Life history trade-offs in cancer evolution

Cancer cells forgo translating mRNA transcribed from genes of nonspecialized tasks

The coupling of transcription and translation enables prokaryotes to regulate mRNA stability and reduce nonfunctional transcripts. Eukaryotes evolved other means to perform these functions. Here, we quantify the disparity between gene expression and protein levels and attempt to explain its origins. We collected publicly available simultaneous measurements of gene expression, protein level, division rate, and growth inhibition of breast cancer cells under drug perturbation. We used the cell lines as entities with shared origin, different evolutionary trajectories, and cancer hallmarks to define tasks subject to specializing and trading-off. We observed varying average mRNA and protein correlation across cell lines, and it was consistently higher for the gene products in the cancer hallmarks. The enrichment of hallmark gene products signifies the resources invested in it as a task. Enrichment based on mRNA or protein abundance corresponds to the relative resources dedicated to transcription and translation. The differences in gene- and protein-based enrichment correlated with nominal division rates but not growth inhibition under drug perturbations. Comparing the range of enrichment scores of the hallmarks within each cell signifies the resources dedicated to each. Cells appear to have a wider range of enrichment in protein synthesis relative to gene transcription. The difference and range of enrichment of the hallmark genes and proteins correlated with cell division and inhibition in response to drug treatments. We posit that cancer cells may express the genes coding for seemingly nonspecialized tasks but do not translate them to the corresponding proteins. This trade-off may cost the cells under normal conditions but confer benefits during stress.

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.

Testing Adaptive Therapy Protocols Using Gemcitabine and Capecitabine in a Preclinical Model of Endocrine-Resistant Breast Cancer

Adaptive therapy, an ecologically inspired approach to cancer treatment, aims to overcome resistance and reduce toxicity by leveraging competitive interactions between drug-sensitive and drug-resistant subclones, prioritizing patient survival and quality of life instead of killing the maximum number of cancer cells. In preparation for a clinical trial, we used endocrine-resistant MCF7 breast cancer to stimulate second-line therapy and tested adaptive therapy using capecitabine, gemcitabine, or their combination in a mouse xenograft model. Dose modulation adaptive therapy with capecitabine alone increased survival time relative to MTD but not statistically significantly (HR = 0.22, 95% CI = 0.043-1.1, p = 0.065). However, when we alternated the drugs in both dose modulation (HR = 0.11, 95% CI = 0.024-0.55, p = 0.007) and intermittent adaptive therapies, the survival time was significantly increased compared to high-dose combination therapy (HR = 0.07, 95% CI = 0.013-0.42, p = 0.003). Overall, the survival time increased with reduced dose for both single drugs (p < 0.01) and combined drugs (p < 0.001), resulting in tumors with fewer proliferation cells (p = 0.0026) and more apoptotic cells (p = 0.045) compared to high-dose therapy. Adaptive therapy favors slower-growing tumors and shows promise in two-drug alternating regimens instead of being combined.

The impact of food availability on tumorigenesis is evolutionarily conserved

The inability to control cell proliferation results in the formation of tumors in many multicellular lineages. Nonetheless, little is known about the extent of conservation of the biological traits and ecological factors that promote or inhibit tumorigenesis across the metazoan tree. Particularly, changes in food availability have been linked to increased cancer incidence in humans, as an outcome of evolutionary mismatch. Here, we apply evolutionary oncology principles to test whether food availability, regardless of the multicellular lineage considered, has an impact on tumorigenesis. We used two phylogenetically unrelated model systems, the cnidarian Hydra oligactis and the fish Danio rerio, to investigate the impact of resource availability on tumor occurrence and progression. Individuals from healthy and tumor-prone lines were placed on four diets that differed in feeding frequency and quantity. For both models, frequent overfeeding favored tumor emergence, while lean diets appeared more protective. In terms of tumor progression, high food availability promoted it, whereas low resources controlled it, but without having a curative effect. We discuss our results in light of current ideas about the possible conservation of basic processes governing cancer in metazoans (including ancestral life history trade-offs at the cell level) and in the framework of evolutionary medicine.

Testing Adaptive Therapy Protocols using Gemcitabine and Capecitabine on a Mouse Model of Endocrine-Resistant Breast Cancer

Highly effective cancer therapies often face limitations due to acquired resistance and toxicity. Adaptive therapy, an ecologically inspired approach, seeks to control therapeutic resistance and minimize toxicity by leveraging competitive interactions between drug-sensitive and drug-resistant subclones, prioritizing patient survival and quality of life over maximum cell kill. In preparation for a clinical trial in breast cancer, we used large populations of MCF7 cells to rapidly generate endocrine-resistance breast cancer cell line. We then mimicked second line therapy in ER+ breast cancers by treating the endocrine-resistant MCF7 cells in a mouse xenograft model to test adaptive therapy with capecitabine, gemcitabine, or the combination of those two drugs. Dose-modulation adaptive therapy with capecitabine alone increased survival time relative to MTD, but not statistically significant (HR: 0.22, 95% CI 0.043- 1.1 P = 0.065). However, when we alternated the drugs in both dose modulation (HR = 0.11, 95% CI: 0.024 - 0.55, P = 0.007) and intermittent adaptive therapies significantly increased survival time compared to high dose combination therapy (HR = 0.07, 95% CI: 0.013 - 0.42; P = 0.003). Overall, survival time increased with reduced dose for both single drugs (P < 0.01) and combined drugs (P < 0.001). Adaptive therapy protocols resulted in tumors with lower proportions of proliferating cells (P = 0.0026) and more apoptotic cells (P = 0.045). The results show that Adaptive therapy outperforms high-dose therapy in controlling endocrine-resistant breast cancer, favoring slower-growing tumors, and showing promise in two-drug alternating regimens.

Evolutionary fingerprints of EMT in pancreatic cancers

Mesenchymal plasticity has been extensively described in advanced and metastatic epithelial cancers; however, its functional role in malignant progression, metastatic dissemination and therapy response is controversial. More importantly, the role of epithelial mesenchymal transition (EMT) and cell plasticity in tumor heterogeneity, clonal selection and clonal evolution is poorly understood. Functionally, our work clarifies the contribution of EMT to malignant progression and metastasis in pancreatic cancer. We leveraged ad hoc somatic mosaic genome engineering, lineage tracing and ablation technologies and dynamic genetic reporters to trace and ablate tumor-specific lineages along the phenotypic spectrum of epithelial to mesenchymal plasticity. The experimental evidences clarify the essential contribution of mesenchymal lineages to pancreatic cancer evolution and metastatic dissemination. Spatial genomic analysis combined with single cell transcriptomic and epigenomic profiling of epithelial and mesenchymal lineages reveals that EMT promotes with the emergence of chromosomal instability (CIN). Specifically tumor lineages with mesenchymal features display highly conserved patterns of genomic evolution including complex structural genomic rearrangements and chromotriptic events. Genetic ablation of mesenchymal lineages robustly abolished these mutational processes and evolutionary patterns, as confirmed by cross species analysis of pancreatic and other human epithelial cancers. Mechanistically, we discovered that malignant cells with mesenchymal features display increased chromatin accessibility, particularly in the pericentromeric and centromeric regions, which in turn results in delayed mitosis and catastrophic cell division. Therefore, EMT favors the emergence of high-fitness tumor cells, strongly supporting the concept of a cell-state, lineage-restricted patterns of evolution, where cancer cell sub-clonal speciation is propagated to progenies only through restricted functional compartments. Restraining those evolutionary routes through genetic ablation of clones capable of mesenchymal plasticity and extinction of the derived lineages completely abrogates the malignant potential of one of the most aggressive form of human cancer.

Tumors produce glucocorticoids by metabolite recycling, not synthesis, and activate Tregs to promote growth

Glucocorticoids are steroid hormones with potent immunosuppressive properties. Their primary source is the adrenals, where they are generated via de novo synthesis from cholesterol. In addition, many tissues have a recycling pathway in which glucocorticoids are regenerated from inactive metabolites by the enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1, encoded by Hsd11b1). Here, we find that multiple tumor types express Hsd11b1 and produce active glucocorticoids. Genetic ablation of Hsd11b1 in such cells had no effect on in vitro growth, but reduced in vivo tumor progression, which corresponded with increased frequencies of CD8+ tumor-infiltrating lymphocytes (TILs) expressing activation markers and producing effector cytokines. Tumor-derived glucocorticoids were found to promote signatures of Treg activation and suppress signatures of conventional T cell activation in tumor-infiltrating Tregs. Indeed, CD8+ T cell activation was restored and tumor growth reduced in mice with Treg-specific glucocorticoid receptor deficiency. Importantly, pharmacologic inhibition of 11β-HSD1 reduced tumor growth to the same degree as gene knockout and rendered immunotherapy-resistant tumors susceptible to PD-1 blockade. Given that HSD11B1 expression is upregulated in many human tumors and that inhibition of 11β-HSD1 is well tolerated in clinical studies, these data suggest that targeting 11β-HSD1 may be a beneficial adjunct in cancer therapy.

Mathematical Modeling of Clonal Interference by Density-Dependent Selection in Heterogeneous Cancer Cell Lines

Many cancer cell lines are aneuploid and heterogeneous, with multiple karyotypes co-existing within the same cell line. Karyotype heterogeneity has been shown to manifest phenotypically, thus affecting how cells respond to drugs or to minor differences in culture media. Knowing how to interpret karyotype heterogeneity phenotypically would give insights into cellular phenotypes before they unfold temporally. Here, we re-analyzed single cell RNA (scRNA) and scDNA sequencing data from eight stomach cancer cell lines by placing gene expression programs into a phenotypic context. Using live cell imaging, we quantified differences in the growth rate and contact inhibition between the eight cell lines and used these differences to prioritize the transcriptomic biomarkers of the growth rate and carrying capacity. Using these biomarkers, we found significant differences in the predicted growth rate or carrying capacity between multiple karyotypes detected within the same cell line. We used these predictions to simulate how the clonal composition of a cell line would change depending on density conditions during in-vitro experiments. Once validated, these models can aid in the design of experiments that steer evolution with density-dependent selection.

An oncospace for human cancers

Human cancers comprise an heterogeneous array of diseases with different progression patterns and responses to therapy. However, they all develop within a host context that constrains their natural history. Since it occurs across the diversity of organisms, one can conjecture that there is order in the cancer multiverse. Is there a way to capture the broad range of tumor types within a space of the possible? Here we define the oncospace, a coordinate system that integrates the ecological, evolutionary and developmental components of cancer complexity. The spatial position of a tumor results from its departure from the healthy tissue along these three axes, and progression trajectories inform about the components driving malignancy across cancer subtypes. We postulate that the oncospace topology encodes new information regarding tumorigenic pathways, subtype prognosis, and therapeutic opportunities: treatment design could benefit from considering how to nudge tumors toward empty evolutionary dead ends in the oncospace.

Cell starvation increases uptake of extracellular Thymosin β4 and its complexes with calcium

Cell metastasis is the main cause of cancer mortality. Inhibiting early events during cell metastasis and invasion could significantly improve cancer prognosis, but the initial mechanisms of cell transition and migration are barely known. Calcium regulates cell migration, whilst Thymosin β4 is a G-actin and iron binding peptide associated with tumor metastasis and ferroptosis. Under normal cell growth conditions, intracellular free calcium ions and Thymosin β4 concentrations are strictly regulated, and are not influenced by extracellular supplementation. However, cell starvation decreases intracellular Thymosin β4 and increases extracellular peptide uptake above the normal range. Unexpectedly, cell starvation significantly increases internalization of extracellular Ca²⁺/Thymosin β4 complexes. Elucidating the role of Ca²⁺/Thymosin β4 in the early events of metastasis will likely be important in the future to develop therapies targeting metastasis.

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 antiproliferative and apoptotic potential of Clinacanthus nutans against human breast cancer cells through targeted apoptosis pathway

Clinacanthus nutans dichloromethane fraction (CN-Dcm) extract has previously been proven to suppress breast cancer (MCF7) cell proliferation. Despite this, the extrinsic and intrinsic apoptosis mechanisms involved in C. nutans extract-treated MCF7 cells are still unknown. This study was intended to subfractionate CN-Dcm extract using column chromatography and analyse the treated MCF7 cells using the CellTiter 96® AQueous One Solution Cell Proliferation (MTS) assay, Annexin V/propidium iodide (PI) assay, western blot, and reverse transcription-qualitative polymerase chain reaction (RT-qPCR). Out of nine subfraction extracts (SF1 to SF9), SF2 extract strongly inhibited MCF7 cells with the lowest IC50 value (23.51 ± 1.00 µg/mL) and substantially induced apoptosis in the MCF7 cells. In treated MCF7 cells, SF2 extract significantly upregulated the expression of P53, BAX, BID, caspase-8, caspase-9, and caspase-3, while downregulating the expression of BCL2. The presence of potential bioactive chemical compounds in the SF2 extract was identified using liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). Thus, the SF2 extract has the potential to induce apoptosis in MCF7 cells through intrinsic and extrinsic pathways.

Disruption of cancer cell functions by task-specific drug perturbations

Cancer expands clonally, capitalizing on the variations between growing cells. Cancer cells specialize in one or more functions to gain an advantage. This study examined the prediction that cells would be vulnerable to drugs that perturb their specific tasks. We analyzed the correlation between gene expression and the response to drug perturbations in different cancer cells. Next, we assigned every cancer cell to an archetype based on gene expression. Finally, we calculated the enrichment of the cancer hallmark gene sets in each cell, archetypes, and response to drug treatment. We found that the extremes of gene expression were susceptible to change in response to perturbations. This correlation predicted the growth rate inhibition of breast cancer cells. Cancer hallmarks were enriched differently in the archetypes, and this enrichment predicted the cell’s response to perturbations. We present evidence that specialized cancer cells are sensitive to compounds that perturb their tasks.

Population genetics of clonally transmissible cancers

Populations of cancer cells are subject to the same core evolutionary processes as asexually reproducing, unicellular organisms. Transmissible cancers are particularly striking examples of these processes. These unusual cancers are clonal lineages that can spread through populations via physical transfer of living cancer cells from one host individual to another, and they have achieved long-term success in the colonization of at least eight different host species. Population genetic theory provides a useful framework for understanding the shift from a multicellular sexual animal into a unicellular asexual clone and its long-term effects on the genomes of these cancers. In this Review, we consider recent findings from transmissible cancer research with the goals of developing an evolutionarily informed perspective on transmissible cancers, examining possible implications for their long-term fate and identifying areas for future research on these exceptional lineages.

Cancer Susceptibility as a Cost of Reproduction and Contributor to Life History Evolution

Reproduction is one of the most energetically demanding life-history stages. As a result, breeding individuals often experience trade-offs, where energy is diverted away from maintenance (cell repair, immune function) toward reproduction. While it is increasingly acknowledged that oncogenic processes are omnipresent, evolving and opportunistic entities in the bodies of metazoans, the associations among reproductive activities, energy expenditure, and the dynamics of malignant cells have rarely been studied. Here, we review the diverse ways in which age-specific reproductive performance (e.g., reproductive aging patterns) and cancer risks throughout the life course may be linked via trade-offs or other mechanisms, as well as discuss situations where trade-offs may not exist. We argue that the interactions between host–oncogenic processes should play a significant role in life-history theory, and suggest some avenues for future research.

Tumour immunotherapy: lessons from predator-prey theory

With the burgeoning use of immune-based treatments for cancer, never has there been a greater need to understand the tumour microenvironment within which immune cells function and how it can be perturbed to inhibit tumour growth. Yet, current challenges in identifying optimal combinations of immunotherapies and engineering new cell-based therapies highlight the limitations of conventional paradigms for the study of the tumour microenvironment. Ecology has a rich history of studying predator-prey dynamics to discern factors that drive prey to extinction. Here, we describe the basic tenets of predator-prey theory as applied to 'predation' by immune cells and the 'extinction' of cancer cells. Our synthesis reveals fundamental mechanisms by which antitumour immunity might fail in sometimes counterintuitive ways and provides a fresh yet evidence-based framework to better understand and therapeutically target the immune-cancer interface.

Cancer cell foraging to explain bone-specific metastatic progression

Metastatic cancer is lethal and patients who suffer bone metastases fare especially poorly. Bone-specific metastatic progression in prostate and breast cancers is a highly observed example of organ-specific metastasis, or organotropism. Though research has delineated the sequential steps of the metastatic cascade, the determinants of bone-specific metastasis have remained elusive for decades. Applying fundamental ecological principles to cancer biology models of metastasis provides novel insights into metastatic organotropism. We use critical concepts from foraging theory and movement ecology to propose that observed bone-specific metastasis is the result of habitat selection by foraging cancer cells. Furthermore, we posit that cancer cells can only perform habitat selection if and when they employ a reversible motile foraging strategy. Only a very small percentage of cells in a primary tumor harbor this ability. Therefore, our habitat selection model emphasizes the importance of identifying the rare subset of cancer cells that might exhibit habitat selection, ergo achieve bone-specific metastatic colonization.

Find the path of least resistance: Adaptive therapy to delay treatment failure and improve outcomes

Cytotoxic chemotherapy and targeted therapies help people with advanced cancers, but for most, treatment fails. Cancer heterogeneity is one cause of treatment failure, but also suggests an opportunity to improve outcomes; reconceptualising cancer therapy as an ecological problem offers the strategy of adaptive therapy. If an agent is active against a patient's cancer, instead of traditional continuous dosing at the maximum tolerated dose until treatment failure, the patient and their oncologist may instead choose to pause treatment as soon as the cancer responds. When tumour burden increases, the cancer is rechallenged with the same agent in hope of delivering another response, ideally before symptoms occur or quality-of-life is impacted. These 'loops' of 'pause/restart' allows an active treatment to be used strategically, to delay the development of evolutionary selection within the cancer, delaying the onset of treatment resistance, controlling the cancer for longer. Modelling predicts patients can navigate several 'loops', potentially increasing the utility of an active treatment by multiples, and early trials suggest at least doubling of progression-free survival. In this narrative review we confront how cancer heterogeneity limits treatment effectiveness, re-examine cancer as an ecological problem, review the data supporting adaptive therapy and outline the challenges and opportunities faced in clinical practice to implement this evolutionary concept. In an era where multiple novel active anti-neoplastic agents are being used with ancient inflexibile maximum tolerated dose for maximum duration approaches, adaptive dosing offers a personalised, n = 1 approach to cancer therapy selection.

Positive selection and enhancer evolution shaped lifespan and body mass in great apes

Within primates, the great apes are outliers both in terms of body size and lifespan, since they include the largest and longest-lived species in the order. Yet, the molecular bases underlying such features are poorly understood. Here, we leveraged an integrated approach to investigate multiple sources of molecular variation across primates, focusing on over ten thousand genes, including ∼1,500 previously associated with lifespan, and additional ∼9,000 for which an association with longevity has never been suggested. We analyzed dN/dS rates, positive selection, gene expression (RNA-seq) and gene regulation (ChIP-seq). By analyzing the correlation between dN/dS, maximum lifespan and body mass we identified 276 genes whose rate of evolution positively correlates with maximum lifespan in primates. Further, we identified 5 genes, important for tumor suppression, adaptive immunity, metastasis and inflammation, under positive selection exclusively in the great ape lineage. RNA-seq data, generated from the liver of six species representing all the primate lineages, revealed that 8% of ∼1,500 genes previously associated with longevity are differentially expressed in apes relative to other primates. Importantly, by integrating RNA-seq with ChIP-seq for H3K27ac (which marks active enhancers), we show that the differentially expressed longevity genes are significantly more likely than expected to be located near a novel "ape-specific" enhancer. Moreover, these particular ape-specific enhancers are enriched for young transposable elements, and specifically SINE-Vntr-Alus (SVAs). In summary, we demonstrate that multiple evolutionary forces have contributed to the evolution of lifespan and body size in primates.

Evolution under spatially heterogeneous selection in solid tumors

Spatial genetic and phenotypic diversity within solid tumors has been well documented. Nevertheless, how this heterogeneity affects temporal dynamics of tumorigenesis has not been rigorously examined because solid tumors do not evolve as the standard population genetic model due to the spatial constraint. We therefore, propose a neutral spatial (NS) model whereby the mutation accumulation increases toward the periphery; the genealogical relationship is spatially determined and the selection efficacy is blunted (due to kin competition). In this model, neutral mutations are accrued and spatially distributed in manners different from those of advantageous mutations. Importantly, the distinctions could be blurred in the conventional model. To test the NS model, we performed a three-dimensional multiple microsampling of two hepatocellular carcinomas. Whole-genome sequencing (WGS) revealed a 2-fold increase in mutations going from the center to the periphery. The operation of natural selection can then be tested by examining the spatially determined clonal relationships and the clonal sizes. Due to limited migration, only the expansion of highly advantageous clones can sweep through a large part of the tumor to reveal the selective advantages. Hence, even multiregional sampling can only reveal a fraction of fitness differences in solid tumors. Our results suggest that the NS patterns are crucial for testing the influence of natural selection during tumorigenesis, especially for small solid tumors.

Clonal Architecture and Evolutionary Dynamics in Acute Myeloid Leukemias

Acute myeloid leukemias (AML) results from the accumulation of genetic and epigenetic alterations, often in the context of an aging hematopoietic environment. The development of high-throughput sequencing-and more recently, of single-cell technologies-has shed light on the intratumoral diversity of leukemic cells. Taking AML as a model disease, we review the multiple sources of genetic, epigenetic, and functional heterogeneity of leukemic cells and discuss the definition of a leukemic clone extending its definition beyond genetics. After introducing the two dimensions contributing to clonal diversity, namely, richness (number of leukemic clones) and evenness (distribution of clone sizes), we discuss the mechanisms at the origin of clonal emergence (mutation rate, number of generations, and effective size of the leukemic population) and the causes of clonal dynamics. We discuss the possible role of neutral drift, but also of cell-intrinsic and -extrinsic influences on clonal fitness. After reviewing available data on the prognostic role of genetic and epigenetic diversity of leukemic cells on patients' outcome, we discuss how a better understanding of AML as an evolutionary process could lead to the design of novel therapeutic strategies in this disease.

Cell competition, cooperation, and cancer

Complex multicellular organisms require quantitative and qualitative assessments on each of their constitutive cell types to ensure coordinated and cooperative behavior towards overall functional proficiency. Cell competition represents one of the operating arms of such quality control mechanisms and relies on fitness comparison among individual cells. However, what is exactly included in the fitness equation for each cell type is still uncertain. Evidence will be discussed to suggest that the ability of the cell to integrate and collaborate within the organismal community represents an integral part of the best fitness phenotype. Thus, under normal conditions, cell competition will select against the emergence of altered cells with disruptive behavior towards tissue integrity and/or tissue pattern formation. On the other hand, the winner phenotype prevailing as a result of cell competition does not entail, by itself, any degree of growth autonomy. While cell competition per se should not be considered as a biological driving force towards the emergence of the neoplastic phenotype, it is possible that the molecular machinery involved in the winner/loser interaction could be hijacked by evolving cancer cell populations.

Drug-induced resistance evolution necessitates less aggressive treatment

Increasing body of experimental evidence suggests that anticancer and antimicrobial therapies may themselves promote the acquisition of drug resistance by increasing mutability. The successful control of evolving populations requires that such biological costs of control are identified, quantified and included to the evolutionarily informed treatment protocol. Here we identify, characterise and exploit a trade-off between decreasing the target population size and generating a surplus of treatment-induced rescue mutations. We show that the probability of cure is maximized at an intermediate dosage, below the drug concentration yielding maximal population decay, suggesting that treatment outcomes may in some cases be substantially improved by less aggressive treatment strategies. We also provide a general analytical relationship that implicitly links growth rate, pharmacodynamics and dose-dependent mutation rate to an optimal control law. Our results highlight the important, but often neglected, role of fundamental eco-evolutionary costs of control. These costs can often lead to situations, where decreasing the cumulative drug dosage may be preferable even when the objective of the treatment is elimination, and not containment. Taken together, our results thus add to the ongoing criticism of the standard practice of administering aggressive, high-dose therapies and motivate further experimental and clinical investigation of the mutagenicity and other hidden collateral costs of therapies.

Principles of seed banks and the emergence of complexity from dormancy

Across the tree of life, populations have evolved the capacity to contend with suboptimal conditions by engaging in dormancy, whereby individuals enter a reversible state of reduced metabolic activity. The resulting seed banks are complex, storing information and imparting memory that gives rise to multi-scale structures and networks spanning collections of cells to entire ecosystems. We outline the fundamental attributes and emergent phenomena associated with dormancy and seed banks, with the vision for a unifying and mathematically based framework that can address problems in the life sciences, ranging from global change to cancer biology.

Rethinking the biology of metastatic melanoma: a holistic approach

Over the past decades, melanoma-related mortality has remained nearly stable. The main reason is treatment failure of metastatic disease and the inherently linked knowledge gap regarding metastasis formation. In order to elicit invasion, melanoma cells manipulate the tumor microenvironment, gain motility, and adhere to the extracellular matrix and cancer-associated fibroblasts. Melanoma cells thereby express different cell adhesion molecules like laminins, integrins, N-cadherin, and others. Epithelial-mesenchymal transition (EMT) is physiological during embryologic development, but reactivated during malignancy. Despite not being truly epithelial, neural crest-derived malignancies like melanoma share similar biological programs that enable tumorigenesis, invasion, and metastasis. This complex phenomenon is termed phenotype switching and is intertwined with oncometabolism as well as dormancy escape. Additionally, it has been shown that primary melanoma shed exosomes that create a favorable premetastatic niche in the microenvironment of secondary organs and lymph nodes. Although the growing body of literature describes the aforementioned concepts separately, an integrative holistic approach is missing. Using melanoma as a tumor model, this review will shed light on these complex biological principles in an attempt to clarify the mechanistic metastatic pathways that dictate tumor and patient fate.

Evolution of core archetypal phenotypes in progressive high grade serous ovarian cancer

The evolution of resistance in high-grade serous ovarian cancer (HGSOC) cells following chemotherapy is only partially understood. To understand the selection of factors driving heterogeneity before and through adaptation to treatment, we profile single-cell RNA-sequencing (scRNA-seq) transcriptomes of HGSOC tumors collected longitudinally during therapy. We analyze scRNA-seq data from two independent patient cohorts to reveal that HGSOC is driven by three archetypal phenotypes, defined as oncogenic states that describe the majority of the transcriptome variation. Using a multi-task learning approach to identify the biological tasks of each archetype, we identify metabolism and proliferation, cellular defense response, and DNA repair signaling as consistent cell states found across patients. Our analysis demonstrates a shift in favor of the metabolism and proliferation archetype versus cellular defense response archetype in cancer cells that received multiple lines of treatment. While archetypes are not consistently associated with specific whole-genome driver mutations, they are closely associated with subclonal populations at the single-cell level, indicating that subclones within a tumor often specialize in unique biological tasks. Our study reveals the core archetypes found in progressive HGSOC and shows consistent enrichment of subclones with the metabolism and proliferation archetype as resistance is acquired to multiple lines of therapy.

The many faces of cancer evolution

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

Testing Multi-Task Cancer Evolution: How Do We Test Ecological Hypotheses in Cancer?

Recently several authors described a family of models, according to which different cancer types and subtypes fall within a space of selective trade-offs between archetypes that maximize the performance of different tasks: cell division, biomass and energy production, lipogenesis, immune interaction, and invasion and tissue remodeling. On this picture, inter- and intratumor heterogeneity can be explained in part as a product of these selective trade-offs in different cancers, at different stages of cancer progression. The aim of this Perspective is to critically assess this approach. I use this case study to consider more generally both the advantages of using ecological models in the context of cancer, and the challenges facing testing of such models.

Genetic and Non-Genetic Mechanisms Underlying Cancer Evolution

Simple Summary

Our manuscript summarizes the up-to-date data on the complex and dynamic nature of adaptation mechanisms and evolutionary processes taking place during cancer initiation, development and progression. Although for decades cancer has been viewed as a process governed by genetic mechanisms, it is becoming more and more clear that non-genetic mechanisms may play an equally important role in cancer evolution. In this review, we bring together these fundamental concepts and discuss how those tightly interconnected mechanisms lead to the establishment of highly adaptive quickly evolving cancers. Furthermore, we argue that in depth understanding of cancer progression from the evolutionary perspective may allow the prediction and direction of the evolutionary path of cancer populations towards drug sensitive phenotypes and thus facilitate the development of more effective anti-cancer approaches.

Abstract

Cancer development can be defined as a process of cellular and tissular microevolution ultimately leading to malignancy. Strikingly, though this concept has prevailed in the field for more than a century, the precise mechanisms underlying evolutionary processes occurring within tumours remain largely uncharacterized and rather cryptic. Nevertheless, although our current knowledge is fragmentary, data collected to date suggest that most tumours display features compatible with a diverse array of evolutionary paths, suggesting that most of the existing macro-evolutionary models find their avatar in cancer biology. Herein, we discuss an up-to-date view of the fundamental genetic and non-genetic mechanisms underlying tumour evolution with the aim of concurring into an integrated view of the evolutionary forces at play throughout the emergence and progression of the disease and into the acquisition of resistance to diverse therapeutic paradigms. Our ultimate goal is to delve into the intricacies of genetic and non-genetic networks underlying tumour evolution to build a framework where both core concepts are considered non-negligible and equally fundamental.

An evolutionary mismatch narrative to improve lifestyle medicine: a patient education hypothesis

An evolutionary perspective provides a unifying explanation for the modifiable risk factors and lifestyle-based interventions for the leading causes of morbidity and mortality globally. Non-communicable diseases develop from an evolutionary mismatch between the prior environment and modern patterns of behavior; however, it is unclear whether an evolutionary mismatch narrative could promote positive behavior change in patients. We hypothesize that educating patients about evolutionary mismatch could augment efforts to improve healthful behavior. Specifically, explaining the 'why' behind what is being recommended could promote health literacy and adherence. Furthermore, we offer suggestions of how clinicians could educate patients about evolutionary mismatch for key-lifestyle factors, diet and physical activity, as well as several specific modern diseases. We also consider how to sidestep patients' skepticism of evolutionary theory. Here, we lay the groundwork for research on how educating patients with an evolutionary mismatch narrative could impact health behaviors and improve outcomes.

Variation in the life history strategy underlies functional diversity of tumors

Classical r- vs. K-selection theory describes the trade-offs between high reproductive output and competitiveness and guides research in evolutionary ecology. While its impact has waned in the recent past, cancer evolution may rekindle it. Herein, we impose r- or K-selection on cancer cell lines to obtain strongly proliferative r cells and highly competitive K cells to test ideas on life-history strategy evolution. RNA-seq indicates that the trade-offs are associated with distinct expression of genes involved in the cell cycle, adhesion, apoptosis, and contact inhibition. Both empirical observations and simulations based on an ecological competition model show that the trade-off between cell proliferation and competitiveness can evolve adaptively. When the r and K cells are mixed, they exhibit strikingly different spatial and temporal distributions. Due to this niche separation, the fitness of the entire tumor increases. The contrasting selective pressure may operate in a realistic ecological setting of actual tumors.

Adriamycin-resistant cells are significantly less fit than adriamycin-sensitive cells in cervical cancer

Adriamycin (ADR) is an important chemotherapy agent in many advanced cancers, but the emergence of drug resistance during treatment is a major limitation to its successful use. Recent studies have suggested that drug-resistant cells become less fit and their growth could be inhibited by parental cells without cytotoxic treatment. In this study, we examined the fitness differences between HeLa and HeLa/ADR cells. Compared with the parental cell line, HeLa/ADR cells showed significantly lower growth rates, both in vitro and in vivo. There was no difference in the apoptosis rate between them, but G1 arrest and reduced DNA synthesis were found in HeLa/ADR cells. Further study indicated that HeLa/ADR cells failed to compete for space and nutrition against parental cells in vivo. Taken together, we demonstrate that HeLa/ADR cells are less fit and their growth can be inhibited by parental cells in the absence of ADR; therefore, the maintenance of a certain amount of ADR-sensitive cells during treatment may facilitate the control of the development of ADR resistance.

Extrachromosomal DNA (ecDNA) in cancer pathogenesis

In cancer, oncogenes and surrounding regulatory regions can untether themselves from chromosomes, forming extrachromosomal DNA particles (ecDNAs). Because of their non-chromosomal inheritance, ecDNA drives high oncogene copy number and intratumoral genetic heterogeneity, endowing tumors with the ability to rapidly change their genomes, accelerating tumor evolution, and contributing to therapeutic resistance. Further, the circular topology of ecDNA leads to enhanced chromatin accessibility, altered gene regulation, and massive oncogene transcription, driving tumor growth and progression, and placing ecDNA at the interface of cancer genomics and epigenetics. Recent studies show that ecDNA is a common event in many of the most aggressive forms of cancer, potentially challenging our current precision oncology approaches. In this review, we discuss what is known about ecDNA and its biological and clinical impact, highlighting new research and suggesting the promise, and some of the challenges ahead for the field.

Can some microbes promote host stress and benefit evolutionarily from this strategy?

Microbes can influence host physiology and behavior in many ways. Here we review evidence suggesting that some microbes can contribute to host stress (and other microbes can contribute to increased resilience to stress). We explain how certain microbes, which we call "stress microbes," can potentially benefit evolutionarily from inducing stress in a host, gaining access to host resources that can help fuel rapid microbial replication by increasing glucose levels in the blood, increasing intestinal permeability, and suppressing the immune system. Other microbes, which we term "resilience microbes," can potentially benefit from making hosts more resilient to stress. We hypothesize that "stress microbes" use a fast life history strategy involving greater host exploitation while "resilience microbes" use a slow life history strategy characterized by more aligned evolutionary interests with the host. In this paper, we review the evidence that microbes affect host stress and explain the evolutionary pressures that could lead microbes to manipulate host stress, discuss the physiological mechanisms that are known to be involved in both stress and microbial activity, and provide some testable predictions that follow from this hypothesis.

Ecological and Evolutionary Consequences of Anticancer Adaptations

Cellular cheating leading to cancers exists in all branches of multicellular life, favoring the evolution of adaptations to avoid or suppress malignant progression, and/or to alleviate its fitness consequences. Ecologists have until recently largely neglected the importance of cancer cells for animal ecology, presumably because they did not consider either the potential ecological or evolutionary consequences of anticancer adaptations. Here, we review the diverse ways in which the evolution of anticancer adaptations has significantly constrained several aspects of the evolutionary ecology of multicellular organisms at the cell, individual, population, species, and ecosystem levels and suggest some avenues for future research.

Breast Cancer Subtypes Underlying EMT-Mediated Catabolic Metabolism

Efficient catabolic metabolism of adenosine triphosphate (ATP) and reduced nicotinamide adenine dinucleotide phosphate (NADPH) is essentially required for cancer cell survival, especially in metastatic cancer progression. Epithelial–mesenchymal transition (EMT) plays an important role in metabolic rewiring of cancer cells as well as in phenotypic conversion and therapeutic resistance. Snail (SNAI1), a well-known inducer of cancer EMT, is critical in providing ATP and NADPH via suppression of several gatekeeper genes involving catabolic metabolism, such as phosphofructokinase 1 (PFK1), fructose-1,6-bisphosphatase 1 (FBP1), and acetyl-CoA carboxylase 2 (ACC2). Paradoxically, PFK1 and FBP1 are counter-opposing and rate-limiting reaction enzymes of glycolysis and gluconeogenesis, respectively. In this study, we report a distinct metabolic circuit of catabolic metabolism in breast cancer subtypes. Interestingly, PFKP and FBP1 are inversely correlated in clinical samples, indicating different metabolic subsets of breast cancer. The luminal types of breast cancer consist of the pentose phosphate pathway (PPP) subset by suppression of PFKP while the basal-like subtype (also known as triple negative breast cancer, TNBC) mainly utilizes glycolysis and mitochondrial fatty acid oxidation (FAO) by loss of FBP1 and ACC2. Notably, PPP remains active via upregulation of TIGAR in the FBP1-loss basal-like subset, indicating the importance of PPP in catabolic cancer metabolism. These results indicate different catabolic metabolic circuits and thus therapeutic strategies in breast cancer subsets.

Modeling How Heterogeneity in Cell Cycle Length Affects Cancer Cell Growth Dynamics in Response to Treatment

Tumors are complex, dynamic, and adaptive biological systems characterized by high heterogeneity at genetic, epigenetic, phenotypic, as well as tissue microenvironmental level. In this work, utilizing cellular automata methods, we focus on intrinsic heterogeneity with respect to cell cycle duration and explore whether and to what extent this heterogeneity affects cancer cell growth dynamics when cytotoxic treatment is applied. We assume that treatment acts on cancer cells specifically during mitosis and compare it with a (cell cycle-non-specific) cytotoxic treatment that acts randomly regardless of the cell cycle phase. We simulate the spatiotemporal evolution of tumor cells with different initial spatial configurations and different cell length probability distributions. We observed that in heterogeneous populations, strong selection forces act on cancer cells favoring the faster cells, when the death rates are lower than the proliferation rates. However, at higher mitotic death rates, selection of the slower proliferative cells is favored, leading to slower post-treatment regrowth rates, as compared to untreated growth. Of note, random cell death progressively eliminates the slower proliferative cells, consistently, favoring highly proliferative phenotypes. Interestingly, compared to the monoclonal populations that exhibit complete response at high random death rates, emergent resistance arises naturally in heterogeneous populations during treatment. As divergent selection forces may act on a heterogeneous cancer cell population, we argue that treatment plan selection can considerably alter the post-treatment tumor dynamics, cell survival, and emergence of resistance, proving its significant biological and therapeutic impact.

Cancer Microbiome; Opportunities and Challenges

BACKGROUND

Microbe-host association has emerged as a modulator in modern medicine. Cancer and its associated host microbes are collectively referred to as the cancer microbiome. The cancer microbiome is complex, and many aspects remain unclear including metabolic plasticity, microenvironment remodeling, cellular communications, and unique signatures within the host, all of which have a vital role in homeostasis and pathogenesis of host physiology. However, the role of the microbiome in cancer initiation, progression, and therapy is still poorly understood and remains to be explored.

OBJECTIVE

The objective of this review is to elucidate the role of the microbiome in cancer metabolism and the tumor microenvironment. It also focuses on the importance of therapeutic opportunities and challenges in the manipulation of the cancer microbiome.

METHODS

A literature search was conducted on the role of the microbiome in cancer initiation, progression, and therapy.

CONCLUSION

The tumor microenvironment and cancer metabolism are significant in host-microbiome interactions. The microbiome can modulate standard cancer therapies like chemotherapy and immunotherapy. Microbiome transplantation has also been demonstrated as an effective therapy against cancer. Furthermore, the modulation of the microbiome also has potential clinical outcomes in modern medicine.

Predation shapes the impact of cancer on population dynamics and the evolution of cancer resistance

Cancer is a widespread disease that affects most of the metazoans. However, cancer development is a slow process and, long before causing the death of the individual, may weaken organisms' capacities and impair their interactions with other species. Yet, the impact of cancer development on biotic interactions, and over the dynamics of the whole ecosystem, is still largely unexplored. As well, the feedback of altered biotic interactions on the evolution of resistance against cancer in the context of community ecology has not been investigated. From this new perspective, we theoretically investigate how cancer can challenge expected interaction outcomes in a predator-prey model system, and how, in return, these altered interaction outcomes could affect evolution of resistance mechanism against cancer. First, we demonstrate a clear difference between prey and predator vulnerability to cancer, with cancer having a limited impact on prey populations. Second, we show that biotic interactions can surprisingly lead to a null or positive effect of cancer on population densities. Finally, our evolutionary analysis sheds light on how biotic interactions can lead to diverse resistance levels in predator populations. While its role in ecosystems is mostly unknown, we demonstrate that cancer in wildlife is an important ecological and evolutionary force to consider.

Age-dependent expression of cancer-related genes in a long-lived seabird

Studies of model animals like mice and rats have led to great advances in our understanding of the process of tumorigenesis, but this line of study has less to offer for understanding the mechanisms of cancer resistance. Increasing the diversity of nonmodel species from the perspective of molecular mechanisms of natural cancer resistance can lead to new insights into the evolution of protective mechanisms against neoplastic processes and to a wider understanding of natural cancer defense mechanisms. Such knowledge could then eventually be harnessed for the development of human cancer therapies. We suggest here that seabirds are promising, albeit currently completely ignored candidates for studying cancer defense mechanisms, as they have a longer maximum life span than expected from their body size and rates of energy metabolism and may have thus evolved mechanisms to limit neoplasia progression, especially at older ages. We here apply a novel, intraspecific approach of comparing old and young seabirds for improving our understanding of aging and neoplastic processes in natural settings. We used the long-lived common gulls (Larus canus) for studying the age-related pattern of expression of cancer-related genes, based on transcriptome analysis and databases of orthologues of human cancer genes. The analysis of differently expressed cancer-related genes between young and old gulls indicated that similarly to humans, age is potentially affecting cancer risk in this species. Out of eleven differentially expressed cancer-related genes between the groups, three were likely artifactually linked to cancer. The remaining eight were downregulated in old gulls compared to young ones. The downregulation of five of them could be interpreted as a mechanism suppressing neoplasia risk and three as increasing the risk. Based on these results, we suggest that old gulls differ from young ones both from the aspect of cancer susceptibility and tumor suppression at the genetic level.

Eco-oncology: Applying ecological principles to understand and manage cancer

Cancer is a disease of single cells that expresses itself at the population level. The striking similarities between initiation and growth of tumors and dynamics of biological populations, and between metastasis and ecological invasion and community dynamics suggest that oncology can benefit from an ecological perspective to improve our understanding of cancer biology. Tumors can be viewed as complex, adaptive, and evolving systems as they are spatially and temporally heterogeneous, continually interacting with each other and with the microenvironment and evolving to increase the fitness of the cancer cells. We argue that an eco-evolutionary perspective is essential to understand cancer biology better. Furthermore, we suggest that ecologically informed therapeutic approaches that combine standard of care treatments with strategies aimed at decreasing the evolutionary potential and fitness of neoplastic cells, such as disrupting cell-to-cell communication and cooperation, and preventing successful colonization of distant organs by migrating cancer cells, may be effective in managing cancer as a chronic condition.

Snail augments fatty acid oxidation by suppression of mitochondrial ACC2 during cancer progression

This study reports a mechanism of mitochondrial ATP generation whereby EMT-inducer Snail controls ACC2 abundance and subsequent fatty acid oxidation to support cancer survival under starvation conditions.

Despite the importance of mitochondrial fatty acid oxidation (FAO) in cancer metabolism, the biological mechanisms responsible for the FAO in cancer and therapeutic intervention based on catabolic metabolism are not well defined. In this study, we observe that Snail (SNAI1), a key transcriptional repressor of epithelial–mesenchymal transition, enhances catabolic FAO, allowing pro-survival of breast cancer cells in a starved environment. Mechanistically, Snail suppresses mitochondrial ACC2 (ACACB) by binding to a series of E-boxes located in its proximal promoter, resulting in decreased malonyl-CoA level. Malonyl-CoA being a well-known endogenous inhibitor of fatty acid transporter carnitine palmitoyltransferase 1 (CPT1), the suppression of ACC2 by Snail activates CPT1-dependent FAO, generating ATP and decreasing NADPH consumption. Importantly, combinatorial pharmacologic inhibition of pentose phosphate pathway and FAO with clinically available drugs efficiently reverts Snail-mediated metabolic reprogramming and suppresses in vivo metastatic progression of breast cancer cells. Our observations provide not only a mechanistic link between epithelial–mesenchymal transition and catabolic rewiring but also a novel catabolism-based therapeutic approach for inhibition of cancer progression.

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.

Resistance to targeted therapies as a multifactorial, gradual adaptation to inhibitor specific selective pressures

Despite high initial efficacy, targeted therapies eventually fail in advanced cancers, as tumors develop resistance and relapse. In contrast to the substantial body of research on the molecular mechanisms of resistance, understanding of how resistance evolves remains limited. Using an experimental model of ALK positive NSCLC, we explored the evolution of resistance to different clinical ALK inhibitors. We found that resistance can originate from heterogeneous, weakly resistant subpopulations with variable sensitivity to different ALK inhibitors. Instead of the commonly assumed stochastic single hit (epi) mutational transition, or drug-induced reprogramming, we found evidence for a hybrid scenario involving the gradual, multifactorial adaptation to the inhibitors through acquisition of multiple cooperating genetic and epigenetic adaptive changes. Additionally, we found that during this adaptation tumor cells might present unique, temporally restricted collateral sensitivities, absent in therapy naïve or fully resistant cells, suggesting the potential for new therapeutic interventions, directed against evolving resistance.

Acquired resistance to cancer therapies reflects the ability of cancers to adapt to therapy-imposed selective pressures. Here, the authors elucidate the dynamics of developing resistance to ALK inhibitors in an ALK+ lung cancer cell line showing that resistance originates from drug-specific tolerant cancer cells and it develops as a gradual adaptation.

A unified simulation model for understanding the diversity of cancer evolution

Because cancer evolution underlies the therapeutic difficulties of cancer, it is clinically important to understand the evolutionary dynamics of cancer. Thus far, a number of evolutionary processes have been proposed to be working in cancer evolution. However, there exists no simulation model that can describe the different evolutionary processes in a unified manner. In this study, we constructed a unified simulation model for describing the different evolutionary processes and performed sensitivity analysis on the model to determine the conditions in which cancer growth is driven by each of the different evolutionary processes. Our sensitivity analysis has successfully provided a series of novel insights into the evolutionary dynamics of cancer. For example, we found that, while a high neutral mutation rate shapes neutral intratumor heterogeneity (ITH) characterized by a fractal-like pattern, a stem cell hierarchy can also contribute to shaping neutral ITH by apparently increasing the mutation rate. Although It has been reported that the evolutionary principle shaping ITH shifts from selection to accumulation of neutral mutations during colorectal tumorigenesis, our simulation revealed the possibility that this evolutionary shift is triggered by drastic evolutionary events that occur in a short time and confer a marked fitness increase on one or a few cells. This result helps us understand that each process works not separately but simultaneously and continuously as a series of phases of cancer evolution. Collectively, this study serves as a basis to understand in greater depth the diversity of cancer evolution.

Tumour heterogeneity and the evolutionary trade-offs of cancer

Tumours vary in gene expression programmes and genetic alterations. Understanding this diversity and its biological meaning requires a theoretical framework, which could in turn guide the development of more accurate prognosis and therapy. Here, we review the theory of multi-task evolution of cancer, which is based upon the premise that tumours evolve in the host and face selection trade-offs between multiple biological functions. This theory can help identify the major biological tasks that cancer cells perform and the trade-offs between these tasks. It introduces the concept of specialist tumours, which focus on one task, and generalist tumours, which perform several tasks. Specialist tumours are suggested to be sensitive to therapy targeting their main task. Driver mutations tune gene expression towards specific tasks in a tissue-dependent manner and thus help to determine whether a tumour is specialist or generalist. We discuss potential applications of the theory of multi-task evolution to interpret the spatial organization of tumours and intratumour heterogeneity.

Comparative Molecular Life History of Spontaneous Canine and Human Gliomas

Sporadic gliomas in companion dogs provide a window on the interaction between tumorigenic mechanisms and host environment. We compared the molecular profiles of canine gliomas with those of human pediatric and adult gliomas to characterize evolutionarily conserved mammalian mutational processes in gliomagenesis. Employing whole-genome, exome, transcriptome, and methylation sequencing of 83 canine gliomas, we found alterations shared between canine and human gliomas such as the receptor tyrosine kinases, TP53 and cell-cycle pathways, and IDH1 R132. Canine gliomas showed high similarity with human pediatric gliomas per robust aneuploidy, mutational rates, relative timing of mutations, and DNA-methylation patterns. Our cross-species comparative genomic analysis provides unique insights into glioma etiology and the chronology of glioma-causing somatic alterations.

In Silico implementation of evolutionary paradigm in therapy design: Towards anti-cancer therapy as Darwinian process

In here presented in silico study we suggest a way how to implement the evolutionary principles into anti-cancer therapy design. We hypothesize that instead of its ongoing supervised adaptation, the therapy may be constructed as a self-sustaining evolutionary process in a dynamic fitness landscape established implicitly by evolving cancer cells, microenvironment and the therapy itself. For these purposes, we replace a unified therapy with the 'therapy species', which is a population of heterogeneous elementary therapies, and propose a way how to turn the toxicity of the elementary therapy into its fitness in a way conforming to evolutionary causation. As a result, not only the therapies govern the evolution of different cell phenotypes, but the cells' resistances govern the evolution of the therapies as well. We illustrate the approach by the minimalistic ad hoc evolutionary model. Its results indicate that the resistant cells could bias the evolution towards more toxic elementary therapies by inhibiting the less toxic ones. As the evolutionary causation of cancer drug resistance has been intensively studied for a few decades, we refer to cancer as a special case to illustrate purely theoretical analysis.

Special Collection on Ecological and Evolutionary Approaches to Cancer Control: Cancer Finds a Conceptual Home

Despite a century of intense investigation, cancer biology and treatment remain plagued by unanswered questions. Even basic questions regarding the fundamental forces driving the formation of cancer remain controversial. Recent approaches view cancer in the context of a complex web of interactions among cancer cells of the tumor, together with their interactions with the many cells and constituents of the complex and highly dynamic tumor microenvironment. As seen in this special collection, we believe that viewing cancer as a process of evolution driven by ongoing ecological processes playing out within a dynamic environment offers many insights and potential new pathways for cancer control.