Skip to main content

Advertisement

SpringerLink
Log in

Comparative transcriptomic analysis of circulating endothelial cells in sickle cell stroke

  • Original Article
  • Published:
Annals of Hematology Aims and scope Submit manuscript

Abstract

Ischemic stroke (IS) is one of the most impairing complications of sickle cell anemia (SCA), responsible for 20% of mortality in patients. Rheological alterations, adhesive properties of sickle reticulocytes, leukocyte adhesion, inflammation and endothelial dysfunction are related to the vasculopathy observed prior to ischemic events. The role of the vascular endothelium in this complex cascade of mechanisms is emphasized, as well as in the process of ischemia-induced repair and neovascularization. The aim of the present study was to perform a comparative transcriptomic analysis of endothelial colony-forming cells (ECFCs) from SCA patients with and without IS. Next, to gain further insights of the biological relevance of differentially expressed genes (DEGs), functional enrichment analysis, protein–protein interaction network (PPI) construction and in silico prediction of regulatory factors were performed. Among the 2469 DEGs, genes related to cell proliferation (AKT1, E2F1, CDCA5, EGFL7), migration (AKT1, HRAS), angiogenesis (AKT1, EGFL7) and defense response pathways (HRAS, IRF3, TGFB1), important endothelial cell molecular mechanisms in post ischemia repair were identified. Despite the severity of IS in SCA, widely accepted molecular targets are still lacking, especially related to stroke outcome. The comparative analysis of the gene expression profile of ECFCs from IS patients versus controls seems to indicate that there is a persistent angiogenic process even after a long time this complication has occurred. Thus, this is an original study which may lead to new insights into the molecular basis of SCA stroke and contribute to a better understanding of the role of endothelial cells in stroke recovery.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Kato GJ, Piel FB, Reid CD et al (2018) Sickle cell disease. Nat Rev Dis Primers 4:18010. https://doi.org/10.1038/nrdp.2018.10

    Article  PubMed  Google Scholar 

  2. Balkaran B, Char G, Morris JS et al (1992) Stroke in a cohort of patients with homozygous sickle cell disease. J Pediatr 120:360–366. https://doi.org/10.1016/S0022-3476(05)80897-2

    Article  CAS  PubMed  Google Scholar 

  3. Ohene-Frempong K, Weiner SJ, Sleeper LA et al (1998) Cerebrovascular accidents in sickle cell disease: rates and risk factors. Blood 91:288–294

    CAS  PubMed  Google Scholar 

  4. Driscoll MC (2003) Stroke risk in siblings with sickle cell anemia. Blood 101:2401–2404. https://doi.org/10.1182/blood.V101.6.2401

    Article  CAS  PubMed  Google Scholar 

  5. Adams R, McKie V, Nichols F et al (1992) The use of transcranial ultrasonography to predict stroke in sickle cell disease. N Engl J Med 326:605–610. https://doi.org/10.1056/NEJM199202273260905

    Article  CAS  PubMed  Google Scholar 

  6. Adams RJ (2013) Toward a stroke-free childhood in sickle cell disease. Stroke 44:2930–2934. https://doi.org/10.1161/STROKEAHA.113.001312

    Article  PubMed  Google Scholar 

  7. Adams RJ, McKie VC, Hsu L et al (1998) Prevention of a first stroke by transfusions in children with sickle cell anemia and abnormal results on transcranial doppler ultrasonography. N Engl J Med 339:5–11. https://doi.org/10.1056/NEJM199807023390102

    Article  CAS  PubMed  Google Scholar 

  8. Ware RE, Davis BR, Schultz WH et al (2016) Hydroxycarbamide versus chronic transfusion for maintenance of transcranial doppler flow velocities in children with sickle cell anaemia—TCD with transfusions changing to hydroxyurea (TWiTCH): a multicentre, open-label, phase 3, non-inferiority trial. The Lancet 387:661–670. https://doi.org/10.1016/S0140-6736(15)01041-7

    Article  CAS  Google Scholar 

  9. Runge A, Brazel D, Pakbaz Z (2022) Stroke in sickle cell disease and the promise of recent disease modifying agents. J Neurol Sci 442:120412. https://doi.org/10.1016/j.jns.2022.120412

    Article  CAS  PubMed  Google Scholar 

  10. Liao S, Luo C, Cao B et al (2017) Endothelial progenitor cells for ischemic stroke: update on basic research and application. Stem Cells Int 2017:1–12. https://doi.org/10.1155/2017/2193432

    Article  CAS  Google Scholar 

  11. Moubarik C, Guillet B, Youssef B et al (2011) Transplanted late outgrowth endothelial progenitor cells as cell therapy product for stroke. Stem Cell Rev Rep 7:208–220. https://doi.org/10.1007/s12015-010-9157-y

    Article  PubMed  Google Scholar 

  12. Rakkar K, Othman O, Sprigg N et al (2020) Endothelial progenitor cells, potential biomarkers for diagnosis and prognosis of ischemic stroke: protocol for an observational case-control study. Neural Regen Res 15:1300. https://doi.org/10.4103/1673-5374.269028

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Yan F, Liu X, Ding H, Zhang W (2022) Paracrine mechanisms of endothelial progenitor cells in vascular repair. Acta Histochem 124:151833. https://doi.org/10.1016/j.acthis.2021.151833

    Article  CAS  PubMed  Google Scholar 

  14. Shirota T, He H, Yasui H, Matsuda T (2003) Human endothelial progenitor cell-seeded hybrid graft: proliferative and antithrombogenic potentials in vitro and fabrication processing. Tissue Eng 9:127–136. https://doi.org/10.1089/107632703762687609

    Article  CAS  PubMed  Google Scholar 

  15. Alwjwaj M, Kadir RA, Bayraktutan U (2021) The secretome of endothelial progenitor cells: a potential therapeutic strategy for ischemic stroke. Neural Regen Res 16:1483. https://doi.org/10.4103/1673-5374.303012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Hur J, Yoon C-H, Kim H-S et al (2004) Characterization of two types of endothelial progenitor cells and their different contributions to neovasculogenesis. Arterioscler Thromb Vasc Biol 24:288–293. https://doi.org/10.1161/01.ATV.0000114236.77009.06

    Article  CAS  PubMed  Google Scholar 

  17. Ito MT, da Silva Costa SM, Baptista LC, et al (2020) Angiogenesis-related genes in endothelial progenitor cells may be involved in sickle cell stroke. J Am Heart Assoc 9(3):e014143. https://doi.org/10.1161/JAHA.119.014143

  18. de Bertozzo VHE, da Silva Costa SM, Ito MT et al (2023) Comparative transcriptome analysis of endothelial progenitor cells of HbSS patients with and without proliferative retinopathy. Exp Biol Med 248:677–684. https://doi.org/10.1177/15353702231157927

    Article  CAS  Google Scholar 

  19. Banno K, Yoder MC (2018) Tissue regeneration using endothelial colony-forming cells: promising cells for vascular repair. Pediatr Res 83:283–290. https://doi.org/10.1038/pr.2017.231

    Article  CAS  PubMed  Google Scholar 

  20. Flanagan JM, Frohlich DM, Howard TA et al (2011) Genetic predictors for stroke in children with sickle cell anemia. Blood 117:6681–6684. https://doi.org/10.1182/blood-2011-01-332205

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Amlie-Lefond C, Flanagan J, Kanter J, Dobyns WB (2018) The genetic landscape of cerebral steno-occlusive arteriopathy and stroke in sickle cell anemia. J Stroke Cerebrovasc Dis 27:2897–2904. https://doi.org/10.1016/j.jstrokecerebrovasdis.2018.06.004

    Article  PubMed  Google Scholar 

  22. Flanagan JM, Sheehan V, Linder H et al (2013) Genetic mapping and exome sequencing identify 2 mutations associated with stroke protection in pediatric patients with sickle cell anemia. Blood 121:3237–3245. https://doi.org/10.1182/blood-2012-10-464156

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Lee J-M, Fernandez-Cadenas I, Lindgren AG (2021) Using human genetics to understand mechanisms in ischemic stroke outcome: from early brain injury to long-term recovery. Stroke 52:3013–3024. https://doi.org/10.1161/STROKEAHA.121.032622

    Article  PubMed  PubMed Central  Google Scholar 

  24. Manzoni C, Kia DA, Vandrovcova J et al (2018) Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences. Brief Bioinform 19:286–302. https://doi.org/10.1093/bib/bbw114

    Article  CAS  PubMed  Google Scholar 

  25. Sakamoto TM, Lanaro C, Ozelo MC et al (2013) Increased adhesive and inflammatory properties in blood outgrowth endothelial cells from sickle cell anemia patients. Microvasc Res 90:173–179. https://doi.org/10.1016/j.mvr.2013.10.002

    Article  CAS  PubMed  Google Scholar 

  26. Lin Y, Weisdorf DJ, Solovey A, Hebbel RP (2000) Origins of circulating endothelial cells and endothelial outgrowth from blood. J Clin Investig 105:71–77. https://doi.org/10.1172/JCI8071

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Andrews S (2010) FastQC: a quality control tool for high throughput sequence data. In: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/. Accessed 15 Oct 2021

  28. Dobin A, Davis CA, Schlesinger F et al (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29:15–21. https://doi.org/10.1093/bioinformatics/bts635

    Article  CAS  PubMed  Google Scholar 

  29. Liao Y, Smyth GK, Shi W (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30:923–930. https://doi.org/10.1093/bioinformatics/btt656

    Article  CAS  PubMed  Google Scholar 

  30. RStudio Team (2021) RStudio: Integrated Development Environment for R. RStudio, PBC, Boston, MA. https://www.rstudio.com/

  31. Robinson MD, McCarthy DJ, Smyth GK (2010) <tt>edgeR</tt> : a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26:139–140. https://doi.org/10.1093/bioinformatics/btp616

    Article  CAS  PubMed  Google Scholar 

  32. Kolde R (2019) Pheatmap: pretty heatmaps. R package version 1.0.12. In: https://CRAN.Rproject.org/package=pheatmap. Accessed 28 Jul 2023

  33. Blighe K, Lun A (2021) PCAtools: PCAtools: everything principal components analysis. R package version 2.4.0. In: https://github.com/kevinblighe/PCAtools. Accessed 28 Jul 2023

  34. Blighe K, Rana S, Lewis M (2021) EnhancedVolcano: publication-ready volcano plots with enhanced colouring and labeling. R package version 1.10.0. In: https://github.com/kevinblighe/EnhancedVolcano. Accessed 28 Jul 2023

  35. Dennis G, Sherman BT, Hosack DA et al (2003) DAVID: database for annotation, visualization, and integrated discovery. Genome Biol 4:P3

    Article  PubMed  Google Scholar 

  36. Doncheva NT, Morris JH, Gorodkin J, Jensen LJ (2019) Cytoscape StringApp: network analysis and visualization of proteomics data. J Proteome Res 18:623–632. https://doi.org/10.1021/acs.jproteome.8b00702

    Article  CAS  PubMed  Google Scholar 

  37. Shannon P, Markiel A, Ozier O et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504. https://doi.org/10.1101/gr.1239303

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Chin C-H, Chen S-H, Wu H-H et al (2014) cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol 8:S11. https://doi.org/10.1186/1752-0509-8-S4-S11

    Article  PubMed  PubMed Central  Google Scholar 

  39. SankeyMATIC tool SankeyMATIC: a Sankey diagram builder for everyone. In: http://sankeymatic.com/. Accessed 3 Aug 2023

  40. Clarke DJB, Kuleshov MV, Schilder BM et al (2018) eXpression2Kinases (X2K) Web: linking expression signatures to upstream cell signaling networks. Nucleic Acids Res 46:W171–W179. https://doi.org/10.1093/nar/gky458

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Zhang ZG, Zhang L, Jiang Q, Chopp M (2002) Bone marrow-derived endothelial progenitor cells participate in cerebral neovascularization after focal cerebral ischemia in the adult mouse. Circ Res 90:284–288. https://doi.org/10.1161/hh0302.104460

    Article  CAS  PubMed  Google Scholar 

  42. Li J, Ma Y, Miao X-H et al (2021) Neovascularization and tissue regeneration by endothelial progenitor cells in ischemic stroke. Neurol Sci 42:3585–3593. https://doi.org/10.1007/s10072-021-05428-3

    Article  PubMed  Google Scholar 

  43. Somanath PR, Razorenova OV, Chen J, Byzova TV (2006) Akt1 in endothelial cell and angiogenesis. Cell Cycle 5:512–518. https://doi.org/10.4161/cc.5.5.2538

    Article  CAS  PubMed  Google Scholar 

  44. Hallstrom TC, Mori S, Nevins JR (2008) An E2F1-dependent gene expression program that determines the balance between proliferation and cell death. Cancer Cell 13:11–22. https://doi.org/10.1016/j.ccr.2007.11.031

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Ladu S, Calvisi DF, Conner EA et al (2008) E2F1 inhibits c-Myc-driven apoptosis via PIK3CA/Akt/mTOR and COX-2 in a mouse model of human liver cancer. Gastroenterology 135:1322–1332. https://doi.org/10.1053/j.gastro.2008.07.012

    Article  CAS  PubMed  Google Scholar 

  46. Chang L, Xi L, Liu Y et al (2018) SIRT5 promotes cell proliferation and invasion in hepatocellular carcinoma by targeting E2F1. Mol Med Rep 17:342–349. https://doi.org/10.3892/MMR.2017.7875

    Article  CAS  PubMed  Google Scholar 

  47. Chaussepied M, Ginsberg D (2004) Transcriptional regulation of AKT activation by E2F. Mol Cell 16:831–837. https://doi.org/10.1016/j.molcel.2004.11.003

    Article  CAS  PubMed  Google Scholar 

  48. Meng P, Ghosh R (2014) Transcription addiction: can we garner the Yin and Yang functions of E2F1 for cancer therapy? Cell Death Dis 5(8):e1360–e1360. https://doi.org/10.1038/cddis.2014.326

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Nishiyama T, Ladurner R, Schmitz J et al (2010) Sororin mediates sister chromatid cohesion by antagonizing Wapl. Cell 143:737–749. https://doi.org/10.1016/j.cell.2010.10.031

    Article  CAS  PubMed  Google Scholar 

  50. Nguyen M-H, Koinuma J, Ueda K et al (2010) Phosphorylation and activation of cell division cycle associated 5 by mitogen-activated protein kinase play a crucial role in human lung carcinogenesis. Cancer Res 70:5337–5347. https://doi.org/10.1158/0008-5472.CAN-09-4372

    Article  CAS  PubMed  Google Scholar 

  51. Xu J, Zhu C, Yu Y et al (2019) Systematic cancer-testis gene expression analysis identified CDCA5 as a potential therapeutic target in esophageal squamous cell carcinoma. EBioMedicine 46:54–65. https://doi.org/10.1016/j.ebiom.2019.07.030

    Article  PubMed  PubMed Central  Google Scholar 

  52. Shen A, Liu L, Chen H et al (2019) Cell division cycle associated 5 promotes colorectal cancer progression by activating the ERK signaling pathway. Oncogenesis 8:19. https://doi.org/10.1038/s41389-019-0123-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Chen H, Chen J, Zhao L et al (2019) CDCA5, transcribed by E2F1, promotes Oncogenesis by enhancing cell proliferation and inhibiting apoptosis via the AKT pathway in hepatocellular carcinoma. J Cancer 10:1846–1854. https://doi.org/10.7150/jca.28809

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Parker LH, Schmidt M, Jin S-W et al (2004) The endothelial-cell-derived secreted factor Egfl7 regulates vascular tube formation. Nature 428:754–758. https://doi.org/10.1038/nature02416

    Article  CAS  PubMed  ADS  Google Scholar 

  55. Campagnolo L, Leahy A, Chitnis S et al (2005) EGFL7 is a chemoattractant for endothelial cells and is up-regulated in angiogenesis and arterial injury. Am J Pathol 167:275–284. https://doi.org/10.1016/S0002-9440(10)62972-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Badiwala MV, Tumiati LC, Joseph JM, et al (2010) Epidermal growth factor-like domain 7 suppresses intercellular adhesion molecule 1 expression in response to hypoxia/reoxygenation injury in human coronary artery endothelial cells. Circulation 122(11 Suppl):S156–61. https://doi.org/10.1161/CIRCULATIONAHA.109.927715

  57. Gustavsson M, Mallard C, Vannucci SJ et al (2007) Vascular response to hypoxic preconditioning in the immature brain. J Cereb Blood Flow Metab 27:928–938. https://doi.org/10.1038/sj.jcbfm.9600408

    Article  CAS  PubMed  Google Scholar 

  58. Li Q, Cheng K, Wang A-Y et al (2019) microRNA-126 inhibits tube formation of HUVECs by interacting with EGFL7 and down-regulating PI3K/AKT signaling pathway. Biomed Pharmacother 116:109007. https://doi.org/10.1016/j.biopha.2019.109007

    Article  CAS  PubMed  Google Scholar 

  59. Schmidt M, Paes K, De Mazière A et al (2007) EGFL7 regulates the collective migration of endothelial cells by restricting their spatial distribution. Development 134:2913–2923. https://doi.org/10.1242/dev.002576

    Article  CAS  PubMed  Google Scholar 

  60. Soncin F (2003) VE-statin, an endothelial repressor of smooth muscle cell migration. EMBO J 22:5700–5711. https://doi.org/10.1093/emboj/cdg549

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Wu XY, Liu WT, Wu ZF et al (2016) Identification of HRAS as cancer-promoting gene in gastric carcinoma cell aggressiveness. Am J Cancer Res 6:1935–1948

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Li Q, Decker-Rockefeller B, Bajaj A, Pumiglia K (2018) Activation of Ras in the vascular endothelium induces brain vascular malformations and hemorrhagic stroke. Cell Rep 24:2869–2882. https://doi.org/10.1016/j.celrep.2018.08.025

    Article  CAS  PubMed  Google Scholar 

  63. Montaner J, Ramiro L, Simats A et al (2020) Multilevel omics for the discovery of biomarkers and therapeutic targets for stroke. Nat Rev Neurol 16:247–264. https://doi.org/10.1038/s41582-020-0350-6

    Article  PubMed  Google Scholar 

  64. Pepper MS (1997) Transforming growth factor-beta: vasculogenesis, angiogenesis, and vessel wall integrity. Cytokine Growth Factor Rev 8:21–43. https://doi.org/10.1016/S1359-6101(96)00048-2

    Article  CAS  PubMed  Google Scholar 

  65. Cheng X, Yang Y-L, Li W-H et al (2020) Cerebral ischemia-reperfusion aggravated cerebral infarction injury and possible differential genes identified by RNA-Seq in rats. Brain Res Bull 156:33–42. https://doi.org/10.1016/j.brainresbull.2019.12.014

    Article  CAS  PubMed  Google Scholar 

  66. Downward J (2009) A tumour gene’s fatal flaws. Nature 462:44–45. https://doi.org/10.1038/462044a

    Article  CAS  PubMed  ADS  Google Scholar 

  67. Tarassishin L, Suh H-S, Lee SC (2011) Interferon regulatory factor 3 plays an anti-inflammatory role in microglia by activating the PI3K/Akt pathway. J Neuroinflammation 8:187. https://doi.org/10.1186/1742-2094-8-187

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Vadas O, Burke JE, Zhang X, et al (2011) Structural basis for activation and inhibition of class I phosphoinositide 3-kinases. Sci Signal 4(195):re2. https://doi.org/10.1126/scisignal.2002165

  69. Thorpe LM, Spangle JM, Ohlson CE et al (2017) PI3K-p110α mediates the oncogenic activity induced by loss of the novel tumor suppressor PI3K-p85α. Proc Natl Acad Sci 114:7095–7100. https://doi.org/10.1073/pnas.1704706114

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  70. Chang Milbauer L, Wei P, Enenstein J et al (2008) Genetic endothelial systems biology of sickle stroke risk. Blood 111:3872–3879. https://doi.org/10.1182/blood-2007-06-097188

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Zhang SJ, Zhang H, Wei YJ et al (2006) Adult endothelial progenitor cells from human peripheral blood maintain monocyte/macrophage function throughout in vitro culture. Cell Res 16:577–584. https://doi.org/10.1038/sj.cr.7310075

    Article  CAS  PubMed  Google Scholar 

  72. Mikirova NA, Jackson JA, Hunninghake R et al (2009) Circulating endothelial progenitor cells: a new approach to anti-aging medicine? J Transl Med 7:106. https://doi.org/10.1186/1479-5876-7-106

    Article  PubMed  PubMed Central  Google Scholar 

  73. Ding D-C, Shyu W-C, Lin S-Z, Li H (2007) The role of endothelial progenitor cells in ischemic cerebral and heart diseases. Cell Transplant 16:273–284. https://doi.org/10.3727/000000007783464777

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank all the patients; the research staff of Human Genetics Laboratory, Center for Molecular Biology and Genetic Engineering, UNICAMP, Campinas, SP, Brazil and the Hematology and Hemotherapy Center, UNICAMP, Campinas, SP, Brazil.

Funding

This work was supported by FAPESP (Fundação de Amparo à Pesquisa do Estado de S. Paulo) [grant numbers: 2021/14089–0, 2014/00984–3, 2019/18886–1] and CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) [finance code 001].

Author information

Authors and Affiliations

  1. Laboratory of Human Genetics, Center for Molecular Biology and Genetic Engineering—CBMEG, Universidade Estadual de Campinas—UNICAMP, Campinas, São Paulo, 13083-875, Brazil

    Júlia Nicoliello Pereira de Castro, Sueli Matilde da Silva Costa, Ana Carolina Lima Camargo, Mirta Tomie Ito, Bruno Batista de Souza, Victor de Haidar e Bertozzo, Thiago Adalton Rosa Rodrigues & Mônica Barbosa de Melo

  2. Hematology and Hemotherapy Center, Universidade Estadual de Campinas—UNICAMP, Campinas, São Paulo, Brazil

    Carolina Lanaro, Dulcinéia Martins de Albuquerque, Roberta Casagrande Saez, Sara Teresinha Olalla Saad, Margareth Castro Ozelo & Fernando Ferreira Costa

  3. Neuroimaging Laboratory, Department of Neurology, Universidade Estadual de Campinas—UNICAMP, Campinas, São Paulo, Brazil

    Fernando Cendes

Authors
  1. Júlia Nicoliello Pereira de Castro
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sueli Matilde da Silva Costa
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ana Carolina Lima Camargo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mirta Tomie Ito
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Bruno Batista de Souza
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Victor de Haidar e Bertozzo
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Thiago Adalton Rosa Rodrigues
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Carolina Lanaro
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Dulcinéia Martins de Albuquerque
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Roberta Casagrande Saez
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Sara Teresinha Olalla Saad
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Margareth Castro Ozelo
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Fernando Cendes
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Fernando Ferreira Costa
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Mônica Barbosa de Melo
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors participated in the design, interpretation of the study and review of the manuscript. Sample collection was performed by Mirta Tomie Ito and Roberta Casagrande Saez; neurological evaluation was conducted by Fernando Cendes; cell isolation and culture were performed by Sueli Matilde da Silva Costa, Mirta Tomie Ito, Roberta Casagrande Saez, Dulcinéia Martins de Albuquerque and Carolina Lanaro; review of medical records was done by Júlia Nicoliello Pereira de Castro, Sueli Matilde da Silva Costa, Victor de Haidar e Bertozzo, Mirta Tomie Ito and Thiago Adalton Rosa Rodrigues; transcriptomic data analysis and interpretation were performed by Júlia Nicoliello Pereira de Castro, Ana Carolina Lima Camargo, Bruno Batista de Souza, Sueli Matilde da Silva Costa and Mônica Barbosa de Melo; gene ontology analysis was conducted by Júlia Nicoliello Pereira de Castro, Sueli Matilde da Silva Costa, Ana Carolina Lima Camargo and Victor de Haidar e Bertozzo; protein–protein interaction network was constructed by Júlia Nicoliello Pereira de Castro and Thiago Adalton Rosa Rodrigues; In silico prediction of regulatory factors was conducted by Júlia Nicoliello Pereira de Castro and Ana Carolina Lima Camargo. The whole work was supervised by Sueli Matilde da Silva Costa, Fernando Ferreira Costa and Mônica Barbosa de Melo. The manuscript was written by Júlia Nicoliello Pereira de Castro, Sueli Matilde da Silva Costa and Mônica Barbosa de Melo. Júlia Nicoliello Pereira de Castro and Sueli Matilde da Silva Costa are equal contributors to the work.

Corresponding author

Correspondence to Mônica Barbosa de Melo.

Ethics declarations

Ethics approval

This study was approved by the Research Ethics Committees of the Faculty of Medical Sciences, UNICAMP, in accordance with national guidelines (protocol nº 4.859.604) and with the Helsinki Declaration of 1975, as revised in 2008.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 17 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

de Castro, J.N.P., da Silva Costa, S.M., Camargo, A.C.L. et al. Comparative transcriptomic analysis of circulating endothelial cells in sickle cell stroke. Ann Hematol 103, 1167–1179 (2024). https://doi.org/10.1007/s00277-024-05655-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00277-024-05655-6

Keywords

Search

Navigation