Ситуационное нарушение эритрополиса приводит к анемии у недавно диагностированных пациентов с несколькими миэлома.

Introduction

Multiple myeloma (MM) is a hematologic malignancy characterized by the uncontrolled proliferation of plasma cells ( Kyle & Rajkumar, 2008 ; Pu et al., 2024 ; Rajkumar, 2024 ). This abnormal growth disrupts normal hematopoiesis, leading to various complications, including calcium elevation, renal insufficiency, anemia, and bone disease. Among these, more than 60% of MM patients have anemia, and its severity often correlates with disease stage ( Bahlis et al., 2023 ). The reduction in hemoglobin levels not only serves as a poor prognostic factor but is also associated with increased mortality ( Liu et al., 2020 ; Mittelman, 2003 ; Musto et al., 1997 ; Sankaran and Weiss, 2015 ; Shamir et al., 2025 ). Understanding the cause of anemia and developing effective treatments are essential to improving the quality of life in MM patients.

The pathogenesis of anemia in MM is predominantly driven by impaired erythropoiesis. Among the various pathological factors contributing to this impairment, deficient production of erythropoietin (EPO) plays a central role. Ineffective erythropoiesis in MM is frequently attributed to insufficient EPO, a critical stimulator of red blood cell production ( Deshet-Unger et al., 2016 ; Hiram-Bab et al., 2015 ). This EPO deficiency is particularly pronounced in patients with myeloma-associated renal failure ( Knudsen et al., 1994 ). Beyond EPO deficiency, the bone marrow microenvironment in MM further disrupts erythropoiesis through multiple mechanisms. Malignant plasma cells promote apoptosis of erythroid precursors via death ligands such as FasL and TRAIL ( Silvestris et al., 2002 ; Silvestris et al., 2001 ). Myeloma-secreted cytokines, including CCL3 ( Han et al., 2024 ; Vallet et al., 2011 ), suppress erythropoiesis by downregulating transcription factors GATA1 and KLF1 in hematopoietic progenitor cells, impairing erythroid differentiation ( Liu et al., 2020 ). Additionally, dysfunctional erythroblastic island macrophages overproduce IL-6, which promotes myeloma growth and suppresses erythroid differentiation ( Huang et al., 2023 ). By far, most researches have focused on the role of the microenvironment in MM erythropoiesis. However, the stage-specific phenotypic and transcriptional features of erythropoiesis in MM-associated anemia remain largely unexplored.

Erythropoiesis is a complex, tightly controlled cellular process that comprises early erythropoiesis, terminal erythroid differentiation, and reticulocyte maturation. Many studies have reported that abnormalities at any stage of erythropoiesis can lead to abnormal erythrocyte production and subsequently cause anemia ( Cazzola, 2022 ). Previous studies have shown that normal human erythroid progenitor cells and terminal erythroid cells display distinct stage-specific phenotypes and transcriptional regulation ( An et al., 2014 ; Yang et al., 2024 ). Yet, it remains unclear what the phenotypic signatures and transcriptional regulation profiles are in early and terminal erythropoiesis in NDMM patients with anemia. This study aims to illuminate stage-specific cellular and molecular defects in early and late erythropoiesis that contribute to anemia in NDMM.

Materials and methods

Patients’ information and clinical data

Patients’ information and clinical data of newly diagnosed patients with multiple myeloma (NDMM) and healthy controls were collected at Zhengzhou University People’s Hospital between 2017 and 2025. The clinical characteristics of these NDMM patients are summarized in Table 1 . Diagnosis of NDMM was established according to the International Myeloma Working Group criteria ( Rajkumar et al., 2014 ). The diagnostic threshold for anemia in NDMM is a hemoglobin value > 20 g/L below the lower limit of normal, or a hemoglobin value < 100 g/L ( van de Donk et al., 2021 ).

Collection of mononuclear cells from bone marrow

This study included NDMM patients who met the International Myeloma Working Group criteria and had not received prior therapy. BM aspirates were obtained from the Zhengzhou University People’s Hospital and were residual specimens from routine clinical testing. This study was approved by the Henan Provincial People’s Hospital (Approval No. 2023–013). For mononuclear cell isolation, approximately 2–4 mL of BM aspirate was collected in EDTA-anticoagulated tubes, then diluted 2.5-fold with PBS containing 2% FBS and 2 mM EDTA (PBS/2% FBS/2 mM EDTA). The cell suspension was filtered through a 70 μm cell strainer (Biosharp, No. BS-70-CS), and the single-cell suspension was carefully layered onto 4 mL of Ficoll-Paque™ PLUS density gradient media (Cytiva, No. 17144002) in a 15 mL centrifuge tube. The cells were centrifuged at 400 g (1400 rpm) for 30 min with no brake at room temperature. Then the buffy coat (middle layer) containing mononuclear cells was collected with a transfer pipette into a 50 mL tube (up to 25 mL per tube), and washed twice with PBS/2% FBS/2 mM EDTA.

Antibody staining and flow cytometry analysis

For staining of human primary BM erythropoiesis, 3 × 10 6 mononuclear cells were stained with FITC-GPA (Biolegend, No.306610), APC/CH7-CD71 (BD bioscience, No.563671), PE-CD117 (BD bioscience, No.323408), APC-CD34 (BD bioscience, No.555824), Hoechst33342 (Solarbio No.C0031), PE/CF594-CD105 (BD bioscience, No.562380), PE/Cy7-IL3R (eBioscience, No.25123942), PE/Cy7-CD41a (Biolegend, No. 303718), PE/Cy7-CD45RA (Biolegend, No. 304126), then incubated on ice for 30 min in the dark. Following antibody staining and washing, cells were resuspended and subsequently stained with 7-AAD (0.5 μg/mL) on ice for 10 min in the dark. Finally, stained cells were analyzed within 1 h using an LSR Fortessa flow cytometer (Becton Dickinson).

Staining of cultured erythroblasts was performed as previously described ( Yan et al., 2021 ). Briefly, 0.1 × 10 6 cells were stained with FITC-GPA, APC/CH7-CD71, and PE/CF594-CD105, then incubated on ice for 30 min in the dark. For staining apoptotic cells, 0.1 × 10 6 cells were incubated with Annexin V (Beyotime, C1062S) on ice for 20 min in the dark. For enucleation, 0.1 × 10 6 cells were stained with Hoechst 33,342 (Beyotime, C1022) and incubated at 37 °C in the dark for 30 min.

Colony-forming assay

A total of 5 × 10 5 BM mononuclear cells were counted and resuspended in 1 mL IMDM supplemented with 2% FBS. From this suspension, 5 × 10 4 mononuclear cells were taken and resuspended in 1 mL MethoCult H4330 (Stemcell #04330) medium for the CFU-E colony assay, and 1 mL MethoCult H4434 (Stemcell #04434) for the BFU-E colony assay, respectively. Cells were incubated at 37 °C in a humidified incubator with 5% CO 2 . Colonies were counted under an inverted microscope on Day 7 (CFU-E) and Day 14 (BFU-E), respectively.

Fluorescence-activated cell sorting of human bone marrow erythroid cells

For sorting primary erythroid progenitors and terminal erythroblasts from human BM, total mononuclear cells were stained using the method of staining primary BM erythropoiesis. The sorting strategy was as follows: erythroid progenitor cells (GPA − CD117 + CD34 +/− CD45RA − CD41a − IL-3Rα − CD71 + ), terminal erythroblasts (GPA + CD71 hi Hoechst33342 + ). Cell sorting was performed using a BD FACSAria™ Fusion cell sorter.

Cytospin and giemsa staining

Cytospins were prepared on coated slides using 1 × 10 5 cells with a Thermo Scientific Shandon 4 Cytospin. For Giemsa staining, Giemsa stock solution (Solarbio, G1010) was diluted 1:10 with Giemsa dilution buffer. Slides were fixed with methanol for 2 min, stained with the diluted Giemsa solution for 15 min at room temperature, and rinsed twice with distilled water. Stained cells were imaged using an inverted microscope.

RNA-seq analysis

RNA was extracted from sorted BM primary erythroid progenitor cells and terminal erythroblasts. RNA isolation, cDNA library construction, and sequencing were performed at the Annoroad Gene Technology Institute on an Illumina NovaSeq 6000 platform using a PE150 (paired-end 150 bp) strategy, with libraries constructed from erythroid progenitors and terminal erythroblasts using the low-input Clontech SMART-Seq HT kit with Nxt HT (Takara Bio United States of America, San Jose, CA, United States of America). Raw RNA-seq data were filtered using fastp to remove low-quality reads. Gene expression was quantified with kallisto using the human reference genome hg38, and pairwise comparisons between groups were performed with DESeq2. Fold change ≥1.5 and adjusted p-value ≤0.05 were used to identify differentially expressed genes (DEGs). Principal component analysis (PCA) was conducted on log-transformed normalized counts for expressed genes. Gene Ontology (GO) enrichment analysis was performed using Metascape, with GO terms considered significant at adjusted p -value ≤0.01. Pathway enrichment analysis was performed using GSEA, with KEGG pathways considered significant at an adjusted FDR ≤0.25. The RNA-seq data supporting this study have been deposited in the NCBI Gene Expression Omnibus (GEO) database under accession number GSE301441 .

Intracellular ROS analysis

1 × 10 6 mononuclear cells were stained using the method of staining primary BM erythropoiesis. Then the cells were stained with CellROX dye H2DCFDA (Beyotime, S0035) at a final concentration of 5 μM for 20 min at 37 °C. The cells were then washed with ice-cold PBS and resuspended in the FACS buffer (PBS +3% FBS). Finally, stained cells were analyzed within 1 h using an LSR Fortessa flow cytometer (Becton Dickinson).

Differentiation of bone marrow CD34 + cells to erythroid cells

Hematopoietic stem/progenitor cells (HSPCs) were isolated using the Ultrapure CD34 Microbeads kit (Miltenyi Biotec, No. 130–100–453) according to the manufacturer’s protocol. The purified CD34 + cells were cultured in erythroid-inducing medium following established protocols ( Qu et al., 2018 ; Wang S. et al., 2022 ). The base medium consisted of Iscove’s Modified Dulbecco’s Medium (IMDM) supplemented with 3% human AB serum, 2% human plasma, 10 μg/mL insulin, 3 IU/mL heparin, and 1% penicillin/streptomycin. The culture was divided into four phases with specific cytokine supplementation: phase 1 (Day 0–7): 200 μg/mL holo-transferrin, 3 IU/mL EPO, 10 ng/mL SCF, and 1 ng/mL IL-3; phase 2 (Day 7–11): 200 μg/mL holo-transferrin, 1 IU/mL EPO, and 10 ng/mL SCF; phase 3 (Day 11–15): 1 mg/mL holo-transferrin and 1 IU/mL EPO; and phase 4 (Day 15–20): 1 mg/mL holo-transferrin alone. Medium changes were refreshed on days 4, 7, 11, and 15. The detailed experimental scheme is illustrated in Figure 6A .

Statistical analysis

SPSS Statistics 27.0.1 and GraphPad Prism 8 software were used for statistical analysis. FlowJo™ v10 software was used for FCS data analysis. The table data are presented as mean ± Standard Error of the Mean (SEM) or median (interquartile range, IQR), and comparisons are performed using independent-samples t-tests. Categorical variables are expressed as percentages, and the chi-squared test was used to compare them.

Results

Prevalence and clinical correlates of anemia in newly diagnosed multiple myeloma

In this study, we analyzed blood parameters from 300 healthy controls and 300 patients with newly diagnosed multiple myeloma (NDMM). Among the NDMM patients, 138 (46%) presented with anemia (hemoglobin <100 g/L) at diagnosis. Comprehensive clinical data, including demographic characteristics (age, gender), immunoglobulin isotypes, complete blood parameters, and key biochemical markers (albumin, urea, creatinine, serum calcium, lactate dehydrogenase [LDH], and β 2 -microglobulin [β 2 -MG]), are summarized in Table 1 . Disease staging was assessed using both the Durie-Salmon (DS) and International Staging System (ISS) criteria. Comparative analysis revealed significantly lower hemoglobin (HGB) levels, red blood cell (RBC) counts, and hematocrit (HCT) levels in NDMM patients compared with healthy controls ( Figures 1Aa–c ), along with elevated mean corpuscular volume (MCV) and red cell distribution width (RDW) ( Figures 1Ad,e ). According to International Myeloma Working Group criteria ( Rajkumar et al., 2014 ), the distribution of anemia severity was as follows: 11.67% (35/300) of patients had mild anemia (HGB 90–99 g/L), 31% (93/300) had moderate anemia (HGB 60–89 g/L), and 3.3% (10/300) had severe anemia (HGB <60 g/L) ( Figure 1B ). Among NDMM patients, the distribution of monoclonal immunoglobulin isotypes was comparable between the anemic and non-anemic groups ( Figure 1C ), suggesting no clear association between immunoglobulin isotype and anemia in MM patients. Notably, advanced-stage disease (Durie-Salmon stage III and R-ISS stage III) was associated with markedly lower hemoglobin levels ( Figures 1Da,b ), consistent with the previously reported correlation between disease progression and anemia severity ( Liu et al., 2020 ). Correlation analysis revealed a significant inverse relationship between bone marrow plasma cell percentage and hemoglobin levels in our patient cohort ( Figure 1E ), supporting earlier findings that plasma cell infiltration impairs erythropoiesis in MM-associated anemia. Overall, the clinical characteristics observed in this cohort corroborate earlier findings and provide a basis for further investigation.

The bone marrow erythroid progenitors showed quantitative and functional defects in NDMM-A patients

The erythropoiesis process comprises three main developmental stages: early-stage erythroid progenitors, including burst-forming unit-erythroid (BFU-E) and colony-forming unit-erythroid (CFU-E) cells; terminal erythroid differentiation, encompassing proerythroblasts (ProEs), basophilic erythroblasts (BasoEs), polychromatic erythroblasts (PolyEs), and orthochromatic erythroblasts (OrthoEs); and reticulocyte maturation, including reticulocytes (Retic) and mature red blood cells (RBCs) ( Da Costa et al., 2020 ; Ebert et al., 2008 ; Heimpel et al., 2006 ). To characterize defective erythropoiesis in NDMM patients, we systematically analyzed erythroblasts at different developmental stages using the cell surface markers CD34, CD117, IL3R, CD45RA, CD41a, CD71, CD105, and GPA, as well as the nucleic acid dye Hoechst33342 and the cell viability dye 7AAD ( Yan et al., 2021 ). Representative gating strategies of erythroid progenitor cells in mononuclear cells are shown in Figure 2A . Comparative analysis of erythroid progenitor cells revealed significant differences between HDs (0.67% ± 0.02%) and NDMM-A patients (0.17% ± 0.01%), NDMM-non anemia (0.60% ± 0.02%) and NDMM-A patients (0.17% ± 0.01%). In comparison, the HD (0.67% ± 0.02%) and NDMM-non-anemia (0.60% ± 0.02%) groups were comparable, as shown in Figure 2B . The impaired function of erythroid progenitor cells in NDMM-A was further confirmed by their reduced numbers of BFU-E and CFU-E colonies compared to those from HDs and NDMM-non anemia patients ( Figures 2C, a-b ). We next compared the colony-forming ability of erythroid progenitors among the NDMM-A, NDMM-non anemia, and HD groups. In the NDMM-A group, the sizes of BFU-E and CFU-E colonies were smaller than those in the control groups ( Figure 2D ; Supplementary Figure S1 ; Supplementary Figure S2 ). This observation was supported by quantitative analysis, which showed that the average cell number per BFU-E and CFU-E colony was significantly reduced in NDMM-A compared to both HDs and NDMM-non anemia ( Figures 2E,a,b ).

Transcriptome analyses revealed both a response to external stimulus and intrinsic dysregulation in erythroid progenitors from NDMM-A patients

To obtain a molecular understanding of impaired erythroid progenitor cells in NDMM, we performed transcriptomic analysis of primary BM early-stage erythroid progenitor cells (including BFU-E and CFU-E) from both normal individuals and patients with NDMM-associated anemia. The gating strategy for isolating human BM erythroid progenitors is shown in Supplementary Figure S3A . Cytospin images of sorted erythroid progenitor cells are shown in Supplementary Figure S3B . Principal component analysis (PCA) revealed separation between NDMM-A and HDs erythroid progenitor cells ( Supplementary Figure S4 ). Approximately 13,621 genes are depicted as a volcano plot, including 1538 differentially expressed genes (DEGs) ( Figure 3A ). The heatmap of differentially expressed genes (DEGs) expression is shown in Figure 3B , with the DEGs listed in Supplementary Table S1 . Gene ontology analysis of DEGs with increased or decreased expression in NDMM patients is shown in Figures 3C,D . Interestingly, DEGs with increased expression were not only involved in positive regulation of immune response ( Figure 3C ), such as OAS3 and OAS2 ( Figures 3E–a ) ( Padariya et al., 2021 ), but also included cytokines that play a role in immune modulatory, such as as IL1B ( Jefferies, 2019 ) and TNFSF13B ( Mackay and Browning, 2002 ) ( Figures 3E–b ). We also found that MYCT1 ( Figures 3E–c ), which is the key gene promoting apoptosis ( Fu et al., 2018 ), showed higher expression in NDMM-A erythroid progenitor cells than in HDs. These changes may be attributed to differences in the BM microenvironment between NDMM-A patients and HDs. On the other hand, the DEGs with decreased expression in NDMM-As are enriched in cell cycle-related pathways, such as CDC20 ( Gao et al., 2020 ) and AURKB ( Shaalan et al., 2021 ) ( Figures 3E-d ). To confirm this result, we performed an EdU incorporation assay to assess cell cycle status. As shown in Figures 3Fa–b , the percentages of cells in S-phase were much higher in HDs erythroid progenitor cells (∼30%) than in NDMM-A erythroid progenitor cells (∼18%), indicating a defective cell cycle of NDMM-A erythroid progenitor cells, which may contribute to the smaller size of colonies from NDMM-A.

In addition, erythroid-specific transcription factor GATA1 and GFI1B showed decreased expression, while myeloid transcription factor ELF1 showed increased expression ( Figure 3G ). GATA1 suppression is reported to be due to secreted CCL3 in MM patients ( Liu et al., 2020 ), which disrupts the switch and the balance between proliferation and differentiation ( Munugalavadla et al., 2005 ) . GFI1B is reported to regulate human erythroid differentiation through Smad2/TIF1-gamma ( Randrianarison-Huetz et al., 2010 ) . The downregulation of ELF1 is necessary for erythroid differentiation ( Calero-Nieto et al., 2010 ). Together, these findings suggest that the impaired proliferation and colony-forming ability of erythroid progenitors are both influenced by external stimulation and intrinsic dysregulation.

A global reduction occurred in each stage of terminal erythroblasts and reticulocytes in NDMM-A patients

We further systematically characterized terminal erythroblasts and reticulocytes by flow cytometry using CD71, Hoechst33342, CD105, and GPA markers ( Yan et al., 2021 ). Initial gating of CD71 + and GPA + populations consists of two distinct subsets: nucleated erythroblasts (Hoechst33342 + ) and reticulocytes (Hoechst33342 - ), shown as Figure 4A . Within the terminal erythroblasts (CD71 + GPA + Hoechst33342 + ) population, which were further separated into four precursor populations based on CD105 and GPA expression: GPA low CD105 high as ProEs, GPA high CD105 high/int as BasoEs, GPA high CD105 low as PolyEs, and GPA high CD105 - as OrthoEs ( Figure 4A ). Quantitative analysis revealed severe terminal erythroblast depletion in NDMM-A patients compared to HDs and NDMM-non anemia ( Figure 4B ). Stage-specific analysis demonstrated a decrease at each stage of terminal erythropoiesis in NDMM-A patients ( Figure 4C ). Furthermore, the percentage of reticulocytes in BM mononuclear cells (CD71 + GPA + Hoechst33342 - ) was also significantly decreased in NDMM-A patients compared to HDs and NDMM-non anemia ( Figure 4D ). These findings collectively highlight overall suppression at all stages of terminal erythropoiesis in NDMM-A patients.

Genes involved in the positive regulation of p53 signal and oxidative phosphorylation (OXPHOS) showed increased expression in terminal erythroblasts of NDMM-A patients

To understand the reduction of terminal erythroblasts in NDMM-A patients, we also performed comparative transcriptomic analysis between terminal erythroblasts (including ProEs, BasoEs, PolyEs, and OrthoEs) isolated from NDMM-A and HDs’ bone marrow. The gating strategy for isolating human BM terminal erythroblasts is shown in Supplementary Figure S3A . Cytospin images of sorted terminal erythroblasts are shown in Supplementary Figure S3B . Principal component analysis (PCA) revealed separation between NDMM-A and HDs terminal erythroblasts ( Supplementary Figure S5 ). A volcano plot shows approximately 13,724 genes, including 638 DEGs ( Figure 5A ). The heatmap of DEGs expression is shown in Figure 5B , with the DEGs listed in Supplementary Table S2 . GO enrichment of DEGs with increased expression in NDMM-A patients revealed dysregulation of translation, and positive regulation of signal transduction by p53 class mediator ( Figure 5C ). Interestingly, the expression levels of ribosome protein genes, including RPL37 , RPS15 , RPS20 , and RPL26 , which have been shown to lead to p53 stabilization and induce cell death and cell cycle arrest ( Daftuar et al., 2013 ; Zhang et al., 2010 ), were all significantly upregulated in NDMM-A terminal erythroblasts ( Figure 5D ). Gene set enrichment analysis (GSEA) further revealed upregulation of genes involved in oxidative phosphorylation (OXPHOS) in NDMM-A terminal erythroblasts ( Figure 5E ). Notably, expression levels of mitochondrial apoptosis marker, cytochrome c oxidase subunit Vic ( COX6C ) ( Wang C. et al., 2022 ), and also the expression of genes involved in the function of mitochondrial complex III, ubiquinol cytochrome c reductase binding protein ( UQCRB ) ( Jung et al., 2010 ), and ubiquinol cytochrome c reductase hinge ( UQCRH ) ( Gao et al., 2016 ) were significantly elevated in NDMM-A terminal erythroblasts with all fold change > 1 ( Figure 5F ). These components are known to promote mitochondrial reactive oxygen species (ROS) production. To validate these findings, we quantified intracellular ROS levels using DCFH-DA. Consistent with transcriptomic data, flow cytometric analysis confirmed elevated total ROS ( Figure 5G ) in NDMM-A terminal erythroblasts compared to HDs. Taken together, our results indicated that decreased terminal erythroblasts in NDMM-A patients were due to mitochondrial OXPHOS hyperactivation and p53 pathway induction, ultimately leading to ROS-mediated cell death.

Erythroid cells differentiated from BM CD34 + cells of NDMM-A patients exhibited impaired proliferation and enucleation

Previous studies have shown that extrinsic factors can influence erythropoiesis in MM patients with anemia ( Bouchnita et al., 2016 ). While it remains unclear whether the intrinsic erythroid differentiation is also compromised. Our transcriptomic analyses revealed both microenvironmental and intrinsic dysregulation, including decreased expression of key erythroid regulators, such as GATA1 and GFI1B . To confirm the intrinsic erythroid defects without the influence of the BM microenvironment, we compared the in vitro erythroid differentiation potential of BM HSPCs-CD34 + from anemic NDMM patients (NDMM-A-CD34 + ) to those from healthy controls (HDs-CD34 + ) using a three-phase erythroid differentiation protocol ( Qu et al., 2018 ; Wang S. et al., 2022 ), as detailed in Figure 6A . Cell growth was first monitored, and the growth curve is presented in Figure 6B . Under the same experimental conditions, HDs-CD34 + cells generated 6 times more erythroid cells than NDMM-A-CD34 + cells on culture day 15. To explore the underlying cause of this defective cell growth, we checked erythroblast apoptosis on different culture days. Representative flow cytometry plots of 7-AAD and Annexin V double staining on day 7 are shown in Figures 6C–a . Quantitative analysis revealed that significantly increased apoptosis in NDMM-A-CD34 + derived erythroid cells on days 4, 6, 7, 9, and 11 compared to HDs ( Figures 6C,b ). Next, we evaluated erythroid differentiation using GPA. The percentages of terminal erythroblasts were comparable between groups on days 4, 6, 7, and 9, indicating that the differentiation of erythroid cells was similar between HDs and from NDMM-A-CD34 + ( Figure 6D ).

Enucleation is the final step in erythropoiesis, and enucleation rates have been reported to correlate with disease status in MDS ( An et al., 2023 ). We also assessed this process using Hoechst33342 staining. Representative profiles are shown in Figures 6E–a . Quantitative analysis revealed a significantly lower enucleation rate in NDMM-A-CD34 + derived OrthoEs than in controls ( Figures 6E–b ). Consistent with these findings, morphological analysis on day 15 further supported defective erythroid maturation in NDMM-A patients ( Figure 6F ). Together, these data demonstrate that intrinsic impairments in erythroid development, particularly in survival and enucleation, contribute to anemia in NDMM patients.

Discussion

The mechanisms underlying anemia in newly diagnosed multiple myeloma (NDMM) remain poorly explored, despite its high prevalence and clinical consequences. Here, we integrated clinical, functional, and transcriptomic analyses to explain these mechanisms. Compared with healthy donors and NDMM-non anemia patients, NDMM patients with anemia exhibited reduced erythroid progenitors, terminal erythroblasts, and reticulocytes, along with impaired colony-forming capacity. Stage-specific transcriptomic dysregulation was observed; erythroid progenitor cells showed downregulation of cell cycle and key erythropoietic regulators, while terminal erythroblasts displayed activated oxidative phosphorylation and P53 pathways, accompanied by elevated ROS. In vitro culture of CD34 + cells further confirmed intrinsic erythroid defects, including poor proliferation, increased apoptosis, and defective enucleation in NDMM-A-derived erythroblasts. These results reveal stage-specific and cell-intrinsic erythropoietic impairment in MM, providing a transcriptomic resource for future research.

To investigate impaired erythropoiesis in NDMM-associated anemia, we first analyzed BM erythroid progenitor cells (BFU-E and CFU-E) from NDMM-A patients and controls. Flow cytometry analysis revealed a significant decrease in the proportion of erythroid progenitors in NDMM-A patients. This reduction was further confirmed by a decreased number of BFU-E and CFU-E colonies in methylcellulose assays. Moreover, the colony-forming capacity of these progenitors was compromised, as evidenced by a reduction in the number of cells per colony. These results indicate not only a quantitative decrease in erythroid progenitors in NDMM-A BM, but also an intrinsic functional impairment in their proliferative potential under standard culture conditions containing 3 U/ml rhEPO in methylcellulose medium. This finding aligns with earlier studies demonstrating a reduced number or reduced sensitivity of EPO receptors (EPOR) on BFU-E and CFU-E in myeloma patients, which can be partially restored by high concentrations of rhEPO ( Aoki et al., 1992 ). Reduced EPOR sensitivity may be linked to overproduction of cytokines in the BM microenvironment of MM patients. For instance, elevated serum levels of cytokines such as TNF-α ( Jasrotia et al., 2020 ) in NDMM patients can suppress erythropoiesis by downregulating EPOR signaling and key erythroid transcription factors (GATA-1, FOG-1) ( Buck et al., 2008 ). Consistently, our RNA-seq data of erythroid progenitor cells further confirmed the downregulation of EPOR expression (data not shown). EPOR downregulation in MM provides a mechanistic explanation for the observed erythroid progenitor cell dysfunction under physiological EPO levels in vitro . The impaired colony-forming ability of erythroid progenitors seems at odds with clinical observations that rh-EPO is effective in improving anemia in multiple myeloma patients. Actually, the standard therapeutic doses of rhEPO ( Terpos et al., 2015 ) (e.g., 30,000–40,000 U/week) far exceed the concentration used in colony assays (3 U/ml) and physiological status. High-dose rhEPO application likely overcomes the observed progenitor defect by supersaturating the available EPOR, thereby amplifying downstream survival and proliferative signals even in a setting of reduced receptor sensitivity or number.

Transcriptomic analysis revealed stage-specific regulation in early- and late-stage erythropoiesis in NDMM-A patients. Transcriptomic profiling of erythroid progenitors from NDMM-A revealed significant upregulation of the immune response pathway, including OAS3 and OAS2 , compared with HDs. Additionally, elevated IL1B expression was observed in NDMM-A patients, which is consistent with previous reports that plasma IL-1β level is correlated with the risk of cachexia in patients with MM ( Mazurek et al., 2024 ). It has been reported that myeloma-cell-secreted type I interferon (IFN) induces the expression of IFN-stimulated genes such as IFIT1, IFIT3, OAS2, and OAS3 , which are critically involved in innate antiviral responses ( Kawano et al., 2018 ), and our data showed consistent results. Furthermore, type I IFN production, particularly IFNα, has been shown to suppress erythropoiesis by negatively modulating erythropoietin (EPO) signaling ( Han et al., 2024 ). These observations collectively suggest a model in which tumor-mediated induction of type I IFN signaling contributes to anemia. The upregulation of IFN-responsive genes (e.g., OAS3, OAS2 ) and the cytokine IL1B in erythroblasts of NDMM-A patients may reflect a response to chronic inflammatory signals emanated from the malignant microenvironment. These alterations could impair erythroid maturation and amplify inflammatory cascades, potentially facilitating immune evasion by myeloma cells, thereby confirming the microenvironmental effects of erythropoiesis defects in MM. In addition, our ex vivo experiments indicated normal erythroid differentiation but a significantly reduced enucleation rate, which differs from the in vivo erythropoietic phenotype observed in MM patients. This discrepancy between in vivo and ex vivo findings further supports previous reports that the bone marrow microenvironment plays an essential role in the erythropoietic defects observed in anemic MM patients.

NDMM-A BM terminal erythroblasts indicated upregulation of genes involved in translation, p53-mediated pathway, and OXPHOS in NDMM-A patients. Elevated ROS levels were also confirmed in terminal erythroblasts from NDMM-A BM. The results indicated that p53 activation is an intrinsic response to the elevated oxidative environment, ultimately leading to a decrease in erythroid precursors.

In vitro studies are generated under controlled culture conditions with optimal levels of EPO and other erythroid-supportive cytokines, effectively decouple the intrinsic erythropoiesis from extrinsic inhibitory factors. The inherent defects are confirmed by in vitro differentiation assays, which indicated elevated apoptosis and defective enucleation in erythroblasts derived from NDMM-A CD34 + cells. The persistence of these defects in this context provides evidence for a cell-autonomous defect within the erythroid lineage of MM patients that is independent of the bone marrow microenvironment. However, the underlying mechanisms remain to be fully elucidated.

Together, anemia in MM patients is affected by both the microenvironment of erythropoiesis and intrinsic dysregulation within erythroblasts. These findings offer valuable insights for clinical intervention.

Acknowledgements

We gratefully acknowledge the support from the Institute of Hematology at Henan Provincial People’s Hospital, The Translational Medicine Center of Henan Provincial People’s Hospital, and the Institute of Erythroid Development, College of Life Sciences, Zhengzhou University.

Funding Statement

The author(s) declared that financial support was received for this work and/or its publication. This research was supported by the Science and Technology Research Project of Henan (Grant No. 232102311003), the National Natural Science Foundation of China (NSFC) grant (Grant No. 82400143, 82370126, 82470184, 82470116, 82300135). The Henan Provincial Medical Science and Technology Joint Provincial-Ministerial Program (Grant No. SBGJ202402017). Natural Science Foundation of Henan Province (252300421125).

Edited by: Yann Gibert , Indiana University, Purdue University Indianapolis, United States

Reviewed by: Michele Cea , University of Genoa, Italy

Shalini Sharma , University of Arizona, United States

Tao Guan , Shanxi Provincial Cancer Hospital, China

Abbreviations: MM, multiple myeloma; NDMM, newly diagnosed multiple myeloma; NDMM-non anemia, NDMM patients without anemia; NDMM-A, NDMM patients with anemia; NDMM-CD34 + , BM HSPCs-CD34 + from anemic NDMM patients; HDs-CD34 + , BM HSPCs-CD34 + from healthy controls; HSPCs, hematopoietic stem/progenitor cells; BFU-E, burst-forming unit-erythroid; CFU-E, colony-forming unit-erythroid cells; ProEs, proerythroblasts; BasoEs, basophilic erythroblasts; PolyEs, polychromatic erythroblasts; OrthoEs, orthochromatic erythroblasts; Retic, reticulocyte; RBCs, mature red blood cells; DEGs, differentially expressed genes.

Data availability statement

The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding authors.

Ethics statement

The studies involving humans were approved by Henan Provincial People’s Hospital (Approval No. 2023–013). The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participant's legal guardians/next of kin.

Author contributions

SW: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing – original draft, Writing – review and editing. WF: Investigation, Methodology, Writing – review and editing. CC: Data curation, Investigation, Writing – review and editing. HK: Resources, Writing – review and editing. SL: Data curation, Investigation, Writing – review and editing. JG: Resources, Writing – review and editing. DaL: Resources, Writing – review and editing. RM: Resources, Writing – review and editing. DoL: Methodology, Software, Writing – original draft. HC: Resources, Writing – review and editing. XQ: Supervision, Writing – review and editing. ML: Resources, riting – review and editing. CA: Funding acquisition, Resources, Writing – review and editing. HZ: Conceptualization, Funding acquisition, Project administration, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing. ZZ: Funding acquisition, Supervision, Validation, Visualization, Writing – review and editing.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcell.2026.1718025/full#supplementary-material

Representative images of BFU-E and CFU-E colonies derived from bone marrow (BM) cells of healthy controls and NDMM patients with anemia. Scale bar: 100 μm.

(A) Flow cytometry gating strategy for isolating BM erythroid progenitor cells and terminal erythroblasts from mononuclear cells in human bone marrow. (B) Representative images of sorted erythroid progenitors and terminal erythroblasts from healthy controls and NDMM patients with anemia. Scale bar: 20 μm.

Complete list of differentially expressed genes (DEGs) in BM erythroid progenitor cells from healthy controls and NDMM patients with anemia.

Complete list of differentially expressed genes (DEGs) in BM terminal erythroblasts from healthy controls and NDMM patients with anemia.

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Associated Data

Supplementary Materials

Representative images of BFU-E and CFU-E colonies derived from bone marrow (BM) cells of healthy controls and NDMM patients with anemia. Scale bar: 100 μm.

(A) Flow cytometry gating strategy for isolating BM erythroid progenitor cells and terminal erythroblasts from mononuclear cells in human bone marrow. (B) Representative images of sorted erythroid progenitors and terminal erythroblasts from healthy controls and NDMM patients with anemia. Scale bar: 20 μm.

Complete list of differentially expressed genes (DEGs) in BM erythroid progenitor cells from healthy controls and NDMM patients with anemia.

Complete list of differentially expressed genes (DEGs) in BM terminal erythroblasts from healthy controls and NDMM patients with anemia.

Data Availability Statement

The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding authors.