Trends in Cancer
ReviewModeling Tumor Clonal Evolution for Drug Combinations Design
Section snippets
Quantitative Approach To Study Tumor Evolution and Therapeutic Response
Recent data from tumor sequencing has increased attention on the broad relevance of intratumoral heterogeneity in cancer patients and their treatment. In light of these studies, the tumor biology field now more than ever regards cancer as an ongoing evolutionary process. As such, a systematic and comprehensive understanding of this malignancy and its dynamics will require capitalizing on quantitative methods from population genetics, evolution, and engineering. Several excellent reviews on
Tumor Clonal Evolution and Intratumoral Heterogeneity
The notion of cancer as a clonal evolutionary process dates to seminal work in 1976 by Nowell [13]. A key consequence of tumor clonal evolution is intratumoral heterogeneity – the founder clone develops successive alterations with fitness advantages subject to selection (see Glossary) forces (e.g., tumor progression, metastasis, and drug resistance). Heterogeneity in tumor cells across different regions was indeed observed by pathologists as early as the 1800s, based on cell morphology and
Quantitative Approaches to Modeling Clonal Evolution
Mathematical modeling of tumor development and metastasis has been the subject of comprehensive reviews periodically over the past decade 6, 29. Building on these, we will introduce here vital fundamental tools from population genetics [30] and evolutionary dynamics [31] as applied to cancer, and then move to emphasize a view of clonal evolution based on fitness landscapes and focus on relation to therapy. Mathematical studies of cancer began as early as the 1950s, from works by Nordling [32],
Fitness Landscapes
The mathematical models discussed thus far lack connection of genotype to phenotype, and of either or both to parameters characterizing ‘fitness’ of the population in a given environment (e.g., drug treatment condition). This can be accomplished via description of a fitness landscape (also known as adaptive landscape) 59, 60 – a mapping of a multidimensional genotype (and/or phenotype) space to its corresponding fitness. An idealized realization of this space may be seen in 3D (Figure 1A), with
Traversing the Fitness Landscape
Topology of landscapes is of particular importance because it provides information regarding evolutionary trajectories, predictability, or rate of adaptation. In particular, rugged landscapes (bearing multiple peaks and valleys) can occur as a result of sign epistasis, whereby the effects of a specific allele depend contextually on the genetic background at the other loci. This would cause particular paths along the fitness landscape to become inaccessible. Pathway inaccessibility in a rugged
Effects of Drug Treatment on Clonal Evolution
In parallel with the rising utility of NGS in studying intratumoral heterogeneity and tumor progression, analyses of matched biopsies of patients before and after drug treatment have also revealed extensive clonal dynamics. The mechanisms by which resistance/relapse occurs can be via (i) de novo mutations (e.g., genotoxic chemotherapy that induces mutagenesis), (ii) selection of a pre-existing resistant subclone with higher fitness, or (iii) tumor reduction and competitive release (whereby
Concluding Remarks
With our increased focus on viewing cancer through the evolutionary lens, we must necessarily equip ourselves with the quantitative tools from population genetics, evolutionary dynamics, and engineering to understand how cancer evolves and respond to treatment. We have presented here an overview of the quantitative approaches (Figure 2) that are becoming increasingly used in cancer research. Coupled with the enabling technology of high-throughput NGS, several themes are starting to emerge that
Acknowledgment
This work was supported by the Koch Institute Support (core) grant P30-CA14051 from the National Cancer Institute and the Integrative Cancer Biology Program grant U54-CA112967 (to M.T.H., D.A.L). B.Z. is supported by National Institutes of Health (NIH)/National Institute of General Medical Sciences (NIGMS) Interdepartmental Biotechnology Training Program 5T32GM008334.
Glossary
- Control theory
- studies the behavior of dynamical systems (e.g., electronics, mechanics, tumor population) in response to varying inputs, with the goal of developing ways to control the system and desired output responses.
- Deterministic process
- a deterministic process will always yield the same result given the same initial condition.
- Epistasis
- genetic interaction where the effect of one genetic alteration depends on the presence of one or more other alterations (genetic background).
- Exponential growth
References (128)
Dissecting cancer evolution at the macro-heterogeneity and micro-heterogeneity scale
Curr. Opin. Genet. Dev.
(2015)- et al.
Evolution of acquired resistance to anti-cancer therapy
J. Theor. Biol.
(2014) - et al.
Improving cancer treatment via mathematical modeling: surmounting the challenges is worth the effort
Cell
(2015) - et al.
Tracing the tumor lineage
Mol. Oncol.
(2010) Cancer initiation with epistatic interactions between driver and passenger mutations
J. Theor. Biol.
(2014)- et al.
Tumor heterogeneity: causes and consequences
Biochim. Biophys. Acta
(2010) Locally disordered methylation forms the basis of intratumor methylome variation in chronic lymphocytic leukemia
Cancer Cell
(2014)Isolation of a highly quiescent subpopulation of primitive leukemic cells in chronic myeloid leukemia
Blood
(1999)Population genetics of tumor suppressor genes
J. Theor. Biol.
(2005)A branching process model of ovarian cancer
J. Theor. Biol.
(2012)