| Background:Lung cancer is one of the most common malignancies. Today, in the worldwide, about 1800000 new cases of lung cancer were diagnosed in 2012 year, accounting for 13% of the total new cancer patients, it was top in the incidence and mortality of all malignancies for male and ranked third in the incidence and second in the mortality for female. Non-small cell lung cancer(NSCLC) accounts for about 80% of all lung cancer cases, and about 75% of NSCLC patients are diagnosed at a locally advanced stage, and with a old age, so the 5 year survival rate of NSCLC is poor. Few effective prevention or thearapy strategie for NSCLC patients was found today, so find effective biomarkers for prediction and prognostic for NSCLC is very important.The main treatment for NSCLC was surgery. In order to improve the cure rate and survival rate of patients, chemotherapy or radiotherapy was usually used before or after surgery, expecially for patients with advanced stage and can not be treat with surgery. But tumor heterogeneity existed in patients and the curative effects were differents in patients with same treatment strategy. So personalized medicine has dawned, but few biomarker was used in clinical treatment, more effective biomarkers were need to be found and used in treatment. Today, the molecular and cellular level differences, for cell receptors, genetic and molecular signaling for application of drug targets of molecular targeted therapy has become the current clinical application research hotspot in the field of lung cancer, but the markers are still very few.Single nucleotide polymorphism(SNP) is the most common form of genetic variations(a single nucleotide variation), and its minimum frequency of variation is 1%. The emerging evidences have shown that SNPs may be used as promising surrogate biomarkers of individual genetic background to predict therapeutic responses and prognosis in cancer patients. Recently, several studies have shown associations between host genetic polymorphisms in some genes and survival of NSCLC. But the effects were limited, so finding more effective SNPs on prediction of patients’ outcomes was very important for personalized medicine.Re-programming metabolic pathways was important hallmarker for tumor cells. In 1930, Otto Warburg found that tumors become more hypoxic and therefore they need to rely on non-oxidative energy source such as glycolysis even in the presence of oxygen. It is increasingly evident that many genes involved in metabolic pathways play direct roles in tumorigenesis and tumorprogression. Metabolic pathways including glycolysis, and tricarboxylic acid cycle, amino acid as well as nucleotide biosynthesis were abnormal in many tumors. Genes involved in metabolic pathways may used as diagnostic markers and potential therapeutic implications for NSCLC.Aims: To find and validate the predictive role of SNPs in tumor metabolism-related genes in NSCLC patients’ overall survival(OS) and recurrence free survival(RFS).Methods: 42 functional SNPs in 14 metabolism-related genes were genotyped to assess their associations with clinical parameters and prognosis of 500 Han Chinese NSCLC patients. Genotyping was performed using SEQUENOM Mass ARRAY platform. The association between SNP outcomes of NSCLC patients were analysised by Cox regression, log-rank test and survival tree analysis, and we also used TCGA data to evaluate the expression and copy number variation of genes.Results: The variant-containing genotypes of rs1059292 in 5’-flanking region of CD98 gene were significantly associated with an increased risk of death in the multivariate analysis. In addition, rs1059292 also showed a borderline significant association with tumor progression. Functional analysis demonstrated that variant genotype of SNP rs1059292 significantly enhanced the transcription activity of CD98 gene promoter. VV genotype of SNP rs1049434(MCT1) was significantly associated with better OS and RFS of NSCLC patients. VV genotype of another SNP rs995343(MCT2) exhibited an association with worse RFS of NSCLC patients.Our results showed that SDHC gene: SNP rs12064957, IDH2 gene: SNP rs11540478 and FH gene: SNP rs1414493 were associated with OS of NSCLC patients. Furthermore, survival tree analysis indicated that FH: rs1414493 was the primary risk factor contributing to OS of NSCLC patients and the IDH2: rs4932158 was the primary risk factor contributing to RFS of NSCLC patients.The variant genotype of rs7248411 and rs8191356 in GPI gene were significantly associated with an decreased risk of death in the multivariate analysis. Unfavorable genotypes of SNP rs7248411 and rs8191356 showed a significant cumulative effect on OS and RFS of NSCLC patients. In stratified analysis, the association remained significant in patients with different tumor stage and differentiation.Our data showed that SNP rs2847153 in TYMS gene was significantly associated with NSCLC recurrence under recessive model. We further identified a significant interaction between rs2847153 and chemotherapy in modifying clinical outcome of patients. Another two SNP rs2290707 and rs2853231 in RRM2 B gene were also associated with outcomes of NSCLC patients.Conclusion: ①SNP rs1059292、rs1049434、rs995343 in CD98、MCT1、MCT2 genes are significantly associated with outcomes of Chinese NSCLC patients. ②SNP rs12064957、rs11540478、rs1414493 in TCA pathway genes may serve as independent prognosis biomarkers for NSCLC patient. ③SNP rs7248411、rs8191356 in GPI gene are significantly associated with clinical outcomes of NSCLC patients. ④SNP rs2847153 in TYMS and SNP rs2290707、rs2853231 in RRM2 B gene may affect clinical outcomes and can be used to predict the outcomes in NSCLC patients. |
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