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Early and multiple origins of metastatic lineages within primary tumors.


ABSTRACT: Many aspects of the evolutionary process of tumorigenesis that are fundamental to cancer biology and targeted treatment have been challenging to reveal, such as the divergence times and genetic clonality of metastatic lineages. To address these challenges, we performed tumor phylogenetics using molecular evolutionary models, reconstructed ancestral states of somatic mutations, and inferred cancer chronograms to yield three conclusions. First, in contrast to a linear model of cancer progression, metastases can originate from divergent lineages within primary tumors. Evolved genetic changes in cancer lineages likely affect only the proclivity toward metastasis. Single genetic changes are unlikely to be necessary or sufficient for metastasis. Second, metastatic lineages can arise early in tumor development, sometimes long before diagnosis. The early genetic divergence of some metastatic lineages directs attention toward research on driver genes that are mutated early in cancer evolution. Last, the temporal order of occurrence of driver mutations can be inferred from phylogenetic analysis of cancer chronograms, guiding development of targeted therapeutics effective against primary tumors and metastases.

SUBMITTER: Zhao ZM 

PROVIDER: S-EPMC4776530 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Early and multiple origins of metastatic lineages within primary tumors.

Zhao Zi-Ming ZM   Zhao Bixiao B   Bai Yalai Y   Iamarino Atila A   Gaffney Stephen G SG   Schlessinger Joseph J   Lifton Richard P RP   Rimm David L DL   Townsend Jeffrey P JP  

Proceedings of the National Academy of Sciences of the United States of America 20160208 8


Many aspects of the evolutionary process of tumorigenesis that are fundamental to cancer biology and targeted treatment have been challenging to reveal, such as the divergence times and genetic clonality of metastatic lineages. To address these challenges, we performed tumor phylogenetics using molecular evolutionary models, reconstructed ancestral states of somatic mutations, and inferred cancer chronograms to yield three conclusions. First, in contrast to a linear model of cancer progression,  ...[more]

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