A general approach for detecting expressed mutations in AML cells using single cell RNA-sequencing
Year: 2019
Type: article
Abstract: Virtually all tumors are genetically heterogeneous, containing mutationally-defined subclonal cell populations that often have distinct phenotypes. Single-cell RNA-sequencing has revealed that a variety of tumors are also transcriptionally heterogeneous, but the relationship between expression heterogeneity and subclonal architecture is unclear. Here, we address this question in the context of Acute Myeloid Leukemia (AML) by integrating whole genome sequencing with single-cell RNA-sequencing (using the 10x Genomics Chromium Single Cell 5’ Gene Expression workflow). Applying this approach to five cryopreserved AML samples, we identify hundreds to thousands of cells containing tumor-specific mutations in each case, and use the results to distinguish AML cells (including normal-karyotype AML cells) from normal cells, identify expression signatures associated with subclonal mutations, and find cell surface markers that could be used to purify subclones for further study. This integrative approach for connecting genotype to phenotype is broadly applicable to any sample that is phenotypically and genetically heterogeneous.
Source: Nature Communications
Language: English
Subfield: Hematology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $5,200
Awards: G1405447797, G1951917308, G198466603, G2400099182, G2792050511, G2804094967, G2857667098, G3037337392, G3757861302, G4376424465, Genomics Of Acute Myeloid Leukemia., Molecular Pathogenesis of Acute Myeloid Leukemia, Comprehensive Informatic Analyses of AML Genomes and Epigenomes, Washington University Paul Calabresi K12 Career Development Award for Clinical Oncology
OpenAlex ID: W2968098426
