| The incidence of lung cancer has long been the 1st malignant tumor in China,and more than 85% patients are non-small cell lung cancer(NSCLC).The epithelial growth factor receptor tyrosine kinase inhibitor(EGFR-TKI)is the effective target therapy drug for advanced NSCLC.However,there is a huge difference in the efficacy of patients and almost all of the patients eventually develop TKI-resistance in tumor progression.Single nucleotide polymorphism(SNP)is one of the important genetic basis of pharmacogenomics.Genotype of pathway gene specific SNPs(tag SNPs)not only influenced the prognosis of the treatment,and could be used biomarkers of the predictors of clinical effect.In order to clarify the molecular mechanism that affects the curative effect and prognosis of EGFR-TKI,we intend to study the relationship between tag SNPs and the curative effect and prognosis of EGFR-TKI by PI3K/Akt/mTOR pathway strategy,which is also helpful for us to provide the basis for improving the individualized therapeutic effect of NSCLC and reversing drug resistance.Methods:1.According to the principle of clinical experimental design,we evaluated the sample size and set up the entry standard.we also collected clinical information and biological samples from the patients and established the NSCLC case database and specimen bank.Relying on the SNP databases,Genetic Law and Bioinformatics Technology,we sucessfully found the tag SNPs in PI3K/AKT/mTOR signaling Pathway.2.Detection of tag SNPs genotyping by multiple snapshot method in peripheral blood samples.3.To investigate the relationship between clinicopathological characteristics,the tag SNPs of PI3K/AKT/mTOR signaling pathway and the curative effect of EGFR-TKI.4.The data of PFS and OS in patients with non-small cell lung cancer treated with EGFR-TKI were statistically analyzed,and survival curves were drawn.Univariate and multivariate analysis was used to further explore the related factors affecting the prognosis of patients with non-small cell lung cancer(NSCLC).5.Statistical processing: Epidata software was used to establish database;Chi-square test was used to analyze whether the distribution of tag SNP genotypes was in accordance with Hardy-Weinberg balance;Genetic software Haploview 4.0 was used to analyze the linkage disequilibrium between tag SNP loci on genes;Chi-square test,Univariate and multivariate analysis was used to evaluate the relationship between tag SNPs,biological information and the curative effect and prognosis of EGFR-TKI.Survival analysis was performed by Kaplan-meier method.All statistical analyses were carried out with SPSS 19.0 software for bilateral test with a significant level of 0.05.Results:1.According to the degree of linkage disequilibrium between SNPs in PI3K/AKT/mTOR pathway gene and the screening strategy,the block map of each SNP was constructed by Haploview software.Two tag SNPs: rs884225 and rs1468727 from EGFR gene;two tags SNPs: rs3729679 and rs7634251 from PIK3 CA gene;three tags SNPs from AKT1 gene: rs2494750,rs2498786 and rs1130233;and 1 from AKT2 gene: rs62107593;two SNPs: rs1034528 and rs3806317 from mTOR gene,and one tag SNP: rs701848 from PTEN gene were finally selected.2.A total of 220 patients with advanced non-small cell lung cancer(NSCLC)were enrolled in this study.The overall effective rate including CR and PR was 23.6%,the overall disease control rate including CR,PR and SD was 61.4%.The effective rate(29.6% vs 17.1%,p=0.039)and the disease control rate(69.6% vs 52.4%,p=0.012)of female patients was higher than male patients.The effective rate(27.7% vs 15.3%,p=0.044)and the disease control rate(66.2% vs 51.4%,p=0.012)of non-smoking patients were higher than those of smoking patients.The effective rate(26.2% vs 6.9%,p=0.020)and the disease control rate(65.4% vs 34.5%,p=0.002)were higher than those of non-adenocarcinoma patients(including 8 cases of adenosquamous carcinoma and 21 cases of squamous cell carcinoma).The effective rate(44.4% vs 7.1% vs 18.2%,p=0.000)and the disease control rate(81.5% vs 36.9% vs 69.1%,p=0.000)of patients with EGFR sensitivity mutation was higher than unmutated and unknown patients,the difference of which was statistically significant.3.There were significant differences in the effective rate(36.4% vs 23.4% vs 13.5%,p=0.031)and the disease control rate(77.3% vs 61.3% vs 48.1%,p=0.014)of the three genotypes of EGFR rs884225 locus(TT,CT and CC).There were also significant differences in the effective rate(14.7% vs 32.4% vs 15.4%,p=0.004)and the disease control rate(47.1% vs 69.4% vs 56.4%,p=0.035)of the three genotypes of AKT1 rs1130233 locus(CC,CT and TT).The combined analysis was carried out because of the low frequency of the GG group and the result showed that there was significant difference in the the disease control rate(58.2% vs 75.0%,p=0.030)of GA genotype and non-GA genotype.Combined with rs884225 of EGFR gene and rs1130233 of AKT1 gene,there were significant differences in effective rate(48.0% vs 20.5%,p=0.005)and disease control rate(100.0% vs 56.4%,p=0.000)between dominant group(CC+CT)and non-dominant group.4.The confounding factors,such as age,sex,pathological type,stage,mutation status,ECOG score,TKI drug types,smoking status and the number of previous treatment lines were adjusted respectively.The disease control rate of TT genotype at rs884225 locus of EGFR gene was 4.956 times(95%CI 1.672-14.694,p=0.004)higher than that of CC genotype by non-conditional Logistic regression analysis in codominant model.The disease control rate of TT genotype was 3.334 times(95%CI 1.332-8.334,p=0.010)higher than that of non-TT genotype in dominant model.The disease control rate of AA genotype at rs884225 locus of PIK3 CA gene was 0.451 times(95%CI 0.211-0.963,p=0.040)higher than that of non-AA genotype by in recessive model.The disease control rate of CT genotype at rs1130233 locus of AKT1 gene was 6.586 times(95%CI 2.279-19.030,p=0.000)higher than that of CC genotype in codominant model.The disease control rate of CC genotype was 0.226 times(95%CI 0.086-0.597,p=0.003)higher than that of non-CC genotype in dominant model.5.The result showed that women(6.84 m vs 5.27 m,p=0.011),adenocarcinoma(6.30 m vs 4.66 m,p=0.048)and patients with EGFR mutation(9.14 m vs 2.60 m vs 6.56 m,p=0.000)had longer progression-free survival using Log-Rank test in Kaplan Meier.There was no correlation between the progression-free survival and age,ECOG score,smoking status,stage,the type of TKIs and the number of previous treatment lines.In terms of gene polymorphism,the time of disease progression of TT genotype at rs884225 locus of EGFR gene was longer(7.96 m vs 5.64 m vs 5.51 m,p=0.005)and CT genotype at rs1130233 locus of AKT1 gene was also longer(7.01 m vs 4.74 m vs 5.34 m,p=0.001).The multivariate Cox proportional risk regression model showed that,The risk of disease progression was higher in patients with lower ECOG score(HR=1.452,95%CI 1.057-1.994,p=0.021)and smoking history(HR=1.524,95%CI 1.035-2.244,p=0.033).The mutated patients(HR=0.045,95%CI 0.026-0.079,p=0.000)and unknown patients(HR=0.112,95%CI 0.064-0.196,p=0.000)had a lower risk of disease progression,the difference of which was statistically significant.The risk of disease progression in patients with CT genotype(HR=3.197,95%CI 1.994-5.127,p=0.000)or CC genotype(HR=2.881,95%CI 1.701-4.880,p=0.000)at rs884225 locus of EGFR gene was higher than that in patients with TT genotype.The risk of disease progression in patients with CC genotype(HR=2.118,95%CI 1.369-3.278,p=0.000)or TT genotype(HR=2.118,95%CI 1.369-3.278,p=0.000)was higher than others,which had Significant statistical difference.Combined with rs884225 of EGFR gene and rs1130233 of AKT1 gene,the time of disease progression in the dominant group(CC+CT)was better than that in the non-dominant group,and there was significant difference(10.33 m vs 5.52 m,p=0.000).6.Univariate survival analysis showed that: There was no significant difference between age,sex,ECOG score,smoking status,disease stage,TKI type,EGFR mutation status,the number of therapeutic lines,gene polymorphisms,previous treatment lines and total survival time.Multivariate survival analysis showed that the overall prognosis of smoking patients was worse than that of non-smoking patients(HR=1.627,95%CI 1.074-2.466,p=0.022),and the difference was statistically significant.Other clinicopathological features and genetic changes were not correlated with prognosis.Conclusions:1.The human genome SNP database,Genetic Law,bioinformatics software and methods can be used to screen out the key Tag,which could optimize the efficiency of testing and improve the efficiency of scientific research.2.Women,non-smokers,adenocarcinomas and patients with EGFR mutation have a better efficacy of EGFR-TKI.3.The effective rate of EGFR-TKI treatment was higher in patients with TT genotype of rs884225 locus of EGFR gene and CT genotype of rs1130233 locus of AKT1 gene,and multivariate analysis showed that both of them were predictors of therapeutic effect of EGFR-TKI.Combined analysis is better in predicting curative effect.4.The time of disease progression in EGFR-TKI was closely related to sex,rs884225 locus polymorphism of EGFR gene,rs1130233 locus polymorphism of AKT1 gene and EGFR mutation status,but there was no correlation between age,ECOG score,smoking status,TKI type and the number of previous treatment lines.5.There was no statistical correlation between total survival and clinicopathological features of NSCLC patients,and smoking was the only independent prognostic factor of NSCLC. |
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