Determining cell type abundance and expression from bulk tissues with digital cytometry.

Determining cell type abundance and expression from bulk tissues with digital cytometry.

Publication date: May 06, 2019

Single-cell RNA-sequencing has emerged as a powerful technique for characterizing cellular heterogeneity, but it is currently impractical on large sample cohorts and cannot be applied to fixed specimens collected as part of routine clinical care. We previously developed an approach for digital cytometry, called CIBERSORT, that enables estimation of cell type abundances from bulk tissue transcriptomes. We now introduce CIBERSORTx, a machine learning method that extends this framework to infer cell-type-specific gene expression profiles without physical cell isolation. By minimizing platform-specific variation, CIBERSORTx also allows the use of single-cell RNA-sequencing data for large-scale tissue dissection. We evaluated the utility of CIBERSORTx in multiple tumor types, including melanoma, where single-cell reference profiles were used to dissect bulk clinical specimens, revealing cell-type-specific phenotypic states linked to distinct driver mutations and response to immune checkpoint blockade. We anticipate that digital cytometry will augment single-cell profiling efforts, enabling cost-effective, high-throughput tissue characterization without the need for antibodies, disaggregation or viable cells.

Newman, A.M., Steen, C.B., Liu, C.L., Gentles, A.J., Chaudhuri, A.A., Scherer, F., Khodadoust, Esfahani, Luca, B.A., Steiner, D., Diehn, M., and Alizadeh, A.A. Determining cell type abundance and expression from bulk tissues with digital cytometry. 22539. 2019 Nat Biotechnol.

Concepts Keywords
Antibodies Antibodies
Cell Type Sequencing
Cytometry Omics
Digital Cytometry
Dissection RNA-Seq
Heterogeneity Transcriptome
Immune Checkpoint Blockade Laboratory techniques
Melanoma Gene expression
Phenotypic Cell biology
RNA Sequencing RNA
Throughput Molecular biology
Transcriptomes Branches of biology
Tumor Melanoma

Semantics

Type Source Name
pathway BSID Melanoma
disease MESH melanoma
disease DOID melanoma
disease MESH tumor
disease MESH multiple
pathway BSID Gene Expression
gene UNIPROT LARGE1

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