ABSTRACT
Objective
This study evaluates the prognostic value of bone marrow‐derived mesenchymal stem cells (MSCs) in predicting the progression of Myelodysplastic Syndrome (MDS) to Acute Myeloid Leukemia (AML).
Methods
MSC‐like cells were analyzed using flow cytometry in a cohort of 49 MDS patients, including transformed and non‐transformed groups.
Results
A non‐hematopoietic CD13‐bright cell population, enriched for MSC markers CD105 and CD90, was identified in 80% of patients at diagnosis. Elevated of these MSC‐like cells were significantly associated with earlier progression to leukemia and reduced overall survival. Multivariate analysis confirmed MSC content as an independent predictor of leukemia transformation.
Conclusion
MSC‐like cell content at MDS diagnosis may serve as a novel biomarker of predicting malignant transformation to AML. Further validation in larger cohorts and better phenotypic characterization of this cell population are needed.
Trial Registration
The authors have confirmed clinical trial registration is not needed for this submission
Keywords: biomarkers, flow cytometry, MDS, mesenchymal stem cells, secondary AML
1. Introduction
Myelodysplastic syndrome (MDS) is a myeloid malignancy characterized by genomic lesions in early myeloid progenitors, which confer a competitive advantage over their normal counterparts [1]. The Revised International Prognostic Scoring System (R‐IPSS) aids in stratifying MDS patients into five risk categories with different prognoses. In addition, other prognostic models have been developed, such as a flow cytometry‐based MDS score, which further refines risk stratification by incorporating immunophenotypic abnormalities on progenitor cells [2]. Approximately 30%–40% of MDS patients may progress to secondary acute myeloid leukemia (sAML), developing inferior overall survival (OS) [3]. This underscores the importance of monitoring and early intervention of higher‐risk patients [4, 5]. Routinely, hypomethylating agents are the initial line of treatment for high‐risk MDS patients who are not suitable candidates for transplantation, despite their inability to eradicate the foundational mutant clones responsible for the disease [6, 7]. Although specific genetic mutations, such as those in the ASXL1 or TP53 genes, have been identified as independent risk factors for a higher likelihood of transformation to AML [8], other biological and clinical parameters, including established prognostic scoring systems, may also contribute to predicting disease progression in MDS.
Mesenchymal stem cells (MSCs) represent a key non‐hematopoietic component of the bone marrow niche, a specialized microenvironment that supports hematopoietic stem cells and progenitors [9]. Although, MSC levels are not quantified by flow cytometry (FC) in the diagnostic routine for MDS patients, MSC populations have emerged as significant players in the pathogenesis of MDS and its progression to AML [9, 10, 11]. Therefore, we wondered whether quantification of MSC levels by FC could be a predictive marker for transformation to sAML in MDS patients. Human MSCs are phenotypically characterized by positive expression of CD105, CD73, and CD90 surface markers, and negative expression of hematopoietic markers such as CD45, CD34, CD14 or CD11B, CD79alpha or CD19, and HLA‐DR [12]. We retrospectively analyzed the MSC phenotype of a cohort of 43 MDS patients and 6 MDS/MPN (29 transformed and 20 non‐transformed) at different time points (Table 1 and Table S1). To ascertain the stromal nature of these bone marrow cells, we incorporated the MSC‐specific markers CD105 and CD90 into our FC panel and sorted the MSC‐like cells for further culturing. Our analyses demonstrated the clinical relevance of MDS‐derived MSCs abundance at diagnosis as a potential predictor of sAML.
TABLE 1.
Summary of characteristics of MDS patients.
|
Total (%) N = 49 |
NT (%) N = 20 |
T (%) N = 29 |
p |
|
|---|---|---|---|---|
| Age (years) | ||||
| >70 | 19 (38.8) | 4 (20) | 15 (51.7) |
< 0.05 |
| <70 | 30 (61.2) | 16 (80) | 14 (48.3) | |
| Sex | ||||
| Male | 29 (59.2) | 12 (60) | 17 (58.6) | NS |
| Female | 20 (40.8) | 8 (40) | 12 (41.4) | |
| Karyotype | ||||
| Normal | 17 (34.7) | 7 (35) | 10 (34.5) | NS |
| Altered | 20 (40.8) | 6 (30) | 14 (48.3) | |
| Hb (g/dL) | ||||
| >10 | 22 (44.9) | 16 (80) | 11 (37.9) | < 0.01 |
| <10 | 27 (55.1) | 4 (20) | 18 (62.1) | |
| Platelet count (p.µL) | ||||
| >100.000 | 32 (65.3) | 17 (85) | 15 (51.7) | < 0.05 |
| <100.000 | 17 (34.7) | 3 (15) | 14 (24.1) | |
| Neutrophils | ||||
| >1.8×109/L | 20 (40.8) | 13 (65) | 7 (24.1) | < 0.01 |
| <1.8×109/L | 29 (59.2) | 7 (35) | 22 (79.9) | |
| Blasts count (%) | ||||
| >10% | 16 (32.7) | 0 (0) | 16 (55.2) |
< 0.01 |
| <10% | 33 (67.3) | 20 (100) | 13 (44.8) | |
| dxMSC‐like | ||||
| Low | 37 (77.1) | 18 (94.7) | 19 (65.5) | < 0.05 |
| High | 11 (22.9) | 1 (5.3) | 10 (34.5) | |
| intMSC‐like | ||||
| Low | 16 (55.2) | |||
| High | 13 (44.8) | |||
| tMSC‐like | ||||
| Low | 22 (75.9) | |||
| High | 7 (24.1) | |||
|
M‐IPSS |
||||
| Low‐Risk | 24 (53.3) | 13 (65) | 11 (37.9) | 0.01 |
| High‐Risk | 11 (24.4) | 3 (15) | 8 (27.6) | |
| NV | 10 (20.4) | 4 (20) | 10 (34.5) | |
|
Azacitidine |
||||
| Yes | 29 (59.2) | 15 (75) | 14 (48.3) | NS |
| No | 20 (40.8) | 5 (25) | 15 (51.7) | |
|
Death |
< 0.01 |
|||
| No | 16 (32.7) | 16 (80) | 0 | |
| Yes | 33 (67.3) | 4 (20) | 29 (100) | |
|
Median follow up, months (range) |
34 (3–169) |
36.5 (7–169) |
33 (3–119) |
NS |
2. Results
2.1. Characterization of MSC‐Like Cells by FC and Culture
In order to explore the impact of MSCs levels in AML transformation, we recruited a retrospective cohort 43 MDS patients and 6 MDS/MPN patients, 29 of which transformed to sAML (T) (median follow up of time of transformation was 16 months) and 20 patients that after a median follow up of three years did not transform (NT) (Table S3). Using our diagnostic FC panel that includes eight surface markers (Table S2), in near 80% of both NT and T patients (n = 39) at diagnosis, we identified a prominently CD13‐positive population that was negative for a range of markers, including CD45, CD34, CD117, CD11B, CD71, CD64, and CD16 (Figure S1). Given its particular phenotype, we designated this population as “MSC‐like cells” (Figure S1). To ascertain the stromal nature of these bone marrow cells, we incorporated the MSC‐specific markers CD105 and CD90 into our FC panel and sorted the MSC‐like cells (Supporting Information) of 8 representative MDS patients. This analysis revealed that more than 60% of CD13brightCD45low/neg cells, in every patient, were positive for both CD105 and CD90 markers, confirming the enrichment in MSC phenotype (Figure S2A,B). Then, these CD13brightCD45low/negCD105posCD90poscells, were sorted and grown in culture (Figure S2A). Ten days later, sorted MSC‐like cells emerged on the culture plates, displaying the characteristic MSC morphology (Figure S2C). In addition, we sorted the CD13brightCD45low/neg cells, excluding the MSC canonical markers CD105 and CD90, and following our diagnostic FC panel to verify whether MSC‐like cell were present in that compartment. This experiment revealed sparse MSC‐like cells growth in the culture after 10 days (Figure S3A,B).
2.2. Retrospective Analysis of MSC‐Like Cells
To determine the dynamics of MSC‐like cell content in malignant transformation of MDS, we quantified the percentage of MSC‐like cells in 29 patients that transformed to sAML at the diagnosis stage (dxMSC‐like) and after progression to AML (tMSC‐like). In addition, an intermediate MSC‐like stage (intMSC‐like) was considered, representing measurements taken between diagnosis and before AML progression. As a control, we also included 20 NT patients in the analysis. Both NT and T had similar median follow‐up with 36.5 (range: 7–169) and 33 (range: 3–119) months, respectively (Table S3), similar altered karyotype and similar men and women distribution. However, mutations in the TP53 gene were restricted to the T group (Table S1). At diagnosis, the T group showed significantly increased incidence of anemia (p < 0.01), neutropenia (p < 0.01), and higher blast counts (p < 0.01) compared to the NT group (Table 1). Interestingly, dxMSC‐like content was significantly (p < 0.05) higher in T patients (Figure 1A). Besides, a longitudinal analysis of the MSC‐like population revealed a peak of intMSC‐like cells in T patients (N = 15) that tended to occur prior to progression to sAML (Figure 1B and Figure S4A,B) with a median follow up of 14.5 months before transformation (Table S3). However, this peak was not significantly higher compared to the levels observed at diagnosis or during the leukemia stage (Figure 1 Band Figure S4A), as confirmed by a paired t‐test, which showed no statistically significant differences. Notably, the intMSC‐like content was higher in patients with a peak compared to those without (Figure 1C), and the peaking group exhibited significantly lower time to sAML (ttsAML) levels than non‐peaking patients (Figure 1D).
FIGURE 1.
Quantification and prognostic impact of MSC‐like cells in MDS. (A) Scatter plot with bar illustrating the percentage of MSC‐like content at diagnosis of NT (No Transformed, n = 19) and T (Transformed, n = 29) patients. The NT group shows significant lower percentage than T group. (B) Scatter plot with bar comparing MSC‐like content among three stages of the disease: dxMSC‐like (diagnosis), intMSC‐like (before transformation and after Aza treatment), and tMSC‐like (in the leukemia phase). A transient peak of MSC‐like cells is observed before AML progression. DxMSC‐like includes the content of MSC‐like cells at diagnosis of both NT and T patients. (C) Scatter plot with bar representation showing the percentage of intMSC‐like content in no‐Peak and Peak groups. The no‐Peak group includes patients without an increase in MSC‐like cells before AML transformation, while the Peak group includes patients with an observed increase in MSC‐like cells before transformation. (D) Scatter plot with bar representation depicting the time to secondary acute myeloid leukemia (sAML) progression (in months) for no‐Peak and Peak groups. (E, F) Kaplan‐Meier survival curves representing time to sAML transformation. These panels illustrate thelikelihood of progression to AML, based on the presence of MSC‐like cells at the time of diagnosis. Patients with high dxMSC‐like content have an early progression to sAML in the total cohort of patients (E) and in the T group (F). Values represent mean ± ES. * p < 0.05. Each black dot represents an individual data point.
2.3. Clinical Relevance of MSC‐Like Cells in MDS Outcomes
In order to explore the clinical impact of this MSC‐like population in disease progression, we assessed the influence of dxMSC‐like cell content on both sAML risk and OS, using Kaplan–Meier survival analysis. Our findings indicate that patients with high dxMSC‐like cell content (cut‐off point in Table S3) experienced significantly shorter ttsAML progression (16.45 ± 3.23 months) compared to those with lower dxMSC‐like cell levels (71.80 ± 13.61 months, p < 0.01; Figure 1E, Table S4). In addition, high dxMSC‐like cell content was associated with reduced OS, with patients exhibiting shorter survival durations compared to those with lower levels (30.75 ± 4.83 months vs. 63.88 ± 11.47 months, p = 0.06; Figure S5A). Notably, within the T‐group, patients with high dxMSC‐like cell content demonstrated a significantly shorter ttsAML progression compared to those with lower dxMSC‐like cell levels (14.6 ± 3.1 months vs. 25.7 ± 4.4 months, p = 0.05; Figure 1F, Table S4). Interestingly, we found that patients with elevated intMSC‐like cells content had significantly shorter ttsAML (p < 0.05) and survival (p < 0.05) (Figure S5B,C). However, this predictive capacity was lost after transformation (Figure S5D). This analysis also allowed us to confirm that the acquisition of new mutations in the T group had a negative impact on the leukemia evolution (p = 0.06) and OS (p < 0.01) (Figure S5E,F). Finally, multivariate Cox regression analysis in both T and NT groups (Table S5) demonstrated that dxMSC‐like content independently predicted short ttsAML in MDS at diagnosis: (HR = 3.06, 95%CI = 1.08–12.0).
3. Discussion
Given the crucial role of bone marrow MSCs in regulating hematopoiesis, this study investigates the dynamics of the MSC content during MDS progression to sAML in a cohort of 29 patients (T group), using samples from 20 MDS patients that do not transform as a group control (NT group). Through a FC approach, we identified a MSC‐like population characterized by CD13bright CD45low/negCD34neg, CD71neg, CD117neg, CD11Bneg, CD16neg, and CD64neg phenotypic markers across various disease stages. A similar CD13 bright population was previously observed in normal bone marrow samples [13]. At MDS diagnosis, the amount of these MSC‐like cells was significantly higher in the T group than the NT group, suggesting their influence in AML evolution. This was confirmed in further analyses, where we demonstrated that elevated levels of MSC‐like cells at the time of diagnosis were independently associated with shorter ttsAML and associated with OS. In addition, we observed a transient peak of intMSC‐like cells prior to transformation, which negatively impacts on both ttsAML and OS. These data suggest the idea that nascent blasts locally disrupt the hematopoietic niche, performing a “niche peeling” to make bone marrow stromal cells detectable by FC as proposed by Duarte et al [14]. This peak of intMSC‐like cells may also be attributed to the administration of azacitidine, a treatment known to promote transient MSC expansion in vitro [15]. In this study, more than 75% of T patients with elevated levels of intMDS‐like cells received azacytidine, but we did not find the impact on MDS progression to sAML [16] and OS (data not shown).
Altogether, our findings highlight the critical role of the bone marrow niche cells in T and NT MDS patients and demonstrate their potential as an independent predictive biomarker of malignant transformation. Although these observations are very promising, further validation in a larger cohort along with more detailed phenotypic and molecular characterization of MSC‐like cells are essential to elucidate their exact role in sAML progression.
Author Contributions
Mireia Atance: conceptualization, data curation, methodology, writing–original draft. Cristina Serrano: writing–editing, resources, investigation. Carlos Soto: resources. Juan Manuel Alonso‐Domínguez writing–editing. Carlos Blas: resources. Raque Mata: resources. Tamara Castaño resource, Sara Perlado: resources. Teresa Arquero: resources, Jose Luis López‐Lorenzo: resources, supervision, investigation. M. Ángeles Pérez: resources. Belen Rosado: resources. Rafael Martos: resources. Ana Río-Machin: writing–editing Pilar Llamas‐Sillero: resources, supervision, investigation. Rocio N. Salgado: data curation, methodology. Juana Serrano‐López: conceptualization, data curation, methodology, formal analysis, supervision, funding acquisition, writing–original draft.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Supporting Information
Acknowledgments
We want to thank Zahara García de Castro and Omaira Alberquilla for sorting technical assistance and Raquel Gonzalo Hernández and Susana Castañón for providing MDS samples. We want to thank PETHEMA foundation for supporting part of the study.
Funding: This study was supported by the Pethema Foundation, Grant Number: PIC139/22_FJD.
Data Availability Statement
The authors have nothing to report.
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Supplementary Materials
Supporting Information
Data Availability Statement
The authors have nothing to report.