Aptamer-based Mass Cytometry For Molecular Profiling Of Hematological Malignancy

High heterogeneity is an important feature of malignant tumors.Hematological malignancies,for example,are classified into more than 100 subtypes according to their origin,genetic abnormalities and clinical symptoms,according to guidelines published by the World Health Organization(WHO).Different subtypes of the same disease may have completely different responses to the same clinical regimen.For example,combination chemotherapy with all-trans retinoic acid and arsenic trioxide is more than 80 percent effective in acute promyelocytic leukemia(APL),but less effective in other leukemia subtypes.Therefore,accurate molecular typing of cancer will provide important information for clinical diagnosis,treatment and prognosis evaluation of the disease.Although genome sequencing and transcriptome sequencing have become the most commonly used classification strategies,they are unable to provide phenotypic and functional data on cell surface proteins.Surface protein analysis at the single cell level would be an attractive alternative for cancer typing and diagnosis.To achieve this goal,fluorescence flow cytometry provides a wellestablished single-cell measurement technique with high throughput and simple operation.However,the multiplex analysis capability of traditional fluorescent dyes is limited due to the spectral overlap problem of fluorescent groups.As an advanced alternative,mass cytometry,which has the advantages of minimal signal overlap and cell background noise,has shown the ability to synchronically measure more than 40 parameters in a single experiment.Despite their efficacy in multiplex single-cell assays,the probes currently used for analysis are primarily antibodies,and the antibody-mediated cancer classification potential is limited by the inadequacy of the probe types.In order to solve the above problems,aptamers were introduced as probes for molecular profiling.Aptamers are a new type of recognition ligand,often referred to as "chemical antibodies",which have inherent advantages such as high specificity,simple synthesis,low immunogenicity and conv enient modification.In addition,with intact living cells as the selected object,various aptamers for different cell surface biomarkers can be generated through Cell-SELEX(systematic evolution of ligands by exponential enrichment),which is a favorable complement to antibodies.At the same time,related mass tags are synthesized to make aptamers more effective for mass cytometry detection.Finally,we successfully applied aptamer-mass tags to the molecular profiling of hematological malignancy cell lines and clinical samples,and combined with machine learning,realized the classification of clinical samples.(1)In Chapter 2,we loaded metal ions on the autonomously synthesized polymer,connected it with aptamers through click chemistry,optimized the reaction conditions of click chemistry,and finally got the optimal reaction conditions of aptamer-mass tag.The targeting of aptamers detected by flow cytometry was not affected,and it was also proved that the polymer is suitable for many metal ions and aptamers.Finally,six aptamer-mass tags were combined to realize the molecular profiling and differentiation of CEM and Ramos cells.(2)In Chapter 3,we tested the binding ability of multiple aptamers to CEM and Ramos cells by flow cytometry,and finally 15 aptamers suitable for molecular profiling were selected.We then attached each of the 15 aptamers to a polymer chelated with different metal ions,enabling them to be used for mass cytometry detection.The 15 aptamer-mass tags were used to achieve molecular profiling of 8 hematological malignancy cell lines,and the 8 cell lines were distinguished by vi SNE analysis and unsupervised principal component analysis.Finally,aptamers were combined with antibodies to realize the molecular profiling of clinical samples of hematological malignancy.(3)In Chapter 4,we use machine learning algorithm to classify the test results of clinical samples,aiming to improve the accuracy of disease classification.First,we calculate the importance of each aptamer in classification.According to the calculation results,we use partial least squares discriminant analysis(PLS-DA)to build 20 different models and select the best model.Then,ten-fold cross-validation and receiver operating characteristic curve(ROC)were used to analyze the performance of the model and the results showed that the model has excellent performance.Finally,we collected new clinical samples and input the mass cytometry detection results into the model.It got good classification results.(4)In Chapter 5,we improved the synthesis of polymers and new polymer was designed and synthesized for aptamer.The optimal aptamer-polymer was obtained by adjusting the ratio of initiator and catalyst and the ratio of aptamer to polymer,and purified by high performance liquid chromatography.At the same time,we demonstrated its targeting ability by flow cytometry,and it is also verified that this designed polymer is suitable for a variety of metal ions and aptamers,demonstrating the potential of aptamer-mass tags in the field of mass cytometry.