Variables significant for survival analysis in univariate analysis

MDSRS+ event free survival (EFS) stratified by estimated MEP percentage in the four genetic subgroups (A-D).

Myeloid malignancies are clonal diseases of haematopoietic stem cell or haematopoietic progenitor cell origin, for which allogeneic haematopoietic stem cell transplantation remains the only curative treatment for most patients. However, the severe side effects and high relapse rates underscore the need for novel therapies. The success of adoptive transfer of chimeric antigen receptor (CAR) T cells targeting B cell-specific cell surface molecules in B cell cancers has not been replicated in myeloid malignancies. T cells engineered to express cancer-directed T cell receptors (TCRs) could provide an alternative, enabling targeting also of the intracellular proteome. In this Perspective, we have collated and reviewed available data from clinical trials exploiting TCR-engineered T cells for the treatment of haematological malignancies and discuss specific characteristics that make myeloid malignancies attractive candidates for TCR-based therapies. We also highlight the need to efficiently target the rare and notoriously therapy-resistant leukaemic stem cells, which represent the roots of myeloid malignancies, to achieve cures. This will require identification of novel targets and TCRs, and we discuss different target categories and strategies that can be applied towards this goal. We also highlight the importance of standardized preclinical testing and publicly available data to enable rapid identification and clinical advancement of promising TCRs towards clinical application. Allogeneic haematopoietic stem cell transplantation remains the cornerstone of curative treatment for advanced myeloid malignancies. In this Perspective, Foldvari et al. propose that T cells engineered to express tumour-reactive T cell receptors (TCRs) may offer a safer and more effective alternative. They outline key considerations for identifying and validating suitable target antigens and matching TCRs, and for advancing these therapies towards clinical application.

UMAP plot of MDSRS+ bone marrow CD34 mononuclear cells transcriptomes. Each point is one patient, overlaid with results from unsupervised clustering.

Cumulative proportion of principal components derived from principal component analysis. The first 14 explain 2/3 of the total variability.

– Results from Gene Ontology enrichment analysis (molecular function dataset) for the top 250 contributors of principal component 1 (PC1)

Treatment. Number of cases that underwent to each treatment category and the associated hazard-ratio for death is reported for each genetic subgroup and for the whole cohort.

Clonal hierarchy analysis of SF3B1-SRSF2 co-mutated cases. A. Results from the hierarchical rank analysis of mutations detected by DNAseq in the 4 cases harboring both SF3B1 and SRSF2 mutation using Pyclone. The analysis was also performed using DPClust, which provided converging results (data not shown). Tumor cell fraction (axes) for each detected clone and its 95% confidence interval (dot size) is represented in a scatter-plot, using different color according to the cluster driving mutation (SF3B1, red; SRSF2, blue; other drivers, gray). SF3B1 dominancy in MDS392 and MDS 640, together with the SRSF2 large clone size are suggestive of both splicing factor mutations in the same clone. On the contrary, MDS694 and MDS965 had a dominant SF3B1 clone associated with a very little and probably independent SRSF2 secondary clone. B. Results from single-cell derived colony-forming unit (CFU) genotyping confirming the concurrent double splicing factor mutations within the same clone in patient MDS382 and MDS640. CFU experiment was not carried out for the other two cases because of the very low probability of SF3B1/SRSF2 double positive clone identification, as already suggested by current data in the literature related to the presence of SF3B1K700E mutation (ref. 1).

Prognostic effect of genomic and transcriptomic analyses on MDSRS+ outcome. Overall survival (OS) stratified by genomic (A), transcriptomic classification (B) and estimated MEP percentage (C) in all MDSRS+ (A-C) and MDS-RS-SLD/MLD only (D-F). Multivariable Cox proportional hazard model for OS in all MDSRS+ including age, IPSS-mol score and estimated MEP percentage as continuous variables (G). OS stratified by estimated MEP percentage and IPSS-mol risk category (full representation of the 6 IPSS-mol categories shown in Supplemental Figure 21B).

Transcriptomic impact on SF3B1 mutant MDS and low blasts outcome. Overall survival (OS) and Event Free Survival (EFS) stratified by transcriptomic classification (A-B) and estimated MEP percentage (C-D), respectively, in SF3B1 mutant MDS and low blasts, as defined according to ICC and WHO 2022 classification.

Dynamic steady-state lineage contribution of human hematopoietic stem cell (HSC) clones needs to be assessed over time. However, clonal contribution of HSCs has only been investigated at single time points and without assessing the critical erythroid and platelet lineages. Here we screened for somatic mutations in healthy aged individuals, identifying expanded HSC clones accessible for lineage tracing of all major blood cell lineages. In addition to HSC clones with balanced contribution to all lineages, we identified clones with all myeloid lineages but no or few B and T lymphocytes or all myeloid lineages and B cells but no T cells. No other lineage restriction patterns were reproducibly observed. Retrospective phylogenetic inferences uncovered a 'hierarchical' pattern of descendant subclones more lineage biased than their ancestral clone and a more common 'stable' pattern with descendant subclones showing highly concordant lineage contributions with their ancestral clone, despite decades of separation. Prospective lineage tracing confirmed remarkable stability over years of HSC clones with distinct lineage replenishment patterns.

List of differentially expressed genes associated with EMK, INT and IMP profile.

Demographic and clinical features of cases and controls included into the study.

EMK and IMP signature validation on HSPC sorted populations. Differential gene expression analysis across MDSRS+ with EMK profile, MDSRS- with IMP profile and NBM (3 cases each) according to Lin marker expression. Differential expressed genes (row) between EMK and IMP groups were selected. Each row represents a gene, and each column represents a sample. Design comparison (case) and sorted population (condition) are shown as covariates.

Hemogenic endothelium (HE) is recognized as the origin of all definitive blood cells, including hematopoietic stem cells (HSCs); however, the mechanisms governing the hematopoietic progenitor versus HSC fate choice within the HE remain unknown. Here we combine differentiation assays with full-length single-cell transcriptome data for extra-embryonic yolk sac (YS) and intra-embryonic aorta–gonad–mesonephros (AGM) region HE populations. We identified and localized three differentiation trajectories, each containing a distinct HE subset: erythromyeloid progenitor-primed HE in the YS plexus, lymphomyeloid progenitor-primed HE in large YS arteries and hematopoietic stem and progenitor cell-primed HE in the AGM. Chromatin modifiers and spliceosome components were enriched in AGM HE. This correlated with a higher isoform complexity of the AGM HE transcriptome. Distinct AGM HE-specific isoform expression patterns were observed for a broad range of genes, including stemness-associated factors like Runx1. Our data form a unique resource for studying cell fate decisions in different HE populations. Neo et al. map blood emergence from three hemogenic endothelial (HE) populations biased toward distinct blood fates. HE primed for stem progenitors shows elevated chromatin and RNA splicing gene expression and greater isoform diversity.

Item consensus for K=3 showing stable item-consensus values across the whole cohort.

Overall survival of MDSRS+ with SRSF2 and TP53MH genotype stratified by RS burden. Cases (colored Kaplan-Meier curves) were compared to historical controls (gray curve) with similar clinical and molecular features and no RS (i.e. RS<5%) from two large studies evaluating clinical characteristics of SRSF2 and TP53MH -mutated MDS, respectively (ref. 2,3). SF3B1 mutated MDSRS+ were not considered for this analysis because of the small number of cases with RS between 5 and 15% (2 out of 82 SF3B1-mutated ones) and consolidated evidences in the literature showing no effect of RS burden on SF3B1-mutated MDS outcome (ref. 4,5); sample size also limited further analysis in the MDSRS+ NOS category.

Unsupervised consensus clustering analysis on gene expression data. Consensus clustering applied to the MDSRS+ cohort revealed 3 transcriptomic profiles, named EMK, INT and IMP according to the results from gene set enrichment analysis.

Scatter plots comparing mean PSI values between the MDSRS+ and healthy donors used as normal bone marrow controls (NBM), stratified by genetic classification. Significantly associated events (FDR < 0.0001) are color coded by splicing alterations subtypes.