An Evolutionary Approach to Clonally Complex Hematologic Disorders

Abstract

Emerging clonal complexity has brought into question the way in which we perceive and, in turn, treat disorders of the hematopoietic system. Former models of cellintrinsic clonal dominance driven by acquisition of driver genes in a stereotypic sequence are often insufficient in explaining observations such as clonal hematopoiesis, and new paradigms are in order.Here, we review the evidence within the hematologic malignancy field and also borrow from perspectives rooted in evolutionary biology to reframe pathogenesis of hematologic disorders as dynamic processes involving complex interplays of genetic and nongenetic subclones and the tissue microenvironment in which they reside.Significance: Hematopoietic malignant and premalignant syndromes exhibit vast clonal diversity that is subject to selection imposed by the tissue microenvironment, as well as artificial selection by therapy. Tackling these disorders requires an appreciation of heterogeneity at both genetic and nongenetic levels, which can be borrowed from evolutionary biology principles. Models and drug development strategies that veer away from targeting solely dominant clones and, instead, embrace this complexity to outsmart it are required for long-term remission.

Toward a systems-level probing of tumor clonality

“… 104 Though not as well-studied, additional non-genetic programs associated with transcriptional control, RNA splicing, and chromatin and DNA states can further diversify the gamut of cell-intrinsic variabilities that may in turn impart clonal fitness. 13 , 105 Therefore, the genetic and non-genetic diversity reported in CHIP is a multiscale process, likely operating through a combination of changes on molecular, cellular, and chronological levels ( Figure 3 B). These changes may be a direct consequence of aging or could themselves be drivers of the “aging phenotype”; decoupling these cell-intrinsic and extrinsic scenarios will be critical to pursue in future studies.…”

Multi-omics analysis of longitudinal patient samples reveals the molecular mechanism of AML progression

“…Additionally, there are only a few studies that compare the mutational profiles of diagnosis and relapse samples in AML patients, and they focus on coding mutations (Farrar et al, 2016;Masetti et al, 2016), despite growing evidence that non-coding mutations in regulatory elements or structural variants altering enhancer usage can also drive oncogenesis (Northcott et al, 2014;Zhu et al, 2020). This underscores the significance of epigenetic changes in the course of the disease and emphasizes the necessity of considering the intrinsic and extrinsic disease heterogeneity (Levin et al, 2021;Schwenger & Steidl, 2021;Vicente-Dueñas et al, 2018). Furthermore, there is a paucity of comprehensive molecular characterization of longitudinal AML samples, including diagnosis and relapse pairs.…”