Longitudinal single-cell analysis of a myeloma mouse model identifies subclonal molecular programs associated with progression

• Published in: Nature communications Vol. 12; no. 1; p. 6322
• Main Authors: Croucher, Danielle C, Richards, Laura M, Tsofack, Serges P, Waller, Daniel, Li, Zhihua, Wei, Ellen Nong, Huang, Xian Fang, Chesi, Marta, Bergsagel, P Leif, Sebag, Michael, Pugh, Trevor J, Trudel, Suzanne
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 03.11.2021; Nature Publishing Group UK; Nature Portfolio
• Subjects: Animals; Copy number; Disease Models, Animal; Disease Progression; DNA Copy Number Variations; Gene expression; Genetic Heterogeneity; Heterogeneity; Humans; Mice; Mice, Inbred C57BL; Multiple myeloma; Multiple Myeloma - genetics; Multiple Myeloma - metabolism; Myc protein; Perturbation; Precursors; Protein Serine-Threonine Kinases - genetics; Single-Cell Analysis - methods; Therapeutic targets; Transcription; Tumors
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-021-26598-w

Molecular programs that underlie precursor progression in multiple myeloma are incompletely understood. Here, we report a disease spectrum-spanning, single-cell analysis of the Vκ*MYC myeloma mouse model. Using samples obtained from mice with serologically undetectable disease, we identify malignant cells as early as 30 weeks of age and show that these tumours contain subclonal copy number variations that persist throughout progression. We detect intratumoural heterogeneity driven by transcriptional variability during active disease and show that subclonal expression programs are enriched at different times throughout early disease. We then show how one subclonal program related to GCN2 stress response is progressively activated during progression in myeloma patients. Finally, we use chemical and genetic perturbation of GCN2 in vitro to support this pathway as a therapeutic target in myeloma. These findings therefore present a model of precursor progression in Vκ*MYC mice, nominate an adaptive mechanism important for myeloma survival, and highlight the need for single-cell analyses to understand the biological underpinnings of disease progression.