AUTHOR=Qi Zhifeng , Yuan Shuhua , Zhou Xixi , Ji Xunming , Liu Ke Jian TITLE=Isobaric Tags for Relative and Absolute Quantitation-Based Quantitative Serum Proteomics Analysis in Ischemic Stroke Patients With Hemorrhagic Transformation JOURNAL=Frontiers in Cellular Neuroscience VOLUME=15 YEAR=2021 URL=https://www.frontiersin.org/journals/cellular-neuroscience/articles/10.3389/fncel.2021.710129 DOI=10.3389/fncel.2021.710129 ISSN=1662-5102 ABSTRACT=

Hemorrhagic transformation (HT), which occurs with or without reperfusion treatments (thrombolysis and/or thrombectomy), deteriorates the outcomes of ischemic stroke patients. It is essential to find clinically reliable biomarkers that can predict HT. In this study, we screened for potential serum biomarkers from an existing blood bank and database with 243 suspected acute ischemic stroke (AIS) patients. A total of 37 patients were enrolled, who were diagnosed as AIS without receiving reperfusion treatment. They were divided into two groups based on whether they were accompanied with HT or not (five HT and 32 non-HT). Serum samples were labeled by isobaric tags for relative and absolute quantitation (iTRAQ) and analyzed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) and compared under NCBInr database. A total of 647 proteins in sera samples were captured, and the levels of 17 proteins (12 upregulated and five downregulated) were significantly different. These differentially expressed proteins were further categorized with Gene Ontology functional classification annotation and Kyoto Encyclopedia of Genes and Genomes metabolic pathway analysis into biological processes. Further protein–protein interaction analysis using String database discovered that, among the differentially expressed proteins, 10 pairs of proteins were found to have crosstalk connections, which may have direct (physical) and indirect (functional) interactions for the development of HT. Our findings suggest that these differentially expressed proteins could serve as potential biomarkers for predicting HT after ischemic stroke.