Genomics Inform.  2018 Dec;16(4):e17. 10.5808/GI.2018.16.4.e17.

Single-Cell Sequencing in Cancer: Recent Applications to Immunogenomics and Multi-omics Tools

Affiliations
  • 1Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA. jungmin.choi@rockefeller.edu
  • 2Laboratory of Human Genetics and Genomics, The Rockefeller University, New York, NY 10065, USA.

Abstract

Tumor heterogeneity, the cellular mosaic of multiple lineages arising from the process of clonal evolution, has continued to thwart multi-omics analyses using traditional bulk sequencing methods. The application of single-cell sequencing, in concert with existing genomics methods, has enabled high-resolution interrogation of the genome, transcriptome, epigenome, and proteome. Applied to cancers, these single-cell multi-omics methods bypass previous limitations on data resolution and have enabled a more nuanced understanding of the evolutionary dynamics of tumor progression, immune evasion, metastasis, and treatment resistance. This review details the growing number of novel single-cell multi-omics methods applied to tumors and further discusses recent discoveries emerging from these approaches, especially in regard to immunotherapy.

Keyword

computational biology; epigenomics; genetic heterogeneity; immunotherapy; neoplasms; single-cell analysis

MeSH Terms

Clonal Evolution
Computational Biology
Epigenomics
Genetic Heterogeneity
Genome
Genomics
Immune Evasion
Immunotherapy
Neoplasm Metastasis
Population Characteristics
Proteome
Single-Cell Analysis
Transcriptome
Proteome
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