The Ecology and Evolution of Cancer: The Ultra-Microevolutionary Process

Author:

Wu Chung-I123,Wang Hurng-Yi4,Ling Shaoping12,Lu Xuemei2

Affiliation:

1. State Key Laboratory of Biocontrol, College of Ecology and Evolution, Sun Yat-Sen University, Guangzhou 510275, China;

2. CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China;

3. Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637;

4. Graduate Institute of Clinical Medicine and Hepatitis Research Center, National Taiwan University and Hospital, Taipei 106, Taiwan;

Abstract

Although tumorigenesis has been accepted as an evolutionary process ( 20 , 102 ), many forces may operate differently in cancers than in organisms, as they evolve at vastly different time scales. Among such forces, natural selection, here defined as differential cellular proliferation among distinct somatic cell genotypes, is particularly interesting because its action might be thwarted in multicellular organisms ( 20 , 29 ). In this review, selection is analyzed in two stages of cancer evolution: Stage I is the evolution between tumors and normal tissues, and Stage II is the evolution within tumors. The Cancer Genome Atlas (TCGA) data show a low degree of convergent evolution in Stage I, where genetic changes are not extensively shared among cases. An equally important, albeit much less highlighted, discovery using TCGA data is that there is almost no net selection in cancer evolution. Both positive and negative selection are evident but they neatly cancel each other out, rendering total selection ineffective in the absence of recombination. The efficacy of selection is even lower in Stage II, where neutral (non-Darwinian) evolution is increasingly supported by high-density sampling studies ( 81 , 123 ). Because natural selection is not a strong deterministic force, cancers usually evolve divergently even in similar tissue environments.

Publisher

Annual Reviews

Subject

Genetics

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