A population genetics perspective on the determinants of intra-tumor heterogeneity

Zheng Hu, Ruping Sun, Christina Curtis

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Cancer results from the acquisition of somatic alterations in a microevolutionary process that typically occurs over many years, much of which is occult. Understanding the evolutionary dynamics that are operative at different stages of progression in individual tumors might inform the earlier detection, diagnosis, and treatment of cancer. Although these processes cannot be directly observed, the resultant spatiotemporal patterns of genetic variation amongst tumor cells encode their evolutionary histories. Such intra-tumor heterogeneity is pervasive not only at the genomic level, but also at the transcriptomic, phenotypic, and cellular levels. Given the implications for precision medicine, the accurate quantification of heterogeneity within and between tumors has become a major focus of current research. In this review, we provide a population genetics perspective on the determinants of intra-tumor heterogeneity and approaches to quantify genetic diversity. We summarize evidence for different modes of evolution based on recent cancer genome sequencing studies and discuss emerging evolutionary strategies to therapeutically exploit tumor heterogeneity. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

Original languageEnglish (US)
Pages (from-to)109-126
Number of pages18
JournalBiochimica et Biophysica Acta - Reviews on Cancer
Volume1867
Issue number2
DOIs
StatePublished - Apr 2017
Externally publishedYes

Bibliographical note

Funding Information:
This work was funded by awards from the NIH (R01CA182514), Susan G. Komen Foundation (IIR13260750), and the Breast Cancer Research Foundation (BCRF-16-032) to C.C. Z.H. is supported by an Innovative Genomics Initiative (IGI) Postdoctoral Fellowship.

Publisher Copyright:
© 2017 Elsevier B.V.

Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

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