Convergence of oncogenic cooperation at single-cell and single-gene levels drives leukemic transformation

Identifying how genetic alterations cooperate in cancer is challenging. Here the authors analyze leukemia mouse models with both oncogenic NRAS and EZH2 mutations using single-cell RNA-sequencing, evaluate oncogenic cooperation, and identify GEM as a regulator of leukemia-initiating cells. Cancers develop from the accumulation of somatic mutations, yet it remains unclear how oncogenic lesions cooperate to drive cancer progression. Using a mouse model harboring NRas(G12D) and EZH2 mutations that recapitulates leukemic progression, we employ single-cell transcriptomic profiling to map cellular composition and gene expression alterations in healthy or diseased bone marrows during leukemogenesis. At cellular level, NRas(G12D) induces myeloid lineage-biased differentiation and EZH2-deficiency impairs myeloid cell maturation, whereas they cooperate to promote myeloid neoplasms with dysregulated transcriptional programs. At gene level, NRas(G12D) and EZH2-deficiency independently and synergistically deregulate gene expression. We integrate results from histopathology, leukemia repopulation, and leukemia-initiating cell assays to validate transcriptome-based cellular profiles. We use this resource to relate developmental hierarchies to leukemia phenotypes, evaluate oncogenic cooperation at single-cell and single-gene levels, and identify GEM as a regulator of leukemia-initiating cells. Our studies establish an integrative approach to deconvolute cancer evolution at single-cell resolution in vivo.

Automated summary

Identifying how genetic alterations cooperate in driving cancer progression is challenging. This study analyzed leukemia mouse models with oncogenic NRAS and EZH2 mutations, revealing their cooperation in regulating leukemia-initiating cells and identifying GEM as a potential regulator. Integrating histopathology, leukemia repopulation, and leukemia-initiating cell assays helped validate transcriptome-based cellular profiles and elucidate the role of gene mutations in cancer evolution at single-cell resolution in vivo.