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Clin Transl Med. 2017 Dec 28;6(1):46. doi: 10.1186/s40169-017-0177-y.

Using single-cell multiple omics approaches to resolve tumor heterogeneity.

Author information

1
Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA.
2
Department of Molecular Biosciences and Bioengineering, Honolulu, HI, USA.
3
Icahn Institute and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
4
Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA. lgarmire@cc.hawaii.edu.
5
Department of Molecular Biosciences and Bioengineering, Honolulu, HI, USA. lgarmire@cc.hawaii.edu.

Abstract

It has become increasingly clear that both normal and cancer tissues are composed of heterogeneous populations. Genetic variation can be attributed to the downstream effects of inherited mutations, environmental factors, or inaccurately resolved errors in transcription and replication. When lesions occur in regions that confer a proliferative advantage, it can support clonal expansion, subclonal variation, and neoplastic progression. In this manner, the complex heterogeneous microenvironment of a tumour promotes the likelihood of angiogenesis and metastasis. Recent advances in next-generation sequencing and computational biology have utilized single-cell applications to build deep profiles of individual cells that are otherwise masked in bulk profiling. In addition, the development of new techniques for combining single-cell multi-omic strategies is providing a more precise understanding of factors contributing to cellular identity, function, and growth. Continuing advancements in single-cell technology and computational deconvolution of data will be critical for reconstructing patient specific intra-tumour features and developing more personalized cancer treatments.

KEYWORDS:

Cancer; Gene expression; Heterogeneity; Methylation; Multi-omics; Mutation; Single-cell sequencing

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