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| Author(s): |
Júlia Nicoliello Pereira de Castro
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | Campinas, SP. |
| Institution: | Universidade Estadual de Campinas (UNICAMP). Faculdade de Ciências Médicas |
| Defense date: | 2023-12-14 |
| Examining board members: |
Mônica Barbosa de Melo;
Robson Franscisco Carvalho;
Magnun Nueldo Nunes dos Santos
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| Advisor: | Mônica Barbosa de Melo; Sueli Matilde da Silva Costa |
| Abstract | |
Sickle cell anemia (SCA) is a hemoglobinopathy that results from a single homozygous mutation in the seventh codon of the beta-globin gene. However, there is extensive clinical variability with systemic involvement. Neurological alterations are common, and are related to the severity of the disease, fatal in 15% of cases, with ischemic stroke (IS) as the main complication. Erythrocyte sickling is the primary event in the pathophysiology of the disease. The consequence is a vasculopathy, which results in hemolysis, inflammation, endothelial activation, and vasoconstriction, contributing to ischemic events. In this context, the role of the vascular endothelium in the cascade of events leading to this phenotype is emphasized, as well as in the process of ischemia-induced repair and neovascularization. Thus, the gene expression analysis of endothelial cells can contribute to the understanding of the molecular pathways involved. The main objective of this study was to perform a comparative analysis, through RNA-Seq, of the gene expression profile of colony-forming endothelial cells (CEFCs) cultured from peripheral blood of individuals with SCA, divided into groups with and without IS. After quality analysis (FastQC software) and transcript alignment and assembly (STAR software), the identification of read counts (Rsubread package) and differential gene expression analysis (edgeR package) were performed in the Rstudio environment. Subsequently, gene ontology (GO) in silico analysis was conducted using DAVID online tool. Additionally, Cytoscape software was used to construct a protein interaction network (PPI), and cytohubba plugin was employed to identify the "hub-genes" of the main network. Prediction of transcription factors (TFs) as potential regulators of gene expression was performed using the online tool Expression2Kinases (X2K). Additionally, The Human Protein Atlas (THPA) secretome database was utilized to identify upregulated differentially expressed genes (DEGs) encoding potentially secreted proteins (PSPs). After obtaining the DEGs related to PSPs, functional enrichment was conducted using the online tool EnrichR. A total of 2,469 DEGs were identified. The top 5 hub genes in the PPI network were AKT1, HRAS, PI3KR1, CDC20, and MAPK11. In the prediction of TFs, E2F1 and IRF3 genes are differentially expressed. Among the upregulated DEGs, 129 encodes PSPs. We highlight MMP1, EGFL7, and TGFB1. Finally, the genes AKT1 and HRAS (overall analysis) and EGFL7 and MMP1 (secretome-based on transcriptome) were selected for validation by qRT-PCR, and the genes HRAS and MMP1 were validated. The main genes obtained are involved in proliferation, migration, immune response, and angiogenesis cascades, which are relevant pathways for the pathogenesis and repair of IS in SCA. Therefore, the present study provides an exploratory analysis of the mechanisms involved in this severe cerebrovascular complication, and may enable the identification of biomarkers, as well as new therapeutic strategies (AU) | |
| FAPESP's process: | 21/14089-0 - Evaluation of gene expression profile of endothelial progenitor cells of patients with sickle cell anemia and stroke |
| Grantee: | Júlia Nicoliello Pereira de Castro |
| Support Opportunities: | Scholarships in Brazil - Master |