Plasma from patients undergoing allogeneic hematopoietic stem cell transplantation promotes NETOSIS in vitro and correlates with inflammatory parameters and clinical severity

Abstract

Introduction: NETosis, the mechanism by which neutrophils release extracellular traps (NETs), is closely related to inflammation. During the allogeneic hematopoietic stem cell transplantation (allo-HSCT), different stimuli can induce NETs formation. Inflammation and endothelial injury have been associated with acute graft-versus-host disease (aGVHD) and complications after allo-HSCT. We focus on the study of NETosis and its relation with cytokines, hematological and biochemical parameters and clinical outcomes before, during and after allo-HSCT.

Methods: We evaluate the capacity of plasma samples from allo-HSCT patients to induce NETosis, in a cell culture model. Plasma samples from patients undergoing allo-HSCT had a stronger higher NETs induction capacity (NETsIC) than plasma from healthy donors throughout the transplantation process. An optimal cut-off value by ROC analysis was established to discriminate between patients whose plasma triggered NETosis (NETs+IC group) and those who did not (NETs-IC group).

Results: Prior to conditioning treatment, the capacity of plasma samples to trigger NETosis was significantly correlated with the Endothelial Activation and Stress Index (EASIX) score. At day 5 after transplant, patients with a positive NETsIC had higher interleukin (IL)-6 and C-reactive protein (CRP) levels and also a higher Modified EASIX score (M-EASIX) than patients with a negative NETsIC. EASIX and M-EASIX scores seek to determine inflammation and endothelium damage, therefore it could indicate a heightened immune response and inflammation in the group of patients with a positive NETsIC. Cytokine levels, specifically IL-8 and IL-6, significantly increased after allo-HSCT with peak levels reached on day 10 after graft infusion. Only, IL-10 and IL-6 levels were significantly higher in patients with a positive NETsIC. In our small cohort, higher IL-6 and IL-8 levels were related to early severe complications (before day 15 after transplant).

Discussion: Although early complications were not related to NETosis by itself, NETosis could predict overall non-specific but clinically significant complications during the full patient admission. In summary, NETosis can be directly induced by plasma from allo-HSCT patients and NETsIC was associated with clinical indicators of disease severity, cytokines levels and inflammatory markers.

Keywords: Allo-HSCT; Cytokines; EASIX score; IL-6; Inflammation; NETosis; NETs; aGVHD.

Figure 1

Assessment of the capacity of plasma samples from allo-HSCT patients to induce NETs formation, in vitro. (A) Representative images from patients and controls. (B) Iodide solution (right panel) and anti-MPO-FITC (central panel) images merged in the left panel to demonstrate co-localization of MPO and extracellular DNA ejected in cells undergoing NETosis. (C) Comparison of total NETs counts between allo-HSCT patients and healthy controls. Total NET counts were calculated as the sum of NETs induced by plasma samples in the 10-field counts. (D) Comparison of total NETs counts induced from allo-HSCT patient samples at different time points studied (D-1, D0, D5, D10, D15 and D20) and healthy controls. Each dot represents one individual patient sample and lines represent the average. Data are given as mean (T-test and ANOVA tests. p-values: **p<0.01, ***p < 0.001).

Figure 2

Representation of total NETs counts of all patients and at all time points evaluated. (A) Heat map showing, in red, the patient’s samples with a positive NETsIC and, in pale orange, samples with a negative NETsIC. (B) Percentage of patients who presented a positive (red) and negative (pale orange) NETsIC. The percentages of positive and negative patient groups were calculated for each of the studied times. (C) Heat map showing, in red, the patient’s samples with a strong NETsIC and, in pale orange, samples with a non-strong NETsIC. (D) Percentage of patients who presented a positive (red) and negative (pale orange) strong-NETsIC. The percentages of positive and negative patients were calculated for each of the studied times.

Figure 3

Cytokine levels in allo-HSCT patients before (D-1) and after allo-HSCT (D0, D5, D10, D15 and D20). (A) Median serum concentration (pg/ml) of IL-8 (green line), IL-6 (yellow line), IL-10 (purple line), TNF-α (orange line) and IL-12p70 (pink line). (B–F) The bold color line shows the mean cytokines levels of serum samples from allo-HSCT patients (results are shown on an x10 scale). Dotted and continuous color lines represent the mean cytokines levels of NETs+IC and NETs-IC patient groups, respectively (scale x10). Gray dots represent an individual patient sample and successive repeated measures on the same individual are represented by connecting lines.

Figure 4

Correlation of IL-8 (A), IL-6 (B) and IL-10 (C) serum levels and total NETs counts. (D) Comparison of H3Cit sera levels between NETs+IC and NETs-IC patient groups. (E) Comparison of H3Cit sera levels between D-1 and D5 after allo-HSCT. (F) Correlation between H3Cit sera levels (ng/ml) and total NETs counts. (G) Correlation between EASIX score and total NETs count on D-1 (Prior to conditioning regimen). In the correlation analysis, each dot represents a sample. Data are given as mean (T-test. p-values: *p<0.05).

Figure 5

Serum cytokine levels and presence of severe complications. Comparison of IL-6 (A) and IL-8 (B) levels (pg/ml) between patients who showed early severe complications (red line) and patients who did not (blue line). Comparison of IL-6 (C), IL-8 (D) and IL-10 (E) levels (pg/ml) and NETsIC (F) between patients who presented complications during admission (red line) and patients who did not (blue line). (T-test and ANOVA tests p-values: *p<0.05).