A Polymorphism At The Mir-502Binding Site In The3’ Untranslated Region Of The Set8Gene Is Associated With Clinical Characteristicsthe And The Outcome Of Lung Cancer

Objective: Lung cancer has become one of the most common malignanttumor, in the global scope，lung cancer overall morbidity and mortality standfirst on the list of all kinds of cancer, the incidence and mortality of the diseaseare increasing day by day. MicroRNA(miRNA) is a kind of small no-codingRNA, about30%of protein-coding genes is regulated by miRNA in thehuman genome.Single nucleotide polymorphisms (SNPS) is a polymorphismthat caused by changing Single nucleotide sequence in the genome level, it isthe most important genetic variation between different individual.In the3’untranslated region of the SET8gene has the miR-502binding site,singlenucleotide polymorphisms site rs16917496exists in the miR-502binding sitein the3’ untranslated region of the SET8gene.Studies found that，this siteregulate the expression of the SET8gene, and it relate with the early happenof tumor. This study analyzes the relationship of polymorphism at themiR-502binding site in the3’ untranslated region of the SET8gene withclinical features and the outcome of in patients with lung cancer firstly，at thesame time, analysis the relationship between clinical characteristics andprognosis in patients.Aim is to study the relationship that polymorphism at themiR-502binding site in the3’ untranslated region of the SET8gene with theoutcome of lung cancer.Methods: The317cases of lung cancer patients were collected that werehospitalized in the respiratory department of fourth hospital of Hebei medicaluniversity from May2001to May2011. All of the patients are identified aslung cancer by the histopathological and/or cell pathological.All patientseliminated extrapulmonary primary tumor and genetic diseasehistory.According to the requirements, we record sex, age, pathological type, clinical staging, smoking status and treatment of all patients accurately. All ofthe317cases patients’ gene type were analysised. The195cases had accuratesurvival data, survival analysis was done. Take their hollow venous bloodbefore they accept radiation and chemotherapy. The5ml venous blood are putin the tube that contain folic acid sodium. Genomic DNA is extracted by usingproteinase K digestion followed by a salting out procedure. After DNAidentification qualified, we using polymerase chain reaction to objectivefragments amplification.Then test SNP site by ligase detection reaction. ThemiR-502binding site in the3’ untranslated region of the SET8gene weregenotyped.To compute the SNP distribution in the frequency of different groups ofpatients with lung cancer by of the chi-square test, and the relative risk degreeodds ratio (OR) and95%confidence interval (CI)by unconditional logisticregression method.The survival rates and survival curves are evaluated by theKaplan-Meier method,and compared by the Log-Rank test. Screening riskfactors that may influence the outcome of lung cancer. We put them that havethe statistical significance in COX regression model.To calculate p-value,relative risk(RR)and the confidence interval(CI)to find out Independent riskfactors that relationship with the outcome of lung cancer. All statisticalanalysis are used SPSS18.0package, P<0.05is considered significant for allstatistical analyses.Results:1All study subjects, male accounted for67.5%(n=214), female accountedfor32.5%(103cases), the mean age of59.09+/-10.67years. Less than60were accounted for56.2%(178cases),>60years old accounted for43.8%(139cases). Pulmonary squamous cell carcinoma accounts for26.8%(n=85),adenocarcinoma accounted for49.8%(158cases), small cell lungcancer accounted for23.4%(74cases). Smokers accounted for50.5%(160cases), nonsmokers accounted for49.5%(157cases). Treated was85.8%(272cases), untreated accounted for14.2%(45cases).In patients with lung cancer that had accurate survival data, non small cell lung cancer152cases, male accounted for65.8%(n=100), femaleaccounted for34.2%(52cases), mean age60.36+/-10.73years. Less than60were accounted for48%(73cases),>60years old accounted for52%(79cases). Pulmonary squamous cell carcinoma accounts for30.9%(n=47),adenocarcinoma accounted for69.1%(105cases). Patients with stage IIIaccounted for30.3%(n=46), patients with stage IV accounted for69.7%(106cases). Smokers accounted for48.7%(74cases), nonsmokers accountedfor51.3%(78cases). Treated was82.9%(126cases), untreated accounted for17.1%(26cases). Small cell lung cancer43cases, male accounted for62.8%(n=27), female accounted for37.2%(16cases), mean age56.60+/-10.63years. Less than60were accounted for67.4%(29cases),>60years oldaccounted for32.6%(14cases). Limitation period accounted for30.2%(13cases), extensive stage accounted for69.8%(30cases). Smokers accounted for53.5%(23cases), nonsmokers accounted for46.5%(20cases). Treated was93%(40cases), untreated accounted for7%(3cases).2All lung cancer patients, between different pathological type (NSCLCgroup and SCLC group, P=0.764, OR=1.061,95%CI=0.720-1.565,squamous cell carcinoma with the group of adenocarcinoma, P=0.121, OR=0.734,95%CI=0.4961.085), gender (male patients and female, P=0.485,OR=0.881,95%CI=0.6181.257), age (≤60years and>60years, P=0.729, OR=1.060,95%CI=0.7611.478), smoking (smoking patients andnot smoking, P=0.500, OR=0.893,95%CI=0.6421.242), the difference ofallele distribution frequency (T and C) were no statistically significant3All lung cancer patients, between different pathological type (NSCLCgroup and SCLC group TT, CT and CC genotype frequencies were29.6%,27.5%,7.7%and32.1%,22.3%,11.6%; Squamous cell carcinoma group andadenocarcinoma group TT, CT and CC genotype frequencies were25.9%,26.7%,10.4%and31.7%,27.9%,6.3%), gender (male patients with femalepatients TT, CT and CC genotype frequencies were28.9%,26.8%,8.7%and35.2%,36.9%,29%), age (≤60years and>60years TT, CT and CC genotypefrequencies were30.9%,26.1%,8.5%and29.3%,26.5%,8.8%), smoking (smoking patients and not smoking TT, CT and CC genotype frequencies were28.7%,26.6%,9%and31.7%,25.9%,8.2%), CT genotypes, CC genotype andCT+CC gene type, against to the advantages of the genotype TT, differenceof genotype distribution frequency were not statistically significan（tP＞0.05）.4In non-small cell lung cancer group, Single factor analysis showed that,set8genotype (CC genotype, CT genotype and TT genotype, p=0.688), gender(male and female, p=0.842), age (≤60years and>60years, p=0.776),pathological types (squamous cell carcinoma and adenocarcinoma patients, p=0.403), smoking (smokers and nonsmokers, p=0.543), influence onprognosis were no statistically significant.Pathologic stage (phase III and IV, P=0.003), treatment (treatment group and no, P=0.000), influence onprognosis were statistically significant. Multifactor analysis showed that,phase III patients and IV, the latter risk of death was1.904times of the former(P=0.007, RR=1.904,95%CI=1.194-3.038). The treatment groupcompared with no treatment group, the former risk of death is0.434times ofthe latter (P=0.000, RR=0.434,95%CI=0.273-0.690).5In small cell lung cancer group, Single factor analysis showed that,gender (male and female, P=0.087), clinical staging (limited disease andextensive disease，P=0.939), smoking (smokers and nonsmokers, P=0.349),influence on prognosis were no statistically significant. SET8genotype (CC+CT genotype and TT genotype, P=0.043), age (≤60years and>60years, P=0.029), treatment (treatment group and no treatment group, P=0.000),influence on prognosis were statistically significant. Multivariate analysisshowed that, CC+CT the genotype have longer survival time then TT genes,the former risk of death was0.438times then TT genotype (P=0.031, RR=0.438,95%CI=0.207-0.926), set8genotype can be used as independentprognostic factors of SCLC. Age was unconcerned with small cell lung cancerdeath risk (P=0.122, RR=1.806,95%CI=0.855-3.816), age is not becomesmall cell lung cancer prognosis of the independent factors. The treatmentgroup compared with no treatment group, the former risk of death is0.059times of the latter (P=0.000, RR=0.059,95%CI=0.012-0.287). Conclusion:1Rs16917496polymorphic loci in genotype,T,C allele frequency and thegenotype（TT, TC, CC）distribution of different clinical features（Including thepathological type, gender, age, smoking status）of lung cancer have nosignificant difference.2Set8genotype was correlated with the outcome of SCLC,it can be used asthe independent risk factors that relationship with the outcome of SCLC, CC+CT the genotype have longer survival time then TT genes.3Set8genotype was unconcerned with the outcome of NSCLC.4Treatment can be used as the the independent risk factors that relationshipwith the outcome of lung cancer, the treatment group compared with notreatment one, its prognosis was improved obviously.5TNM staging can be used as the the independent risk factors thatrelationship with the outcome of NSCLC, the stage III group compared withthe stage IV, its prognosis was improved obviously. Gender, age, pathologicaltypes and smoking status, can notbe used as the the independent risk factorsthat relationship with the outcome of NSCLC.6Gender, age, clinical staging and smoking status, can’t be used as the theindependent risk factors that relationship with the outcome of SCLC.