Abstract
Abstract Advancement in the diagnosis and surveillance of gliomas has been limited posing both diagnostic and therapeutic challenges. Definitive diagnosis, distinction of progression versus pseudoprogression and prognosis assessment still depend on invasive neurosurgical biopsy procedure. Minimally-invasive plasma sampling could minimize the risks associated with invasive tissue sampling. Therefore, we aimed to identify specific plasma protein patterns of low- and high-grade glioma patients, compared to healthy individuals and investigated whether different plasma-derived protein signatures were associated with survival in glioma patients. Plasma samples were from patients with glioma grades I to IV collected during tumor removal and from healthy controls donating blood were processed for Liquid Chromatography Mass Spectrometry (LC/MS) proteomics after depletion of the 14 most abundant plasma proteins, in order to specifically detect low-abundant tumor-derived proteins. Overall, 646 proteins were measured across 104 plasma samples from glioma patients and 57 plasmas from the healthy cohort. PCA showed 2 clusters of samples, one containing low- and high-grade glioma samples and the other containing healthy and some grade IV (GBM) plasma samples. Interestingly, a spatial analysis of tumor location by MRI associated the GBM samples separated from healthy samples with subventricular vicinity. 26 differentially expressed proteins (DEPs) were identified discriminating between glioma and healthy samples and 30 DEPs discriminating GBM and healthy samples. The top most overexpressed proteins in gliomas vs controls were SERPINA3, F13A1, and TKT. Multivariate analysis identified SERPINA3, PPBP and MYH9 as strong discriminators of healthy vs GBM but also of low-grade vs GBM, indicating that these proteins may represent specific plasma biomarkers for GBM. SERPINA3, MYL1 and CLU were associated with poor survival in GBM. In conclusion, we describe sets of plasma derived proteins, in particular SERPINA3, as predictive biomarkers that could be used to assess tumor progression allowing patient-centered treatment options.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
