bioRxivCancer BiologyPreprint
Recurrent leukaemia stem cell states define the antigenic landscape of paediatric Acute Myeloid Leukaemia
Sina KanannejadiD, Macarena Oporto EspuelasiD, Claudia D’OriaiD, Filippo MartignanoiD, Ilaria Marina MichelozziiD, Soumick ChatterjeeiD, Edoardo GiacopuzziiD, Eduardo Gomez Castaneda, Aurora Casiraghi, Theodoros XenakisiD, George T. HalliD, Efstratios KirtsiosiD, Cecilia ReyneriiD, Hannah L. MacphersoniD, Jack Luke BartramiD, Rebecca Thomas, Sergi CastellanoiD, Persis Jal AmroliaiD, Alice GiustacchiniiD
Abstract
Paediatric acute myeloid leukaemia (pAML) remains a leading cause of childhood cancer mortality, with disease heterogeneity representing a major obstacle to effective immunotherapy. To enable rational immunotherapy design accounting for such heterogeneity, we combined single-cell transcriptomics and surface proteomics (CITE-seq). Using an integrated framework for malignant cell identification and unbiased gene program identification, we resolved three conserved leukaemia stem cell (LSC) subtypes, primitive (P-LSC), monocytic (M-LSC), and erythroid-like (E-LSC), that frequently coexist within individual patients in varying proportions and represent distinct stem-cell states with characteristic immunophenotypes and transcriptional programmes. Quantitative surface antigen profiling revealed that no single target achieved full LSC coverage. CLEC12A, an antigen currently being evaluated clinically, was expressed across P-LSC and M-LSC but was largely absent from E-LSC. In contrast, CD84 provided complementary coverage in the P and M groups and served as the primary target in the E-LSC population. The combination of CLEC12A and CD84 provided broad coverage across all three LSC subtypes, while sparing healthy haematopoietic stem cells. Validation across independent single-cell and bulk cohorts confirmed the robustness of this combination. These findings establish a paediatric-specific framework for antigen prioritisation in AML, identify CLEC12A/CD84 as a robust dual-targeting strategy across heterogeneous LSC states, and provide a blueprint for the rational design of next-generation CAR T-cell combinations.
- organism: human
- assay: scRNA-seq
- assay: CITE-seq
- research focus: cell type annotation
- approach: statistical model
- Citations
- 0
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