The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure¹. The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion^2,3. However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH)^4,5,6,7,8. Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention.

Single-cell RNA sequencing can reveal valuable insights into cellular heterogeneity within tumour microenvironments (TMEs), paving the way for a deep understanding of cellular mechanisms contributing to cancer. However, high heterogeneity among the same cancer types and low transcriptomic variation in immune cell subsets present challenges for accurate, high-resolution confirmation of cells’ identities. Here we present scATOMIC; a modular annotation tool for malignant and non-malignant cells. We trained scATOMIC on >300,000 cancer, immune, and stromal cells defining a pan-cancer reference across 19 common cancers and employ a hierarchical approach, outperforming current classification methods. We extensively confirm scATOMIC’s accuracy on 225 tumour biopsies encompassing >350,000 cancer and a variety of TME cells. Lastly, we demonstrate scATOMIC’s practical significance to accurately subset breast cancers into clinically relevant subtypes and predict tumours’ primary origin across metastatic cancers. Our approach represents a broadly applicable strategy to analyse multicellular cancer TMEs.

Disease recurrence causes significant mortality in B-progenitor acute lymphoblastic leukemia (B-ALL). Genomic analysis of matched diagnosis and relapse samples shows relapse often arising from minor diagnosis subclones. However, why therapy eradicates some subclones while others survive and progress to relapse remains obscure. Elucidation of mechanisms underlying these differing fates requires functional analysis of isolated subclones. Here, large-scale limiting dilution xenografting of diagnosis and relapse samples, combined with targeted sequencing, identified and isolated minor diagnosis subclones that initiate an evolutionary trajectory toward relapse [termed diagnosis Relapse Initiating clones (dRI)]. Compared with other diagnosis subclones, dRIs were drug-tolerant with distinct engraftment and metabolic properties. Transcriptionally, dRIs displayed enrichment for chromatin remodeling, mitochondrial metabolism, proteostasis programs, and an increase in stemness pathways. The isolation and characterization of dRI subclones reveals new avenues for eradicating dRI cells by targeting their distinct metabolic and transcriptional pathways before further evolution renders them fully therapy-resistant. Significance: Isolation and characterization of subclones from diagnosis samples of patients with B-ALL who relapsed showed that relapse-fated subclones had increased drug tolerance and distinct metabolic and survival transcriptional programs compared with other diagnosis subclones. This study provides strategies to identify and target clinically relevant subclones before further evolution toward relapse. See related article by E. Waanders et al.

Down with leukemia: Down syndrome is a congenital disorder caused by the trisomy of chromosome 21, and it is associated with a greatly increased risk of leukemia with origins in fetal development. Infants with Down syndrome are often born with a preleukemic condition, which later resolves in most cases. By using gene-edited human cells implanted into mouse models, Wagenblast et al. recapitulated the development of preleukemia and leukemia in the context of Down syndrome (see the Perspective by Roberts and Vyas). A specific mutation triggered a preleukemic condition in the context of trisomy 21 as expected, but progression to full-blown leukemia required a different genetic path and was not dependent on trisomy 21. Science , abf6202, this issue p. eabf6202 ; see also abj3957, p. 155

Accumulating evidence from clinical trials indicates that specific targeting of the IGF1 receptor (IGF1R) is not efficient as an anti-breast cancer treatment. One possible reason is that the mitogenic signals from the insulin receptor (IR) can be processed independently or as compensation to inhibition of the IGF1R. In this study, we highlight the role of the IR in mediating breast tumor progression in both WT mice and a hyperinsulinemic MKR mouse model by induction ofIr(Insr) orIgf1rknockdown (KD) in the mammary carcinoma Mvt-1 cell line. By using the specific IR antagonist-S961, we demonstrated thatIgf1r-KD induces elevated responses by the IR to IGF1. On the other hand,Ir-KD cells generated significantly smaller tumors in the mammary fat pads of both WT and MKR mice, as opposed to control cells, whereas theIgf1r-KD cells did not. The tumorigenic effects of insulin on the Mvt-1 cells were also demonstrated using microarray analysis, which indicates alteration of genes and signaling pathways involved in proliferation, the cell cycle, and apoptosis following insulin stimulation. In addition, the correlation between IR and the potential prognostic marker for aggressive breast cancer, CD24, was examined in theIr-KD cells. Fluorescence-activated cell sorting (FACS) analysis revealed more than 60% reduction in CD24 expression in theIr-KD cells when compared with the control cells. Our results also indicate that CD24-expressing cells can restore, at least in part, the tumorigenic capacity ofIr-KD cells. Taken together, our results highlight the mitogenic role of the IR in mammary tumor progression with a direct link to CD24 expression.