| Background & objective:Primary liver cancer is a common malignant tumor in the world,the onset is hidden,most of the patients are in the middle or late stage at the time of diagnosis,the opportunity of radical resection is lost,and the prognosis is poor.therefore,the early diagnosis of liver cancer is very important.At present,the clinical diagnosis of liver cancer mainly depends on alpha-fetoprotein(AFP)combined with imaging examination,but the diagnostic value of AFP-negative liver cancer and small liver cancer is not ideal.The prognosis monitoring of liver cancer mainly depends on AFP and imaging examination,which needs more simple and reliable monitoring methods.Aptamer is a segment of oligonucleotide sequence,which can specifically bind to biological targets and has a good application prospect in tumor diagnosis and treatment.In this study,some aptamers were selected to evaluate the value of diagnosis and prognosis of liver cancer,and the relationship between aptamers and clinical characteristics of liver cancer was analyzed in order to explore the mechanism of combination of aptamers and targets.The purpose of this study is to provide a new strategy for the establishment of a new technology for diagnosis and treatment of liver cancer.Method:1.Collection of serum samples and clinical data: Serum samples of patients with liver cancer and liver cirrhosis newly treated in the first affiliated Hospital of Nanchang University from January 2015 to December 2020 were collected and frozen at-80 ℃.At the same time,consult the in-hospital electronic case system to collect the corresponding clinical data.2.Optimize the experimental conditions of small samples and evaluate the diagnostic value of aptamers for liver cancer: Seven aptamers selected in the study group were selected,and the triple fluorescence values of 64 serum samples(32 cases of liver cancer and 32 cases of liver cirrhosis)were determined by the triple fluorescence method of aptamers serum.the area under the receiver working characteristic curve(AUROC)was used to evaluate the diagnostic value of aptamers in different experimental conditions.In order to determine the best experimental concentration of aptamer.A liver cancer diagnosis model based on triple fluorescence indicator of aptamers was constructed by multivariate binary Logistic regression analysis.The aptamers with AUROC greater than 0.9 were further expanded to verify its diagnostic value.3.The diagnostic value of optimized aptamers in liver cancer was evaluated by large samples: The selected aptamers were verified by expanding the samples.The serum triple fluorescence of each optimized aptamer was measured,and the diagnostic model of liver cancer was constructed by multivariate binary Logistic regression analysis.The diagnostic value of optimized aptamer was evaluated by AUROC.4.Multiple modeling methods were used to evaluate the diagnostic value of aptamers for liver cancer: Discriminant analysis,decision tree and neural network were used to establish liver cancer diagnosis models with the fluorescence value of optimized aptamers as independent variables,and the diagnostic value of each model was compared with binary Logistic regression modeling.5.Differential value of aptamer and aptamer group to different clinicopathological features of hepatocellular carcinoma: patients with hepatocellular carcinoma were divided into hepatocellular carcinoma and cholangiocarcinoma,hepatitis B related liver cancer and non-hepatitis B related liver cancer,early liver cancer and non-early liver cancer,vascular invasion and non-vascular invasion,sclerosing liver cancer and non-sclerosing liver cancer.AUROC was used to evaluate the value of aptamer and aptamer group(combination)in the differential diagnosis of liver cancer.6.Correlation analysis between aptamer-related fluorescence and clinical indicators: Pearson or Spearman correlation analysis was used to evaluate the correlation between aptamer-related fluorescence and blood test indicators.7.Construction and evaluation of prognostic model: univariate and multivariate COX regression were used to screen the variables related to prognosis,and multivariate COX regression was used to construct a risk score model.According to the median value,the patients were divided into high-risk group and low-risk group.KM curve was used to analyze the survival difference between the two groups.The C index of each risk scoring model was calculated respectively.At the same time,the aptamer risk score models were calculated to predict the 1-,2-and 3-year survival rate of liver cancer.AUROC evaluation was used to evaluate the predictive effect.The consistency and clinical net benefit of the evaluation model of drawing correction curve and clinical decision curve.Results:1.The best experimental concentration of small sample optimized aptamer:64 cases of small sample(32 cases of liver cancer).The optimization results showed that the optimal modeling concentrations of aptamers AP-8-1-5,AP-8-2-7,AP-9-90,AP-9-152,AP-6-2-20,AP-8-1-7 and AP-9-74 were 0.06 pmol/ μL,0.12 pmol/ μL,0.08 pmol/ μL,0.08 pmol/ μL,0.10 pmol/ μL,0.12 pmol/ μL,0.06 pmol/ μL respectively.2.The diagnostic value of small sample evaluation of optimized aptamers for liver cancer: According to the serum triple fluorescence values of each aptamer measured under the best experimental concentration,four aptamers with good diagnostic value were selected,namely AP-8-1-5,AP-8-2-7,AP-9-90 and AP-9-152.the maximum AUROC of multi-index modeling for diagnosis of liver cancer was0.935,0.932,0.949 and 0.964,respectively.3.Evaluation of the diagnostic value of optimal aptamers for liver cancer in large samples: The samples were expanded to 337 cases of liver cancer and 318 cases of liver cirrhosis.The results showed that the aptamers AP-8-1-5,AP-8-2-7,AP The AUROCs of-9-90 and AP-9-152 to distinguish liver cancer from liver cirrhosis were 0.952,0.979,0.938,and 0.951,respectively;the AUROCs to distinguish small liver cancer from liver cirrhosis were 0.944,0.991,0.956,and 0.920,respectively;The AUROCs of liver cirrhosis were 0.957,0.988,0.945,and 0.950,respectively;the AUROCs of distinguishing AFP-positive liver cancer from liver cirrhosis were 0.948,0.972,0.932,and 0.937,respectively.4.The diagnostic value of optimized aptamers for liver cancer was evaluated by different modeling methods: Binary Logistic regression,discriminant analysis,decision tree and neural network were used to model and evaluate the diagnostic value of aptamers.The results showed that the AUROC of aptamer AP-8-1-5 to distinguish liver cancer from liver cirrhosis was 0.923,0.921,0.860 and0.936,respectively.The AUROC of AP-8-2-7 was 0.958,0.957,0.890 and 0.968,respectively.The AUROC of AP-9-90 was 0.886,0.921,0.809 and 0.898,respectively,and the AUROC was of AP-9-152 was 0.920,0.921,0.848 and 0.936,respectively.Among the four modeling methods,neural network modeling is the best for the diagnosis of liver cancer.5.Prediction of clinicopathological features of liver cancer by aptamer and aptamer group: Aptamer has the greatest value in distinguishing early stage of TNM from non-early stage liver cancer,in which aptamer AP-9-90 is the best,and the maximum AUROC of the two groups is 0.752.After aptamer combination,the ability to distinguish between the two groups was improved,and the maximum AUROC was0.818.6.Correlation analysis between aptamer-associated fluorescence and clinical indicators: Aptamer-associated fluorescence(SEA)was correlated with albumin,globulin,high density lipoprotein and hemoglobin,suggesting that the expression level of aptamer target protein may be related to liver function.7.Construction of prognosis model of liver cancer: Aptamers closely related to prognosis were screened by multivariate COX proportional hazard model,which were AP-8-1-5,AP-9-152,AP-8-2-7 and AP-8-1-7,respectively.Risk score models were constructed for these four aptamers.KM curve analysis showed that there were survival differences among the risk score models of each aptamer.8.Evaluation of the prognostic model of liver cancer: The C index of the prognostic model constructed by aptamers AP-8-1-5,AP-9-152,AP-8-2-7 and AP-8-1-7 was 0.650,0.643,0.643 and 0.627 respectively.The correction curve and decision curve showed that the model had good consistency and clinical net benefit.Conclusions:1.There are differences in the diagnostic value of serum triple fluorescence with different concentrations of aptamers,and the diagnostic value can be improved by optimizing the experimental concentration of aptamers.2.The optimized liver cancer serum aptamers are effective in the differentiation of liver cancer from liver cirrhosis,including small liver cancer and liver cirrhosis,AFP negative liver cancer and liver cirrhosis,AFP positive liver cancer and liver cirrhosis.3.Liver cancer serum aptamers have a good ability to distinguish early TNM liver cancer from non-early liver cancer,which can be effectively improved by aptamer group.4.There is a certain correlation between aptamer-related fluorescence and liver function,suggesting that the target content in serum is related to the state of liver function.5.The aptamer-based prognostic prediction score system of liver cancer has a good value in the evaluation of the prognosis of liver cancer. |
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