case for new chemicals, except when it may be possible to extrapolate by read-across and/or grouping, and is also supported by Level 0/1, 2 and 3 data.

The challenge will be how to integrate the differing pieces of information and how to ascertain the minimum information requirements. For negatives, to ensure that they truly are negative for agreed key event NGTxC mechanisms, one will need to conclude after screening conducted in all the Level 2 tests in the IATA, and after each test result use the test result information to make an informed decision as to which next test to conduct, such that it will contribute the most pertinent information. Thus the list of Level 2 tests will need to be 1) sufficiently comprehensive in coverage of the hallmarks of cancer, 2) predictive of the test endpoints, and 3) the information will need to be integrated to guarantee true across the board negative results for NGTxC. The conclusion might also be determined in conjunction with a Level 3 test, which includes initiation, promotion, such that the protocol takes into consideration effects at the promotion stage and KERs leading to adversity. When integrating a probabilistic Bayesian approach into the decision tree of the IATA, decisions as to where the confidence is sufficient to make a regulatory decision will require a consensus approach.

## 8 Future long-term goals

Following through with the vision expressed in *Toxicity Testing in the 21st Century* (NAS, 2007), in the future information derived from test methods and assays performed *in silico* and *in vitro* (i.e., Level 0/1/2/3) could be sufficiently robust for decision making. One long term vision may be to define adversity on a cellular level and translate the respective *in vitro* BMD to a corresponding *in vivo* dose by kinetic modelling and classify according to potency. Classification essentially could be based on adverse cellular effects and respective *in vivo* potency estimates; indeed this may lead to proposals for major rearrangements of GHS classification. An important starting point for developing such an approach would be an assessment of the validation basis for current standard animal tests and the uncertainty inherent in defining adverse effects on standard “apical” animal testing endpoints compared with the uncertainties that could be considered acceptable when defining adversity on a cellular level. On such a basis, resources could then be targeted towards the TG development of the selected *in vitro* tests.
<figure><img src="image_33.png" /></figure>

## 9 Conclusions and future perspectives

NGTxC contribute to cancer risk by a variety of mechanisms, which are not yet included in international chemical regulatory approaches. Whilst there have been valuable efforts at the international level to validate *in vitro* assays proposed to start to address this important discrepancy, these have not been wholly successful for a number of reasons, including a lack of mechanistic understanding and difficulties in defining how to meaningfully apply individual *in vitro* tests, such as the Cell Transformation Assays, for NGTxC assessment.

To address this need, an integrated approach to the testing and assessment of NGTxC is beginning to be developed internationally at the OECD, and here we have explored considerations as to what could be the basis for the development of an IATA for NGTxC, with a preliminary organization of the major mechanisms of NGTxC into blocks, identifying related mechanisms, and identifying relevant *in vitro* assays and markers. The follow-up work will present conceptual ways forward, looking in much more detail at how this approach could apply to a new chemical, such that (long-term) *in vivo* toxicity studies are no longer needed. It is acknowledged that concluding without animal studies may not be possible quite yet. However, if all earlier level assays give a red flag, then does there need to be a “societal debate” on finally conducting an animal study? Or is it enough to make the decision based on the red flags already provided? This is a major gap that needs exploring, and it is likely that further examples will also be drawn from the experience gathered from pharmaceutical safety evaluations.

In March 2016, an OECD nominated government and stakeholder expert group was established to address the development of an IATA for NGTxC, for which this paper provides the thought starter to initiate, frame and build the IATA(s). With expertise in the appropriate assay-specific knowledge, this group will fully scope, review and prioritize the assays that could be part of an IATA for NGTxC testing in a consensus fashion, together with designing a framework in which these assays would sit. Where appropriate, systematic review approaches, expert knowledge, WoE, identification of data gaps and uncertainty analyses will be utilized to facilitate consensus, to provide a solid basis for the prioritization of assays for test method development within each KE block in the agreed IATA(s) structure. Broader OECD consultation is then foreseen, with subsequent synthesis and the production of a comprehensive OECD guidance document. Information regarding the effect level and/or dose response curve is fundamental in risk assessment. Therefore, the alternative methods ought to provide this type of information in order to be used in current human hazard and risk chemical safety assessment for NGTxC. In several regulatory frameworks, such as REACH, information on the effect level and/or dose response curve and information on the Classification and Labelling form an essential step in the risk management of chemicals. With a strong international drive to reduce animal testing and costs, it is essential that proper and robust methods for addressing NGTxC MoA are developed and put in

place, and it is the construction of an IATA, under the auspices of the OECD that will be a primary way to address this crucial gap internationally.

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## Conflict of interest

The authors declare that they have no potential or actual conflicts of interest.

## Acknowledgements

The authors received no specific funding for this paper. We are grateful for the stimulating discussions and comments from the OECD Working Group of National Coordinators of the Test Guideline Programme.

We applied the “sequence-determines-credit” (SDC) approach for the sequence of authors, and all authors made major contributions to the text.

## Correspondence to

Miriam N. Jacobs
Department of Toxicology
Centre for Radiation, Chemical and Environmental Hazards
Public Health England
Chilton, OXON, OX11 0RQ, UK
Phone: +44 1235 825175
e-mail: Miriam.Jacobs@phe.gov.uk