The Mechanisms of How Genomic Heterogeneity Impacts Bio-Emergent Properties: The Challenges for Precision Medicine
While the promise of precision medicine has generated excitement and high expectations, there are challenges for some key assumptions on which the concept is based. Since most common and complex diseases belong to adaptive systems where fuzzy inheritance interacts with the dynamic environment during nonlinear somatic cell evolution, both disease progression and treatment response are less predictable if based only on the precision of gene profiles. Although increased voices have expressed their concerns for this neo-reductionist approach (reduction based on big data), few have directly studied the conceptual limitations of precision medicine. In this chapter, we will focus on the relationship between bio-heterogeneity and emergent properties, a subject crucial to understanding why the targeting of lower-level agents (genes and pathways) provides unsatisfactory results at higher levels of this system such as clinical outcomes, which is practically the ultimate goal. Such analyses illustrate that dynamic interactions of heterogeneity in lower-level agents lead to the unpredictability of complex adaptive systems. As a result, stress-induced multiple genomic heterogeneity-mediated evolutionary processes present the greatest challenges for precision medicine.
This chapter is part of a series of studies entitled “The mechanisms of somatic cell and organismal evolution.”
- 6.Kolodkin A, Simeonidis E, Westerhoff HV. Computing life: add logos to biology and bios to physics. Prog Biophys Mol Biol. 2014;111(2–3):69–74.Google Scholar
- 13.Heng HH. Genome chaos: rethinking genetics, evolution, and molecular medicine. Cambridge: Academic Press; 2019.Google Scholar
- 20.Ye CJ, Liu G, Heng HH. Experimental induction of genome chaos. Methods Mol. Biol. 2018;1769:337–52.Google Scholar
- 26.Heppner GH, Miller BE. Therapeutic implications of tumor heterogeneity. Semin Oncol. 1989;16(2):91–105.Google Scholar
- 34.Sturmberg JS, Martin CM, editors. Handbook of systems and complexity in health. New York: Springer; 2013.Google Scholar