Proteomics Study Of Gastric Adenocarcinoma Based On Mass Spectrometry

ObjectiveGastric adenocarcinoma is one of the common malignant tumors of the digestive tract and has been a serious threat to human health.Because gastric adenocarcinoma is biologically and genetically heterogeneous,and the clinical symptoms of patients are not obvious,the treatment is already in advanced or advanced stage,so the treatment effect is poor.At present,the screening and diagnosis strategies for gastric adenocarcinoma are still unable to meet the demand,so finding simple and effective screening and auxiliary diagnosis methods has high application value for clinical practice.This study is based on mass spectrometry for serum and tissue proteomics research of gastric adenocarcinoma.It is proposed to establish a serum diagnostic prediction model for gastric adenocarcinoma,identify differential proteins/peptides of the model,and perform in situ protein characterizeation an alysis of gastric adenocarcinoma tissues and adjacent tissues.It is intended to search for serum and tissue new tumor markers of gastric adenocarcinoma,providing new strategies and new directions for screening and pathologically assisted diagnosis of high-risk populations of gastric adenocarcinoma.Methods1.Serum samples were collected from 60 patients with gastric adenocarcinoma confirmed by histopathology were collected,and 60 serum specimens of healthy persons in the same period in the physical examination center.The low-abundance protein of the above se rum samples were enriched by weak cation magnetic beads（WCX-MB）and analyzed by MALDI-TOF MS.The differential protein/peptide peaks were screened by statistical methods（P<0.05）.A series of bioinformatics software for data integration analysis,using GA,SNN,QC three mathematical algorithms to establish a diagnostic model for gastric adeno-carcinoma.Finally,the validation group was used to evaluate the performance of the diagnostic prediction model,and the sensitivity,specificity and accuracy of the model were obtained.2.Serum samples were collected from 21 patients with gastric adenocarcinoma who received surgical treatment 20-35 days after surgery,and the preoperative serum was collected as the basic data.Similarly,the above methods were used for detection and analys is to screen the preoperative and postoperative differentially expressed protein/peptide peaks of patients with gastric adenocarcinoma and compare them with the differentially expressed protein/peptide peaks of the predictive model for gastric adenocarcinoma diagnosis,so as to find the specific difference peaks that are expected to be potential serum tumor markers for gastric adenocarcinoma.3.30serum samples of gastric adenocarcinoma with high expression of target protein/polypeptide were selected for protein identification and function prediction by liquid chro-matography-electrospray ionization mass spectrometry（LC-ESI-MS/MS）.By weak cationi-c magnetic beads（WCX-MB）extraction low abundance proteins/peptides,and use within the protein enzyme（trypsin）will be mixed protein solution for digested peptides mixture,using the LC-ESI-MS/MS detection peptides,enzyme solution to get peptides secondary mass spectrogram,the Maxquant search Uniprot KB human database software,to predict the amino acid sequence of peptides,than in the database of protein amino acid sequence and protein target information is obtained.Finally,GO analysis was performed on the differential proteins and protein interaction network diagram was constructed.4.Fresh gastric adenocarcinoma tissues and their matched paracancerous tissues were collected from 8 patients undergoing radical resection of gastric cancer.MALDI-IMS technology was used to scan and detect the protein molecules related to gastric adenocarcinoma,and protein spectra of different tissues were obtained.All the mass spectra data were smoothed,aligned and normalized by SCi LS Lab software,and a complete mass spectra was obtained.Results1.By comparing the serum protein spectra of gastric adenocarcinoma patients and healthy people,26 protein/polypeptide peaks with statistical significance（P<0.05）were screened after analysis,and three predictive models of gastric adenocarcinoma diagnosis（GA,SNN,QC）were established by using the differential peaks.Among them,the GA model had the best efficacy,sensitivity 93.30%,specificity 96.70%,and accuracy 90.00%.This model includes 20 protein/polypeptide peaks,and the 6 AUC^ROC values greater than 0.8 in the model have a reliable significance for the differentiation between gastric adenocarcinoma patients and healthy people.2.Eleven protein/peptide peaks with statistically significant differences（P<0.05）were screened by preoperative and postoperative serum differential protein/peptide spectra a-nalysis of patients with gastric adenocarcinoma.Compared with GA model,4 specific peaks of difference（m/z 2088.31,2661.01,2952.57 and 5904.36）were finally screened.These peaks showed significant differences between the gastric adenocarcinoma group and the healthy group,as well as between the preoperative and postoperative groups of gastric adenocarcinoma patients（P<0.05）,and the protein/peptide they represented was expected to be a potential serum tumor marker for gastric adenocarcinoma.3.The peptides were detected by LC-ESI-MS/MS,and the human database Uniprot-KB was searched by Maxquant software to predict the amino acid sequence of the peptides.The six different peaks with AUC^ROC value greater than 0.8 in the GA model were used for protein matching in a"bottom-up"manner.Among them,5 protein/polypeptide peaks m/z1617.44,2088.31,2105.46,2486.78 and 2952.57 were matched as transferrin,Serpin A1,complement C3,copper-blue protein and complement C3,respectively.The protein/peptide peaks m/z 2088.31,2661.01,2952.57 and 5904.36 of the potential gastric adenocarcinoma serum markers were only matched with two of them.The predicted difference peak m/z2088.31 was Serpin A1.The predicted difference peak m/z2952.57 was complement C-3.Serpin A1 and complement C3 can promote the development of gastric adenocarcinoma.4.Through MALDI-IMS analysis of fresh gastric adenocarcinoma tissues and adjac-ent tissues,four protein peaks with statistical differences（P<0.05）were screened,inclu-ding m/z 4151.239,4962.588,5005.679 and 5700.083,which could be used to distinguish the two kinds of tissues.Which m/z 4962.588,5005.679,5700.083,in gastric adenocarcinoma tissue increased,4151.219 in the tissue adjacent to carcinoma high expression,and in the form of mass spectrum image of in situ characterization of the four different peaks in the tissue adjacent to carcinoma tissues and the spatial distribution,by searching the imag-ing protein database Ma Tisse,m/z 4962.588,5005.679,matching for the same kind of protein molecules thymosin beta 4,5700.083 m/z matches for histone H2,m/z 4151.239 matching to albumin.Conclusions1.The diagnostic model of gastric adenocarcinoma established by GA algorithm can accurately distinguish patients with gastric adenocarcinoma and healthy people,and can be used for screening and assisting diagnosis of high-risk population of gastric adenocarcinoma.Provides a new high-throughput cancer detection strategy for gastric adenocarcinoma screening.2.The protein/peptide represented by serum mass spectrum peak m/z 2088.31,2661.01,2952.57,and 5904.36 is closely related to the development of gastric adenocarcinoma.3.By LC-ESI-MS/MS analysis,the predicted proteins Serpin A1 and complement C3can promote the development of tumors.They are expected to be potential serum tumor markers of gastric adenocarcinoma,which can be used for the diagnosis and postoperative evaluation of gastric adenocarcinoma.Provide new reference indicators.4.MALDI-IMS technology can be used to characterize the spatial distribution of differentially expressed molecules in situ without markers,and the two proteins,thymosin4 and histone H2A 2-a,matched by imaging database,may be potential tissue markers for gastric adenocarcinoma.MALDI-IMS assists in the diagnosis of tumors at the molecular level of the protein and graphically displays the molecular information in the tissue,providing a new development direction for the auxiliary molecular pathology diagnosis.