Decoding the role of inflammatory signaling in shaping HSC heterogeneity and engraftment in gene therapy-treated β-thalassemia pediatric patients
Bibliographic record
Abstract
Abstract Stress conditions influence hematopoietic stem cell (HSC) fate and lineage output, underscoring hematopoietic flexibility to external stimuli. In β-thalassemia (Bthal), chronic bone marrow (BM) stress since anemia and ineffective erythropoiesis remodels the BM microenvironment, affecting HSC biology (Aprile et al Blood 2020). We recently showed that BM HSCs/MPPs (multipotent progenitors) in pediatric Bthal patients are activated and primed towards erythroid differentiation, with reduced stemness pathways, altered inflammatory signaling (e.g. TGFβ, TNFα-NFKB), and decreased dormancy signatures (Lidonnici MR et al., Nat Commun 2025). In the Tiget-Bthal clinical trial, HSC lentiviral gene therapy (GT) led to initial transfusion independence for most patients, correlating with engraftment of gene-corrected HSCs (Marktel S. et al. Nat Med 2019). However, a subset of pediatric patients showed poor engraftment with a drop in genetically marked cells post-GT despite optimal transduction efficiency and vector copy number (VCN) in the administered drug product and adequate conditioning, requiring transfusional support. We hypothesize that HSC heterogeneity and the status of BM microenvironment influence repopulating capacity and the consequent hematopoietic reconstitution in GT-treated patients. To investigate HSC diversity in nine Bthal patients treated with gene therapy, we performed single-cell RNA sequencing (scRNAseq) on CD34+ cells and HSCs/MPPs from BM pre-GT, mobilized peripheral blood (mPB, GT source), and BM post-GT. On the basis of clinical outcome and molecular follow-up, the patients here are referred to as with high (HE) or low engraftment (LE) of genetically modified cells. No difference in HSPC (hematopoietic stem and progenitor cell) composition in the CD34+ compartment was observed across timepoints or between HE and LE patients, consistently with immunophenotypic analyses. Gene set enrichment analysis using stemness signatures and MSigDB gene sets identified differences in HSCs/MPPs across samples. Specifically, mPB HSCs/MPPs from LE patients showed lower dormancy scores and reduced TNFα via NFkB signaling enrichment compared to HE patients. Integration with HSC meta-programs (Zeng et al., bioRxiv 2023) revealed that LE HSCs/MPPs had reduced enrichment for the inflammatory memory HSC program (HSC-iM), consistent with downregulation of TNFα via NFkB signaling. Analysis of differentially expressed genes by DESeq2 identified upregulation of IFN-responsive genes in LE mPB HSCs/MPPs. These data suggest diverse responses to inflammatory stimuli in a heterogeneous HSC population. Post-GT analysis showed that BM HSCs/MPPs in LE patients were more quiescent, exhibited reduced cycling, and showed an elevated hypoxic signature. These cells were enriched for the expression of dormancy-associated genes, as well as HSC-iM genes, including those related to the IFN-γ and IL-1 signaling pathways. Measurement of BM plasma cytokines (IFN-γ and IL-1b) correlated with HSC/MPP transcriptomic profiles, linking high basal homeostatic inflammatory microenvironment to stem cell status. It is noteworthy that TNFα, IFN-γ, and IL-1b levels were already altered in the BM plasma of Bthal patients compared to healthy controls. These data suggest that inflammatory stress, likely induced in Bthal BM by chronic stimulus to erythroid proliferation and hypoxia, may drive the affected HSC into dormancy as a protective adaptation to protect the integrity of the stem cell pool. Finally, re-analysis of vector integration sites (Calabria et al. Nature 2024), stratified by patients' groups, confirmed fewer active HSPCs in LE compared to HE patients, indicating reduced contribution of genetically modified HSPCs to hematopoiesis. Overall, our data indicate that the degree of HSC dormancy in the stem cell source and prevalence of inflammatory transcriptional signatures are critical to preserving HSC function and ensuring effective engraftment and hematopoietic reconstitution. Ongoing analyses using specific inflammatory-related signatures will delineate HSC subset composition and underscore heterogeneity concerning activation, lineage commitment, stemness, and inflammation. Understanding how distinct HSC subsets respond to inflammatory cues in vivo will guide strategies to predict patient responses and refine conditioning regimens or ex vivo manipulation protocols, ultimately improving gene therapy efficacy for β-thalassemia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".