Thrombospondin-1, Platelet Factor 4, and Galectin-1 Are Associated with Engraftment in Patients with Sickle Cell Disease who Underwent Haploidentical Hematopoietic Stem Cell Transplantation

Abstract

Sickle cell disease (SCD) is an inherited red blood cell disorder that leads to significant morbidity and early mortality. The most widely available curative approach remains allogeneic hematopoietic stem cell transplantation (HSCT). HLA-haploidentical (haplo) HSCT expands the donor pool considerably and is a practical alternative for these patients, but traditionally with an increased risk of allograft rejection. Biomarkers in patient plasma could potentially help predict HSCT outcome and allow treatment at an early stage to reverse or prevent graft rejection. Reliable, noninvasive methods to predict engraftment or rejection early after HSCT are needed. We sought to detect variations in the plasma proteomes of patients who engrafted compared with those who rejected their grafts. We used a mass spectrometry-based proteomics approach to identify candidate biomarkers associated with engraftment and rejection by comparing plasma samples obtained from 9 engrafted patients and 10 patients who experienced graft rejection. A total of 1378 proteins were identified, 45 of which were differentially expressed in the engrafted group compared with the rejected group. Based on bioinformatics analysis results, information from the literature, and immunoassay availability, 7 proteins-thrombospondin-1 (Tsp-1), platelet factor 4 (Pf-4), talin-1, moesin, cell division control protein 42 homolog (CDC42), galectin-1 (Gal-1), and CD9-were selected for further analysis. We compared these protein concentrations among 35 plasma samples (engrafted, n = 9; rejected, n = 10; healthy volunteers, n = 8; nontransplanted SCD, n = 8). ELISA analysis confirmed the significant up-regulation of Tsp-1, Pf-4, and Gal-1 in plasma samples from engrafted patients compared with rejected patients, healthy African American volunteers, and the nontransplanted SCD group (P < .01). By receiver operating characteristic analysis, these 3 proteins distinguished engrafted patients from the other groups (area under the curve, >0.8; P < .05). We then evaluated the concentration of these 3 proteins in samples collected pre-HSCT and at days +30, +60, +100, and +180 post-HSCT. The results demonstrate that Tsp-1 and Pf-4 stratified engrafted patients as early as day 60 post-HSCT (P < .01), and that Gal-1 was significantly higher in engrafted patients as early as day 30 post-HSCT (P < .01). We also divided the rejected group into those who experienced primary (n = 5) and secondary graft rejection (n = 5) and found that engrafted patients had significantly higher Tsp-1 levels compared with patients who developed primary graft rejection at days +60 and +100 (P < .05), as well as higher Pf-4 levels compared with patients who developed primary graft rejection at post-transplantation (PT) day 100. Furthermore, Tsp-1 levels were significantly higher at PT days 60 and 100 and Pf-4 levels were higher at PT day 100 in engrafted patients compared with those who experienced secondary graft rejection. Increased concentrations of plasma Gal-1, Tsp-1, and Pf-4 could reflect increased T regulatory cells, IL-10, and TGF-β, which are essential players in the initiation of immunologic tolerance. These biomarkers may provide opportunities for preemptive intervention to minimize the incidence of graft rejection.

Keywords: Biomarkers; Engraftment; Haplo-HSCT; Proteomics; Rejection; Sickle cell disease.

Figure 1.

Schematic workflow for the TMT-based proteomic study.

Figure 2.

Identification of the differentially expressed proteins. A) Volcano plot showing log2 fold change plotted against log10 adjusted p value for engrafted samples versus rejected samples. Data points in the upper right (ratio > 1.25) and upper left (ratio < 0.75) sections with p < 0.05 represent proteins that are significantly differentially expressed in engrafted patients according to the protein analysis of the 10-plex TMT labeled plasma samples after removing proteins with < 2 quantified peptides. The Volcano plot was generated using GraphPad Prism software version 7. B) Venn diagram showing the overlapping of proteins between TMT 1 and TMT 2. C) Heat map visualization of the differentially expressed proteins in 18 patients. green, downregulation, red, upregulation. Clustering proteomic data is based on differential proteins.

Figure 3.

Bioinformatics analysis of differentially expressed proteins in the plasma of engrafted and rejected patients. A) Pathway analysis of the differentially expressed proteins. Only the top 20 are presented with their p-value and number of genes in each pathway. B) Gene Ontology (GO) enrichment of differentially expressed proteins. The functional enrichment of proteins in the constructed interaction network was carried out online in the STRING database. Only the ten most significantly enriched GO terms in each GO category (Biological Process, Molecular Function, and Cellular Component) with their p-values are presented.

Figure 4.

Verification of the differentially expressed proteins by ELISA (Gal-1, Pf4, Tsp-1, and Tln-1). Protein expression was measured in the healthy volunteer group (n = 8), non-transplanted SCD group (n = 8), engrafted group (n = 9), and rejected group (n = 10). n, number of subjects. P-values were calculated with the unpaired Student’s T test, *p < 0.05, and **p < 0.01, and data are presented as mean ± standard error of the mean (SEM).

Figure 5.

Prognostic biomarkers of engraftment. Plasma biomarker concentrations measured by ELISA in engrafted and rejected patients at different days pre- and post-HSCT (Baseline and days 30, 60, 100, and 180 post-transplant). p values were calculated with the unpaired Student’s T test, *p < 0.05, and **p < 0.01 and data are presented as mean ± standard error of the mean (SEM).