Tumor dose-response curve

All of these considerations indicate that the biology behind the shape of the tumor dose-response curve is much more complex than a simple conclusion that mutagenic activity = linear dose-response. Ultimately, biologically based dose-response models and use of biomarker data may make it possible to extend the tumor dose-response curve to low doses based on biological data, rather than presumptions about the shape of the dose-response curve. In the shorter term, it is important to recognize that the biology is complex, and linear extrapolation from tumor data is a health-protective science policy decision. 

Risk Estimation. As mentioned above, chronic risk is expressed as a probability of occurrence per year or per lifetime of some adverse consequence caused by exposure to the pollutant. Statutory mandates have focused on human health effects as the primary expression of chronic risks. The basis of the risk calculation is the dose/response curve that relates the adverse effect to the amount or rate of a chemical taken in to the subject. Because of regulatory emphasis of cancer, most of the work devoted to the deviation of dose/response curves has been concerned with the probability of appearance of a tumor as the adverse effect. 

There is a step-wise dose response curve/relationship between exposure, cell proliferation and tumor development. 

As shown in Table 2-2, 300 mg/kg/day is the cancer effect level (CEL) for renal tubular cell adenomas in male rats and 600 mg/kg/day is the CEL for hepatocellular carcinomas and hepatoblastomas in mice (NTP 1987). A qj (the upper-bound estimate of the low-dose slope of the dose-response curve as determined by the multistage procedure) of 6x10 per mg/kg/day has been calculated from the data on renal tumors in rats (Battelle and Crump 1986). The qi for the mouse liver tumor data is 2.4x10 per mg/kg/day (HEAST 1992). These values are currently under review by the EPA (HEAST 1990) and have not been included in the IRIS (1998) database. 

However, in addition to the dose levels at which the various effects are observed as well as to the steepness of the dose-response curve, the type of the various effects observed is also a very important aspect in the dose-response assessment. If effect A is an alteration in an unspecihc liver enzyme blood level, effect B is an increase in the relative liver weight, and effect C is the incidence of liver tumors, then both effects B and C obviously are evaluated as being more severe effects than effect A i.e., an example of an exception from situation 1 and 3 above. Similarly, effect C is evaluated as being more severe than effect B i.e., an example of an exception from situation 2 above. 

For non-threshold mechanisms of genotoxic carcinogenicity, the dose-response relationship is considered to be linear. The observed dose-response curve in some cases represents a single ratedetermining step however, in many cases it may be more complex and represent a superposition of a number of dose-response curves for the various steps involved in the tumor formation (EC 2003). Because of the small number of doses tested experimentally, i.e., usually only two or three, almost all data sets fit equally well various mathematical functions, and it is generally not possible to determine valid dose-response curves on the basis of mathematical modeling. This issue is addressed in further detail in Chapter 6. 

Eor most of the toxic effects that might be exerted by a chemical substance, including at least certain types of genotoxic carcinogenicity, the dose-response curve is S-shaped as illustrated in Eigure 4.1 where the carcinogenic response is the mmor incidence. This means that no or only a few tumors occur at the lower dose levels, but the mmor incidence increases as the dose level increases, in many cases until a plateau is reached. 

The second step of the dose-response assessment is an extrapolation to lower dose levels, i.e., below the observable range. The purpose of low-dose extrapolation is to provide as much information as possible about risk in the range of doses below the observed data. The most versatile forms of low-dose extrapolation are dose-response models that characterize risk as a probability over a range of environmental exposure levels. Otherwise, default approaches for extrapolation below the observed data range should take into account considerations about the agent s mode of action at each tumor site. Mode-of-action information can suggest the likely shape of the dose-response curve at these lower doses. Both linear and nonlinear approaches are available. 

The linear approach should be used in two distinct circumstances (1) When there are mode-of-action data to indicate that the dose-response curve is expected to have a linear component below the POD. Agents that are generally considered to be linear in this region include agents that are DNA-reactive and have direct mutagenic activity. (2) As a default when the weight of evidence evaluation of all available data is insufficient to establish the mode of action for a tumor site, because linear extrapolation generally is considered to be a health-protective approach. 

For linear extrapolation, a line is drawn from the POD (from observed data), generally as a default, a LED (the 95% lower conhdence limit on a dose associated with an extra tumor risk) chosen to be representative of the lower end of the observed range, to the origin (zero dose/zero response), corrected for background incidences. This implies a proportional (linear) relationship between risk and dose at low doses (note that the dose-response curve generally is not linear at higher doses). The slope of this line, known as the slope factor, is an upper-bound estimate of risk per increment of dose that can be used to estimate risk probabihties for different exposure levels. The slope factor is equal to O.OI/LEDqi if the LEDqi is used as the POD. 

The T25 approach was discussed at a workshop organized by the European Centre for the Ecotoxicologicy and Toxicology of Chemicals (ECETOC) (Roberts et al. 2001, ECETOC 2002). It was concluded that the use of the T25 method in risk assessment is problematic due to uncertainties arising from the false assumption of both precision and linearity in the dose-response curves for tumor induction. 

Fig 3. Schematic dose-response curves for incidence of tumors in relation to dose and dose rate of high-LET and low-LET radiation, (from Upton, 1984 also see Thomson etal., 1982 Sinclair, 1983). 

Scheinberg and Strand (26) have addressed the therapeutic effects of a tumor-specific antibody against the Rauscher erythro-leukemia. A dose response corrrelation between this antibody and tumor inhibition was measured. The dose response curve... 

For these reasons, a threshold will exist for genotoxic carcinogens in practice. However, one problem of demonstrating this experimentally is the absence of sufficiently sensitive biomarkers, which can detect effects at very low doses. Using the appearance of tumors as the endpoint is too insensitive, and therefore, the true nature of the dose-response curve at low doses is unknown. Thus, the bottom of the dose-response curve is an area of uncertainty, effectively a "black box" (Fig. 2.10). New and more sensitive biomarkers will help in this. 

Experimental agents were evaluated in vitro against 60 human tumor cells derived from nine cancer types (leukemia, nonsmall cell lung, colon, melanoma, ovarian, prostate, and breast cancer). For each experimental agent, dose-response curves for... 

Considering all the above data, the U.S. EPA (1991) selected the unit risk of 8.5 x 10 per pg/m, derived from the Weibull time-to-tumor model, as the recommended upper bound estimate of the carcinogenic potency of sulfur mustard for a lifetime exposure to HD vapors. However, U.S. EPA (1991) stated that "depending on the unknown true shape of the dose-response curve at low doses, actual risks may be anywhere from this upper bound down to zero". The Weibull model was considered to be the most suitable because the exposures used were long-term, the effect of killing the test animals before a full lifetime was adjusted for, and the sample size was the largest obtainable from the McNamara et al. (1975) data. 

Cancer risk assessment involves a quantitative estimate of the carcinogenic activity of a carcinogen. For genotoxic carcinogens, this estimate is derived from the cancer potency of the carcinogen. Cancer potency is defined as the slope of the dose-response curve for induction of tumors, and is a function of the dose and the magnitude of response, measured as a slope. The endpoint is the cancer incidence or frequency of occurrence of cancer (tumor induction) in... 

Fig. 1. A typical dose response curve obtained by clonogenic assay. The human colon tumor cell line HT29 in exponential growth was exposed to mitomycin C for 3 h and then plated out at a density of 500 cells/6 cm Petri dish. The mean colony count in the control dishes was 281, which is a cloning efficiency of 56%. Three flasks of cells were used at each dose level and each point is the mean standard error of the mean of the three estimates. Estimation of the IC50 value (the drug concentration required to kill 50% of the cells) is shown by the straight lines.

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