Ecology meets cancer biology: the cancer swamp promotes the lethal cancer phenotype

Modeling tumors as species-rich ecological communities

Many advanced cancers resist therapeutic intervention. This process is fundamentally related to intra-tumor heterogeneity: multiple cell populations, each with different mutational and phenotypic signatures, coexist within a tumor and its metastatic nodes. Like species in an ecosystem, many cancer cell populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity nor are able to predict its consequences. Here we propose that the Generalized Lotka-Volterra model (GLV), a standard tool to describe complex, species-rich ecological communities, provides a suitable framework to describe the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties, such as outgrowth and multistability, provide a new understanding of the disease. Additionally, we discuss potential extensions of the model and their application to three active areas of cancer research, namely phenotypic plasticity, the cancer-immune interplay and the resistance of metastatic tumors to treatment. Our work outlines a set of questions and a tentative road map for further research in cancer ecology.

"Patchiness" in mechanical stiffness across a tumor as an early-stage marker for malignancy

Mechanical phenotyping of tumors, either at an individual cell level or tumor cell population level is gaining traction as a diagnostic tool. However, the extent of diagnostic and prognostic information that can be gained through these measurements is still unclear. In this work, we focus on the heterogeneity in mechanical properties of cells obtained from a single source such as a tissue or tumor as a potential novel biomarker. We believe that this heterogeneity is a conventionally overlooked source of information in mechanical phenotyping data. We use mechanics-based in-silico models of cell-cell interactions and cell population dynamics within 3D environments to probe how heterogeneity in cell mechanics drives tissue and tumor dynamics. Our simulations show that the initial heterogeneity in the mechanical properties of individual cells and the arrangement of these heterogenous sub-populations within the environment can dictate overall cell population dynamics and cause a shift towards the growth of malignant cell phenotypes within healthy tissue environments. The overall heterogeneity in the cellular mechanotype and their spatial distributions is quantified by a "patchiness" index, which is the ratio of the global to local heterogeneity in cell populations. We observe that there exists a threshold value of the patchiness index beyond which an overall healthy population of cells will show a steady shift towards a more malignant phenotype. Based on these results, we propose that the "patchiness" of a tumor or tissue sample, can be an early indicator for malignant transformation and cancer occurrence in benign tumors or healthy tissues. Additionally, we suggest that tissue patchiness, measured either by biochemical or biophysical markers, can become an important metric in predicting tissue health and disease likelihood just as landscape patchiness is an important metric in ecology.

In vitro competition between two transmissible cancers and potential implications for their host, the Tasmanian devil

Since the emergence of a transmissible cancer, devil facial tumour disease (DFT1), in the 1980s, wild Tasmanian devil populations have been in decline. In 2016, a second, independently evolved transmissible cancer (DFT2) was discovered raising concerns for survival of the host species. Here, we applied experimental and modelling frameworks to examine competition dynamics between the two transmissible cancers in vitro. Using representative cell lines for DFT1 and DFT2, we have found that in monoculture, DFT2 grows twice as fast as DFT1 but reaches lower maximum cell densities. Using co-cultures, we demonstrate that DFT2 outcompetes DFT1: the number of DFT1 cells decreasing over time, never reaching exponential growth. This phenomenon could not be replicated when cells were grown separated by a semi-permeable membrane, consistent with exertion of mechanical stress on DFT1 cells by DFT2. A logistic model and a Lotka-Volterra competition model were used to interrogate monoculture and co-culture growth curves, respectively, suggesting DFT2 is a better competitor than DFT1, but also showing that competition outcomes might depend on the initial number of cells, at least in the laboratory. We provide theories how the in vitro results could be translated to observations in the wild and propose that these results may indicate that although DFT2 is currently in a smaller geographic area than DFT1, it could have the potential to outcompete DFT1. Furthermore, we provide a framework for improving the parameterization of epidemiological models applied to these cancer lineages, which will inform future disease management.

Immune Checkpoint Inhibitors in Recipients of Renal Allografts

Kidney transplant recipients are at increased risk of malignancy as a result of immunosuppression and are increasingly exposed to checkpoint inhibitors (CPIs). However, CPI therapy can precipitate allograft rejection. This review aims to summarize the current literature describing the epidemiology, immunological mechanisms, diagnosis, and treatment of CPI-associated allograft rejection.Initial studies of CPIs suggested allograft rejection post commencement of CPIs occured commonly (40-60%), occurring between 2 and 6 weeks after CPI initiation, with a cancer response rate approaching 50%. More recent studies with predefined, structured immunosuppressive regimens have seen rejection rates of 0-12.5%, with rejection occurring later. Allograft biopsy remains the mainstay of diagnosis; however, noninvasive tools are emerging, including donor-derived cell-free DNA, urinary chemokine assessment, and defining alloreactive T-cell clones prior to or during CPI therapy.

Metastatic cells exploit their stoichiometric niche in the network of cancer ecosystems

Metastasis is a nonrandom process with varying degrees of organotropism-specific source-acceptor seeding. Understanding how patterns between source and acceptor tumors emerge remains a challenge in oncology. We hypothesize that organotropism results from the macronutrient niche of cells in source and acceptor organs. To test this, we constructed and analyzed a metastatic network based on 9303 records across 28 tissue types. We found that the topology of the network is nested and modular with scale-free degree distributions, reflecting organotropism along a specificity/generality continuum. The variation in topology is significantly explained by the matching of metastatic cells to their stoichiometric niche. Specifically, successful metastases are associated with higher phosphorus content in the acceptor compared to the source organ, due to metabolic constraints in proliferation crucial to the invasion of new tissues. We conclude that metastases are codetermined by processes at source and acceptor organs, where phosphorus content is a limiting factor orchestrating tumor ecology.

The need for evolutionary theory in cancer research

Sir Richard Peto is well known for proposing puzzling paradoxes in cancer biology-some more well-known than others. In a 1984 piece, Peto proposed that after decades of molecular biology in cancer research, we are still ignorant of the biology underpinning cancer. Cancer is a product of somatic mutations. How do these mutations arise and what are the mechanisms? As an epidemiologist, Peto asked if we really need to understand mechanisms in order to prevent cancer? Four decades after Peto's proposed ignorance in cancer research, we can simply ask, are we still ignorant? Did the great pursuit to uncover mechanisms of cancer eclipse our understanding of causes and preventions? Or can we get closer to treating and preventing cancer by understanding the underlying mechanisms that make us most vulnerable to this disease?

Cells in the polyaneuploid cancer cell (PACC) state have increased metastatic potential

Although metastasis is the leading cause of cancer deaths, it is quite rare at the cellular level. Only a rare subset of cancer cells (~ 1 in 1.5 billion) can complete the entire metastatic cascade: invasion, intravasation, survival in the circulation, extravasation, and colonization (i.e. are metastasis competent). We propose that cells engaging a Polyaneuploid Cancer Cell (PACC) phenotype are metastasis competent. Cells in the PACC state are enlarged, endocycling (i.e. non-dividing) cells with increased genomic content that form in response to stress. Single-cell tracking using time lapse microscopy reveals that PACC state cells have increased motility. Additionally, cells in the PACC state exhibit increased capacity for environment-sensing and directional migration in chemotactic environments, predicting successful invasion. Magnetic Twisting Cytometry and Atomic Force Microscopy reveal that cells in the PACC state display hyper-elastic properties like increased peripheral deformability and maintained peri-nuclear cortical integrity that predict successful intravasation and extravasation. Furthermore, four orthogonal methods reveal that cells in the PACC state have increased expression of vimentin, a hyper-elastic biomolecule known to modulate biomechanical properties and induce mesenchymal-like motility. Taken together, these data indicate that cells in the PACC state have increased metastatic potential and are worthy of further in vivo analysis.

The tumor ecosystem in head and neck squamous cell carcinoma and advances in ecotherapy

The development of head and neck squamous cell carcinoma (HNSCC) is a multi-step process, and its survival depends on a complex tumor ecosystem, which not only promotes tumor growth but also helps to protect tumor cells from immune surveillance. With the advances of existing technologies and emerging models for ecosystem research, the evidence for cell-cell interplay is increasing. Herein, we discuss the recent advances in understanding the interaction between tumor cells, the major components of the HNSCC tumor ecosystem, and summarize the mechanisms of how biological and abiotic factors affect the tumor ecosystem. In addition, we review the emerging ecological treatment strategy for HNSCC based on existing studies.

Modeling cancer's ecological and evolutionary dynamics

In this didactic paper, we present a theoretical modeling framework, called the G-function, that integrates both the ecology and evolution of cancer to understand oncogenesis. The G-function has been used in evolutionary ecology, but has not been widely applied to problems in cancer. Here, we build the G-function framework from fundamental Darwinian principles and discuss how cancer can be seen through the lens of ecology, evolution, and game theory. We begin with a simple model of cancer growth and add on components of cancer cell competition and drug resistance. To aid in exploration of eco-evolutionary modeling with this approach, we also present a user-friendly software tool. By the end of this paper, we hope that readers will be able to construct basic G function models and grasp the usefulness of the framework to understand the games cancer plays in a biologically mechanistic fashion.

The theory of tumor ecosystem

Cancer cells can be conceived as “living organisms” interacting with cellular or non‐cellular components in the host internal environment, not only the local tumor microenvironment but also the distant organ niches, as well as the immune, nervous and endocrine systems, to construct a self‐sustainable tumor ecosystem. With increasing evidence for the systemic tumor‐host interplay, we predict that a new era of cancer therapy targeting the ecosystemic vulnerability of human malignancies has come. Revolving around the tumor ecosystem scoped as different hierarchies of primary, regional, distal and systemic onco‐spheres, we comprehensively review the tumor‐host interaction among cancer cells and their local microenvironment, distant organ niches, immune, nervous and endocrine systems, highlighting material and energy flow with tumor ecological homeostasis as an internal driving force. We also substantiate the knowledge of visualizing, modelling and subtyping this dynamically intertwined network with recent technological advances, and discuss ecologically rational strategies for more effective cancer therapies.

The role of metabolic ecosystem in cancer progression — metabolic plasticity and mTOR hyperactivity in tumor tissues

Despite advancements in cancer management, tumor relapse and metastasis are associated with poor outcomes in many cancers. Over the past decade, oncogene-driven carcinogenesis, dysregulated cellular signaling networks, dynamic changes in the tissue microenvironment, epithelial-mesenchymal transitions, protein expression within regulatory pathways, and their part in tumor progression are described in several studies. However, the complexity of metabolic enzyme expression is considerably under evaluated. Alterations in cellular metabolism determine the individual phenotype and behavior of cells, which is a well-recognized hallmark of cancer progression, especially in the adaptation mechanisms underlying therapy resistance. In metabolic symbiosis, cells compete, communicate, and even feed each other, supervised by tumor cells. Metabolic reprogramming forms a unique fingerprint for each tumor tissue, depending on the cellular content and genetic, epigenetic, and microenvironmental alterations of the developing cancer. Based on its sensing and effector functions, the mechanistic target of rapamycin (mTOR) kinase is considered the master regulator of metabolic adaptation. Moreover, mTOR kinase hyperactivity is associated with poor prognosis in various tumor types. In situ metabolic phenotyping in recent studies highlights the importance of metabolic plasticity, mTOR hyperactivity, and their role in tumor progression. In this review, we update recent developments in metabolic phenotyping of the cancer ecosystem, metabolic symbiosis, and plasticity which could provide new research directions in tumor biology. In addition, we suggest pathomorphological and analytical studies relating to metabolic alterations, mTOR activity, and their associations which are necessary to improve understanding of tumor heterogeneity and expand the therapeutic management of cancer.

Diversity of Vascular Niches in Bones and Joints During Homeostasis, Ageing, and Diseases

The bones and joints in the skeletal system are composed of diverse cell types, including vascular niches, bone cells, connective tissue cells and mineral deposits and regulate whole-body homeostasis. The capacity of maintaining strength and generation of blood lineages lies within the skeletal system. Bone harbours blood and immune cells and their progenitors, and vascular cells provide several immune cell type niches. Blood vessels in bone are phenotypically and functionally diverse, with distinct capillary subtypes exhibiting striking changes with age. The bone vasculature has a special impact on osteogenesis and haematopoiesis, and dysregulation of the vasculature is associated with diverse blood and bone diseases. Ageing is associated with perturbed haematopoiesis, loss of osteogenesis, increased adipogenesis and diminished immune response and immune cell production. Endothelial and perivascular cells impact immune cell production and play a crucial role during inflammation. Here, we discuss normal and maladapted vascular niches in bone during development, homeostasis, ageing and bone diseases such as rheumatoid arthritis and osteoarthritis. Further, we discuss the role of vascular niches during bone malignancy.

Predator-Prey in Tumor-Immune Interactions: A Wrong Model or Just an Incomplete One?

Tumor-immune interactions are often framed as predator-prey. This imperfect analogy describes how immune cells (the predators) hunt and kill immunogenic tumor cells (the prey). It allows for evaluation of tumor cell populations that change over time during immunoediting and it also considers how the immune system changes in response to these alterations. However, two aspects of predator-prey type models are not typically observed in immuno-oncology. The first concerns the conversion of prey killed into predator biomass. In standard predator-prey models, the predator relies on the prey for nutrients, while in the tumor microenvironment the predator and prey compete for resources (e.g. glucose). The second concerns oscillatory dynamics. Standard predator-prey models can show a perpetual cycling in both prey and predator population sizes, while in oncology we see increases in tumor volume and decreases in infiltrating immune cell populations. Here we discuss the applicability of predator-prey models in the context of cancer immunology and evaluate possible causes for discrepancies. Key processes include "safety in numbers", resource availability, time delays, interference competition, and immunoediting. Finally, we propose a way forward to reconcile differences between model predictions and empirical observations. The immune system is not just predator-prey. Like natural food webs, the immune-tumor community of cell types forms an immune-web of different and identifiable interactions.

Cancer recurrence and lethality are enabled by enhanced survival and reversible cell cycle arrest of polyaneuploid cells

We present a unifying theory to explain cancer recurrence, therapeutic resistance, and lethality. The basis of this theory is the formation of simultaneously polyploid and aneuploid cancer cells, polyaneuploid cancer cells (PACCs), that avoid the toxic effects of systemic therapy by entering a state of cell cycle arrest. The theory is independent of which of the classically associated oncogenic mutations have already occurred. PACCs have been generally disregarded as senescent or dying cells. Our theory states that therapeutic resistance is driven by PACC formation that is enabled by accessing a polyploid program that allows an aneuploid cancer cell to double its genomic content, followed by entry into a nondividing cell state to protect DNA integrity and ensure cell survival. Upon removal of stress, e.g., chemotherapy, PACCs undergo depolyploidization and generate resistant progeny that make up the bulk of cancer cells within a tumor.

What Is the Storage Effect, Why Should It Occur in Cancers, and How Can It Inform Cancer Therapy?

Intratumor heterogeneity is a feature of cancer that is associated with progression, treatment resistance, and recurrence. However, the mechanisms that allow diverse cancer cell lineages to coexist remain poorly understood. The storage effect is a coexistence mechanism that has been proposed to explain the diversity of a variety of ecological communities, including coral reef fish, plankton, and desert annual plants. Three ingredients are required for there to be a storage effect: (1) temporal variability in the environment, (2) buffered population growth, and (3) species-specific environmental responses. In this article, we argue that these conditions are observed in cancers and that it is likely that the storage effect contributes to intratumor diversity. Data that show the temporal variation within the tumor microenvironment are needed to quantify how cancer cells respond to fluctuations in the tumor microenvironment and what impact this has on interactions among cancer cell types. The presence of a storage effect within a patient’s tumors could have a substantial impact on how we understand and treat cancer.

Cancer cells employ an evolutionarily conserved polyploidization program to resist therapy

Unusually large cancer cells with abnormal nuclei have been documented in the cancer literature since 1858. For more than 100 years, they have been generally disregarded as irreversibly senescent or dying cells, too morphologically misshapen and chromatin too disorganized to be functional. Cell enlargement, accompanied by whole genome doubling or more, is observed across organisms, often associated with mitigation strategies against environmental change, severe stress, or the lack of nutrients. Our comparison of the mechanisms for polyploidization in other organisms and non-transformed tissues suggest that cancer cells draw from a conserved program for their survival, utilizing whole genome doubling and pausing proliferation to survive stress. These polyaneuploid cancer cells (PACCs) are the source of therapeutic resistance, responsible for cancer recurrence and, ultimately, cancer lethality.

Cancer Cells and M2 Macrophages: Cooperative Invasive Ecosystem Engineers

Many aspects of cancer can be explained utilizing well-defined ecological principles. Applying these principles to cancer, cancer cells are an invasive species to a healthy organ ecosystem. In their capacity as ecosystem engineers, cancer cells release cytokines that recruit monocytes to the tumor and polarize them to M2-like protumor macrophages. Macrophages, recruited by the cancer cells, act as a secondary invasive species. The ecosystem engineering functions of M2-macrophages in turn support and stimulate cancer cell survival and proliferation. The cooperative ecosystem engineering of both the primary invasive species of the cancer cell and the secondary invasive species of the M2-macrophage thus creates a vicious cycle of tumor promotion. Targeting a specific aspect of this tumor-promoting ecosystem engineering, such as blocking efferocytosis by M2-like macrophages, may improve the response to standard-of-care anticancer therapies. This strategy has the potential to redirect cooperative protumor ecosystem engineering toward an antitumor ecosystem engineering strategy.

Secretome Proteomic Approaches for Biomarker Discovery: An Update on Colorectal Cancer

Searching for new cancer-related biomarkers is a key priority for the early detection of solid tumors, such as colorectal cancer (CRC), in clinically relevant biological fluids. The cell line and/or tumor tissue secretome represents a valuable resource for discovering novel protein markers secreted by cancer cells. The advantage of a secretome analysis is the reduction of the large dynamic range characterizing human plasma/serum, and the simultaneous enrichment of low abundance cancer-secreted proteins, thereby overcoming the technical limitations underlying the direct search in blood samples. In this review, we provided a comprehensive overview of recent studies on the CRC secretome for biomarker discovery, focusing both on methodological and technical aspects of secretome proteomic approaches and on biomarker-independent validation in CRC patient samples (blood and tissues). Secretome proteomics are mainly based on LC-MS/MS analyses for which secretome samples are either in-gel or in-solution trypsin-digested. Adequate numbers of biological and technical replicates are required to ensure high reproducibility and robustness of the secretome studies. Moreover, another major challenge is the accuracy of proteomic quantitative analysis performed by label-free or labeling methods. The analysis of differentially expressed proteins in the CRC secretome by using bioinformatic tools allowed the identification of potential biomarkers for early CRC detection. In this scenario, this review may help to follow-up the recent secretome studies in order to select promising circulating biomarkers to be validated in larger screenings, thereby contributing toward a complete translation in clinical practice.

Poly-aneuploid cancer cells promote evolvability, generating lethal cancer

Cancer cells utilize the forces of natural selection to evolve evolvability allowing a constant supply of heritable variation that permits a cancer species to evolutionary track changing hazards and opportunities. Over time, the dynamic tumor ecosystem is exposed to extreme, catastrophic changes in the conditions of the tumor-natural (e.g., loss of blood supply) or imposed (therapeutic). While the nature of these catastrophes may be varied or unique, their common property may be to doom the current cancer phenotype unless it evolves rapidly. Poly-aneuploid cancer cells (PACCs) may serve as efficient sources of heritable variation that allows cancer cells to evolve rapidly, speciate, evolutionarily track their environment, and most critically for patient outcome and survival, permit evolutionary rescue, therapy resistance, and metastasis. As a conditional evolutionary strategy, they permit the cancer cells to accelerate evolution under stress and slow down the generation of heritable variation when conditions are more favorable or when the cancer cells are closer to an evolutionary optimum. We hypothesize that they play a critical and outsized role in lethality by their increased capacity for invasion and motility, for enduring novel and stressful environments, and for generating heritable variation that can be dispensed to their 2N+ aneuploid progeny that make up the bulk of cancer cells within a tumor, providing population rescue in response to therapeutic stress. Targeting PACCs is essential to cancer therapy and patient cure-without the eradication of the resilient PACCs, cancer will recur in treated patients.

An in vitro tumor swamp model of heterogeneous cellular and chemotherapeutic landscapes

The heterogenous, highly metabolic stressed, poorly irrigated, solid tumor microenvironment - the tumor swamp - is widely recognized to play an important role in cancer progression as well as the development of therapeutic resistance. It is thus important to create realistic in vitro models within the therapeutic pipeline that can recapitulate the fundamental stress features of the tumor swamp. Here we describe a microfluidic system which generates a chemical gradient within connected microenvironments achieved through a static diffusion mechanism rather than active pumping. We show that the gradient can be stably maintained for over a week. Due to the accessibility and simplicity of the experimental platform, the system allows for not only well-controlled continuous studies of the interactions among various cell types at single-cell resolution, but also parallel experimentation for time-resolved downstream cellular assays on the time scale of weeks. This approach enables simple, compact implementation and is compatible with existing 6-well imaging technology for simultaneous experiments. As a proof-of-concept, we report the co-culture of a human bone marrow stromal cell line and a bone-metastatic prostate cancer cell line using the presented device, revealing on the same chip a transition in cancer cell survival as a function of drug concentration on the population level while exhibiting an enrichment of poly-aneuploid cancer cells (PACCs) as an evolutionary consequence of high stress. The device allows for the quantitative study of cancer cell dynamics on a stress landscape by real-time monitoring of various cell types with considerable experimental throughput.

Convergent Evolution, Evolving Evolvability, and the Origins of Lethal Cancer

Advances in curative treatment to remove the primary tumor have increased survival of localized cancers for most solid tumor types, yet cancers that have spread are typically incurable and account for >90% of cancer-related deaths. Metastatic disease remains incurable because, somehow, tumors evolve resistance to all known compounds, including therapies. In all of these incurable patients, de novo lethal cancer evolves capacities for both metastasis and resistance. Therefore, cancers in different patients appear to follow the same eco-evolutionary path that independently manifests in affected patients. This convergent outcome, that always includes the ability to metastasize and exhibit resistance, demands an explanation beyond the slow and steady accrual of stochastic mutations. The common denominator may be that cancer starts as a speciation event when a unicellular protist breaks away from its multicellular host and initiates a cancer clade within the patient. As the cancer cells speciate and diversify further, some evolve the capacity to evolve: evolvability. Evolvability becomes a heritable trait that influences the available variation of other phenotypes that can then be acted upon by natural selection. Evolving evolvability may be an adaptation for cancer cells. By generating and maintaining considerable heritable variation, the cancer clade can, with high certainty, serendipitously produce cells resistant to therapy and cells capable of metastasizing. Understanding that cancer cells can swiftly evolve responses to novel and varied stressors create opportunities for adaptive therapy, double-bind therapies, and extinction therapies; all involving strategic decision making that steers and anticipates the convergent coevolutionary responses of the cancers.

Molecular Biology and Evolution of Cancer: From Discovery to Action

Cancer progression is an evolutionary process. During this process, evolving cancer cell populations encounter restrictive ecological niches within the body, such as the primary tumor, circulatory system, and diverse metastatic sites. Efforts to prevent or delay cancer evolution-and progression-require a deep understanding of the underlying molecular evolutionary processes. Herein we discuss a suite of concepts and tools from evolutionary and ecological theory that can inform cancer biology in new and meaningful ways. We also highlight current challenges to applying these concepts, and propose ways in which incorporating these concepts could identify new therapeutic modes and vulnerabilities in cancer.

Treating Cancer as an Invasive Species

To cure a patient's cancer is to eradicate invasive cells from the ecosystem of the body. However, the ecologic complexity of this challenge is not well understood. Here we show how results from eradications of invasive mammalian species from islands-one of the few contexts in which invasive species have been regularly cleared-inform new research directions for treating cancer. We first summarize the epidemiologic characteristics of island invader eradications and cancer treatments by analyzing recent datasets from the Database of Invasive Island Species Eradications and The Cancer Genome Atlas, detailing the superior successes of island eradication projects. Next, we compare how genetic and environmental factors impact success in each system. These comparisons illuminate a number of promising cancer research and treatment directions, such as heterogeneity engineering as motivated by gene drives and adaptive therapy; multiscale analyses of how population heterogeneity potentiates treatment resistance; and application of ecological data mining techniques to high-throughput cancer data. We anticipate that interdisciplinary comparisons between tumor progression and invasive species would inspire development of novel paradigms to cure cancer.

Metastasis and the evolution of dispersal

Despite significant progress in oncology, metastasis remains the leading cause of mortality of cancer patients. Understanding the foundations of this phenomenon could help contain or even prevent it. As suggested by many ecologists and cancer biologists, metastasis could be considered through the lens of biological dispersal: the movement of cancer cells from their birth site (the primary tumour) to other habitats where they resume proliferation (metastatic sites). However, whether this model can consistently be applied to the emergence and dynamics of metastasis remains unclear. Here, we provide a broad review of various aspects of the evolution of dispersal in ecosystems. We investigate whether similar ecological and evolutionary principles can be applied to metastasis, and how these processes may shape the spatio-temporal dynamics of disseminating cancer cells. We further discuss complementary hypotheses and propose experimental approaches to test the relevance of the evolutionary ecology of dispersal in studying metastasis.

Textures of the tumour microenvironment

In this review, we present recent findings on the dynamic nature of the tumour microenvironment (TME) and how intravital microscopy studies have defined TME components in a spatiotemporal manner. Intravital microscopy has shed light into the nature of the TME, revealing structural details of both tumour cells and other TME co-habitants in vivo, how these cells communicate with each other, and how they are organized in three-dimensional space to orchestrate tumour growth, invasion, dissemination and metastasis. We will review different imaging tools, imaging reporters and fate-mapping strategies that have begun to uncover the complexity of the TME in vivo.

Cancer Ecology and Evolution: Positive interactions and system vulnerability

Parallels of cancer with ecology and evolution have provided new insights into the initiation and spread of cancer, and new approaches to therapy. This review describes those parallels while emphasizing some key contrasts. We argue that cancers are less like invasive species than like native species or even crops that have escaped control, and that ecological control and homeo-static control differ fundamentally through both their ends and their means. From our focus on the role of positive interactions in control processes, we introduce a novel mathematical modeling framework that tracks how individual cell lineages arise, and how the many layers of control break down in the emergence of cancer. The next generation of therapies must continue to look beyond cancers as being created by individual renegade cells and address not only the network of interactions those cells inhabit, but the evolutionary logic that created those interactions and their intrinsic vulnerability.

Polyploid giant cancer cells: Unrecognized actuators of tumorigenesis, metastasis, and resistance

Cancer led to the deaths of more than 9 million people worldwide in 2018, and most of these deaths were due to metastatic tumor burden. While in most cases, we still do not know why cancer is lethal, we know that a total tumor burden of 1 kg-equivalent to one trillion cells-is not compatible with life. While localized disease is curable through surgical removal or radiation, once cancer has spread, it is largely incurable. The inability to cure metastatic cancer lies, at least in part, to the fact that cancer is resistant to all known compounds and anticancer drugs. The source of this resistance remains undefined. In fact, the vast majority of metastatic cancers are resistant to all currently available anticancer therapies, including chemotherapy, hormone therapy, immunotherapy, and systemic radiation. Thus, despite decades-even centuries-of research, metastatic cancer remains lethal and incurable. We present historical and contemporary evidence that the key actuators of this process-of tumorigenesis, metastasis, and therapy resistance-are polyploid giant cancer cells.

Development of a database on key characteristics of human carcinogens

A database on mechanistic characteristics of human carcinogenic agents was developed by collecting mechanistic information on agents identified as human carcinogens (Group 1) by the International Agency for Research on Cancer (IARC) in the IARC Monographs on the Evaluation of Carcinogenic Risks to Humans. A two-phase process is described for the construction of the database according to 24 toxicological endpoints, derived from appropriate test systems that were acquired from data obtained from the mechanisms sections of the IARC Monographs (Section 4) and a supplementary PubMed search. These endpoints were then aligned with 10 key characteristics of human carcinogens that reflect the broader attributes of these agents relating to the development of cancer in humans. The considerations involved in linking of toxicological endpoints to key characteristics are described and specific examples of the determination of key characteristics for six specific agents (tamoxifen, hepatitis B virus, arsenic, ultraviolet and solar radiation, tobacco smoking, and dioxin) are provided. Data for humans and animals were tabulated separately, as were results for in-vivo and for in-vitro sources of information. The database was constructed to support a separate analysis of the expression of these endpoints by 86 Group 1 carcinogens, in-vivo and in-vitro along with an analysis of the key characteristics of these agents.

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect

Most models of cancer cell population expansion assume exponential growth kinetics at low cell densities, with deviations to account for observed slowing of growth rate only at higher densities due to limited resources such as space and nutrients. However, recent preclinical and clinical observations of tumor initiation or recurrence indicate the presence of tumor growth kinetics in which growth rates scale positively with cell numbers. These observations are analogous to the cooperative behavior of species in an ecosystem described by the ecological principle of the Allee effect. In preclinical and clinical models, however, tumor growth data are limited by the lower limit of detection (i.e., a measurable lesion) and confounding variables, such as tumor microenvironment, and immune responses may cause and mask deviations from exponential growth models. In this work, we present alternative growth models to investigate the presence of an Allee effect in cancer cells seeded at low cell densities in a controlled in vitro setting. We propose a stochastic modeling framework to disentangle expected deviations due to small population size stochastic effects from cooperative growth and use the moment approach for stochastic parameter estimation to calibrate the observed growth trajectories. We validate the framework on simulated data and apply this approach to longitudinal cell proliferation data of BT-474 luminal B breast cancer cells. We find that cell population growth kinetics are best described by a model structure that considers the Allee effect, in that the birth rate of tumor cells increases with cell number in the regime of small population size. This indicates a potentially critical role of cooperative behavior among tumor cells at low cell densities with relevance to early stage growth patterns of emerging and relapsed tumors.

Metabolism and Gut Microbiota in Cancer Immunoediting, CD8/Treg Ratios, Immune Cell Homeostasis, and Cancer (Immuno)Therapy: Concise Review

The concept of immunoediting, a process whereby the immune system eliminates immunogenic cancer cell clones, allowing the remaining cells to progress and form a tumor, has evolved with growing appreciation of the importance of cancer ecology on tumor progression. As cancer cells grow and modify their environment, they create spatial and nutrient constraints that may affect not only immune cell function but also differentiation, tipping the balance between cytotoxic and regulatory immunity to facilitate tumor growth. Here, we review how immunometabolism may contribute to cancer escape from the immune system, as well as highlight an emerging role of gut microbiota, its effects on the immune system and on response to immunotherapy. We conclude with a discussion of how these pieces can be integrated to devise better combination therapies and highlight the role of computational approaches as a potential tool to aid in combination therapy design. Stem Cells 2019;37:1273-1280.

Targeting the tumour stroma to improve cancer therapy

Cancers are not composed merely of cancer cells alone; instead, they are complex 'ecosystems' comprising many different cell types and noncellular factors. The tumour stroma is a critical component of the tumour microenvironment, where it has crucial roles in tumour initiation, progression, and metastasis. Most anticancer therapies target cancer cells specifically, but the tumour stroma can promote the resistance of cancer cells to such therapies, eventually resulting in fatal disease. Therefore, novel treatment strategies should combine anticancer and antistromal agents. Herein, we provide an overview of the advances in understanding the complex cancer cell-tumour stroma interactions and discuss how this knowledge can result in more effective therapeutic strategies, which might ultimately improve patient outcomes.

Natural Selection Between Two Games with Applications to Game Theoretical Models of Cancer

Evolutionary game theory has been used extensively to study single games as applied to cancer, including in the context of metabolism, development of resistance, and even games between tumor and treatment. However, the situation when several games are being played against each other at the same time has not yet been investigated. Here, we describe a mathematical framework for analyzing natural selection not just between strategies, but between games. We provide theoretical analysis of situations of natural selection between the games of Prisoner's dilemma and Hawk-Dove, and demonstrate that while the dynamics of cooperators and defectors within their respective games is as expected, the distribution of games changes over time due to natural selection. We also investigate the question of mutual invasibility of games with respect to different strategies and different initial population composition. We conclude with a discussion of how the proposed approach can be applied to other games in cancer, such as motility versus stability strategies that underlie the process of metastatic invasion.

Life History Trade-Offs in Tumors

Purpose

In this paper, we provide an overview of a life history theory and how it applies to cancer evolution.

Recent Findings

We review the literature on trade-offs in tumors, focusing on the trade-offs among cellular proliferation, survival, and motility. Trade-offs are critical natural constraints for almost all evolutionary processes. Many ecological studies show that trade-offs among these cellular functions maintain a genetic diversity. In addition, these trade-offs are not fixed, but rather can shift depending on the ecological circumstances in the microenvironment. This can lead to selection for the cellular capacity to respond to these differing microenvironments in ways that promote the fitness of the cancer cell. We relate these life history trade-offs to the recently developed Evo-Eco indexes and discuss how life history theory can help refine our measures of tumor evolution and ecology.

Summary

Life history theory provides a framework for understanding how the spatial and temporal variability in the tumor microenvironment—in particular resources and threats—affect trade-offs among cell survival, cell proliferation, and cell migration. We discuss how these trade-offs can potentially be leveraged in cancer therapy to increase the effectiveness of treatment.

Targeting Strategies for Glucose Metabolic Pathways and T Cells in Colorectal Cancer

Colorectal cancer is a heterogeneous group of diseases that result from the accumulation of different sets of genomic alterations, together with epigenomic alterations, and it is influenced by tumor-host interactions, leading to tumor cell growth and glycolytic imbalances. This review summarizes recent findings that involve multiple signaling molecules and downstream genes in the dysregulated glycolytic pathway. This paper further discusses the role of the dysregulated glycolytic pathway in the tumor initiation, progression and the concomitant systemic immunosuppression commonly observed in colorectal cancer patients. Moreover, the relationship between colorectal cancer cells and T cells, especially CD8+ T cells, is discussed, while different aspects of metabolic pathway regulation in cancer cell proliferation are comprehensively defined. Furthermore, this study elaborates on metabolism in colorectal cancer, specifically key metabolic modulators together with regulators, glycolytic enzymes, and glucose deprivation induced by tumor cells and how they inhibit T-cell glycolysis and immunogenic functions. Moreover, metabolic pathways that are integral to T cell function, differentiation, and activation are described. Selective metabolic inhibitors or immunemodulation agents targeting these pathways may be clinically useful to increase effector T cell responses for colorectal cancer treatment. However, there is a need to identify specific antigens using a cancer patient-personalized approach and combination strategies with other therapeutic agents to effectively target tumor metabolic pathways.

An ecosystem framework for understanding and treating disease

Pathogens and cancers are pervasive health risks in the human population. I argue that if we are to better understand disease and its treatment, then we need to take an ecological perspective of disease itself. I generalize and extend an emerging framework that views disease as an ecosystem and many of its components as interacting in a community. I develop the framework for biological etiological agents (BEAs) that multiply within humans—focusing on bacterial pathogens and cancers—but the framework could be extended to include other host and parasite species. I begin by describing why we need an ecosystem framework to understand disease, and the main components and interactions in bacterial and cancer disease ecosystems. Focus is then given to the BEA and how it may proceed through characteristic states, including emergence, growth, spread and regression. The framework is then applied to therapeutic interventions. Central to success is preventing BEA evasion, the best known being antibiotic resistance and chemotherapeutic resistance in cancers. With risks of evasion in mind, I propose six measures that either introduce new components into the disease ecosystem or manipulate existing ones. An ecosystem framework promises to enhance our understanding of disease, BEA and host (co)evolution, and how we can improve therapeutic outcomes.

Thinking Cancer

Evolutionary theories are necessarily invoked for understanding cancer development at the level of species, at the level of cells and tissues, and for developing effective therapies. It is crucial to view cancer in a Darwinian light, where the differential survival of individual cells is based on heritable variations. In the process of this somatic evolution, multicellularity controls are overridden by cancer cells, which become increasingly autonomous. Ecological epigenetics also helps understand how rogue cells that have basically the same DNA as their normal cell counterpart overcome the tissue homeostasis. As we struggle to wrap our minds around the complexity of these phenomena, we apply often times anthropomorphic terms, such as subversion, hijacking, or hacking, to describe especially the most complex among them-the interaction of tumors with the immune system. In this commentary we highlight examples of the anthropomorphic thinking of cancer and try to put into context the relative meaning of terms and the mechanisms that are oftentimes invoked to justify those terms.

Epigenetic control of macrophage polarization: implications for targeting tumor-associated macrophages

The progression of cancer is a result of not only the growth of the malignant cells but also the behavior of other components of the tumor microenvironment (TME). Tumor-associated macrophages (TAMs) are key components of the TME that influence tumor growth and disease progression. TAMs can either inhibit or support tumor growth depending on their polarization to classically-activated macrophages (M1s) or alternatively-activated macrophages (M2s), respectively. Epigenetic regulation plays a significant role in determining this polarization and manipulating the epigenetic regulation in macrophages would provide a means for selectively targeting M2s thereby eliminating tumor-supporting TAMs while sparing tumor-inhibiting M1 TAMs. Many pharmacologic modulators of epigenetic enzymes are currently used clinically and could be repurposed for treating tumors with high TAM infiltrate. While much research involving epigenetic enzymes and their modulators has been performed in M1s, significantly less is known about the epigenetic regulation of M2s. This review highlights the field’s current knowledge of key epigenetic enzymes and their pharmacologic modulators known to influence macrophage polarization.

Hallmarks of Bone Metastasis

Breast cancer bone metastasis develops as the result of a series of complex interactions between tumor cells, bone marrow cells, and resident bone cells. The net effect of these interactions are the disruption of normal bone homeostasis, often with significantly increased osteoclast and osteoblast activity, which has provided a rational target for controlling tumor progression, with little or no emphasis on tumor eradication. Indeed, the clinical course of metastatic breast cancer is relatively long, with patients likely to experience sequential skeletal-related events (SREs), often over lengthy periods of time, even up to decades. These SREs include bone pain, fractures, and spinal cord compression, all of which may profoundly impair a patient's quality-of-life. Our understanding of the contributions of the host bone and bone marrow cells to the control of tumor progression has grown over the years, yet the focus of virtually all available treatments remains on the control of resident bone cells, primarily osteoclasts. In this perspective, our focus is to move away from the current emphasis on the control of bone cells and focus our attention on the hallmarks of bone metastatic tumor cells and how these differ from primary tumor cells and normal host cells. In our opinion, there remains a largely unmet medical need to develop and utilize therapies that impede metastatic tumor cells while sparing normal host bone and bone marrow cells. This perspective examines the impact of metastatic tumor cells on the bone microenvironment and proposes potential new directions for uncovering the important mechanisms driving metastatic progression in bone based on the hallmarks of bone metastasis.

Gaining insights into cancer biology through exploration of the cancer secretome using proteomic and bioinformatic tools

INTRODUCTION

Tumor-associated proteins released by cancer cells and by tumor stroma cells, referred as 'cancer secretome', represent a valuable resource for discovery of potential cancer biomarkers. The last decade was marked by a great increase in number of studies focused on various aspects of cancer secretome including, composition and identification of components externalized by malignant cells and by the components of tumor microenvironment. Areas covered: Here, we provide an overview of achievements in the proteomic analysis of the cancer secretome, elicited through the tumor-associated interstitial fluid recovered from malignant tissues ex vivo or the protein component of conditioned media obtained from cultured cancer cells in vitro. We summarize various bioinformatic tools and approaches and critically appraise their outcomes, focusing on problems and challenges that arise when applied for the analysis of cancer secretomic databases. Expert commentary: Recent achievements in the omics- analysis of structural and metabolic aspects of altered cancer secretome contribute greatly to the various hallmarks of cancer including the identification of clinically significant biomarkers and potential targets for therapeutic intervention.

Classifying the evolutionary and ecological features of neoplasms

Neoplasms change over time through a process of cell-level evolution, driven by genetic and epigenetic alterations. However, the ecology of the microenvironment of a neoplastic cell determines which changes provide adaptive benefits. There is widespread recognition of the importance of these evolutionary and ecological processes in cancer, but to date, no system has been proposed for drawing clinically relevant distinctions between how different tumours are evolving. On the basis of a consensus conference of experts in the fields of cancer evolution and cancer ecology, we propose a framework for classifying tumours that is based on four relevant components. These are the diversity of neoplastic cells (intratumoural heterogeneity) and changes over time in that diversity, which make up an evolutionary index (Evo-index), as well as the hazards to neoplastic cell survival and the resources available to neoplastic cells, which make up an ecological index (Eco-index). We review evidence demonstrating the importance of each of these factors and describe multiple methods that can be used to measure them. Development of this classification system holds promise for enabling clinicians to personalize optimal interventions based on the evolvability of the patient's tumour. The Evo- and Eco-indices provide a common lexicon for communicating about how neoplasms change in response to interventions, with potential implications for clinical trials, personalized medicine and basic cancer research.

Whole tumor RNA-sequencing and deconvolution reveal a clinically-prognostic PTEN/PI3K-regulated glioma transcriptional signature

The concept that solid tumors are maintained by a productive interplay between neoplastic and non-neoplastic elements has gained traction with the demonstration that stromal fibroblasts and immune system cells dictate cancer development and progression. While less studied, brain tumor (glioma) biology is likewise influenced by non-neoplastic immune system cells (macrophages and microglia) which interact with neoplastic glioma cells to create a unique physiological state (glioma ecosystem) distinct from that found in the normal tissue. To explore this neoplastic ground state, we leveraged several preclinical mouse models of neurofibromatosis type 1 (NF1) optic glioma, a low-grade astrocytoma whose formation and maintenance requires productive interactions between non-neoplastic and neoplastic cells, and employed whole tumor RNA-sequencing and mathematical deconvolution strategies to characterize this low-grade glioma ecosystem as an aggregate of cellular and acellular elements. Using this approach, we demonstrate that optic gliomas generated by altering the germline Nf1 gene mutation, the glioma cell of origin, or the presence of co-existing genetic alterations represent molecularly-distinct tumors. However, these optic glioma tumors share a 25-gene core signature, not found in normal optic nerve, that is normalized by microglia inhibition (minocycline), but not conventional (carboplatin) or molecularly-targeted (rapamycin) chemotherapy. Lastly, we identify a genetic signature conferred by Pten reduction and corrected by PI3K inhibition. This signature predicts progression-free survival in patients with either low-grade or high-grade glioma. Collectively, these findings support the concept that gliomas are composite ecological systems whose biology and response to therapy may be best defined by examining the tumor as a whole.

Revisiting Seed and Soil: Examining the Primary Tumor and Cancer Cell Foraging in Metastasis

Metastasis is the consequence of a cancer cell that disperses from the primary tumor, travels throughout the body, and invades and colonizes a distant site. On the basis of Paget's 1889 hypothesis, the majority of modern metastasis research focuses on the properties of the metastatic "seed and soil," but the implications of the primary tumor "soil" have been largely neglected. The rare lethal metastatic "seed" arises as a result of the selective pressures in the primary tumor. Optimal foraging theory describes how cancer cells adopt a mobile foraging strategy to balance predation risk and resource reward. Further selection in the dispersal corridors leading out of the primary tumor enhances the adaptive profile of the potentially metastatic cell. This review focuses on the selective pressures of the primary tumor "soil" that generate lethal metastatic "seeds" which is essential to understanding this critical component of prostate cancer metastasis.Implication: Elucidating the selective pressures of the primary tumor "soil" that generate lethal metastatic "seeds" is essential to understand how and why metastasis occurs in prostate cancer. Mol Cancer Res; 15(4); 361-70. ©2017 AACR.

GSH-dependent antioxidant defense contributes to the acclimation of colon cancer cells to acidic microenvironment

Due to increased glycolysis and poor local perfusion, solid tumors are usually immersed in an acidic microenvironment. While extracellular acidosis is cytotoxic, cancer cells eventually become acclimated to it. While previous studies have addressed the acute effect of acidosis on cancer cells, little is known about how cancer cells survive chronic acidosis. In this study we exposed colorectal cancer (CRC) cells (HCT15, HCT116 and LoVo) to acidic pH (pH 6.5) continuously for over three months and obtained CRC cells that become acclimated to acidic pH, designated as CRC-acidosis-acclimated or CRC-AA. We unexpectedly found that while acute exposure to low pH resulted in an increase in the level of intracellular reactive oxygen species (ROS), CRC-AA cells exhibited a significantly reduced level of ROS when compared to ancestor cells. CRC-AA cells were found to maintain a higher level of reduced glutathione, via the upregulation of CD44 and glutathione reductase (GSR), among others, than their ancestor cells. Importantly, CRC-AA cells were more sensitive to agents that deplete GSH. Moreover, downregulation of GSR by RNA interference was more deleterious to CRC-AA cells than to control cells. Together, our results demonstrate a critical role of glutathione-dependent antioxidant defense in acclimation of CRC cells to acidic extracellular pH.

GDF15 promotes EMT and metastasis in colorectal cancer

Metastasis is the major cause of cancer deaths, and the epithelial–mesenchymal transition (EMT) has been considered to be a fundamental event in cancer metastasis. However, the role of growth differentiation factor 15 (GDF15) in colorectal cancer (CRC) metastasis and EMT remains poorly understood. Here, we showed that GDF15 promoted CRC cell metastasis both in vitro and in vivo. In addition, the EMT process was enhanced by GDF15 through binding to TGF-β receptor to activate Smad2 and Smad3 pathways. Clinical data showed GDF15 level in tumor tissues, and the serum was significantly increased, in which high GDF15 level correlated with a reduced overall survival in CRC. Thus, GDF15 may promote colorectal cancer metastasis through activating EMT. Promisingly, GDF15 could be considered as a novel prognostic marker for CRC in the clinic.

Ecological paradigms to understand the dynamics of metastasis

The process by which prostate cancer cells non-randomly disseminate to the bone to form lethal metastases remains unknown. Metastasis is the ultimate consequence of the long-range dispersal of a cancer cell from the primary tumor to a distant secondary site. In order to metastasize, the actively emigrating cell must move. Movement ecology describes an individual's migration between habitats without the requirement of conscious decision-making. Specifically, this paradigm describes four interacting components that influence the dynamic process of metastasis: (1) the microenvironmental pressures exerted on the cancer cell, (2) how the individual cell reacts to these external pressures, (3) the phenotypic switch of a cell to gain the physical traits required for movement, and (4) the ability of the cancer cell to navigate to a specific site. A deeper understanding of each of these components will lead to the development of novel therapeutics targeted to interrupt previously unidentified steps of metastasis.