Computational disease progression modeling can provide insights into cancer evolution

摘要

The development of cancer from a single transformed cell to a biologically complex and potentially lethal disease proceeds through the expansion of divergent clonal lineages that establish distinct subpopulations [ ]. This process can be viewed as a Darwinian, multistep evolutionary process at the cellular level driven by intrinsic cell characteristics, most notably the accumulation of genetic alterations, and selection pressures exerted by a co-evolving tumor microenvironment. An understanding of tumor evolution would provide valuable insights into tumor biology and establish a framework for the development of improved cancer taxonomies, prognostics and targeted therapeutics. Conceptual models of evolution have been inferred from the chronological ordering of mutations in single or related tumors, but established models derived from human tumor tissue data that describe cancer progression are lacking for most histotypes.