Detection of nicotine dependent gene br
Detection of nicotine-dependent gene
The distribution of gene loci of CHRNA5 (rs16969968 and rs588765), CHRNA3 (rs578776), and CHRNA4 (rs1044396, rs2229959 and rs2236196) was detected by the following procedures: (1) peripheral blood was collected when pathologic reports of lung cancer; (2) sterile acquisition of five mL of peripheral blood was collected from three groups of patients with EDTA anticoagulant; mononuclear PX 478 were separated within two hours; the plasma was cryopreserved in -80 ℃ ultra-low temperature freezer until subsequent use; and (3) genomic DNA was extracted using the DNA Blood Mini Kit (QIAGEN, Germany) following the recommended protocol. Briefly, 20 µL of QIAGEN protease, 200 µL of mononuclear cells and 200 µL of AL were added to a 1.5 mL microcentrifuge tube and mixed by pulse-vortexing for 15 seconds. After incubating at 56 ℃ for 10 minutes, 200 µL of ethanol (concentration:
96%-100%) was added to the sample and mixed again by pulse-vertexing for 15 seconds. All liquids were added to the spin column and centrifuged at 8000 rpm for 1 minute. Subsequently, AW1 and AW2 were used to wash the column at 8000 rpm for 1 minute. Finally, DNA was collected using AE buffer centrifuged at 8000 rpm for 1 minute. (4) DNA probes were purchased (Taqman, Thermo Fisher), and the amplification system was the standard SNP genotyping system. The polymerase chain reaction (PCR) results were analysed using TaqMan® Genotyper Software. Statistical analysis
Continuous variables were described as the mean ± standard deviation (SD) for normally distributed variables or the median for variables with a skewed distribution. Categorical variables were described as percentages. Comparisons among groups were conducted with unpaired or paired two-tailed t-tests or ANOVA for means if the data were normally distributed or with Wilcoxon’s rank-sum tests if the data were not normally distributed. The test of categorical variables was the row by column chi-square test. All statistical methods were performed using SPSS 20.0 version (IBM Inc., Chicago Illinois, USA, 2011) and GraphPad Prism 5.04 software (GraphPad Software, Inc., San Diego, California). Unless otherwise specified, P < 0.05 was considered statistically significant.
Results Baseline features of patients in each group
In total, 240 patients were included. Among them, 234 (97.5%) were males, 235 (97.9%) patients with non-small cell lung cancer (NSCLC) and 6 (2.1%) patients with small cell lung cancer (SCLC). The patients’ ages ranged from 36 to 80 years old, and their mean ages were 61 years old. The median nicotine tolerance score in the failure of the smoking cessation group was 2. Eighty-six were never smokers, 51 failed to quit smoking, and 104 successfully quit smoking. There was no significant difference in gender composition, occupation, educational level, marital status or household income among the three groups (Table 1). Smoking status in the failure to quit smoking and success group
The smoking duration of the failure to quit smoking group was 43 years, which was significantly higher than that of the successful smoking cessation group (33 years; P < 0.001). The start smoking age in the failure to quit smoking group was significantly younger than that in the successful smoking cessation group (18 vs. 21 years old; P = 0.001; Figure 1).
Relationship between different genotypes of CHRNA5, CHRNA3, CHRNA4 and smoking cessation
There was no significant difference in the distribution of GG, AG and AA genotypes among the three groups of patients (P = 0.388; Table 2). There was no significant difference in the genotype distribution of CHRNA5 (rs588765) among the three groups (P = 0.277; Table 2). There was a significant difference in the GG and AG and AA genotype distribution of CHRNA3 rs578776 among the three groups (P = 0.003), and GG (upper left FAM) had the highest proportion (23.1%) in the success of the smoking cessation group (Table 2). These results indicated that patients with the GG genotype in CHRNA3 rs578776 were more likely to successfully quit smoking. There was a significant difference in the distribution of CHRNA4 rs1044396 genotypes among the three groups of patients (P = 0.001; Table 2). The AA genotype (lower right VIC) of CHRNA4 rs1044396 only appeared in the successful smoking cessation group (7.7%), indicating that patients with this genotype were more likely to quit smoking. There was a significant difference in the distribution of CHRNA4 rs2229959 genotypes among the three groups (P = 0.003; Table 2). The CC genotype (upper left FAM) in the group that quit smoking and never smokers accounted for 8.7% and 1.2%, respectively. However, it did not appear in the failure to quit smoking group, indicating that patients with the CC genotype in rs2229959 were more likely to successfully quit smoking. There was no significant difference in the genotype distribution of CHRNA4 rs2236196