This Key Event Relationship is licensed under the Creative Commons BY-SA license. This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. If you remix, adapt, or build upon the material, you must license the modified material under identical terms.
Relationship: 551
Title
Formation, Pro-mutagenic DNA Adducts leads to Clonal Expansion/Cell Proliferation, to form Altered Hepatic Foci (AHF)
Upstream event
Downstream event
AOPs Referencing Relationship
| AOP Name | Adjacency | Weight of Evidence | Quantitative Understanding | Point of Contact | Author Status | OECD Status |
|---|---|---|---|---|---|---|
| AFB1: Mutagenic Mode-of-Action leading to Hepatocellular Carcinoma (HCC) | non-adjacent | High | High | Agnes Aggy (send email) | Open for citation & comment | EAGMST Under Review |
Taxonomic Applicability
Sex Applicability
Life Stage Applicability
Formation of the pro-mutagenic DNA adduct, N7-AFB1-G (or its conversion product, N7-AFB1-FAPy) is the first step in the initiation of a process that may finish in development of altered
| ID | Experimental Design | Species | Upstream Observation | Downstream Observation | Citation (first author, year) | Notes |
|---|
| Title | First Author | Biological Plausibility |
Dose Concordance |
Temporal Concordance |
Incidence Concordance |
|---|
Biological Plausibility
Dose Concordance Evidence
Temporal Concordance Evidence
Incidence Concordance Evidence
Uncertainties and Inconsistencies
The direct KER relationships between adducts and mutations (MIE→KE#2) and from mutations to AHF (KE#2→KE#3) determine this indirect relationship. Unfortunately, there is a paucity of data to support quantification of a relationship between adducts and AHF; neither to address an AFB1 dose-response for both KEs.
It is clear that the dose-response relationship between adducts and AHF is disproportionate, and thus likely not linear, given that a ~30% reduction in adducts resulted in a 100% reduction in AHF (Johnson et al., 2014). However, a quantitative prediction from DNA adducts to AHF cannot be determined due to lack of data.
There is a study which includes a comparison of AFB1 adduct formation in animals co-administered chemopreventive agent (CDDO-Im) and AHF data (Johnson et al., 2014); these data were developed in rats following 28 d of exposure to AFB1 (young adult rats). Control data for AHF in rats from standard cancer bioassays—thus 18- to 24-month old rats—was analyzed and back-extrapolated in age to determine whether the background level of AHF in the young adult CDD)-Im treated rats was reasonable. Below is provided an analysis of background AHF formation for the placental form of glutathione-S-transferase (GSTP+) foci for use in comparisons of chemoprevention studies with background.
To compare the occurrence of GSTP+ AHF in rats treated with AFB1 and AFB1 + CDDO-Im with controls, a modelled fit of the growth of volume fraction of AHF was developed from data in Popp et al. [9]. Most of the data on AHF in control rats were developed by histological identification of foci rather than enzymatic identification (Harada et al., 1990; Bannash et al., 1985).
One drawback to all these papers on AHF is that parameters for AHF were determined late in the lifetimes of the rats; by contrast, Johnson et al. (2014) examined AHF for up to 28 days of AFB1 administration, a much shorter treatment time and in young adult rats. In addition, many papers used strains and sexes other than F344 males. The use of the same strain and sex in Popp et al. (1985) was considered important for developing the comparison.
To extrapolate the data of Popp et al. (1985) to earlier times in the lives of the rats, the equation derived by Dragan et al. (1995) based on the Moogavkar-Venson-Knudsen (MVK) model was fit to the data of Popp et al. (1985). This equation is as follows:
where E(t) = expected numbers of transformed cells μ1 = initiation frequency α2 = rate of division of initiated cells β2 = rate of differentiation, damage or death of initiated cells Xs = number of susceptible untransformed cells in the liver
The figure below shows the fit to the data of Popp et al. (1985) for male F344 rats, the same strain and sex used by Johnson et al. (2014).
Figure 1. Plot of data on GSTP+ AHF in untreated F344 male rats and the fit to Eq. 1. The number of susceptible cells was assumed to be 3.6E+08 (Popp et al., 1985). The initiation rate (u1) was 1.35e-04 per day and the birth rate minus the death rate (a2 – b2) was 3.89E-03 per day. The data from Popp et al. (1985) are shown as the mean ± 95% CIs.
Data from Johnson et al. (2014) at three time points following the onset of treatment (either AFB1 or AFB1 + CDDO-Im) are shown in comparison to the early extrapolation of occurrence of GSTP+ AHF in control rats.
Figure 2. Plot of the occurrence of GSTP+ AHF in male F344 rats from Johnson et al. (2014) (labeled points with error bars, AFB1 and AFB1 + CDDO-Im) and the early time extrapolated fit (solid line) of the data from Popp et al. (1985). The AFB1 data were so much greater than the other data that a split y-axis was needed.
As can be seen from Fig. 2, the % volume of fraction GSTP+ foci in rats treated with CDDO-Im is zero at both 8 and 14 days, and indistinguishable from the fit to the extrapolated control data at 21 and 28 days. The data of AFB1 administration without CDDO-Im are indistinguishable from the fit to the control data at 8 days but considerably greater than the fit to the control data at later times.
The extrapolation of the data in Popp et al. (1985) from long exposure times to short exposure times represented an uncertainty. Hence, data from Harada et al., (1989) [13] were also examined. These data did not include GSTP+ foci but rather histologically identified foci (e.g., basophilic, eosinophilic, mixed). Data were obtained at 6, 9, 12, 15, 18, and 24 months. These data were also fit to the MVK equation from Dragan et al., (1995) (not shown). When extrapolated to times less than 28 days, these data from Harada et al. (1989) were very similar to those from Popp et al. (1985).
Response-response Relationship
Time-scale
Known Feedforward/Feedback loops influencing this KER
The universality of both DNA adducts and AHF in the pathogenesis of liver cancer suggests that the wide taxonomic applicability noted elsewhere in this AOP is likely true for this KER.

