Single-Cell Analysis in Cancer Genomics

Assieh Saadatpour; Shujing Lai; Guoji Guo; Guo-Cheng Yuan

doi:10.1016/j.tig.2015.07.003

Single-Cell Analysis in Cancer Genomics

Trends Genet. 2015 Oct;31(10):576-586. doi: 10.1016/j.tig.2015.07.003.

Authors

Assieh Saadatpour¹, Shujing Lai², Guoji Guo³, Guo-Cheng Yuan⁴

Affiliations

¹ Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
² Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China.
³ Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China. Electronic address: ggj@zju.edu.cn.
⁴ Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Harvard Stem Cell Institute, Cambridge, MA 02138, USA. Electronic address: gcyuan@jimmy.harvard.edu.

Abstract

Genetic changes and environmental differences result in cellular heterogeneity among cancer cells within the same tumor, thereby complicating treatment outcomes. Recent advances in single-cell technologies have opened new avenues to characterize the intra-tumor cellular heterogeneity, identify rare cell types, measure mutation rates, and, ultimately, guide diagnosis and treatment. In this paper we review the recent single-cell technological and computational advances at the genomic, transcriptomic, and proteomic levels, and discuss their applications in cancer research.

Publication types

Research Support, Non-U.S. Gov't
Review

MeSH terms

Computational Biology
Gene Expression Regulation, Neoplastic
Genome, Human*
Humans
Mutation
Neoplasms / genetics*
Neoplasms / pathology
Proteomics*
Single-Cell Analysis*

Grants and funding

R01 HL119099/HL/NHLBI NIH HHS/United States