RÉSUMÉ
BACKGROUND:Due to the sudden release and the rapid removal by proteases,platelet-rich plasma hydrogel leads to shorter residence times of growth factors at the wound site.In recent years,researchers have focused on the use of hydrogels to encapsulate platelet-rich plasma in order to improve the deficiency of platelet-rich plasma hydrogels. OBJECTIVE:To prepare self-assembled polypeptide-platelet-rich plasma hydrogel and to explore its effects on the release of bioactive factors of platelet-rich plasma. METHODS:The self-assembled polypeptide was synthesized by the solid-phase synthesis method,and the solution was prepared by D-PBS.Hydrogels were prepared by mixing different volumes of polypeptide solutions with platelet-rich plasma and calcium chloride/thrombin solutions,so that the final mass fraction of polypeptides in the system was 0.1%,0.3%,and 0.5%,respectively.The hydrogel state was observed,and the release of growth factors in platelet-rich plasma was detected in vitro.The polypeptide self-assembly was stimulated by mixing 1%polypeptide solution with 1%human serum albumin solution,so that the final mass fraction of the polypeptide was 0.1%,0.3%,and 0.5%,respectively.The flow state of the liquid was observed,and the rheological mechanical properties of the self-assembled polypeptide were tested.The microstructure of polypeptide(mass fraction of 0.1%and 0.001%)-human serum albumin solution was observed by scanning electron microscope and transmission electron microscope. RESULTS AND CONCLUSION:(1)Hydrogels could be formed between different volumes of polypeptide solution and platelet-rich plasma.Compared with platelet-rich plasma hydrogels,0.1%and 0.3%polypeptide-platelet-rich plasma hydrogels could alleviate the sudden release of epidermal growth factor and vascular endothelial growth factor,and extend the release time to 48 hours.(2)After the addition of human serum albumin,the 0.1%polypeptide group still exhibited a flowing liquid,the 0.3%polypeptide group was semi-liquid,and the 0.5%polypeptide group stimulated self-assembly to form hydrogel.It was determined that human serum albumin in platelet-rich plasma could stimulate the self-assembly of polypeptides.With the increase of the mass fraction of the polypeptide,the higher the storage modulus of the self-assembled polypeptide,the easier it was to form glue.(3)Transmission electron microscopy exhibited that the polypeptide nanofibers were short and disordered before the addition of human serum albumin.After the addition of human serum albumin,the polypeptide nanofibers became significantly longer and cross-linked into bundles,forming a dense fiber network structure.Under a scanning electron microscope,the polypeptides displayed a disordered lamellar structure before adding human serum albumin.After the addition of human serum albumin,the polypeptides self-assembled into cross-linked and densely arranged porous structures.(4)In conclusion,the novel polypeptide can self-assemble triggered by platelet-rich plasma and the self-assembly effect can be accurately adjusted according to the ratio of human serum albumin to polypeptide.This polypeptide has a sustained release effect on the growth factors of platelet-rich plasma,which can be used as a new biomaterial for tissue repair.
RÉSUMÉ
Objective:To identify and screen the differential methylation genes in patients with cholangiocarcinoma and to predict the prognosis of patients with CCA.Methods:Cholangiocarcinoma tissues and paracancerous tissues of 8 patients with cholangiocarcinoma in Fujian Provincial Hospital from October 2019 to May 2020 were selected for 850K methylation sequencing analysis to obtain differentially methylated genes. The 2018 genome-wide methylation data and clinical information of 36 patients with cholangiocarcinoma were download from The Cancer Genome Atlas (TCGA) database, the 2012 cholangiocarcinoma methylation data (GSE32879) were download from the Gene Expression Omnibus (GEO) database, and the 2018 TCGA database differential survival genomic data of overall survival (OS) and disease-free survival (DFS) of cholangiocarcinoma were download from the GEPIA2 database. The differentially methylated positions (DMP) and differentially methylated regions (DMR) results of 850K methylation sequencing analysis of submitted samples, methylated genes in TCGA and GEO databases, and cholangiocarcinoma survival genes of samples were jointly submitted for testing, multi-data set analysis was performed by the Sangerbox VENN tool, and common differentially methylated genes were obtained by intersection screening. The minimum P value method was used to determine the cut-off value of gene expression in Sangerbox, and the patients were divided into high and low expression groups of differentially methylated genes. The OS, DFS, disease-specific survival (DSS), disease-free interval (DFI) and progression-free interval (PFI) of cholangiocarcinoma patients were compared between the two groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. Results:A total of 121 954 DMP were identified by 850K methylation sequencing of cholangiocarcinoma tissues and paracancerous tissues of 8 patients; a total of 1 399 differentially methylated genes were identified in DMR, and the common prognosis related genes glucosaminyl (N-acetyl) transferase 1 (GCNT1) and neurotrophic receptor tyrosine kinase 3 (NTRK3) were identified by intersection identification. The expression of GCNT1 in the cholangiocarcinoma tissues was higher than that in the paracancerous tissues, and the difference was statistically significant ( P = 0.040). The expression of NTRK3 in cholangiocarcinoma tissues was higher than that in the paracancerous tissues, but the difference was not statistically significant ( P = 0.790). The minimum P value method was used to predict the prognosis of patients with cholangiocarcinoma based on the combined expression of GCNT1 and NTRK3, and the order was based on the sum of the expression levels of the two genes. When 30% of the ranking was taken as the cut-off value, the difference in DFS between the high expression group and the low expression group in cholangiocarcinoma was the most significant ( P < 0.001); there was no significant difference in OS between the two groups ( P = 0.065). The results of GO functional analysis showed that GCNT1 was involved in protein glycosylation, macromolecule glycosylation, glycosylation, glycoprotein biosynthetic process, glycoprotein metabolic process, transferase activity and transferring glycosyl groups, protein O-linked glycosylation, O-glycan processing, etc., and NTRK3 was involved in neurotrophin signaling pathway, Ras signaling pathway, EGFR tyrosine kinase inhibitor resistance, ErbB signaling pathway, phospholipase D signaling pathway, central carbon metabolism in cancer, natural killer cell mediated cytotoxicity, etc. The results of KEGG analysis showed that GCNT1 was mainly associated with system functions such as mucin-type O-glycan biosynthesis and metabolic pathways, and NTRK3 was mainly associated with cell surface receptor pathways, intracellular signal transduction, positive regulation of stimulatory responses, transmembrane receptor protein tyrosine kinase signaling pathway, enzyme-linked receptor protein signaling pathway, MAPK signaling pathway cascade and regulation, protein phosphorylation signal transduction and other system functions. Conclusions:The expressions of differentially methylated genes GCTNT1 and NTRK3 in cholangiocarcinoma have certain predictive effects on the prognosis of patients with cholangiocarcinoma.