BBA - Reviews on Cancer (v.1867, #2)
Title page (i).
Cancer biology and Mr. Darwin by Robert Gatenby (67-68).
Evolutionary scalpels for dissecting tumor ecosystems by Daniel I.S. Rosenbloom; Pablo G. Camara; Tim Chu; Raul Rabadan (69-83).
Amidst the growing literature on cancer genomics and intratumor heterogeneity, essential principles in evolutionary biology recur time and time again. Here we use these principles to guide the reader through major advances in cancer research, highlighting issues of “hit hard, hit early” treatment strategies, drug resistance, and metastasis. We distinguish between two frameworks for understanding heterogeneous tumors, both of which can inform treatment strategies: (1) The tumor as diverse ecosystem, a Darwinian population of sometimes-competing, sometimes-cooperating cells; (2) The tumor as tightly integrated, self-regulating organ, which may hijack developmental signals to restore functional heterogeneity after treatment. While the first framework dominates literature on cancer evolution, the second framework enjoys support as well. Throughout this review, we illustrate how mathematical models inform understanding of tumor progression and treatment outcomes. Connecting models to genomic data faces computational and technical hurdles, but high-throughput single-cell technologies show promise to clear these hurdles. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
Keywords: Cancer evolution; Intratumor heterogeneity; Combination therapy; Drug resistance; Genomics; Mathematical modeling;
Changing mutational and adaptive landscapes and the genesis of cancer by L. Alexander Liggett; James DeGregori (84-94).
By the time the process of oncogenesis has produced an advanced cancer, tumor cells have undergone extensive evolution. The cellular phenotypes resulting from this evolution have been well studied, and include accelerated growth rates, apoptosis resistance, immortality, invasiveness, and immune evasion. Yet with all of our current knowledge of tumor biology, the details of early oncogenesis have been difficult to observe and understand. Where different oncogenic mutations may work together to enhance the survival of a tumor cell, in isolation they are often pro-apoptotic, pro-differentiative or pro-senescent, and therefore often, somewhat paradoxically, disadvantageous to a cell. It is also becoming clear that somatic mutations, including those in known oncogenic drivers, are common in tissues starting at a young age. These observations raise the question: how do we largely avoid cancer for most of our lives? Here we propose that evolutionary forces can help explain this paradox. As humans and other organisms age or experience external insults such as radiation or smoking, the structure and function of tissues progressively degrade, resulting in altered stem cell niche microenvironments. As tissue integrity declines, it becomes less capable of supporting and maintaining resident stem cells. These stem cells then find themselves in a microenvironment to which they are poorly adapted, providing a competitive advantage to those cells that can restore their functionality and fitness through mutations or epigenetic changes. The resulting oncogenic clonal expansions then increase the odds of further cancer progression. Understanding how the causes of cancer, such as aging or smoking, affect tissue microenvironments to control the impact of mutations on somatic cell fitness can help reconcile the discrepancy between marked mutation accumulation starting early in life and the somatic evolution that leads to cancer at advanced ages or following carcinogenic insults. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
Keywords: Oncogenesis; Fitness landscapes; Microenvironment; Mutation; Somatic cell evolution;
Catch my drift? Making sense of genomic intra-tumour heterogeneity by Andrea Sottoriva; Chris P Barnes; Trevor A Graham (95-100).
The cancer genome is shaped by three components of the evolutionary process: mutation, selection and drift. While many studies have focused on the first two components, the role of drift in cancer evolution has received little attention. Drift occurs when all individuals in the population have the same likelihood of producing surviving offspring, and so by definition a drifting population is one that is evolving neutrally. Here we focus on how neutral evolution is manifested in the cancer genome. We discuss how neutral passenger mutations provide a magnifying glass that reveals the evolutionary dynamics underpinning cancer development, and outline how statistical inference can be used to quantify these dynamics from sequencing data. We argue that only after we understand the impact of neutral drift on the genome can we begin to make full sense of clonal selection.This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer? Edited by Dr. Robert A. Gatenby.
Keywords: Clonal evolution of cancer; Neutral evolution; Selection; Clones; Intra-tumour heterogeneity; Next generation sequencing;
PhyloOncology: Understanding cancer through phylogenetic analysis by Jason A. Somarelli; Kathryn E. Ware; Rumen Kostadinov; Jeffrey M. Robinson; Hakima Amri; Mones Abu-Asab; Nicolaas Fourie; Rui Diogo; David Swofford; Jeffrey P. Townsend (101-108).
Despite decades of research and an enormity of resultant data, cancer remains a significant public health problem. New tools and fresh perspectives are needed to obtain fundamental insights, to develop better prognostic and predictive tools, and to identify improved therapeutic interventions. With increasingly common genome-scale data, one suite of algorithms and concepts with potential to shed light on cancer biology is phylogenetics, a scientific discipline used in diverse fields. From grouping subsets of cancer samples to tracing subclonal evolution during cancer progression and metastasis, the use of phylogenetics is a powerful systems biology approach. Well-developed phylogenetic applications provide fast, robust approaches to analyze high-dimensional, heterogeneous cancer data sets. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
Keywords: Tumor heterogeneity; Cancer stratification; Clonal evolution; Tumor trees; Cancer types;
A population genetics perspective on the determinants of intra-tumor heterogeneity by Zheng Hu; Ruping Sun; Christina Curtis (109-126).
Cancer results from the acquisition of somatic alterations in a microevolutionary process that typically occurs over many years, much of which is occult. Understanding the evolutionary dynamics that are operative at different stages of progression in individual tumors might inform the earlier detection, diagnosis, and treatment of cancer. Although these processes cannot be directly observed, the resultant spatiotemporal patterns of genetic variation amongst tumor cells encode their evolutionary histories. Such intra-tumor heterogeneity is pervasive not only at the genomic level, but also at the transcriptomic, phenotypic, and cellular levels. Given the implications for precision medicine, the accurate quantification of heterogeneity within and between tumors has become a major focus of current research. In this review, we provide a population genetics perspective on the determinants of intra-tumor heterogeneity and approaches to quantify genetic diversity. We summarize evidence for different modes of evolution based on recent cancer genome sequencing studies and discuss emerging evolutionary strategies to therapeutically exploit tumor heterogeneity. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
Advances in understanding tumour evolution through single-cell sequencing by Jack Kuipers; Katharina Jahn; Niko Beerenwinkel (127-138).
The mutational heterogeneity observed within tumours poses additional challenges to the development of effective cancer treatments. A thorough understanding of a tumour's subclonal composition and its mutational history is essential to open up the design of treatments tailored to individual patients. Comparative studies on a large number of tumours permit the identification of mutational patterns which may refine forecasts of cancer progression, response to treatment and metastatic potential.The composition of tumours is shaped by evolutionary processes. Recent advances in next-generation sequencing offer the possibility to analyse the evolutionary history and accompanying heterogeneity of tumours at an unprecedented resolution, by sequencing single cells. New computational challenges arise when moving from bulk to single-cell sequencing data, leading to the development of novel modelling frameworks.In this review, we present the state of the art methods for understanding the phylogeny encoded in bulk or single-cell sequencing data, and highlight future directions for developing more comprehensive and informative pictures of tumour evolution. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
Keywords: Single-cell sequencing; Cancer evolution; Tumour heterogeneity; Phylogenetics;
Somatic clonal evolution: A selection-centric perspective by Jacob Scott; Andriy Marusyk (139-150).
It is generally accepted that the initiation and progression of cancers is the result of somatic clonal evolution. Despite many peculiarities, evolution within populations of somatic cells should obey the same Darwinian principles as evolution within natural populations, i.e. variability of heritable phenotypes provides the substrate for context-specific selection forces leading to increased population frequencies of phenotypes, which are better adapted to their environment. Yet, within cancer biology, the more prevalent way to view evolution is as being entirely driven by the accumulation of “driver” mutations. Context-specific selection forces are either ignored, or viewed as constraints from which tumor cells liberate themselves during the course of malignant progression. In this review, we will argue that explicitly focusing on selection forces acting on the populations of neoplastic cells as the driving force of somatic clonal evolution might provide for a more accurate conceptual framework compared to the mutation-centric driver gene paradigm. Whereas little can be done to counteract the “bad luck” of stochastic occurrences of cancer-related mutations, changes in selective pressures and the phenotypic adaptations they induce can, in principle, be exploited to limit the incidence of cancers and to increase the efficiency of existing and future therapies. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
Keywords: Cancer; Initiation; Progression; Natural selection; Selective pressures; Driver;
Tumor evolution: Linear, branching, neutral or punctuated? by Alexander Davis; Ruli Gao; Nicholas Navin (151-161).
Intratumor heterogeneity has been widely reported in human cancers, but our knowledge of how this genetic diversity emerges over time remains limited. A central challenge in studying tumor evolution is the difficulty in collecting longitudinal samples from cancer patients. Consequently, most studies have inferred tumor evolution from single time-point samples, providing very indirect information. These data have led to several competing models of tumor evolution: linear, branching, neutral and punctuated. Each model makes different assumptions regarding the timing of mutations and selection of clones, and therefore has different implications for the diagnosis and therapeutic treatment of cancer patients. Furthermore, emerging evidence suggests that models may change during tumor progression or operate concurrently for different classes of mutations. Finally, we discuss data that supports the theory that most human tumors evolve from a single cell in the normal tissue. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
Keywords: Single cell genomics; Intratumor heterogeneity; Tumor evolution; Cancer genomics; Genome evolution; Cancer biology;
Mutations, evolution and the central role of a self-defined fitness function in the initiation and progression of cancer by Robert A. Gatenby; Joel Brown (162-166).
The origin and progression of cancer is widely viewed as “somatic evolution” driven by the accumulation of random genetic changes. This theoretical model, however, neglects fundamental conditions for evolution by natural selection, which include competition for survival and a local environmental context. Recent observations that the mutational burden in different cancers can vary by 2 orders of magnitude and that multiple mutations, some of which are “oncogenic,” are observed in normal tissue suggests these neglected Darwinian dynamics may play a critical role in modifying the evolutionary consequences of molecular events. Here we discuss evolutionary principles in normal tissue focusing on the dynamical tension between different evolutionary levels of selection. Normal somatic cells within metazoans do not ordinarily evolve because their survival and proliferation are governed by tissue signals and internal controls (e.g. telomere shortening) that maintain homeostatic function. The fitness of each cell is, thus, identical to the whole organism, which is the evolutionary level of selection. For a cell to evolve, it must acquire a self-defined fitness function so that its survival and proliferation is determined entirely by its own heritable phenotypic properties. Cells can develop independence from normal tissue control through randomly accumulating mutations that disrupt its ability to recognize or respond to all host signals. A self-defined fitness function can also be gained non-genetically when tissue control signals are lost due to injury, inflammation, or infection. Accumulating mutations in cells without a self-defined fitness function will produce no evolution - consistent with reports showing mutations, including some that would ordinarily be oncogenic, are present in cells from normal tissue. Furthermore, once evolution begins, Darwinian forces will promote mutations that increase fitness and eliminate those that do not. Thus, cancer cells will typically have a mutational burden similar to adjacent normal cells and many (perhaps most) mutations observed in cancer cells occurred prior to somatic evolution and may not contribute to the cell's malignant phenotype. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
Keywords: Cancer evolution somatic mutations theory; Somatic evolution; Fitness function;
Mathematical models of cell phenotype regulation and reprogramming: Make cancer cells sensitive again! by David J. Wooten; Vito Quaranta (167-175).
A cell's phenotype is the observable actualization of complex interactions between its genome, epigenome, and local environment. While traditional views in cancer have held that cellular and tumor phenotypes are largely functions of genomic instability, increasing attention has recently been given to epigenetic and microenvironmental influences. Such non-genetic factors allow cancer cells to experience intrinsic diversity and plasticity, and at the tumor level can result in phenotypic heterogeneity and treatment evasion. In 2006, Takahashi and Yamanaka exploited the epigenome's plasticity by “reprogramming” differentiated cells into a pluripotent state by inducing expression of a cocktail of four transcription factors. Recent advances in cancer biology have shown not only that cellular reprogramming is possible for malignant cells, but it may provide a foundation for future therapies. Nevertheless, cell reprogramming experiments are frequently plagued by low efficiency, activation of aberrant transcriptional programs, instability, and often rely on expertise gathered from systems which may not translate directly to cancer. Here, we review a theoretical framework tracing back to Waddington's epigenetic landscape which may be used to derive quantitative and qualitative understanding of cellular reprogramming. Implications for tumor heterogeneity, evolution and adaptation are discussed in the context of designing new treatments to re-sensitize recalcitrant tumors. This article is part of a Special Issue entitled: Evolutionary principles — heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.Display Omitted
Keywords: Epigenetics; Attractors; Reprogramming; Transcription factors; Gene regulatory network; Mathematical modeling;