Cancer as an evolutionary and ecological process.

Neoplasms are microcosms of evolution. Within a neoplasm, a mosaic of mutant cells compete for space and resources, evade predation by the immune system and can even cooperate to disperse and colonize new organs. The evolution of neoplastic cells explains both why we get cancer and why it has been so difficult to cure. The tools of evolutionary biology and ecology are providing new insights into neoplastic progression and the clinical control of cancer.

Spontaneous Gac mutants of Pseudomonas biological control strains: cheaters or mutualists?

Bacteria rely on a range of extracellular metabolites to suppress competitors, gain access to resources, and exploit plant or animal hosts. The GacS/GacA two-component regulatory system positively controls the expression of many of these beneficial external products in pseudomonad bacteria. Natural populations often contain variants with defective Gac systems that do not produce most external products. These mutants benefit from a decreased metabolic load but do not appear to displace the wild type in nature. How could natural selection maintain the wild type in the presence of a mutant with enhanced growth? One hypothesis is that Gac mutants are "cheaters" that do not contribute to the public good, favored within groups but selected against between groups, as groups containing more mutants lose access to ecologically important external products. An alternative hypothesis is that Gac mutants have a mutualistic interaction with the wild type, so that each variant benefits by the presence of the other. In the biocontrol bacterium Pseudomonas chlororaphis strain 30-84, Gac mutants do not produce phenazines, which suppress competitor growth and are critical for biofilm formation. Here, we test the predictions of these alternative hypotheses by quantifying interactions between the wild type and the phenazine- and biofilm-deficient Gac mutant within growing biofilms. We find evidence that the wild type and Gac mutants interact mutualistically in the biofilm context, whereas a phenazine-defective structural mutant does not. Our results suggest that the persistence of alternative Gac phenotypes may be due to the stabilizing role of local mutualistic interactions.

Molecular Characterization of the Highest Risk Adult Patients With Acute Myeloid Leukemia (AML) Through Multi-Omics Clustering.

Background: Acute myeloid leukemia (AML) is a clinically heterogeneous group of cancers. While some patients respond well to chemotherapy, we describe here a subgroup with distinct molecular features that has very poor prognosis under chemotherapy. The classification of AML relies substantially on cytogenetics, but most cytogenetic abnormalities do not offer targets for development of targeted therapeutics. Therefore, it is important to create a detailed molecular characterization of the subgroup most in need of new targeted therapeutics. Methods: We used a multi-omics approach to identify a molecular subgroup with the worst response to chemotherapy, and to identify promising drug targets specifically for this AML subgroup. Results: Multi-omics clustering analysis resulted in three primary clusters among 166 AML adult cancer cases in TCGA data. One of these clusters, which we label as the high-risk molecular subgroup (HRMS), consisted of cases that responded very poorly to standard chemotherapy, with only about 10% survival to 2 years. The gene TP53 was mutated in most cases in this subgroup but not in all of them. The top six genes over-expressed in the HRMS subgroup included E2F4, CD34, CD109, MN1, MMLT3, and CD200. Multi-omics pathway analysis using RNA and CNA expression data identified in the HRMS subgroup over-activated pathways related to immune function, cell proliferation, and DNA damage. Conclusion: A distinct subgroup of AML patients are not successfully treated with chemotherapy, and urgently need targeted therapeutics based on the molecular features of this subgroup. Potential drug targets include over-expressed genes E2F4, and MN1, as well as mutations in TP53, and several over-activated molecular pathways.

Polyploidy, aneuploidy and the evolution of cancer.

Aneuploidy is a ubiquitous feature of cancer and pre-cancerous lesions, yet its significance is poorly characterized. In this chapter, we review the role oftetraploidy and aneuploidy in progression. We examine how aneuploidy may contribute to the evolutionary dynamics prevalent in neoplastic progression, considering whether aneuploidy itself is selectively neutral or advantageous or if it simply acts as a mechanism for the more rapid accumulation of mutations increasing survival and reproduction of cancer cells. We also review evidence from Barrett's esophagus, a pre-malignant condition, demonstrating that tetraploidy and aneuploidy are correlated with an increased risk of progression to cancer. Ultimately, we aim provide testable hypotheses and methods for understanding the role of aneuploidy in cancer.

Energy oversupply to tissues: a single mechanism possibly underlying multiple cancer risk factors.

BACKGROUND AND OBJECTIVES: Several major risk factors for cancer involve vascular oversupply of energy to affected tissues. These include obesity, diabetes and chronic inflammation. Here, we propose a potential mechanistic explanation for the association between energy oversupply and cancer risk, which we call the metabolic cancer suppression hypothesis: We hypothesize that oncogenesis is normally suppressed by organismal physiology that regulates and strictly limits normal energy supply to somatic cells, and that this protection is removed by abnormal oversupply of energy. METHODOLOGY: We evaluate this hypothesis using a computational model of somatic cell evolution to simulate experimental manipulation of the vascular energy supply to a tissue. The model simulates the evolutionary dynamics of somatic cells during oncogenesis. RESULTS: In our simulation experiment, we found that under plausible biological assumptions, elevated energy supply to a tissue led to the evolution of elevated energy uptake by somatic cells, leading to the rapid evolution of both defining traits of cancer cells: hyperproliferation, and tissue invasion. CONCLUSIONS AND IMPLICATIONS: Our results support the hypothesis of metabolic cancer suppression, suggesting that vascular oversupply of energetic resources to somatic cells removes normal energetic limitations on cell proliferation, and that this accelerates cellular evolution toward cancer. Various predictions of this hypothesis are amenable to empirical testing, and have promising implications for translational research toward clinical cancer prevention.

Animal cell differentiation patterns suppress somatic evolution.

Cell differentiation in multicellular organisms has the obvious function during development of creating new cell types. However, in long-lived organisms with extensive cell turnover, cell differentiation often continues after new cell types are no longer needed or produced. Here, we address the question of why this is true. It is believed that multicellular organisms could not have arisen or been evolutionarily stable without possessing mechanisms to suppress somatic selection among cells within organisms, which would otherwise disrupt organismal integrity. Here, we propose that one such mechanism is a specific pattern of ongoing cell differentiation commonly found in metazoans with cell turnover, which we call "serial differentiation." This pattern involves a sequence of differentiation stages, starting with self-renewing somatic stem cells and proceeding through several (non-self-renewing) transient amplifying cell stages before ending with terminally differentiated cells. To test the hypothesis that serial differentiation can suppress somatic evolution, we used an agent-based computer simulation of cell population dynamics and evolution within tissues. The results indicate that, relative to other, simpler patterns, tissues organized into serial differentiation experience lower rates of detrimental cell-level evolution. Self-renewing cell populations are susceptible to somatic evolution, while those that are not self-renewing are not. We find that a mutation disrupting differentiation can create a new self-renewing cell population that is vulnerable to somatic evolution. These results are relevant not only to understanding the evolutionary origins of multicellularity, but also the causes of pathologies such as cancer and senescence in extant metazoans, including humans.

Natural Selection in Cancer Biology: From Molecular Snowflakes to Trait Hallmarks.

Evolution by natural selection is the conceptual foundation for nearly every branch of biology and increasingly also for biomedicine and medical research. In cancer biology, evolution explains how populations of cells in tumors change over time. It is a fundamental question whether this evolutionary process is driven primarily by natural selection and adaptation or by other evolutionary processes such as founder effects and drift. In cancer biology, as in organismal evolutionary biology, there is controversy about this question and also about the use of adaptation through natural selection as a guiding framework for research. In this review, we discuss the differences and similarities between evolution among somatic cells versus evolution among organisms. We review what is known about the parameters and rate of evolution in neoplasms, as well as evidence for adaptation. We conclude that adaptation is a useful framework that accurately explains the defining characteristics of cancer. Further, convergent evolution through natural selection provides the only satisfying explanation both for how a group of diverse pathologies have enough in common to usefully share the descriptive label of "cancer" and for why this convergent condition becomes life-threatening.

In North America, some ovarian cancers express the oncogenes of preventable human papillomavirus HPV-18.

Some researchers in other regions have recommended human papillomavirus (HPV) vaccination to reduce risk of ovarian cancer, but not in North America, where evidence has previously suggested no role for HPV in ovarian cancer. Here we use a large sample of ovarian cancer transcriptomes (RNA-Seq) from The Cancer Genome Atlas (TCGA) database to address whether HPV is involved with ovarian cancer in North America. We estimate that a known high-risk type of HPV (type 18) is present and active in 1.5% of cases of ovarian epithelial cancers in the US and Canada. Our detection methods were verified by negative and positive controls, and our sequence matches indicated high validity, leading to strong confidence in our conclusions. Our results indicate that previous reports of zero prevalence of HPV in North American cases of ovarian cancer should not be considered conclusive. This is important because currently used vaccines protect against the HPV-18 that is active in ovarian tumors and, therefore, may reduce risk in North America of cancers of the ovaries as well as of the cervix and several other organ sites.

A mechanism for the evolution of altruism among nonkin: positive assortment through environmental feedback.

The evolution of altruism often requires genetic similarity among interactors. For structured populations in which a social trait affects all group members, this entails positive assortment, meaning that cooperators and noncooperators tend to be segregated into different groups. Several authors have claimed that mechanisms other than common descent can produce positive assortment, but this claim has not been generally accepted. Here, we describe one such mechanism. The process of "environmental feedback" requires only that the cooperative trait affects the quality of the local environment and that individuals are more likely to leave low-quality than high-quality environments. We illustrate this dynamic using an agent-based spatial model of feeding restraint. Depending on parameter settings, results included both positive assortment (required for the evolution of altruism) and negative assortment (required for the evolution of spite). The mechanism of environmental feedback appears to be a general one that could play a role in the evolution of many forms of cooperation.

The evolution of evolvability in genetic linkage patterns.

A number of factors have been proposed that may affect the capacity for an evolutionary system to generate adaptation. One that has received little recent attention among biologists is linkage patterns, or the ordering of genes on chromosomes. In this study, a simple model of genetic interactions, implemented in an evolutionary simulation, demonstrates that clustering of epistatically interacting genes increases the rate of adaptation. Moreover, long-term evolution with inversion can reorganize linkage patterns from random gene ordering into this more modular organization, thereby facilitating adaptation. These results are consistent with a large body of biological observations and some mathematical theory. Although linkage patterns are neutral with respect to individual fitness in this model, they are subject to lineage level selection for evolvability. At least two candidate mechanisms may contribute to improved evolvability under epistatic clustering: clustering may reduce interference between selection on different traits, and it may allow the simultaneous optimization of different recombination rates for gene pairs with additive and epistatic fitness effects.

The evolution of bacterial social life: From the ivory tower to the front lines of public health.

Drug-resistant bacteria are a huge and growing threat to public health. A solution exists in theory, but had not yet been put to a practical test. The accompanying paper by Ross-Gillespie et al., the theory is put to a test and performs successfully. As predicted, using a drug that targets bacteria's shared secreted 'public goods' molecules instead of cell components did not drive the bacterial evolution of drug resistance, and therefore retained its effectiveness. This result holds great promise for better drugs and vaccines against many infectious diseases, and also for better cancer therapies.

Drugs that target pathogen public goods are robust against evolved drug resistance.

Pathogen drug resistance is a central problem in medicine and public health. It arises through somatic evolution, by mutation and selection among pathogen cells within a host. Here, we examine the hypothesis that evolution of drug resistance could be reduced by developing drugs that target the secreted metabolites produced by pathogen cells instead of directly targeting the cells themselves. Using an agent-based computational model of an evolving population of pathogen cells, we test this hypothesis and find support for it. We also use our model to explain this effect within the framework of standard evolutionary theory. We find that in our model, the drugs most robust against evolved drug resistance are those that target the most widely shared external products, or 'public goods', of pathogen cells. We also show that these drugs exert a weak selective pressure for resistance because they create only a weak correlation between drug resistance and cell fitness. The same principles apply to design of vaccines that are robust against vaccine escape. Because our theoretical results have crucial practical implications, they should be tested by empirical experiments.

The emerging medical ecology of the human gut microbiome.

It is increasingly clear that the human gut microbiome has great medical importance, and researchers are beginning to investigate its basic biology and to appreciate the challenges that it presents to medical science. Several striking new empirical results in this area are perplexing within the standard conceptual framework of biomedicine, and this highlights the need for new perspectives from ecology and from dynamical systems theory. Here, we discuss recent results concerning sources of individual variation, temporal variation within individuals, long-term changes after transient perturbations and individualized responses to perturbation within the human gut microbiome.

Dispersal evolution in neoplasms: the role of disregulated metabolism in the evolution of cell motility.

Here, we apply the theoretical framework of dispersal evolution to understand the emergence of invasive and metastatic cells. We investigate whether the dysregulated metabolism characteristic of cancer cells may play a causal role in selection for cell motility, and thus to the tissue invasion and metastasis that define cancer. With an agent-based computational model, we show that cells with higher metabolism evolve to have higher rates of movement and that "neoplastic" cells with higher metabolism rates are able to persist in a population of "normal" cells with low metabolic rates, but only if increased metabolism is accompanied by increased motility. This is true even when the cost of motility is high. These findings suggest that higher rates of cell metabolism lead to selection for motile cells in premalignant neoplasms, which may preadapt cells for subsequent invasion and metastasis. This has important implications for understanding the progression of cancer from less invasive to more invasive cell types.

Accurate reconstruction of the temporal order of mutations in neoplastic progression.

The canonical route from normal tissue to cancer occurs through sequential acquisition of somatic mutations. Many studies have constructed a linear genetic model for tumorigenesis using the genetic alterations associated with samples at different stages of neoplastic progression from cross-sectional data. The common interpretation of these models is that they reflect the temporal order within any given tumor. Linear genetic methods implicitly neglect genetic heterogeneity within a neoplasm; each neoplasm is assumed to consist of one dominant clone. We modeled neoplastic progression of colorectal cancer using an agent-based model of a colon crypt and found clonal heterogeneity within our simulated neoplasms, as observed in vivo. Just 7.3% of cells within neoplasms acquired mutations in the same order as the linear model. In 41% of the simulated neoplasms, no cells acquired mutations in the same order as the linear model. We obtained similarly poor results when comparing the temporal order with oncogenetic tree models inferred from cross-sectional data. However, when we reconstructed the cell lineage of mutations within a neoplasm using several biopsies, we found that 99.7% cells within neoplasms acquired their mutations in an order consistent with the cell lineage mutational order. Thus, we find that using cross-sectional data to infer mutational order is misleading, whereas phylogenetic methods based on sampling intratumor heterogeneity accurately reconstructs the evolutionary history of tumors. In addition, we find evidence that disruption of differentiation is likely the first lesion in progression for most cancers and should be one of the few regularities of neoplastic progression across cancers.

Theory for the evolution of diffusible external goods.

Organisms from prokaryotes to plants and animals make costly investments in diffusible beneficial external products. While the costs of producing such products are born only by the producer, the benefits may be distributed more widely. How are external goods-producing populations stabilized against invasion by nonproducing variants that receive the benefits without paying the cost? This question parallels the classic question of altruism, but because external goods production need not be altruistic per se, a broader range of conditions may lead to the maintenance of these traits. We start from the physics of diffusion to develop an expression for the conditions that favor the production of diffusible external goods. Important variables in determining the evolutionary outcome include the diffusion coefficient of the good, the distance between individuals, and the uptake rate of the external good. These variables join the coefficient of relatedness and the cost/benefit ratio in an expanded form of Hamilton's rule that includes both selfish and altruistic paths to the evolution of external goods strategies. This expanded framework can be applied to any external goods trait, and is a useful heuristic even when it is difficult to quantify the fitness consequences of producing the good.

The role of multilevel selection in the evolution of sexual conflict in the water strider aquarius remigis.

In evolution, exploitative strategies often create a paradox in which the most successful individual strategy "within" the group is also the most detrimental strategy "for" the group, potentially resulting in extinction. With regard to sexual conflict, the overexploitation of females by harmful males can yield similar consequences. Despite these evolutionary implications, little research has addressed why sexual conflict does not ultimately drive populations to extinction. One possibility is that groups experiencing less sexual conflict are more productive than groups with greater conflict. However, most studies of sexual conflict are conducted in a single isolated group, disregarding the potential for selection among groups. We observed Aquarius remigis water striders in a naturalistic multigroup pool in which individuals could freely disperse among groups. The free movement of individuals generated variation in aggression and sex-ratio among groups, thereby increasing the importance of between-group selection compared to within-group selection. Females dispersed away from local aggression, creating more favorable mating environments for less-aggressive males. Furthermore, the use of contextual analysis revealed that individual male aggression positively predicted fitness whereas aggression at the group level negatively predicted fitness, empirically demonstrating the conflict between levels of selection acting on mating aggression.

Population structure mediates sexual conflict in water striders.

Sexual conflict occurs when males and females act against each others' interest, typically resulting in selection favoring harmful males. We performed laboratory experiments on sexual conflict that both confined individuals in isolated groups, which prevents selection acting counter to this conflict, and provided more naturalistic multigroup population structures. We show that in water striders, aggressive male mating behavior was strongly favored within groups but not favored in a multigroup population when individuals can freely disperse among groups. These observations explain the persistence of less-aggressive males within natural populations.

Cancer research meets evolutionary biology.

There is increasing evidence that Darwin's theory of evolution by natural selection provides insights into the etiology and treatment of cancer. On a microscopic scale, neoplastic cells meet the conditions for evolution by Darwinian selection: cell reproduction with heritable variability that affects cell survival and replication. This suggests that, like other areas of biological and biomedical research, Darwinian theory can provide a general framework for understanding many aspects of cancer, including problems of great clinical importance. With the availability of raw molecular data increasing rapidly, this theory may provide guidance in translating data into understanding and progress. Several conceptual and analytical tools from evolutionary biology can be applied to cancer biology. Two clinical problems may benefit most from the application of Darwinian theory: neoplastic progression and acquired therapeutic resistance. The Darwinian theory of cancer has especially profound implications for drug development, both in terms of explaining past difficulties, and pointing the way toward new approaches. Because cancer involves complex evolutionary processes, research should incorporate both tractable (simplified) experimental systems, and also longitudinal observational studies of the evolutionary dynamics of cancer in laboratory animals and in human patients. Cancer biology will require new tools to control the evolution of neoplastic cells.

Defeating pathogen drug resistance: guidance from evolutionary theory.

Many of the greatest challenges in medicine and public health involve the evolution of drug resistance by pathogens. Recent advances in the theory of natural selection suggest that there are two broad classes of pathogen traits that can be targeted by drugs or vaccines. The first class, consisting of traits that benefit the individual organisms bearing them, causes a strong evolutionary response and the rapid emergence of drug resistance. The second class, consisting of traits that benefit groups of pathogen organisms including the individual provider, causes a weaker evolutionary response and less drug resistance. Although most previous drug development has targeted the first class, it would be advantageous to focus on the second class as targets for drug and vaccine development. Specific examples and test cases are discussed.