| Background and objectives:Early diagnosis,accurate staging and liver function grading are crucial for improving the therapeutic effect and prognosis of patients with primary hepatic carcinoma(PHC),which are based on complete information of clinic,laboratory,imageology and pathology.Therefore,there is the important significance to investigate a "one-stop" method to simultaneously diagnosis PHCs,stage and grade liver function through one test.Aptamers are artificial nucleic acid ligands of biological molecules,which are functionally similar with antibodies but more advantages on the application.Previously,we screened 365 aptamers against PHC serum and developed a novel high throughput diagnostic method based on aptamer-related triple serum fluorescence.We found the combination modeling based on that the triple serum fluorescence had good diagnostic value and certain staging and grading value against PHC,suggesting that a "one-stop" diagnostic method for PHC can be achieved by high-throughput detection and combination modeling of triple serum fluorescence of a group of aptamers that can complement with each other.In the present study,we will construct an aptamer group optimized in the previous stage for high-throughput detection of aptamer-group triple serum fluorescence,and develop a novel "one-stop" PHC diagnostic method and evaluate its diagnostic value.Methods:1.Collection of serum specimens:Serum specimens were collected from patients with PHC,liver cirrhosis(LC),chronic hepatitis(CH)hospitalized before treatment and normal specimens(NS)for health check-up in the First Affiliated Hospital of Nanchang University from 2015 to 2018.2.Selection of representative PHC aptamers by theoretical analysis:The secondary structure of the 365 PHC serum aptamers screened in the previous stage was analyzed by RNA Structure 4.6 software.The sequence homology of each aptamer was analyzed by Clustal X software.Aptamers with different secondary structures and low sequence homology were selected as representative aptamers for artificial synthesis.3.Selection of high-specificity aptamers by mixed serum analysis:On the basis of optimizing experimental conditions,candidate aptamers with high specificity against PHC were optimized by analyzing the specificity of each representative aptamers with PHC mixed serum based on the triple serum fluorescence assays of fluorescence quantitative polymerase chain reaction.4.Construction of the"one-stop"PHC diagnostic aptamer group optimized by single serum samples:On the basis of optimizing detection conditions,the aptamers with high diagnostic value were screened to establish a diagnostic model by detecting fluorescence changes from these high-specificity candidate aptamers on PHC and control serum samples.These aptamers into models constituted the"one-stop" PHC diagnostic aptamer group.5.Evaluation of the one-stop" PHC diagnostic value of aptamer group:The classified serum samples and random consecutive serum samples were collected respectively.The triple serum fluorescences of these serum samples were detected by each aptamer in the PHC "one-stop" diagnostic aptamer group.Using fluorescence indicators as variables,five machine learning models of Logistic regression(LR),discriminant analysis(DA),support vector machine(SVM),decision tree(DT)and neural network(ANN)were established to obtain the diagnostic results of these specimens.The qualitative diagnostic value of the aptamer group against PHC was evaluated by ROC curve analysis.The accuracy of the aptamer group for BCLC and TNM staging of PHC and Child-Pugh grading of liver function were calculated.Results1.Optimized selection of representative aptamers:The secondary structure of 365 PHC serum aptamers analyzed by Sructure 4.6 software indicated the secondary structure of the aptamers was abundant.The sequence homology was analyed by Clustal X software,and 365 aptamers can be divided into 55 families based on sequence homology distribution.Summarizing the rules on the affinity and specificity of homology and secondary structure in published literatures,26 representative aptamers were screened from 365 aptamers.2.Optimized selection of high-specificity aptamers:According to the triple serum fluorescences changes difference between PHC and LC mixed serum detected by the 26 representative PHC serum aptamers,a total of seven sptamers reached the fluorescence growth difference of 10%or more,including Ap-HCS-9-109,Ap-HCS-9-90,Ap-HCS-9-120,Ap-HCS-9-22,Ap-HCS-9-110,Ap-HCS-9-23 and Ap-ANHC-8-1-5.The seven aptamers were selected as high-specific candidate aptamers.3.Construction of the "one-stop" PHC diagnostic aptamer group:According to the triple serum fluorescences results of PHC and LC single serums detected by the seven high-specific candidate aptamers,the AUROC of Ap-HCS-9-120,Ap-HCS-9-90 and Ap-HCS-9-23 distinguishes PHC from LC is greater than 0.75,and the combined analysis of AUROC is above 0.8.The accuracy of Ap-HCS-9-120 in predicting BCLC and TNM staging was higher than 550%,and that of Ap-HCS-9-90 in predicting TNM staging and Child-Pugh staging was 55%and 75%,respectively.Based on the comprehensive analysis,the three aptamers were selected to construct the "one-stop" PHC diagnostic aptamer group.4.The evaluation of the value of aptamer group for the PHC one-stop"diagnosis:Based on the triple serum fluorescence indexes of the classified serum samples and the random serum samples detected by each aptamer of the aptamer group,five machine learning classification models were established,and distinguished PHC from control with AUROC in the range of 0.767-0.992,while the accuracy of BCLC staging,TNM staging and Child-Pugh grading was 40-100%.Among them,most of the combination analysis AUROC were over 0.9.DT was stable under various conditions(AUROC more than 0.9).The accuracy of staging and grading could exceed 90%.Conclusions:1.By secondary structure analysis and sequence homology analysis of 365 PHC serum aptamers,representative aptamers with low sequence homology and abundant secondary structure were optimized.In theory,there were potential candidate aptamers suitable for constructing the PHC "one-stop" diagnostic aptamer group.2.On the basis of optimizing experimental conditions,the triple serum fluorescences of preferred aptamers were detected by mixed serum and single-samples serum successively.Ap-HCS-9-120,Ap-HCS-9-90 and Ap-HCS-9-23 have good value in PHC diagnosis,staging and liver function grading against PHC,and the three aptamers were used for developing the aptamer-group,which can effectively conduct the "one-stop" diagnosis against PHC.3.The triple serum fluorescence intensity of different serum sample systems were detected by the aptamer group,and a series of diagnostic models were developed by five machine learning methods.Each model(especially DT models),has good and similar diagnostic value in different sample systems,superior to AFP.It indicated that the aptamer group has a good performance on the PHC "one-stop"diagnosis against PHC. |
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