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. 2024 Aug 21:15:1421036.
doi: 10.3389/fimmu.2024.1421036. eCollection 2024.

Exploring cell-derived extracellular vesicles in peripheral blood and bone marrow of B-cell acute lymphoblastic leukemia pediatric patients: proof-of-concept study

Fábio Magalhães-Gama  1   2   3   4 , Marina Malheiros Araújo Silvestrini  3   4 , Juliana Costa Ferreira Neves  2   5 , Nilberto Dias Araújo  1   2   6 , Fabíola Silva Alves-Hanna  1   2 , Marlon Wendell Athaydes Kerr  2   6 , Maria Perpétuo Socorro Sampaio Carvalho  2   6 , Andréa Monteiro Tarragô  2   6 , Gemilson Soares Pontes  1   6   7 , Olindo Assis Martins-Filho  3   4   6 , Adriana Malheiro  1   2   6 , Andréa Teixeira-Carvalho  3   4   6 , Allyson Guimarães Costa  1   2   6
Affiliations

Exploring cell-derived extracellular vesicles in peripheral blood and bone marrow of B-cell acute lymphoblastic leukemia pediatric patients: proof-of-concept study

Fábio Magalhães-Gama et al. Front Immunol. .

Abstract

Extracellular vesicles (EVs) are heterogeneous, phospholipid membrane enclosed particles that are secreted by healthy and cancerous cells. EVs are present in diverse biological fluids and have been associated with the severity of diseases, which indicates their potential as biomarkers for diagnosis, prognosis and as therapeutic targets. This study investigated the phenotypic characteristics of EVs derived from peripheral blood (PB) and bone marrow (BM) in pediatric patients with B-cell acute lymphoblastic leukemia (B-ALL) during different treatment stages. PB and BM plasma were collected from 20 B-ALL patients at three time points during induction therapy, referred to as: diagnosis baseline (D0), day 15 of induction therapy (D15) and the end of the induction therapy (D35). In addition, PB samples were collected from 10 healthy children at a single time point. The EVs were measured using CytoFLEX S flow cytometer. Calibration beads were employed to ensure accurate size analysis. The following, fluorescent-labeled specific cellular markers were used to label the EVs: Annexin V (phosphatidylserine), CD235a (erythrocyte), CD41a (platelet), CD51 (endothelial cell), CD45 (leukocyte), CD66b (neutrophil), CD14 (monocyte), CD3 (T lymphocyte), CD19, CD34 and CD10 (B lymphoblast/leukemic blast). Our results demonstrate that B-ALL patients had a marked production of EV-CD51/61+, EV-CD10+, EV-CD19+ and EV-CD10+CD19+ (double-positive) with a decrease in EV-CD41a+ on D0. However, the kinetics and signature of production during induction therapy revealed a clear decline in EV-CD10+ and EV-CD19+, with an increase of EV-CD41a+ on D35. Furthermore, B-ALL patients showed a complex biological network, exhibiting distinct profiles on D0 and D35. Interestingly, fold change and ROC curve analysis demonstrated that EV-CD10+CD19+ were associated with B-ALL patients, exhibited excellent clinical performance and standing out as a potential diagnostic biomarker. In conclusion, our data indicate that EVs represent a promising field of investigation in B-ALL, offering the possibility of identifying potential biomarkers and therapeutic targets.

Keywords: biomarkers; childhood leukemia; extracellular vesicles; leukemic microenvironment; nano-flow cytometry.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Compendium of study. The study population (A), sampling (B), and methods (C), including the steps of the protocol are summarized in this figure.
Figure 2
Figure 2
Characterization of the profile of the extracellular vesicles at diagnosis baseline. The EV populations were measured at the time of diagnosis in the B-ALL PB (formula image) and B-ALL BM (formula image) groups and in the control group (CG) (formula image). The count and immunophenotypic characterization of EVs was performed using flow cytometry, as described in the Materials and Methods section. The results are presented using bar and symbol charts, reported in log10 scale, showing the mean with standard error of the absolute number of EVs/mm3 of plasma. Statistical analyses were performed using Student’s t test or the Mann-Whitney test and significant differences are highlighted by asterisks for p<0.01 (**) or p<0.05 (*).
Figure 3
Figure 3
Kinetics of extracellular vesicles during induction therapy. The EV populations were measured on D0, D15, and D35 in the B-ALL PB (formula image) and B-ALL BM (formula image) groups to assess the behavior of these EVs during remission induction therapy. The count and immunophenotypic characterization of the EVs was performed using flow cytometry, as described in the Materials and Methods section. The results are presented using bar and symbol charts, reported in log10 scale, showing the mean with standard error of the absolute number of EVs/mm3 of plasma. Statistical analyses were performed using a paired t test or Wilcoxon matched-pairs signed-rank test for comparisons between D0, D15 and D35 and significant differences are highlighted by asterisks for p<0.01 (**) or p<0.05 (*).
Figure 4
Figure 4
Kinetics of extracellular vesicles according to size range. The EV populations were analyzed in (A) B-ALL PB (formula image) and (B) B-ALL BM (formula image) groups according to their size, based on Megamix beads size range, being divided into small EVs = 100-200 nm (sEVs), medium EVs = 201-500 nm (mEVs) and large EVs = 501-900 nm (lEVs), represented by the symbols: “formula image”, “formula image” and “formula image”, respectively. For the control group, sEVs, mEVs, and lEVs were represented by gray background lines: “formula image”, “formula image” and “formula image”, respectively. The count, size and immunophenotypic characterization of the EVs was performed using flow cytometry, as described in the Materials and Methods section. The results are presented using symbol charts, reported in log10 scale, showing the median of the absolute number of EVs/mm3 of plasma. Statistical analyses were performed using a paired t test or Wilcoxon matched-pairs signed-rank test for comparisons between sEVs, mEVs, and lEVs and significant differences are represented by the letters: “a” and “b”, which refer to the comparisons with sEVs and mEVs, respectively.
Figure 5
Figure 5
Signature of extracellular vesicles during induction therapy. The overall signature of EV populations in the B-ALL patients was assembled on D0, D15 and D35. Data, originally expressed as absolute number of EVs/mm3 of plasma, were converted into categorical data using the global median values, which were used as a cut-off point to classify the study population as being a low or high producer of the EVs evaluated. The overall signatures were assembled in radar charts using the 50th percentile as the threshold (central circle/gray zone) to identify EV populations with increased levels in a higher proportion of patients. Cellular markers: CD235a (erythrocyte), CD41a (platelet), CD51 (endothelial cell), CD45 (leukocyte), CD66b (neutrophil), CD14 (monocyte), CD3 (T lymphocyte), CD34 and CD10 (B lymphoblast/Leukemic blast) and CD19 (B lymphocyte/B lymphoblast).
Figure 6
Figure 6
Biological network of extracellular vesicles during induction therapy. Integrative networks were assembled to identify the complex interactions among EV populations during induction therapy. Colored nodes are used to identify the EVs in the B-ALL PB (formula image) and B-ALL BM (formula image) groups and in the control group (CG) (formula image), where the larger the node, the greater the number of interactions established. Correlation analysis was employed to construct integrative networks according to significant “r” scores at p<0.05 using the Spearman correlation test. Connecting edges illustrate the positive correlations between pairs of attributes, according to the strength of correlation as described in the Materials and Methods section. Different colored and thickness are used to represent moderate correlations (black fine edges) and strong correlations (dark blue solid edges). Cellular markers: CD235a (erythrocyte), CD41a (platelet), CD51 (endothelial cell), CD45 (leukocyte), CD66b (neutrophil), CD14 (monocyte), CD3 (T lymphocyte), CD34 and CD10 (B lymphoblast/Leukemic blast) and CD19 (B lymphocyte/B lymphoblast).
Figure 7
Figure 7
Fold change and performance of the extracellular vesicles CD10+ and CD19+ as diagnostic biomarkers of B-ALL. The fold changes (A) and significance of fold changes (B) were performed in the peripheral blood of the B-ALL patients at the diagnosis baseline as described in the Materials and Methods section. Receiver operating characteristic (ROC) curve analysis was carried out to assess the performance of EV-CD10+ and EV-CD19+ levels as diagnostic biomarkers for B-ALL (C). ROC curves were assembled to define the cut-off points and calculate the following performance indices: sensitivity (Se), specificity (Sp), likelihood ratio (LR), the best cut-off point, as well as the area under the curve (AUC) and p-value as indicators of global accuracy, as described in the Materials and Methods section.
Figure 8
Figure 8
Profile, kinetic, fold change and performance of extracellular vesicles CD10+CD19+ as diagnostic biomarkers of B-ALL. The EV-CD10+CD19+ (double-positive) populations were analyzed at the diagnosis baseline (A) and during induction therapy (B) in the B-ALL PB (formula image) and B-ALL BM (formula image) groups and in the control group (CG) (formula image). The count and immunophenotypic characterization of EV-CD10+CD19+ was performed using flow cytometry. The results are presented using bar and symbol charts, reported in log10 scale, showing the mean with standard error of the absolute number of EVs/mm3 of plasma. Statistical analyses were performed using the Mann-Whitney test or Wilcoxon matched-pairs signed-rank test and significant differences are highlighted by asterisks for p<0.001 (***) or p<0.05 (*). The fold changes (C) and significance of fold changes (D) were performed in the peripheral blood of the B-ALL patients at the diagnosis baseline. Receiver operating characteristic (ROC) curve analysis (E) was carried out to assess the performance of EV-CD10+CD19+ plasma levels as diagnostic biomarkers for B-ALL. ROC curves were assembled to define the cut-off points and calculate the following performance indices: sensitivity (Se), specificity (Sp), likelihood ratio (LR), the best cut-off point, as well as the area under the curve (AUC) and p-value as indicators of global accuracy.
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The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Financial support was provided in the form of grants from Fundação de Amparo à Pesquisa do Estado do Amazonas (FAPEAM) (Pró-Estado Program - #002/2008, #007/2018, #005/2019 and POSGRAD Program #002/2023 and #002/2024), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) (PROCAD-Amazônia 2018 Program - #88881.200581/2018-01 and PDPG-CONSOLIDACAO-3-4 Program #88887.707248/2022-00). FM-G, MM, JN, NA, MK, and FA-H have fellowships from FAPEAM, CAPES and CNPq (Masters and PhD student fellowships). OM-F is a level 1 research fellow from CNPq and a research fellow from the program supported by the Universidade do Estado do Amazonas (PROVISIT No. 005/2023-PROPESP/UEA). AT-C and AC are a level 2 research fellow from CNPq. The funders made no contribution to the study’s design, data collection and analysis, decision to publish or preparation of the manuscript.

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