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Clinical and Translational Medicine
Published in: Clinical and Translational Medicine 1/2017

Open Access 01-12-2017 | Review

Using single-cell multiple omics approaches to resolve tumor heterogeneity

Authors: Michael A. Ortega, Olivier Poirion, Xun Zhu, Sijia Huang, Thomas K. Wolfgruber, Robert Sebra, Lana X. Garmire

Published in: Clinical and Translational Medicine | Issue 1/2017

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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.
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Metadata
Title
Using single-cell multiple omics approaches to resolve tumor heterogeneity
Authors
Michael A. Ortega
Olivier Poirion
Xun Zhu
Sijia Huang
Thomas K. Wolfgruber
Robert Sebra
Lana X. Garmire
Publication date
01-12-2017
Publisher
Springer Berlin Heidelberg
Published in
Clinical and Translational Medicine / Issue 1/2017
Electronic ISSN: 2001-1326
DOI
https://doi.org/10.1186/s40169-017-0177-y

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