Study on single nucleotid polymorphisms of Muc1 gene and psca gene in gastric cancer patients

three times as high as those without a GC history. 1.1.3. Molecular Mechanism of Gastric cancer Many studies have shown a comprehensive picture of the molecular causes of GC including: gene mutations, non-gene mutations 4 and SNPs. SNPs are common genomic changes in humans, with about one million SNP sites found. SNP has initially explained the phenomenon that individuals are exposed to same environmental conditions but the likelihood of disease development among them is very different. This dissimilarity is attributed to the correlation of genetic traits such as SNP and environmental conditions. In GC,many SNPs are proven to have relation and SNPs of MUC1 and PSCA are specifically focused on research. 1.2. Polymorphism of MUC1 and PSCA genes In humans, the MUC1 gene is located in the long branch of chromosome 1, region 2, band 2 (1q22), with a size of 4407 bp, including 7 exons and 6 introns. The PSCA gene is on chromosome 8, band q24.2. The MUC1’s function is to encode proteins that act as a barrier against exogenous agents to the cell. However, in cancer cells, MUC1 is also considered as a carcinogenic protein. PSCA is responsible for differentiation, immune balance and T-cell activity. The PSCA gene appears in the epithelium of the stomach and it partially reduces activity in gastric tissue with intestinal dysplasia. According to the data of NCBI, there are many SNPs of the MUC1 and PSCA genes associated with the risk of GC, of which rs2070803 and rs4072037 belonging to the MUC1 gene and rs2976392 and rs2294008 belonging to the PSCA gene have been identified to have a strong connection with GC. All SNPs cause structural changes of the proteins; as a result, the function of normal proteins changes accordingly. Rs4072037 (MUC1) involves exon splicing processes thereby creating different variants as well as different functions of protein, which may reduce the mucosal protective function of the MUC1 protein. And rs2070803 (MUC1) is a genetic variation in this region that is related to GC. In vitro studies have shown that rs2294008 can reduce the replication activity of the PSCA gene because it is located at the beginning of this gene's replication, and the function of rs2976392 remains unclear. The combination of these SNPs with histopathological characteristics or history of H.pylori infection, history of drinking, smoking or personal and family history of GC has been a focused and prioritized topic on 5 research with an aim at shedding the light on the complicated mechanism of pathogenesis in GC. Chapter 2: RESEARCH PARTICIPANTS AND METHODOLOGY 2.1. Research participants - Criteria for selecting the case group: All patients with gastric carcinoma were clinically examined, took diagnostic imaging tests and were diagnosed by histopathological criteria. Any patients and their families who did not agree to join the study or simultaneously suffered from other cancers were excluded from the study. - Criteria for selecting the control group: Any individual without stomach pathology abnormality or with acute gastritis confirmed by clinical examination and endoscopy, was paired with GC patients by age and gender. 2.2. Study design: The study followed case – control design, with a sample size being calculated based on OpenEpi software and on the results of Fang Li et al (2012) studying MUC1 and PSCA gene polymorphisms in GC patients. Combining data from the study and the above mentioned software calculation we obtained the minimum sample size of 139 cases and 139 controls needed for this study. During the study, we selected 302 patients in the case group and 304 people in the control group in accordance with the above stated including and excluding criteria. 2.3. Time and location of research - Research time period: From 1/2016 to 8/2019 - Research location: Sampling was taken at Hanoi Medical University Hospital, K Hospital, 108 Central Military Hospital. Samples were analyzed at Center for Testing and Quality Assurance - University Hanoi Medical School and Department of Applied Biology (Kyoto Institute of Technology, Japan) using the same method. 10% of the sample was analyzed at both centers to ensure the accuracy of the results. 6 Quantification of H.pylori IgG by ELISA method was performed at Gen - Protein Research Center and Department of Biochemistry - Hanoi Medical University. And the determination of the Pepsinogen I, II level on the automatic immune system was conducted at the Laboratory Department - Hanoi Medical University Hospital. 2.4. Contents and research variables Smoking status: participants were divided into 2 groups: smokers and non-smokers. According to the concept of the Centers for Disease Control and Prevention (CDC), smokers are people who have smoked at least 100 cigarettes in their lifetime, whereas non-smokers are those who have never smoked or smoked less than 100 cigarettes in their lifetime. Alcohol use was assessed based on WHO standards, in which a 10-gram-alcohol-containing drinking unit is considered to be a standard unit of alcohol. One standard unit is equal to 1 cup of spirits/ whiskey (40 degrees, 30 ml); 1 glass of wine (13.5 degrees, 120 ml); 2/3 of a bottle or a can of beer (330 ml). The research questionnaire was developed based on the WHO's Audit C Test in which harmful drinking is defined when the total score of 3 answered questions for men is ≥ 4 points and for women is ≥ 3 points. And in this study, people who drank alcohol to such a harmful level were called ones with drinking history and the rest were called ones without drinking history. Personal history of gastric disease: This information was collected based on an interview question about the history of gastric disease that was diagnosed by a doctor. Family history of gastric disease: This information was gathered through interview questions, in which the person had a family history of gastric disease when GC runs into their families (diagnosed at the hospital). H.pylori infection history was assessed based on a patient's history of H.pylori infection diagnosis through interviewing, information gathered from medical records and quantitative results of IgG H.pylori test. Patients have a history of H. pylori infection if one of the 3 above results is positive. Patients have no history of H.pylori infection if all three results are negative. 7 2.5. Equipment and chemicals: Using equipment and chemicals of reputable manufacturers: Gene All (Korea), NEB (UK), Sequencing kit (USA), quantifying Pepsinogen (Abbott - USA), quantification of IgG of H.pylori (Germany) 2.6. Research techniques DNA extraction: DNA was extracted from blood samples using the method of Exgene ™ Blood SV Kit (Gene All, Korea). PCR duplicates the genome containing SNP rs4072037, rs2070803, rs2294008 and rs2976392 with 4 specialized primer pairs: SNP Primer sequences Size Rs4072037 5’-AACCCAGGGGTTACTGAGGCTG-3’ 5’-AGTACGCTGCTGGTCATACTCAC-3’ (reverse) 332 bp Rs2070803 5’-CTTAGCTGTCCGGGTGTGAAGT-3’ 5’-TGTGGTTCTAGGCAGGAGCAAC-3’ (reverse) 442 bp Rs2294008 5’-TAGGCTCTGTCCTCCAGAG-3’ 5’-TCTGTCTACCTGCCCCCTAG-3’ (reverse) 545 bp RS2976392 5’-CTGGCCATCTGTCCGCAGCT-3’ 5’-CAGATGGAGGAGGATGGCTGGA-3’ (reverse) 117 bp Performing restriction enzyme reaction: The standard PCR products were incubated with the corresponding specific enzymes including AlwNI for rs4072037, Taqa1 for rs2070803, NlaIII for rs2294008 and PvuII for rs2976392. Post-cut products were in electrophoresis on agarose gels of appropriate concentration to separate post-cut results. The results of SNPs were read by observing the number and size of DNA bands on the electrophoresis. Genetic sequencing: 10% of the samples were confirmed by direct sequencing. 2.7. Statistical Analysis The study used Stata 12.0 data analysis software and R 3.6.2 software in calculating the OR ratio (odds ratio) using the OR algorithm with 95% CI confidence interval; the ratios were compared with the Chi square algorithm; the average was compared with t- student test; the relationship of risk factors and GC was assessed by univariate and multivariate regression models. Especially, algorithms on R software were used to develop GC prognosis model. 8 2.8. Ethics The topic was approved by the ethics council of Hanoi Medical University. Moreover, patients were completely voluntary to participate in the study. Chapter 3: RESULTS 3.1. Characteristics of the research participants Table 3.1. Distribution characteristics by age Age Case Control Total p N % N % n % < 60 y 148 49.1 152 50.0 300 49.5 0.81 ≥ 60 y 154 50.9 152 50.0 306 50.5 Table 3.1 describes the distribution characteristics of the study participants by age(<60 years and ≥ 60 years) . The distribution by age of the two groups was not statistically significant (p> 0.05). Table 3.2: Gender characteristics of the research participants Gender Case Control Total p n % N % n % Male 210 69.5 195 64.1 405 66.8 0.16 Female 92 30.5 109 35.9 201 33.2 Table 3.2. The difference in the sex distribution between the two groups is not statistically significant (p> 0.05). The rate of men (69.5%) infected with the disease was 2.28 times higher than the one of women (30.5%). 9 There are some differences regarding to characteristics of history among research participants. In particular, the rate of patients with the drinking history in the case group (41.7%) was higher than the one in the control group (31.6%) with p <0.05. The proportion of individuals with history of gastric diseases among case group (52.7%) was significantly lower than the control group’s (63.5%) with p <0.05. The percentage of patients with family history of GC in the case group was 12.4%, higher than the one in the control group with 4.0%. And this finding was similar to the criteria of H.pylori infection history with higher rate in the case group , having statistical significance (p <0.05). Table 3.3: Characteristics of pepsinogen concentration Case (n=48) Control (n=128) P Mean SD Mean SD PGI level (ng/mL) 59.7 36.0 60.0 34.8 0.70 PGII level (ng/mL) 14.1 7.7 11.7 7.5 0.02* PGI/PGII ratio 4.6 2.0 5.8 2.2 0.00* * Statistical significance Analysis of pepsinogen I, II concentration and PGI / II ratio of newly infected patients (n = 48) compared with control group (n = 128) showed that the average PGI concentration between the two groups was different with statistical significance. PGII concentration of the case group was higher than of the control group (p <0.05). Especially, the PGI/II ratio of the case group was significantly lower than the one of control group with p <0.05. When compared with the diagnostic threshold, the PGI/II ratio ≤ 3 in the case group was significantly higher than the one in control group with p <0.01. 10 Table 3.4: Analysis of the influence of risk factors on the research participants on logistic regression model OR P 95%CI Gender (Male vs Female) 1.56 0.10 0.92 – 2.64 Age group (≥ 60y vs < 60 y) 0.72 0.09 0.50 – 1.05 Smoking history (Yes vs No) 1.05 0.84 0.66 – 1.65 Drinking history (Yes vs No) 0.50 0.04* 0.26 – 0.95 H.pylori infection history (Yes vs No) 0.42 0.00* 0.29 – 0.61 PG ratio (PGI/II ≤ 3 vs PGI/II >3) 2.56 0.07 0.93 – 7.09 Gastric disease history (Yes vs No) 1.42 0.06 0.99 – 2.04 Family GC history (Yes vs No) 3.69 0.00* 1.78 – 7.66 * Statistical significance Table 3.4 analyzes risk factors of GC by using multivariate regression including age group, sex, smoking history, drinking history, H. pylori infection history, PGI/II ratio, personal history of gastric disease and family history of GC in both case and control groups. The results showed that the rate of male suffering from GC were higher than the one of women with OR = 1.56, the ratio of PGI/II ≤ 3 compared with> 3 with OR = 2.56. The number of patients with history of gastric disease was higher than the one without history with OR = 1.42. The number of patients with family history of GC was higher than the one without history with OR = 3.69. The rest factors had OR <1. 3.2. Results of theMUC1 and PSCA polymorphisms analysis ❖ Rs4072037 of MUC1 gene 11 The gene fragment containing SNP rs4072037 was amplified by PCR reaction with specialized primers. The PCR product was in electrophoresis on 1.5% agarose gel providing the results as shown below: Figure 3.1: Electrophoresis image of amplified PCR product segment containing rs4072037 MUC1 gene on 1.5% agarose gel. M: Standard scale 100bp; B1 - B10: Patient sample; (-): Negative control Figure 3.1 is the result of the electrophoresis test of the PCR segment of the gene containing rs4072037 which consists of a single, clear band, without sub-bands, 332bp in size compared with the standard DNA scale. The specific PCR product was incubated with the restriction enzyme AlwNI. After this incubation time, the cut product was put in the electrophoresis on 1.5% agarose gel along with the 100bp calibration scale to achieve the results as shown below: Figure 3.2: Electrophoresis image of rs4072037 MUC1 gene segmentation M: Standard scale 100bp; B1-B10: Patient sample; Ctrl: Control Based on the specific cleavage site of the enzyme, different DNA strands were created for each genotype to determine the SNP genotype. The GG genotype consists of a 332bp DNA band (B1, 12 B2, B5). The AA genotype consists of two DNA bands of 223bp and 109bp sizes (B4, B7, B8). The AG genotype contains 3 DNA bands of 332bp, 223bp, 109bp (B6, B9, B10). After amplification, some PCR products containing SNP rs4072037 were sequenced. The sequencing results were analyzed by Sequencing Scanner software 2.0 and then compared with MUC1 gene sequence on GeneBank. The results of this sequencing helped to verify the results of genotypes of rs4072037 determined by PCR-RFLP. Figure 3.3: Results of the sequence of genes containing rs4072037 MUC1 gene The genotyping results for the rest SNPs were also obtained by using the same method. Consequently, identification of all 606 genotypes of 4 SNPs belonging to 606 subjects was successfully made. Table 3.5: Distribution of genotypes rs4072037 (MUC1) Case Control Total p n % N % n % Genotypes GG 43 14.2 37 12.2 80 13.2 0.00* AG 110 36.4 162 53.3 272 44.9 AA 149 49.4 105 34.5 254 41.9 Alelle A 196 32.5 236 38.8 432 35.6 0.02* G 408 67.5 372 61.1 780 64.4 *Statistical significance 13 Table 3.5 describes the genetic distribution characteristics of rs4072037 in the case and control groups. In the case group, the AA genotype rate stood at the top (49.4%), while it accounted for 34.5% in the control group. On the other hand, in the control group, the highest percentage of genotype was AG (53.3%) compared with 36.4% in the case group. This difference was statistically significant. The distribution of corresponding alleles between the two groups was also significantly different. Table 3.6: Genotypes of rs4072037 and risk of GC OR p 95% CI AG>GG 0.58 0.04* 0.35 – 0.97 AA>AG 2.09 0.00* 1.48 – 2.96 AA>AG+GG 1.85 0.00* 1.33 – 2.56 AA+AG>GG 1.19 0.45 0.75 – 1.91 A > G 1.32 0.02* 1.04 – 1.67 * Statistical significance Table 3.6 analyzes the correlation between RS4072037 genotypes and GC risk with the method of calculating the odds ratio and the risk of GC. Results showed that people with AA genotype had a higher risk of developing GC than people with AG genotype with OR = 2.09 (95% CI: 1.48 - 2.96). Similarly, people with the AA genotype were at higher risk of developing GC than those with the AG + GG genotype with OR = 1.85 (95% CI: 1.33 - 2.56). The risk of developing GC for the AG genotype was lower than for the GG genotype with OR = 0.58 (OR <1). The risk of GC development for allele A increased by 1.32 times compared to G allele in rs4072037. Analyzing the correlation of genotypes of rs2070803 and risk of GC by using the same method showed that people with GG 14 genotype had a higher risk of developing GC than those with AG genotype with OR = 1.97 (95). % CI: 1.39 - 2.80) and AG genotype reduced the risk of GC by 0.51 times. For rs2294008 and rs2976392, no correlation with GC risk was found. 3.3. Relation between SNPs and risk factors of GC Table 3.7: GC risk analysis of AA genotype compared with AG + GG of rs4072037 MUC1 gene AA AG+GG P OR 95% CI Gender Male 101/65 109/130 0.00* 1.85 1.24 – 2.77 Female 48/40 44/69 0.03* 1.88 1.07 – 3.31 Age <60 75/53 73/99 0.00* 1.92 1.21 – 3.05 ≥60 74/52 80/100 0.01* 1.78 1.12 – 2.82 Smoking Yes 61/39 82/86 0.05* 1.64 1.01 – 2.71 No 88/66 71/113 0.00* 2.12 1.37 – 3.28 Drinking Yes 145/103 147/195 0.00* 1.87 1.34 – 2.60 No 4/2 6/4 0.79 1.33 0.16 – 11.07 H.pylori infection Yes 57/59 54/122 0.00* 2.18 1.34 – 3.54 No 92/46 99/77 0.06 1.55 0.98 – 2.47 PGI/II ≤ 3 ratio Yes 7/3 3/7 0.08 5.44 0.80 – 36.87 No 18/78 20/40 0.04* 2.17 1.03 – 4.55 Histology Intestinal 113/149 116/153 0.53 1.00 0.70 – 1.41 Diffuse 36/149 37/153 0.55 0.99 0.60 – 1.67 *Statistical significance Table 3.7 showed that people with the AA genotype rs4072037 were at higher risk of developing GC than those with the AG + GG genotype in both sex groups, age groups, smoking history groups and H.pylori infection history groups. With regard to the risk of 15 drinking history and the characteristics of PGI/II ratio ≤ 3, the AA genotype only increased the risk of developing GC in the group with drinking history and the group without the PGI/II ratio ≤ 3. Regarding to rs2070803, it was found that people with the GG genotype were at higher risk of developing GC than those with the AG + AA genotype in age subgroups. With rs2294008, there was no statistical significance between the risk of GC development among people with TT genotype and those with CT + CC genotypes; except for patients <60 years, with TT genotypes, the risk of GC increased by 2.87 compared with those with CT + CC genotype. Similarly, with rs2976392, there was no statistical significance between the risk of GC development among people with AA genotypes and those with the AG + GG genotype; except for non-smokers <60 years with AA genotype, the risk of developing GC increased by 3.59 and 2.56 compared with carriers of AG + GG genotype, respectively. Chart 3.1. The AA genotype of rs4072037 in association with several risk factors on the logistic multivariate regression model 0 2.5 5 7.5 10 12.5 15 17.5 20 Age>= 60 + AA Male + AA Smoking + AA Drinking + AA Personal gastritis history + AA Familial GC history + AA Odds Ratio 16 It could be seen in the figure 3.1that there was an increase in the risk of developing GC of genotype AA rs4072037 when being combined with factors age ≥ 60, men, smoking, drinking and especially familial GC history. In particular, people with AA genotype together with family GC history had 6.47 times higher risk. Similarly, the combination of GG genotype of rs2070803and age, gender, history of drinking, smoking, and family history of GC increased the risk of GC development. In particular, the GG genotype associated with family history of GC increased the risk of developing GC by 6.18 times. There was no statistical significance in the risk of developing GC of genotypes TT rs2294008 and AA rs2976392 when combining with risk factors. Chart 3.2: Combining 4 genotypes of four SNPs on two genes Rs4072037 of MUC1 is P1 (where genotype of P11: GG; P12: AG; P13: AA); MUC1's Rs2070803 is P2 (where genotypes of P21: AA; P22: AG; P23: GG); Rs2294008 of PSCA is P3 (where genotypes of P31: CC; P32: CT; P33: TT); Rs2976392 is the P4 of PSCA (where the genotype of P41: GG; P42: AG; P43: AA). The forest plot diagram describes the link between the combination of four 17 genotypes of any SNP and the risk of GC. In the above chart, each horizontal line represents OR (the middle square) and the length of each line corresponds to 95% CI. The chart above indicated that presence combinations of AA genotypes rs4072037 (MUC1) and/or GG genotypes rs2070803 (MUC1) increased the risk of GC, which was statistically significant with OR ranging from 1.7 to 2.2. Using R software that has been world-wide applied for predictive and prognostic studies, we selected a model with the lowest AIC (772.23) in which the risk of GC depended on variables such as gender, history of individual gastric disease, family history of GC, age, smoking history, drinking history and SNP rs4072037. Chart 3.3: Diagnostic curve (ROC) of GC prognosis model The results obtained the area under the curve of the model was 70%, the accuracy of the model was 63% with 95% CI: 0.57 - 0.70. 18 Chart 3.4: Standardized calibration of GC prognostic model Figure 3.14 on the calibration results showed that the ideal and logistic calibration lines were similar. The Brier index to evaluate the quality of the calibration line was 0.2231. Using DynNom algorithm of R software, we created a mathematical representation of the GC risk prediction model based on the above independent variables. Figure 3.3: Mathematic simulation model predicting risk of GC (a) The figure describes the prediction model with independent variables according to the selected model including b1 (history of personal gastritis disease including 1: history; 2: no history); age; (drinking history evaluated by 19 WHO audit C test including 1: history; 0: no history); c1 (family history of GC including 1: history, 2: no history); P1 (genome selection of rs4072037 MUC1 genes include 1: GG genotype; 2: AG genotype; 3: AA genotype). (b) Figure depicting the probability of some patients from the graph of the figure (a). (c) Figure showing the probability of gastric cancer of some patients according to the example in figure (b). Applying the graph in (a) to some patients in which patients 1, 2, and 3 all have risk characteristics for age, history of personal stomach disease, drinking history, and money. family history of GC only differed in genotype of rs4072037 (MUC1), the results showed in Figure (b) that patients with AA genotype had the highest probability of developing GC of 0.765, patients with GG genotype had lower probability of GC of 0.743, patients with AG genotype had the lowest probability of GC of 0.625. Chapter 4 DISCUSSION 4.1. Discuss the characteristics of MUC1 and PSCA Regarding to rs4072037 of MUC1, it was shown that both the A allele and the AA genotype of rs4072037 increased the risk of GC. Our findings were similar to those of Xu (2009) and Jia (2010) on AA genotypes that increased the risk of GC. And especially in the heterozygous model, the AG genotype reduced the risk of developing GC significantly by 0.58 times compared with the AA genotype, which was similar to Giraldi et al. SNP rs4072037 is located at end 5 'of the exon 2 of MUC1 gene which helps to identify the junction point on exon 2. The different nucleotides in this position produce different signal peptides, which leads to changes in the protein coding function between the two cutoff variants. Allele A is associated with GC by reducing MUC1 gene 20 expression on the surface of gastric epithelium. Regarding to MUC1's SNP rs2070803, the GG genotype has the potential to increase the risk of GC, whereas the AG and AA genotypes have likelihood of reducing the risk of GC. Our findings are consistent with Fang Li's, but different from others’, such as that of Saeki (2011), suggesting that the G allele increases the risk of developing GC. Rs2070803 on 1q22 chromosome is a SNP located between MUC1 and TRIM46. MUC1 encodes mucin 1 - a cell surface glycoprotein that has been shown to be a carcinogen in many types of cancer including GC. This protein involves in a cancer marker called CA15.3 that is still widely used in clinical field. Regarding to rs2294008, no significant association with GC was identified. Our findings are similar to those of Lu (2010) but distinguished from others’ including Song (2011) and Matsuo (2009). Similarly, no significant link betweenrs2976392 and GC was found. Our findings resembles Tran Van Chuc’s. According to the synthesized findings of Qiu (2016), the obtained findings were also not consistent. 4.2. Discussing the association between SNPs and risk fact