| Cancer is one of the most difficult diseases for humans to overcome.To improve the overall survival rate of cancer patients,early detection and prognosis of tumor markers including circulating tumor cells(CTCs)have been recognized by experts.The research on circulating tumor cells is divided into two parts: enrichment and detection.The traditional enrichment method is to combine Ep CAM(Epithelial cell adhesion molecule)on the surface of circulating tumor cells with immune nanomagnetic nanoparticles.But not all circulating tumor cells contain Ep CAM,and sometimes the Ep CAM could be loss when tumor cells enter the blood As a traditional method,immunofluorescence staining is used to count the CTCs based on cell fluorescence However,this method can cause damage on viability of CTCs,limiting the downstream analysis.The method based on immunofluorescence staining is also unable to identify the subtype of circulating tumor cells.To improve the shortcomings of traditional enrichment and detection methods,this paper developed a CTC manipulation method based on 3D printed microfluidic chip and a tumor cell detection method based on Raman spectroscopy.The research in this thesis includes:(1)by comparison the fabrication of the test models,a commercial 3D printer that optimally prepares microfluidic chips;(2)3D printing of largesized microfluidic chips to achieve inertial focusing of tumor cells;(3)proposed a novel Raman spectrum splitting algorithm,so that different tumor cell subtypes and different tumor extracellular vesicles can be effectively classified;(4)studied the optimal engineering method of removing support materials of microfluidic chips,for chip mass production.Specific work was described as following.Firstly,the principle and performance of four common 3D printing methods(inkjet printing,stereolithography,digital light projection,and fusion deposition modeling)were studied.For the four 3D printers,two test models,3D printer test model and a microfluidic test model were designed.The 3D printer test model is mainly used to test the printing performance of the printer,and the microfluidic channel test model is mainly used to test the performance of the four printers on different microfluidic channels.By comparing the printed test models,the inkjet printer Pro Jet 3600 HD has the best performance Therefore,the following serpentine microfluidic channels are printed by Pro Jet 3600 HD.Secondly,a 3D printed serpentine microfluidic channel was designed to achieve inertial focusing of tumor cells within the channel.The forces acted on the particles in the serpentine channel were theoretically analyzed.When the channel section size becomes larger,two physical quantities(flow velocities and curvatures of the serpentine channel)need to be changed.Then,the focus state of the small particles at the outlet of the microfluidic channel when the curvature radius and the flow velocity are changed is simulated by COMSOL software,and the focus state is divided into six categories.The microfluidic chip with the optimal curvature radius(r = 5.9 mm)was printed,and the experimental results of different flow rates were compared with the simulation results.Finally,the optimal focusing conditions(r = 5.9 mm,v = 0.1 m / s)were used to perform experiments using tumor cells(4T1 and MCF-7),and the tumor cells in the microfluidic channel were well inertial focused.The Raman spectra of different tumor cells are measured and classified by machine learning algorithms.(1)The Raman spectrum classification of different breast cancer cell subtypes was studied.First,four breast cancer cell subtypes(Luminal A,Luminal B,non-luminal HER-2 positive and triple negative)and a normal breast cell were measured.The Raman spectrum of the cell can be classified through three steps of preprocessing.The peak position,peak intensity,half-peak width,and peak area of the 13 peaks of each spectrum can be obtained by peak searching and peak splitting algorithm.Finally,the support vector machine was used to classify different breast cancer cell subtypes and normal breast cells and to classify the five cells.The highest accuracy between two subtype cell classifications was 96.8 %.The accuracy of the five cell classifications was 72.35 %.(2)The Raman spectra of tumor extracellular vesicles and normal extracellular vesicles were measured.Extracellular vesicles were isolated from the cell culture medium using the polyethylene glycol method.A biocompatible Raman enhancement material was synthesized,and its enhancement factor was characterized.Four different extracellular cells were measured.The enhanced Raman spectrum of vesicles and the classification of different extracellular vesicles using the PCASVM algorithm achieved a classification accuracy rate of more than 85 %.It was found in the research that if Pro Jet 3600 HD is used for mass production of microfluidic chips,the engineering method of microfluidic chip post-processing needs to be studied.For microfluidic chips printed by Pro Jet 3600 HD,there are two types of external support materials and internal support materials.Quantitative methods are proposed for the two supporting materials.For external support materials,this article proposes a mass loss rate based on the reduction in mass to evaluate the removal rate of external support materials.For internal support materials,this article proposes a light transmittance based on the opaque nature of the support materials to evaluate the removal of internal support materials.effectiveness.According to the quantification method of external support material,four removal methods of external support material were studied,and the optimal removal method was obtained.According to the internal support material quantification method,the effects of different removers,different temperatures,and different removal times on the support materials were studied,and the optimal engineering and removal conditions for removing 10 minutes of edible oil at 70 °C were obtained.In order to improve the shortcomings of traditional circulating tumor cell enrichment methods,the advantages and disadvantages of microfluidic chips prepared by different commercial 3D printers were studied,and the inertial focusing of cells in 3D printing largescale microfluidic chips was achieved.To improve the shortcomings of traditional circulating tumor cell detection methods,a peak splitting algorithm was proposed to complete the effective classification of Raman spectra of different breast cancer cell subtypes,cancer cells and normal extracellular vesicles.To solve the problem of mass production of 3D printed microfluidic chips,a quantitative method was proposed to obtain the optimal engineering support material removal conditions.In summary,the basic work of using 3D printed microfluidic chips and Raman spectroscopy to detect circulating tumor cells has been completed,laying the foundation for an integrated detection platform for circulating tumor cells using 3D printed microfluidic chips. |
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