6.4.1 Testing strategy of NCC toxicity assessment
NCC toxicity assessment in a tiered strategy
As outlined above, the tiered testing strategy for the cMINC assay has proven usefull. One could even go one step further to reduce use of the expensive NCCs (Fig. 6.8): A viability assay could be run in a small assay format (384 or 1536-well format) and with few replicates (2 technical replicates, 1-3 biological replicates). In a next step, compounds would be tested in the cMINC assay at the EC90V.
Based on the amount of migration-inhibition at the EC90V, compounds would be classified as negative or weak/strong positives. Positive compounds would then be tested in more detail, as suggested and applied in manuscript 2. Additionally, one could envisage to develop an NCC proliferation assay, as proliferation
6.4 Testing strategy considerations
is another important NCC function and known to be a target of teratogens (see part 1.3.3). Such a proliferation assay could for example consist of an EdU incorporation assay, as used in manuscript 1 and 2. The assay could be performed at high throughput, in a small well format and few replicates. The combined data from viability, proliferation and migration assays could then be combined to a single ’NCC toxicity estimate’ and integrated with other data (other D(N)T assays, risk assessment, ...).
Figure 6.8: Suggested testing strategy to assess NCC toxicity. This tiered approach consists of (1) a viability assay, (2) the cMINC assay, (3) follow-up assays and could be complemented with (4) a proliferation assay.
Role of follow-up migration assays
Figure 6.9: Different migration assays measure differ-ent biological processes. Three different situations are shown: normal or untreated condition as well as two different, hypothetical toxicants. The colored circles rep-resent NCCs, the length of the arrow indicates the speed of each cell. Expected results of the three assays are stated below.
Results of manuscript 2 showed, that follow-up assays can give valuable, complementary informa-tion. It is therefore strongly suggested to include them in a testing strategy. On the one hand the follow-up assays serve as a confirmation step of compounds. On the other hand, they also provide information about possible mechanisms. For ex-ample, a compound that reduces cell speed of all cells by 50% will lead to a reduction of 50% in the cell tracking assay, but would not affect tran-swell migration (Fig. 6.9). On the other hand, a compound that immobilises 50% of the cells would be detected in the transwell assay but would have little effect on the measured cell speed. Results of manuscript 2 have shown, that many toxicants rather act via the second mechanism. Only few toxicants reduced cell speed, but these toxicants then had profound effects on the amount of mi-grated cells.
In the future, one could also consider to include the follow-up assays in the prediction model. For example,
’weak migration-inhibitors’ could be reclassified as ’strong’ if they substantially decrease cell speed. Or
’weak’ compounds that can not be confirmed in follow-up assays could be reclassified as ’no alert’.
Figure 6.10: Position of NCC function assays in the Integrated Testing Strat-egy. The NCC assays would be on a medium-throughput level as part of a D(N)T test battery.
Based on the limitations outlined in 6.1.4, the cMINC assay can only reach a medium throughput. However, it could be part of a test battery for D(N)T testing (see part 1.2.4, Fig. 1.3).
Most of the suggest D(N)T assays have at present a limited throughput (OECD, 2016). The assay with the highest throughput is currently the neurite outgrowth assay. The cMINC assay has a lower throughput, but still higher than most other suggested D(N)T assays.
The D(N)T test battery could be placed downstream of high-throughput screening assays (Fig. 6.10), i.e. the existing ToxCast assays and assays testing for interference with nuclear receptors (Judson et al., 2015; Lynch et al., 2017). Compounds with suspected D(N)T potential would be prioritized to run through the D(N)T test battery. A D(N)T potential would be suspected for example if the compounds interferes with thyroid hormone receptors or - particularly with respect to NCC migration - RA receptors.
Data from the test battery should then be combined to estimate the D(N)T potential. Based on these results, compounds can be prioritized for down-stream assays. Such assays can includein vivo testing in non-mammalian animals or more complexin vitro mechanistic studies.
Relevance of NCC toxicity information
As the cMINC assay needs costly cell production and is limited in downscaling one might ask whether it is worth at all to perform the cMINC assay. The assay should only be used in a test battery, if it gives additional information, e.g. information that would not be obtained from other (higher throughput, cheaper) test systems. At present, the amount of data to answer this question is scarce. First results come from the comparison of the NTP80-compounds among different test systems. This compound list has been tested besides the cMINC assay in three neurite outgrowth assays and a cardiotoxicity assay (Ryan et al., 2016; Sirenko et al., 2017, Delp and Klima, unpublished data). Comparison of the ’specific’
hits of each test system reveals, that the cMINC assay shares more hits with the neurite outgrowth assays than with the cardiotoxicity assay (Fig. 6.11). Moreover, most neurite outgrowth hits were also cMINC hits, but not vice versa. This indicates that the cMINC assay has the potential to detect compounds that would not be detected in the high-throughput neurite outgrowth assay. In particular it is interesting to note, that many drug-like cMINC hits are shared with the neurite outgrowth assay, but that two pesticides and several flame retardants were unique to the cMINC assay. The drug-like hits had in the cMINC assay rather a low specificity and efficacy, which could indicate that some effects could be due to a more broad toxicity mechanism, may be also related to the onset of cytotoxicity. On the other hand, many of the unique cMINC hits had a high specificity, which indicates that the compound might target a
6.4 Testing strategy considerations
cellular process important for NCC.
To summarize, these preliminary results indicate that the cMINC assay might indeed give additional information and detects compounds not recognized by other assays. However, at present only data from five assays with 80 compounds is available. Future studies using more compounds and comparing more different test systems should be used to shed light on this question.
Figure 6.11: Overlap of the (specific) hit compounds of the cMINC with other cell function assays. (A) All compounds of the NTP80-list that were specific in at least one assay are listed. NCC migration results are compared with data for cardiotoxicity (Sirenko et al., 2017) and the combined data of three neurite outgrowth assays using GABAergic/glutamatergic, dopaminergic and peripheral neurons (Ryan et al., 2016, Delp and Klima, unpublished data). Compounds positive in the cMINC assay are highlighted in bold. Color code: green: flame retardants; blue: pesticides; pink: drug-like compounds; brown: industrial; yellow: PAH;
gray: negative controls. (B) Overview of the overlap of hit compounds of the cMINC assay with both other assay types. The numbers indicate the number of shared and unique ’specific’ hit compounds of the assays.
A basic assumption for the relevance of the cMINC data is, that there is a "critical mass" of NCCs that need to arrive at the target tissue. If cells migrate slower and therefore fewer cells arrive at the target, this is assumed to affect NCC function. But as the cells are also at the same time proliferating, inhibition of proliferation can also reduce the critical NCC mass.
At present, we do not know whether reducing cell speed and reducing the number of migrating cells has the same effect. The reduction of cell number is similar to Treacher-Collins syndrome, whereas reduced cell speed is similar to Hirschsprung’s disease. In both cases, disturbed NCC function results in tremendous developmental defects.
What is a biological meaningful effect level?
At present, it remains unanswered to which extend migration-inhibition has to occur in the in vitro assay to result inin vivo disturbances. A 10% reduction in migration could already have drastic consequences, or a >50% loss of migration could remain without consequences, if there are compensatory mechanisms.
Differences to the in vivo situation
Anin vitro assay is inevitably a simplified model of thein vivo situation. For example, NCCs migrate in a three dimensional environmentin vivo, whereas in the cMINC assay cells grow in a two dimensional culture. In vivo, NCCs migrate in chains, streams or as single cells, and the migration type depends on the localization, timing and species (see part 1.3.2). In the cMINC assay, most cells migrate as single cells, sometimes they also form streams. From this can be concluded, that the assay is limited and would not be suitable to detect toxicants that affect the group or three dimensional migration behavior.
Lastly,in vivo there are gradients of signaling molecules in the fetus and NCC react to such gradients.
As such gradients are not present in cell culture, this indicates as illustrated in Fig. 9 in manuscript 2 -that the cMINC assay is not suited to measure polarity and sensing events.
To summarize, a strong migration-inhibition in vitro is likely to translate to an observable pheno-typein vivo, if the tested concentrations are achievedin vivo. However,in vitroassays are a simplification of the real world and therefore we cannot expect anin vitro assay to be fully predictive of thein vivo situation.