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

Yuxuan Liu, Zhimin Gu, Hui Cao, Pranita Kaphle, Junhua Lyu, Yuannyu Zhang, Wenhuo Hu, Stephen S. Chung, Kathryn E. Dickerson and Jian Xu ()
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Yuxuan Liu: University of Texas Southwestern Medical Center
Zhimin Gu: University of Texas Southwestern Medical Center
Hui Cao: University of Texas Southwestern Medical Center
Pranita Kaphle: University of Texas Southwestern Medical Center
Junhua Lyu: University of Texas Southwestern Medical Center
Yuannyu Zhang: University of Texas Southwestern Medical Center
Wenhuo Hu: Memorial Sloan Kettering Cancer Center
Stephen S. Chung: University of Texas Southwestern Medical Center
Kathryn E. Dickerson: University of Texas Southwestern Medical Center
Jian Xu: University of Texas Southwestern Medical Center

Nature Communications, 2021, vol. 12, issue 1, 1-17

Abstract: Abstract 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 NRasG12D 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, NRasG12D 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, NRasG12D 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.

Date: 2021
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DOI: 10.1038/s41467-021-26582-4

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