Altered Interactions Between Unicellular And Multicellular Genes Drive Hallmarks Of Transformation In A Diverse Range Of Solid Tumors

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA(2017)

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摘要
Tumors of distinct tissues of origin and genetic makeup display common hallmark cellular phenotypes, including sustained proliferation, suppression of cell death, and altered metabolism. These phenotypic commonalities have been proposed to stem from disruption of conserved regulatory mechanisms evolved during the transition to multicellularity to control fundamental cellular processes such as growth and replication. Dating the evolutionary emergence of human genes through phylostratigraphy uncovered close association between gene age and expression level in RNA sequencing data from The Cancer Genome Atlas for seven solid cancers. Genes conserved with unicellular organisms were strongly up-regulated, whereas genes of metazoan origin were primarily inactivated. These patterns were most consistent for processes known to be important in cancer, implicating both selection and active regulation during malignant transformation. The coordinated expression of strongly interacting multicellularity and unicellularity processes was lost in tumors. This separation of unicellular and multicellular functions appeared to be mediated by 12 highly connected genes, marking them as important general drivers of tumorigenesis. Our findings suggest common principles closely tied to the evolutionary history of genes underlie convergent changes at the cellular process level across a range of solid cancers. We propose altered activity of genes at the interfaces between multicellular and unicellular regions of human gene regulatory networks activate primitive transcriptional programs, driving common hallmark features of cancer. Manipulation of cross-talk between biological processes of different evolutionary origins may thus present powerful and broadly applicable treatment strategies for cancer.
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关键词
cancer, evolution, transcriptomics, systems biology, atavism
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