Cytogenetic assessment of occupational exposure to antineoplastic agents

This study has evaluated the utility of measuring effects of low level occupational exposure of nursing personnel to antineoplastic agents. The effect measured in this study is chromosomal damage in peripheral lymphocytes (chromosomal breakage and micronuclei frequency).^ Using nursing personnel in three exposure classifications (low, moderate and high) and breast cancer patients before and after treatment with antineoplastic agents, a weak but statistically significant association was found between exposure and chromosomal damage. Of special interest was the finding that consistent glove usage was negatively associated with increased chromosomal damage.^ The study also demonstrated a statistically significant association between the two measures of chromosomal damage: chromosomal breakage and micronuclei frequency. This suggests that the micronucleus method is a useful test for studying cytogenetic effects in lymphocytes. ^

BENZENE MYELOCLASTOGENICITY AND METABOLISM IN CD-1 MICE: A CORRELATION

Benzene was studied in its target organ of effect, the bone marrow, with the micronucleus test and metaphase chromosomal analysis. Groups of 5 or 10, male and female CD-1 mice were treated with one or two p.o. or i.p. doses of benzene (440 mg/kg) or toluene (430, 860 or 1720 mg/kg) or both, and sacrificed 30 or 54h after the first dose. Benzene-treated animals were pretreated with phenobarbital (PB), 3-methylcholanthrene (3MC), (beta)-naphthoflavone ((beta)NF), SKF-525A, or Aroclor 1254. Toluene showed no clastogenic activity and reduced the clastogenic effect of co-administered benzene. None of the pretreatments protected against benzene clastogenicity. 3MC and (beta)NF greatly promoted benzene myeloclastogenicity. Dose response curves for benzene myeloclastogenicity were much steeper with 3MC induction than without. Micronuclei (MN) were 4-6 times higher by p.o. than i.p. benzene administration. This was not due to bacterial flora since no difference was found between germ-free and conventional males gavaged with benzene. A sensitive high-pressure liquid chromatographic method was developed and used to explore the relation between metabolic profiles of benzene in urine and MN after various pretreatments. Phenol (PH), trans-trans-muconic acid (MA) and hydroquinone (HQ) in the 48h male mouse urine accounted, respectively, for 12.8-22.8, 1.8-4.7 and 1.5-3.7% of the single oral dose of benzene (880, 440 and 220 mg/kg). Catechol (CT) was seen in trace amounts. MA was identified by ultraviolet and infrared spectroscopy and elemental analysis. Urinary metabolites--especially MA, HQ, and phenol glucuronide--correlated well with MN and were dependent on both the dose and the metabolism of benzene. Benzene metabolism was most inducible by cytochrome P-448 enzyme inducers, by p.o. > i.p., in males > females, and inhibited by toluene. Ph, CT or HQ administered p.o., 250, 150 and 250 mg/kg, respectively, or at 150 mg/kg x 2 after 3MC pretreatment, failed to reproduce the potent myeloclastogenicity of benzene. In fact, only HQ was mildly clastogenic. ^

Logistic regression with Markov chains as covariates

The tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is an obvious carcinogen for lung cancer. Since CBMN (Cytokinesis-blocked micronucleus) has been found to be extremely sensitive to NNK-induced genetic damage, it is a potential important factor to predict the lung cancer risk. However, the association between lung cancer and NNK-induced genetic damage measured by CBMN assay has not been rigorously examined. ^ This research develops a methodology to model the chromosomal changes under NNK-induced genetic damage in a logistic regression framework in order to predict the occurrence of lung cancer. Since these chromosomal changes were usually not observed very long due to laboratory cost and time, a resampling technique was applied to generate the Markov chain of the normal and the damaged cell for each individual. A joint likelihood between the resampled Markov chains and the logistic regression model including transition probabilities of this chain as covariates was established. The Maximum likelihood estimation was applied to carry on the statistical test for comparison. The ability of this approach to increase discriminating power to predict lung cancer was compared to a baseline "non-genetic" model. ^ Our method offered an option to understand the association between the dynamic cell information and lung cancer. Our study indicated the extent of DNA damage/non-damage using the CBMN assay provides critical information that impacts public health studies of lung cancer risk. This novel statistical method could simultaneously estimate the process of DNA damage/non-damage and its relationship with lung cancer for each individual.^