EconPapers    
Economics at your fingertips  
 

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

Danielle C. Croucher, Laura M. Richards, Serges P. Tsofack, Daniel Waller, Zhihua Li, Ellen Nong Wei, Xian Fang Huang, Marta Chesi, P. Leif Bergsagel, Michael Sebag, Trevor J. Pugh () and Suzanne Trudel ()
Additional contact information
Danielle C. Croucher: University Health Network
Laura M. Richards: University Health Network
Serges P. Tsofack: University Health Network
Daniel Waller: McGill University
Zhihua Li: University Health Network
Ellen Nong Wei: University Health Network
Xian Fang Huang: McGill University
Marta Chesi: Mayo Clinic
P. Leif Bergsagel: Mayo Clinic
Michael Sebag: McGill University
Trevor J. Pugh: University Health Network
Suzanne Trudel: University Health Network

Nature Communications, 2021, vol. 12, issue 1, 1-14

Abstract: Abstract 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.

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-021-26598-w Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26598-w

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-021-26598-w

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-19
Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26598-w