Mutations in the splicing factor SF3B1 are linked to frequent emergence of HLA-DRlow/neg monocytes in lower-risk myelodysplastic neoplasms

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Somatic mutations in the splicing factor SF3B1 occur in about one-third of all myelodysplastic neoplasms (MDS) and define a subgroup of patients characterized by ring sideroblasts (RS), ineffective erythropoiesis, and an indolent disease course in lower-risk (LR) MDS [ 1 ]. They are typically heterozygous missense substitutions, most commonly (>50% in MDS) involving p.K700E ( SF3B1 NM_012433.4: c.2098A>G (p.Lys700Glu), hereafter referred to as SF3B1 K700E ), and have been shown to induce mis-splicing of key genes throughout erythroid differentiation [ 2 , 3 ]. Surprisingly, although SF3B1 mutations are known to target multipotent lymphomyeloid hematopoietic stem cells and clonally propagate to myeloid progenitors [ 4 ], their impact on mature immune cells remains largely unexplored. Clinically, SF3B1 mutations are associated with high response rates to the erythroid maturation agent luspatercept and lower response to immunosuppressive treatment (IST) [ 5 , 6 , 7 ]. In this study, we performed multiplex immunophenotyping in conjunction with machine learning-based analytical approaches on bone marrow (BM)/peripheral blood (PB) samples from newly diagnosed or disease-modifying treatment-naïve SF3B1 mut or SF3B1 wt MDS patients (experimental cohort: Supplementary Table S1 ; Fig. S1 ) and healthy donors (HD) to identify genotype-immunophenotype correlations. Initial gene expression profiling of 730 immune-related genes in SF3B1 mut versus SF3B1 wt MDS BM mononuclear cells (BM-MNCs) revealed a predominantly myeloid cell-related innate immune gene signature (e.g., CYBB , CSF1R ) lacking signs of overt myeloid-driven inflammation (i.e. IL1B , CXCL5 ), whereas lymphoid-related genes were underrepresented (e.g., CD3D , CD79A ) (Supplementary Table S4 , Fig. S2 ). These results are consistent with the reported lower proportion of lymphocytes in BM [ 8 ], mild myeloid dysplasia [ 9 ], and our previous finding of significantly lower IL1B mRNA in BM monocytes from SF3B1 mut LR-MDS [ 10 ]. As IL-1β protein levels in paired BM plasma samples were often below the detection limit, we could not determine whether lower mRNA levels correspond to lower cytokine levels. Next, we conducted high-dimensional mass cytometry (CyTOF) on BM-MNCs and analyzed data using the Tracking Responders EXpanding (T-REX) algorithm to identify immunophenotypic differences associated with LR-MDS and SF3B1 K700E LR-MDS in particular. As expected, LR-MDS ( SF3B1 mut and SF3B1 wt ) showed several immunophenotypic changes consistent with an activated immune response (Fig. 1A , Supplementary Fig. S3 / S4 ), in particular specific clusters resembling terminally differentiated effector memory CD8 + T cells (T TE /TEMRA, cluster 1295), mature CD57 + NK cells (cluster 2495), CD27 + IgD − memory B cells (cluster 795), and γδ T cells with an exhausted immunophenotype (cluster 1395). LR-MDS exhibited dysregulated T-cell homeostasis, with fewer naïve CD4 + and CD8 + T cells, and memory phenotype skewing toward CD8 + effector memory (T EM ) and T TE cells (Supplementary Fig. S4 ). This is consistent with progressive memory differentiation entailing loss of survival, which could contribute to impaired long-term antitumor immunosurveillance. Fig. 1: Monocytes with HLA-DR low/neg immunophenotype emerge frequently in the BM of SF3B1 mut MDS. A T-REX plot of regions of significant change on Uniform Manifold Approximation (UMAP) axes for CD45 + BM-MNCs stained for CyTOF showing distinct LR-MDS-specific (dark red, ≥95% of cells are contributed by LR-MDS samples) and HD-specific (dark blue, ≥95% of cells are contributed by HD) cell clusters. 14 LR-MDS (mean age = 74 years, 4 women, 10 men) and 4 HD (mean age = 58 years, all men) were included in the analysis. LR-MDS group comprises SF3B1 K700E ( n = 5, orange dots; mean age = 75 years, 2 women, 3 men) and SF3B1 wt ( n = 9, blue dots; mean age = 74 years, 2 women, 7 men) patients. Top 10 Marker Enrichment Modeling (MEM) labels with enrichment scores are shown for statistically significant LR-MDS-specific clusters (cutoff >2000 cells) indicated on T-REX plot. B T-REX analysis of CD45 + BM-MNCs stained for CyTOF showing distinct SF3B1 K700E -specific (dark red) and SF3B1 wt -specific (dark blue) cell clusters. Top 10 MEM labels are shown for statistically significant and trend clusters (cutoff >1000 cells) indicated on T-REX plot. A , B Labels on T-REX plot indicate major immune cell subsets (myeloid cells, NK cells, γδ T cells, CD4 + and CD8 + T cells, B cells). C T-REX analysis of CD33 + CD14 + pre-gated monocytes showing SF3B1 K700E -specific (dark red) and SF3B1 wt -specific (dark blue) clusters. Cluster 795 depicts a distinct HLA-DR low/neg monocyte subset in SF3B1 K700E LR-MDS (NOTE: this cluster is not related to cluster 795 shown in (A)). HLA-DR expression was projected onto UMAP axes. A – C Two-sided Mann–Whitney- U -test/Wilcoxon rank-sum test was performed for indicated clusters ( p < 0.05 was considered significant; p -values are shown in brackets). Box plots depict median, IQR (lower and upper hinges), and 1.5 times the IQR (lower and upper whiskers extend to values within 1.5 times the IQR from the hinge). (D) Percentage of CD33 + CD14 + BM monocytes with HLA-DR low/neg immunophenotype in HD (median = 9.7, IQR = 8 [ n = 9, mean age = 69 years, 6 women, 3 men]), SF3B1 mut (median = 37.9, IQR = 34.9 [ n = 17; orange dots, K700E; light orange-filled circles, nonK700E including one K666R, one E622D, one H662Y, and one Y623C; mean age = 71 years, 6 women, 11 men]), and SF3B1 wt (median = 6.3, IQR = 11.2 [ n = 16, mean age = 66 years, 8 women, 8 men]) MDS assessed by diagnostic FCM of freshly stained BM samples (Kruskal–Wallis test with Dunn’s post-hoc test [Bonferroni adjusted p -values]). E Representative HLA-DR staining on CD33 + CD14 + BM monocytes. The black line indicates the set threshold distinguishing low or negative from high HLA-DR expression. F Percentage of CD33 + CD14 + BM monocytes with HLA-DR low/neg immunophenotype in four SF3B1 K700E MDS patients over time. Patients #4, #10, and #11 harbor an isolated SF3B1 K700E mutation. Full size image We then compared SF3B1 K700E to SF3B1 wt LR-MDS using the T-REX pipeline, which identified a SF3B1 K700E -specific cluster comprising CD33 + CD14 + monocytes (cluster 495, p < 0.01) (Fig. 1B , Supplementary Fig. S5 ). Further analysis of CD33 + CD14 + BM-MNCs showed that a remarkable proportion of the monocytes in SF3B1 K700E LR-MDS adopt a HLA-DR low/neg phenotype (Fig. 1C ). Importantly, retrospective analysis of diagnostic flow cytometry data (Fig. 1D–E ) and external validation in two independent cohorts comprising combined 130 MDS (118 LR-MDS) patients (Supplementary Fig. S 6 ) confirmed an increased frequency of HLA-DR low/neg monocytes in SF3B1 mut (both SF3B1 K700E and SF3B1 nonK700E ) compared to SF3B1 wt MDS and HD. The external data support our observation that staining cryopreserved BM-MNCs may underestimate the actual frequency of HLA-DR low/neg monocytes. Additionally, we found a strong correlation between HLA-DR low/neg monocyte frequencies in BM and PB (Supplementary Fig. S7 ). HLA-DR low/neg monocytes in SF3B1 mut MDS were classical monocytes (CM) based on the lack of CD16 surface expression (Supplementary Fig. S7 ). Analysis of longitudinal data from four SF3B1 K700E MDS patients showed a consistently high frequency of HLA-DR low/neg monocytes (Fig. 1F ). To the best of our knowledge, the only other study directly investigating immunophenotypic features in BM of SF3B1 mut MDS reported lower expression of CD11b, CD36, and CD64 on monocytes [ 8 ]. Another study found a higher frequency of thrombomodulin-expressing CM in MDS subtypes with <5% blasts and RS [ 11 ]. The association of SF3B1 mutations with lower monocyte surface HLA-DR expression identified here may be of clinical relevance, for example in view of the predicted poor response of SF3B1 mut MDS to IST [ 6 , 7 ]. Overall, the freq

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