Characterizing heterogeneity in leukemic cells using single-cell gene expression analysis

DSpace/Manakin Repository

Characterizing heterogeneity in leukemic cells using single-cell gene expression analysis

Citable link to this page

 

 
Title: Characterizing heterogeneity in leukemic cells using single-cell gene expression analysis
Author: Saadatpour, Assieh; Guo, Guoji; Orkin, Stuart H; Yuan, Guo-Cheng

Note: Order does not necessarily reflect citation order of authors.

Citation: Saadatpour, Assieh, Guoji Guo, Stuart H Orkin, and Guo-Cheng Yuan. 2014. “Characterizing heterogeneity in leukemic cells using single-cell gene expression analysis.” Genome Biology 15 (12): 525. doi:10.1186/s13059-014-0525-9. http://dx.doi.org/10.1186/s13059-014-0525-9.
Full Text & Related Files:
Abstract: Background: A fundamental challenge for cancer therapy is that each tumor contains a highly heterogeneous cell population whose structure and mechanistic underpinnings remain incompletely understood. Recent advances in single-cell gene expression profiling have created new possibilities to characterize this heterogeneity and to dissect the potential intra-cancer cellular hierarchy. Results: Here, we apply single-cell analysis to systematically characterize the heterogeneity within leukemic cells using the MLL-AF9 driven mouse model of acute myeloid leukemia. We start with fluorescence-activated cell sorting analysis with seven surface markers, and extend by using a multiplexing quantitative polymerase chain reaction approach to assay the transcriptional profile of a panel of 175 carefully selected genes in leukemic cells at the single-cell level. By employing a set of computational tools we find striking heterogeneity within leukemic cells. Mapping to the normal hematopoietic cellular hierarchy identifies two distinct subtypes of leukemic cells; one similar to granulocyte/monocyte progenitors and the other to macrophage and dendritic cells. Further functional experiments suggest that these subtypes differ in proliferation rates and clonal phenotypes. Finally, co-expression network analysis reveals similarities as well as organizational differences between leukemia and normal granulocyte/monocyte progenitor networks. Conclusions: Overall, our single-cell analysis pinpoints previously uncharacterized heterogeneity within leukemic cells and provides new insights into the molecular signatures of acute myeloid leukemia. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0525-9) contains supplementary material, which is available to authorized users.
Published Version: doi:10.1186/s13059-014-0525-9
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4262970/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:13581185
Downloads of this work:

Show full Dublin Core record

This item appears in the following Collection(s)

 
 

Search DASH


Advanced Search
 
 

Submitters