MDSC subpopulation dynamics predict disease evolution: a multidimensional biomarker framework for risk assessment in MDS

MDSC亚群动态变化预测疾病进展:MDS风险评估的多维生物标志物框架

阅读:4

Abstract

To delineate subtype-specific associations of myeloid-derived suppressor cells (MDSCs) with tumor burden dynamics, leukemic progenitor features, and immunophenotypic remodeling in myelodysplastic syndromes (MDS), addressing unmet needs in prognostic biomarker discovery. In this cohort study of 70 MDS patients and 10 age-matched healthy controls, we performed multicolor flow cytometry to quantify monocytic (M-MDSC), early (e-MDSC), and granulocytic (G-MDSC) subsets alongside lymphocyte subpopulations (CD19 + B cells, CD3 + T cells, CD56 + NK cells). WT1 transcript levels were assessed via RQ-PCR, with tumor burden stratified by CD34 + blast percentage and IPSS-R criteria. Subtype-specific analysis revealed selective enrichment of monocytic MDSC (M-MDSC) in patients including elevated WT1 transcript levels, and elevated CD34 + cell proportions. Reduced baseline e-MDSC levels (< 2.36%) correlated with prolonged median overall survival (6.5vs4months; P = 0.0174). Notably, granulocytic MDSC (G-MDSC) demonstrated modest diagnostic utility (AUC = 0.7350, P = 0.0167) but failed to stratify patients by IPSS-R risk categories. Mechanistically, MDSC subsets exhibited distinct lymphoid interaction patterns: M-MDSC expansion demonstrated a positive correlation with CD19 + B-cell frequencies (r = 0.3051, P = 0.0102), while e-MDSC accumulation positively correlated with NK cells (r = 0.37, P = 0.001) and inversely correlated with T cells (r=-0.2845, P = 0.0170). M-MDSC and e-MDSC—but not G-MDSC—serve as clinically actionable biomarkers reflecting tumor burden and survival outcomes in MDS. Their distinct interactions with B, T, and NK lymphocytes implicate subset-specific immunosuppressive pathways, offering novel targets for risk-adapted immunotherapy.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。