Genetic susceptibility of CYP1A1 gene and risk of pesticide exposure in prostate cancer

2.1 Chemicals

Standards of pesticide namely, alpha-hexachlorocy- clohexane ( α -HCH), beta-( β -HCH), malathion, chlorpyrifos, α -endosulfan; dichlorodiphenyldichloroethylene (pp-DDE), dichloro diphenyltrichloroethane (pp-DDT), β -ensosulfan, cypermethrin, and fenvalerate were procured from Sigma Aldrich (St. Louis, Mo., USA), having purity higher than 98%. Lichrosolv HPLC grade hexane was obtained from Merck Pvt. Ltd., Mumbai, India.

2.2 Ethical statement and sample size

Necessary ethical clearance was obtained by the Institutional Research Ethics Committee (Reference code: 61th ECMII-BP25) of King George’s Medical University (KGMU), Lucknow, India. The sample size was calculated on the basis of mean difference of stress level in exposed benign prostatic hyperplasia (BPH) and PCa group. In a study Siddique et al. [9] reported that the mean ( ± SD) oxidative stress in BPH subject was 6.7 ± 2.9 while 8.7 ± 4.0 in PCa patients. For getting final sample size by assuming-Difference = 5.0; standard deviation ( ∂ 2 ) = 5.0; an equal number of case and control ( r = 1:1); Z ⁢ α / 2 = 1.96 (Significant level at 5%) and Z ⁢ β = 0.84 (power 80%). Then, the required sample size was calculated by using the following formula.

N = r + 1 1 ⁢ σ 2 ⁢ Z ⁢ β + Z ⁢ α / 2 Diffrence

Here, N = Sample size of each group; r = ratio of control to case; Differences = effect size; Z ⁢ α / 2 = Significant level; Z ⁢ β = power (80%). The calculated number of sample for this study was 63. But for statistical point of view we were enrolled 102 cases and 177 control subjects.

2.3 Study subjects

In total, 102 PCa patients and 177 age matched controls were enrolled in this study. Prostate specific antigen (PSA) is a tissue specific marker that is now widely used for assessment as well as follow-up of PCa patients. In this study, diagnosis of PCa was based on the level of serum PSA (Chemiluminescent Microparticle Immunoassay) followed by histopathological investigation (based on Gleason score). Only histopathologically confirmed cases were enrolled as PCa patients. Age match control subjects were subdivided into two groups: symptomatic BPH (S-BPH, n = 107) and asymptomatic BPH (A-BPH, n = 70). S-BPH was recruited on the basis of chest x-ray, urine and blood test for PSA, colon enema and abdominal ultrasound. Age matched asymptomatic BPH controls were randomly selected among healthy volunteers visiting the outpatient department (OPD) of Urology, King George’s Medical University for their annual physical examination. Subjects with history of acute/chronic prostatitis; liver failure and renal failure, diabetes mellitus were excluded from this study. A written informed consent was obtained from each subject prior to their inclusion in this study.

All the subjects were asked about, age, family history of cancer, dietary habit (vegetarian/non vegetarian), pesticide exposure history (farmers who actively participated in pesticide mixing and application to control crop pest) and lifestyle factors like alcohol consumption (50 drink/year) and smoking. Smoking status was divided into non smoker and established cigarette smoker according to the detail questions which are as follows: “Have you smoked at least 100 cigarettes in your life?” and “Do you now smoke cigarettes?” those respondents considered as non smoker who smoked fewer than 100 cigarettes in their entire life and they have not smoked since 5 years. Current smoker consist of those respondents who report smoking more than 100 cigarettes in their lifetime, and currently smoke every day or some day. After written consent, 5 ml venous blood was collected from each participant and divided into three parts for pesticide quantification (1.5 ml), oxidative stress (1.5 ml) and genotyping (2 ml) and stored at - 80 ∘ C till analysis.

Extraction of organochlorine (OCPs) and organo- phosphate (OPPs) residue from blood was done according to method of Bush et al. [10]. The trace level pesticide (mg/ml or ppm) in the blood sample was analyzed by using Agilent technologies 7890A Gas Chromatograph, equipped with a micro Electron Capture Detector (ECD), capillary column DB-5MS (Perkin Elmer, CA, USA) of 30 m length, 0.25 mm i.d., 0.25 μ m thickness and in an auto injector Agilent technologies 7683B series split-less mode injector with an insert liner of 0.75 mm i.d. The gas chromatograph temperature was programmed as follows: injector temperature: 250 ∘ C, oven temperature: initially ramped from 165 ∘ C to 180 ∘ C at a rate of 3 ∘ C, 200 ∘ C at a rate of 1.5 ∘ C, 230 ∘ C at a rate of 2 ∘ C, 260 ∘ C at a rate of 3.5 ∘ C and finally to 280 ∘ C at a rate of 6 ∘ C per min withhold time of 1.5, 0.5, 0.5, 0.5, 2 and 2.5 min, respectively and electron capture detector temperature was at 300 ∘ C.

2.5 Biochemical estimation

Reactive oxygen species (ROS) (n mole of malondialdehyde (MDA)/ml of plasma) were assessed by Ohkawa et al. [11] using thiobarbituric acid. The antioxidant system including superoxide dismutase (SOD), Catalase (CAT) and Glutathione (GSH) were also measured as per standard protocol [12, 13, 14, 15].

2.6 DNA isolation and genotyping

Genomic DNA was isolated by conventional phenol chloroform extraction method followed by ethanol precipitation and re-suspended in 1 mole Tris-EDTA buffer (pH: 8.0) and stored at - 20 ∘ C for further use. Genotyping of CYP1A1 at site rs4646903T $>$ C and rs1048943A $>$ G were carried out by single nucleotide polymorphism and allele specific polymerase chain reaction with specific primers and restriction enzyme (Table 1). Genotyping was done by using Applied Biosystem TaqMan SNP genotyping assay with stepOnePlus Real-time PCR system (Applied Biosystem, Foster City, USA).

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For continuous data, normality was tested using Kolmogorov Smirov test. For non normal continuous data, χ 2 test, mann whitney U test/kruskal wallis H test were used to compare the groups as appropriate [16]. Categorical data were presented in frequency and percentage. For PSA, Univariate binary logistic regression analysis was used to calculate unadjusted odds ratio (OR) and 95% confidence interval (CI) in different variables between case controls. One way analysis of variance (ANOVA) followed by Tukey post hoc test were applied on multiple comparisons between the stress metabolism and Gleason score (GS). The genotypic data are in Hardy-Weinberg Equilibrium tested by χ 2 test. Genotypic data was compared between case and controls using 2 × 3 and 2 × 2 contingency table calculator available online at (http://faculty.vassar.edu/lowry/VassarStats.html). In the case of statistical significance, further genotypic analysis to calculate the OR and CI were undertaken using dominant and recessive models of comparison. Statistical analysis was carried out using the statistical package for the social science, version 22 (SPSS-22, IBM, Chicago, USA). 0.05 was considered as statistically significant.

3.1 General baseline characters

Baseline profiles of selected subjects are shown in Table 2. Tobacco consumption was found to be predominant risk factor for PCa than both BPH group (PCa versus S-BPH: OR: 3.68; 95% CI: 1.7–7.7; p : 0.001 and PCa versus A-BPH: OR: 16.9; 95% CI: 7.59–37.62; p : 0.001). The proportion of occupational exposure of pesticide was significantly higher in the group with PCa (PCa: 80.4% versus S-BPH: 56.1% and PCa: 80.4% versus A-BPH: 45.7%; All 0.05). Stratified analysis showed that high level of serum PSA was strongly associated with PCa risk (all 0.001). Some PCa Patients recorded normal or low PSA level; this may be due to the orchiectomy or radical prostatectomy that they underwent. We enrolled healthy age matched A-BPH subjects and PSA testing was voluntary. Therefore statistical comparison of PSA between PCa and A-BPH group was restricted.

3.2 Quantification of pesticide by gas chromatography

Compared to BPH controls, PCa had high levels of pesticides (Fig. 1 and Table 3). For example, pesticides namely malathion, chlorpyrifos, β -HCH, pp-DDE and fenvalerate were 2 to 4 fold higher in PCa than BPH groups (all 0.05). However, level of β -HCH and malathion pesticides were correlated with high Gleason scores ( 0.05) which are an indicator of tumor aggressiveness (Table 4).

3.3 Oxidative stress and their scavenging system

Mean level of ROS (n mole of MDA/ml) was 3.91 ± 1.03 and 3.7 ± 0.82 in S-BPH and A-BPH whereas, in PCa group it was almost two fold higher (6.04 ± 1.2). Further, SOD, CAT and GSH level decreased by 2 to 2.9 fold in PCa group than both BPH (all p : 0.01) (Fig. 2). Among PCa group, rise in ROS and reduction in antioxidant level were associated with increasing Gleason score (all p : 0.001) (Fig. 3). The association between ROS and antioxidants with serum PSA was found to be null (data not shown).

Genotypic frequencies in both control groups were in Hardy-Weinberg equilibrium (S-BPH: p = 0.96 and A-BPH: p = 0.903). For rs4646903T $>$ C, the homozygous genotype (TT) was found to be high among controls (S-BPH: 43.9 and A-BPH: 42.8%). However, heterozygous genotype (TC) was significant more prevalent among PCa (54.9%) than controls (S-BPH: 44.8% and A-BPH: 45.7%) (Table 5). The frequency of minor allele CC was slightly higher in PCa patients (46.1%) than BPH group (S-BPH: 33.6%, A-BPH: 36.9%). Further, dominant model, reveals that risk was almost 2 fold high in PCa (PCa versus S-BPH: OR = 2.17; CI: 1.6–3.8; p = 0.008 and PCa versus A-BPH: OR = 2.08; CI: 1.1–3.97; p = 0.024).

In rs1048943A $>$ G, homozygous genotype (AA) was found to be more prevalent among controls (S-BPH: 50.4% and A-BPH: 51.4%) than PCa (34.3%). The frequency of wild-type allele was higher in group with both BPH controls, whereas minor allele genotype was higher in PCa patients. Dominant model indicated that PCa was associated with risk genotype (AG + GG) of rs1048943A $>$ G (PCa versus S-BPH: OR = 1.95; CI: 1.1–3.4 and PCa versus A-BPH: OR = 2.03; CI: 1.8–3.77, all 0.05). We also analyzed genotypic data of symptomatic and asymptomatic BPH subject (Supplementary Table 7). Binary logistic analysis reveals that, symptomatic and asymptomatic BPH group was same at genetic level. Therefore, this combination of PCa and asymptomatic BPH was excluded from further genotypic analysis. Only one type of control is enough for comparing the genetic data with PCa group.

3.5 Association of CYP1A1 genotype with baseline risk variable

For estimation of possible correlation between selected two single nucleotide gene polymorphism with PCa risk, stratified analysis based on two major clinical risk factors including smoker, non-smoker and pesticide exposure and non exposure were performed. Dominant model showed that the combined risk genotype (TC + CC and AG + GG) of CYP1A1 gene had a significant association to those cancer patients who were smoker and exposed to pesticides (Table 6).