The many faces of cancer evolution

Abstract

Cancer cells acquire genotypic and phenotypic changes over the course of the disease. A minority of these changes enhance cell fitness, allowing a tumor to evolve and overcome environmental constraints and treatment. Cancer evolution is driven by diverse processes governed by different rules, such as discrete and irreversible genetic variants and continuous and reversible plastic reprogramming. In this perspective, we explore the role of cell plasticity in tumor evolution through specific examples. We discuss epigenetic and transcriptional reprogramming in "disease progression" of solid tumors, through the lens of the epithelial-to-mesenchymal transition, and "treatment resistance", in the context endocrine therapy in hormone-driven cancers. These examples offer a paradigm of the features and challenges of cell plastic evolution, and we investigate how recent technological advances can address these challenges. Cancer evolution is a multi-faceted process, whose understanding and harnessing will require an equally diverse prism of perspectives and approaches.

Keywords: Cancer; Evolutionary Biology.

Figure 1

Cancer cell plasticity and cancer evolution (A) Schematic representation of the space of cell plasticity trajectories: a cancer cell (colored sphere) moves along two major axes: differentiation status (Y axis) and lineage commitment (X axis). (B) Cell plasticity features. Change of cell state for a cancer cell is color coded (initial state: blue, new state: red). (C) Challenges to address in the study of cell plasticity.

Figure 2

Dormancy in the context of clonal evolution (A) Many alternative models have been proposed to explain emergent genetic heterogeneity commonly observed in newly diagnosed cancers (gray subclones). By definition, curative surgery would remove the substrate for future evolution in the primary lesion. Further evolution of minimal residual disease (MRD) might be dependent on “nongenetic mechanisms”, especially under cytostatic treatment (gray→color transition). In this particular example, the color gradient represents phenotypic adaptation (multiple state transitions, i.e., dormancy entrance to tumor awakening) which can occur while mutational processes and generation of additional ITH are disfavored. Once cells resume proliferation, classical clonal evolution resumes on the backbone of a reprogrammed epigenome. (B) An example of nongenetic adaptation is the selection/induction of dormancy under therapeutic stress. During periods of low circulating hormone (before puberty and after menopause), estrogen-dependent cells appear to survive in a prolonged dormancy status (dark gray dots). We hypothesize that the transcriptional programs underlying endocrine therapies, which effectively mimic hormone deprivation, might possibly be a reboot of tissue-specific developmental pathways (i.e. preservation of hormone-sensing ERα during periods of low hormone circulation via induced/selected dormancy).

Figure 3

New technologies can disentagle nongenetic selection from trancriptional reprogramming (A) Nongenetic inheritance can operate as classical genetic Darwinian selection (i.e. a fitter phenotype is randomly generated before a change in the environment and sweeps through the population) or could be interpreted in a more Lamarckian way (i.e. a change in the external environment elicits a series of coordinate transcriptional responses which can then be fixed and inherited via epigenetic changes). (B) Feature selection or adaptive response (or a combination of thereof) can be tracked and traced by transforming classical genetic barcodes into transcriptional barcodes (inner colors) which can be captured at the same time of single-cell transcriptional profiles (outer colors). By matching lineages and transcriptomes at multiple time points, scientists can potentially deconvolute intermediate states driving the final resistant phenotype.