Screening Serological Diagnosis Of Meningioma Based On Proteomic Techniques Studies On Potential Biomarkers

Background:Meningioma is one of the most common tumors in the central nervous system.Meningioma accounts for approximately one-third of intracranial tumors.It is common in women,rare in children,and prevalent in middle-aged and elderly people.The incidence,underdiagnosis and mortality of meningioma are increasing year by year,and the quality of patients’ life can be affected seriously.Therefore,it is important to effectively detect and diagnose meningiomas at an early stage.Patients can receive early treatment.At present,The clinical diagnosis of meningioma relies on clinical symptoms,imagingand postoperative pathological examination.However,these findings have led to a low rate of early diagnosis of meningioma,so there is an urgent need to find markers that can diagnose meningioma at an early stage.Proteomics can combine high-resolution protein isolation technology and efficient protein identification technology to study the science of life phenomena and patterns holistically,dynamically and quantitatively at the protein level,while mass spectrometrybased proteomics technology can detect protein expression differences in different tissue samples faster and more accurately,and also determine the localization and role of proteins,and ultimately their functions.The combination of these technologies provides a powerful technical support and research platform for the screening and identification of multiple tumor markers.And it helps to develop real-time clinical biomarkers for tumors.Proteomic analysis of biological specimens has been found to provide information for the study of disease pathobiology and the identification of potential alternative markers in different types of brain tumors.Serum protein biomarkers can be considered as promising candidates in the search for diagnostic alternatives to clinical symptoms and imaging and histopathological examination of meningiomas.Methods:1.Total serum proteins from healthy controls and meningioma patients were isolated and purified by Pur Mag i Mac-Cu,and the extracted total serum proteins were detected by Matrix-assisted laser desorption ion time-of-flight mass spectrometry(MALDI-TOF/MS).The detected different expression peaks were analyzed by Clin Pro Tools software,Graphpad Prism 7.0 software and Flex Analysis version 3.0software.2.A genetic algorithm(GA)was used to build a diagnostic prediction model for meningioma using Clin Pro Tools software.3.Serum differentially expressed peptides from healthy controls and meningioma patients were identified by liquid chromatography-electrospray ionization tandem mass spectrometry(LC-ESI-MS/MS),searched with Sequest and Proteome Discoverer 2.5.0(Thermo Scientific),and retrieved in the Uniprot database using Maxquant software.Results:1.In the mass-to-charge ratio range of 800-10000 Da,a total of 70 expression peaks were identified in the serum protein mass spectra of healthy controls and meningioma patients,37 of which were significantly different(P<0.05).Among them,17 peaks were elevated in meningioma patients and 20 peaks were decreased in meningioma patients.Eight of these 37 peaks were significantly different(P<0.0001):m/z:811.55,m/z:899.69,m/z:1042.66,m/z:1947.39,which were elevated in meningioma patients’ sera and decreased in healthy subjects’ sera,including m/z:4823.13,m/z:4534.97,m/z:3374.97,m/z:3446.32 were elevated in the sera of healthy individuals and decreased in the sera of meningioma patients.2.Using Clin Pro Tools software,a genetic algorithm(GA)was used to build a diagnostic prediction model for meningioma.This model contained three mass spectral peaks,in which,m/z:899.69 was up-regulated in meningioma,m/z:4823.13 and m/z:4271.89 were down-regulated in meningioma.The sensitivity and specificity of this model for the diagnosis of meningioma were 89.01% and 97.22%,Further independent samples were blinded to verify the sensitivity and specificity of this model for the diagnosis of meningioma were 83.33%(15/18)and 77.78%(14/18),with a Youden index of 61.11.3.The four peaks with the most significant differences(>1.5-fold)between healthy controls and meningioma patients were identified as insulin-like growth factor binding protein 4(IGFBP4,m/z:811.55),complement 3(C3,m/z:899.69),apolipoprotein A2(APOA2,m/z:1042.66),ezrin,the cytoskeleton-linked protein(EZR,m/z:1947.39).Conclusions:1.serum protein mass spectra of healthy controls and meningioma patients were significantly different,and mass spectrometry-based proteomics studies are effective methods for screening and identification of meningioma markers.2.The diagnostic prediction model of meningioma can provide a reference for early diagnosis of meningioma to some extent.3.IGFBP4,C3,APOA2,EZR are potential serum protein markers for meningioma screening and diagnosis.