Lung adenocarcinomas without driver genes converge to common adaptive strategies through diverse genetic, epigenetic, and niche construction evolutionary pathways.

Somatic evolution selects cancer cell phenotypes that maximize survival and proliferation in dynamic environments. Although cancer cells are molecularly heterogeneous, we hypothesized convergent adaptive strategies to common host selection forces can be inferred from patterns of epigenetic and genetic evolutionary selection in similar tumors. We systematically investigated gene mutations and expression changes in lung adenocarcinomas with no common driver genes (n = 313). Although 13,461 genes were mutated in at least one sample, only 376 non-synonymous mutations evidenced positive evolutionary selection with conservation of 224 genes, while 1736 and 2430 genes exhibited ≥ two-fold increased and ≥ 50% decreased expression, respectively. Mutations under positive selection are more frequent in genes with significantly altered expression suggesting they often "hardwire" pre-existing epigenetically driven adaptations. Conserved genes averaged 16-fold higher expression in normal lung tissue compared to those with selected mutations demonstrating pathways necessary for both normal cell function and optimal cancer cell fitness. The convergent LUAD phenotype exhibits loss of differentiated functions and cell-cell interactions governing tissue organization. Conservation with increased expression is found in genes associated with cell cycle, DNA repair, p53 pathway, epigenetic modifiers, and glucose metabolism. No canonical driver gene pathways exhibit strong positive selection, but extensive down-regulation of membrane ion channels suggests decreased transmembrane potential may generate persistent proliferative signals. NCD LUADs perform niche construction generating a stiff, immunosuppressive microenvironment through selection of specific collagens and proteases. NCD LUADs evolve to a convergent phenotype through a network of interconnected genetic, epigenetic, and ecological pathways.

Exploration of drug resistance mechanisms in triple negative breast cancer cells using a microfluidic device and patient tissues.

Chemoresistance is a major cause of treatment failure in many cancers. However, the life cycle of cancer cells as they respond to and survive environmental and therapeutic stress is understudied. In this study, we utilized a microfluidic device to induce the development of doxorubicin-resistant (DOXR) cells from triple negative breast cancer (TNBC) cells within 11 days by generating gradients of DOX and medium. In vivo chemoresistant xenograft models, an unbiased genome-wide transcriptome analysis, and a patient data/tissue analysis all showed that chemoresistance arose from failed epigenetic control of the nuclear protein-1 (NUPR1)/histone deacetylase 11 (HDAC11) axis, and high NUPR1 expression correlated with poor clinical outcomes. These results suggest that the chip can rapidly induce resistant cells that increase tumor heterogeneity and chemoresistance, highlighting the need for further studies on the epigenetic control of the NUPR1/HDAC11 axis in TNBC.

A mathematical investigation of polyaneuploid cancer cell memory and cross-resistance in state-structured cancer populations.

The polyaneuploid cancer cell (PACC) state promotes cancer lethality by contributing to survival in extreme conditions and metastasis. Recent experimental evidence suggests that post-therapy PACC-derived recurrent populations display cross-resistance to classes of therapies with independent mechanisms of action. We hypothesize that this can occur through PACC memory, whereby cancer cells that have undergone a polyaneuploid transition (PAT) reenter the PACC state more quickly or have higher levels of innate resistance. In this paper, we build on our prior mathematical models of the eco-evolutionary dynamics of cells in the 2N+ and PACC states to investigate these two hypotheses. We show that although an increase in innate resistance is more effective at promoting cross-resistance, this trend can also be produced via PACC memory. We also find that resensitization of cells that acquire increased innate resistance through the PAT have a considerable impact on eco-evolutionary dynamics and extinction probabilities. This study, though theoretical in nature, can help inspire future experimentation to tease apart hypotheses surrounding how cross-resistance in structured cancer populations arises.

Updating the Definition of Cancer.

Most definitions of cancer broadly conform to the current NCI definition: "Cancer is a disease in which some of the body's cells grow uncontrollably and spread to other parts of the body." These definitions tend to describe what cancer "looks like" or "does" but do not describe what cancer "is" or "has become." While reflecting past insights, current definitions have not kept pace with the understanding that the cancer cell is itself transformed and evolving. We propose a revised definition of cancer: Cancer is a disease of uncontrolled proliferation by transformed cells subject to evolution by natural selection. We believe this definition captures the essence of the majority of previous and current definitions. To the simplest definition of cancer as a disease of uncontrolled proliferation of cells, our definition adds in the adjective "transformed" to capture the many tumorigenic processes that cancer cells adopt to metastasize. To the concept of uncontrolled proliferation of transformed cells, our proposed definition then adds "subject to evolution by natural selection." The subject to evolution by natural selection modernizes the definition to include the genetic and epigenetic changes that accumulate within a population of cancer cells that lead to the lethal phenotype. Cancer is a disease of uncontrolled proliferation by transformed cells subject to evolution by natural selection.

Nuclear morphology predicts cell survival to cisplatin chemotherapy.

The emergence of chemotherapy resistance drives cancer lethality in cancer patients, with treatment initially reducing overall tumor burden followed by resistant recurrent disease. While molecular mechanisms underlying resistance phenotypes have been explored, less is known about the cell biological characteristics of cancer cells that survive to eventually seed the recurrence. To identify the unique phenotypic characteristics associated with survival upon chemotherapy exposure, we characterized nuclear morphology and function as prostate cancer cells recovered following cisplatin treatment. Cells that survived in the days and weeks after treatment and resisted therapy-induced cell death showed increasing cell size and nuclear size, enabled by continuous endocycling resulting in repeated whole genome doubling. We further found that cells that survive after therapy release were predominantly mononucleated and likely employ more efficient DNA damage repair. Finally, we show that surviving cancer cells exhibit a distinct nucleolar phenotype and increased rRNA levels. These data support a paradigm where soon after therapy release, the treated population mostly contains cells with a high level of widespread and catastrophic DNA damage that leads to apoptosis, while the minority of cells that have successful DDR are more likely to access a pro-survival state. These findings are consistent with accession of the polyaneuploid cancer cell (PACC) state, a recently described mechanism of therapy resistance and tumor recurrence. Our findings demonstrate the fate of cancer cells following cisplatin treatment and define key cell phenotypic characteristics of the PACC state. This work is essential for understanding and, ultimately, targeting cancer resistance and recurrence.

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.

A life history model of the ecological and evolutionary dynamics of polyaneuploid cancer cells.

Therapeutic resistance is one of the main reasons for treatment failure in cancer patients. The polyaneuploid cancer cell (PACC) state has been shown to promote resistance by providing a refuge for cancer cells from the effects of therapy and by helping them adapt to a variety of environmental stressors. This state is the result of aneuploid cancer cells undergoing whole genome doubling and skipping mitosis, cytokinesis, or both. In this paper, we create a novel mathematical framework for modeling the eco-evolutionary dynamics of state-structured populations and use this framework to construct a model of cancer populations with an aneuploid and a PACC state. Using in silico simulations, we explore how the PACC state allows cancer cells to (1) survive extreme environmental conditions by exiting the cell cycle after S phase and protecting genomic material and (2) aid in adaptation to environmental stressors by increasing the cancer cell's ability to generate heritable variation (evolvability) through the increase in genomic content that accompanies polyploidization. In doing so, we demonstrate the ability of the PACC state to allow cancer cells to persist under therapy and evolve therapeutic resistance. By eliminating cells in the PACC state through appropriately-timed PACC-targeted therapies, we show how we can prevent the emergence of resistance and promote cancer eradication.

Stochastic models of Mendelian and reverse transcriptional inheritance in state-structured cancer populations.

Recent evidence suggests that a polyaneuploid cancer cell (PACC) state may play a key role in the adaptation of cancer cells to stressful environments and in promoting therapeutic resistance. The PACC state allows cancer cells to pause cell division and to avoid DNA damage and programmed cell death. Transition to the PACC state may also lead to an increase in the cancer cell's ability to generate heritable variation (evolvability). One way this can occur is through evolutionary triage. Under this framework, cells gradually gain resistance by scaling hills on a fitness landscape through a process of mutation and selection. Another way this can happen is through self-genetic modification whereby cells in the PACC state find a viable solution to the stressor and then undergo depolyploidization, passing it on to their heritably resistant progeny. Here, we develop a stochastic model to simulate both of these evolutionary frameworks. We examine the impact of treatment dosage and extent of self-genetic modification on eco-evolutionary dynamics of cancer cells with aneuploid and PACC states. We find that under low doses of therapy, evolutionary triage performs better whereas under high doses of therapy, self-genetic modification is favored. This study generates predictions for teasing apart these biological hypotheses, examines the implications of each in the context of cancer, and provides a modeling framework to compare Mendelian and non-traditional forms of inheritance.

It doesn't always pay to be fit: success landscapes.

Landscapes play an important role in many areas of biology, in which biological lives are deeply entangled. Here we discuss a form of landscape in evolutionary biology which takes into account (1) initial growth rates, (2) mutation rates, (3) resource consumption by organisms, and (4) cyclic changes in the resources with time. The long-term equilibrium number of surviving organisms as a function of these four parameters forms what we call a success landscape, a landscape we would claim is qualitatively different from fitness landscapes which commonly do not include mutations or resource consumption/changes in mapping genomes to the final number of survivors. Although our analysis is purely theoretical, we believe the results have possibly strong connections to how we might treat diseases such as cancer in the future with a deeper understanding of the interplay between resource degradation, mutation, and uncontrolled cell growth.

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.

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation.

Conventional cell culture remains the most frequently used preclinical model, despite its proven limited ability to predict clinical results in cancer. Microfluidic cancer-on-chip models have been proposed to bridge the gap between the oversimplified conventional 2D cultures and more complicated animal models, which have limited ability to produce reliable and reproducible quantitative results. Here, we present a microfluidic cancer-on-chip model that reproduces key components of a complex tumor microenvironment in a comprehensive manner, yet is simple enough to provide robust quantitative descriptions of cancer dynamics. This microfluidic cancer-on-chip model, the "Evolution Accelerator," breaks down a large population of cancer cells into an interconnected array of tumor microenvironments while generating a heterogeneous chemotherapeutic stress landscape. The progression and the evolutionary dynamics of cancer in response to drug gradient can be monitored for weeks in real time, and numerous downstream experiments can be performed complementary to the time-lapse images taken through the course of the experiments.

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.

The role of heterogeneous environment and docetaxel gradient in the emergence of polyploid, mesenchymal and resistant prostate cancer cells.

The ability of a population of PC3 prostate epithelial cancer cells to become resistant to docetaxel therapy and progress to a mesenchymal state remains a fundamental problem. The progression towards resistance is difficult to directly study in heterogeneous ecological environments such as tumors. In this work, we use a micro-fabricated "evolution accelerator" environment to create a complex heterogeneous yet controllable in-vitro environment with a spatially-varying drug concentration. With such a structure we observe the rapid emergence of a surprisingly large number of polyploid giant cancer cells (PGCCs) in regions of very high drug concentration, which does not occur in conventional cell culture of uniform concentration. This emergence of PGCCs in a high drug environment is due to migration of diploid epithelial cells from regions of low drug concentration, where they proliferate, to regions of high drug concentration, where they rapidly convert to PGCCs. Such a mechanism can only occur in spatially-varying rather than homogeneous environments. Further, PGCCs exhibit increased expression of the mesenchymal marker ZEB1 in the same high-drug regions where they are formed, suggesting the possible induction of an epithelial to mesenchymal transition (EMT) in these cells. This is consistent with prior work suggesting the PGCC cells are mediators of resistance in response to chemotherapeutic stress. Taken together, this work shows the key role of spatial heterogeneity and the migration of proliferative diploid cells to form PGCCs as a survival strategy for the cancer population, with implications for new therapies.

A bacterial antibiotic resistance accelerator and applications.

The systematic emergence of drug resistance remains a major problem in the treatment of infectious diseases (antibiotics) and cancer (chemotherapy), with possible common fundamental origins linking bacterial antibiotic resistance and emergence of chemotherapy resistance. The common link may be evolution in a complex fitness landscape with connected small population niches. We report a detailed method for observing bacterial adaptive behavior in heterogeneous microfluidic environment designed to mimic the environmental heterogeneity found in natural microbial niches. First, the device is structured with multiple connected micro-chambers that allow the cell population to communicate and organize into smaller populations. Second, bacteria evolve within an antibiotic gradient generated throughout the micro-chambers that creates a wide range of fitness landscapes. High-resolution images of the adaptive response to the antibiotic stress are captured by epifluorescence microscopy at various levels of the bacterial organization for quantitative analysis. Thus, the experimental setup we have developed provides a powerful frame for visualizing evolution at work: bacterial movement, survival and death. It also presents a basis for exploring the rates at which drug resistance arises in bacteria and other biological contexts such as cancer.

Rapid emergence and mechanisms of resistance by U87 glioblastoma cells to doxorubicin in an in vitro tumor microfluidic ecology.

In vitro prediction of the probable rapid emergence of resistance to a drug in tumors could act to winnow out potential candidates for further costly development. We have developed a microfluidic device consisting of ∼500 hexagonal microcompartments that provides a complex ecology with wide ranges of drug and nutrient gradients and local populations. This ecology of a fragmented metapopulation induced the drug resistance in stage IV U87 glioblastoma cells to doxorubicin in 7 d. Exome and transcriptome sequencing of the resistant cells identified mutations and differentially expressed genes. Gene ontology and pathway analyses of the genes identified showed that they were functionally relevant to the established mechanisms of doxorubicin action. Specifically, we identified (i) a frame-shift insertion in the filamin-A gene, which regulates the influx and efflux of topoisomerase II poisons; (ii) the overexpression of aldo-keto reductase enzymes, which convert doxorubicin into doxorubicinol; and (iii) activation of NF-κB via alterations in the nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway from mutations in three genes (CARD6, NSD1, and NLRP13) and the overexpression of inflammatory cytokines. Functional experiments support the in silico analyses and, together, demonstrate the effects of these genetic changes. Our findings suggest that, given the rapid evolution of resistance and the focused response, this technology could act as a rapid screening modality for genetic aberrations leading to resistance to chemotherapy as well as counter selection of drugs unlikely to be successful ultimately.

Nanoscale lateral displacement arrays for the separation of exosomes and colloids down to 20†nm.

Deterministic lateral displacement (DLD) pillar arrays are an efficient technology to sort, separate and enrich micrometre-scale particles, which include parasites, bacteria, blood cells and circulating tumour cells in blood. However, this technology has not been translated to the true nanoscale, where it could function on biocolloids, such as exosomes. Exosomes, a key target of 'liquid biopsies', are secreted by cells and contain nucleic acid and protein information about their originating tissue. One challenge in the study of exosome biology is to sort exosomes by size and surface markers. We use manufacturable silicon processes to produce nanoscale DLD (nano-DLD) arrays of uniform gap sizes ranging from 25 to 235 nm. We show that at low Péclet (Pe) numbers, at which diffusion and deterministic displacement compete, nano-DLD arrays separate particles between 20 to 110 nm based on size with sharp resolution. Further, we demonstrate the size-based displacement of exosomes, and so open up the potential for on-chip sorting and quantification of these important biocolloids.

Oriented collagen fibers direct tumor cell intravasation.

In this work, we constructed a Collagen I-Matrigel composite extracellular matrix (ECM). The composite ECM was used to determine the influence of the local collagen fiber orientation on the collective intravasation ability of tumor cells. We found that the local fiber alignment enhanced cell-ECM interactions. Specifically, metastatic MDA-MB-231 breast cancer cells followed the local fiber alignment direction during the intravasation into rigid Matrigel (∼10 mg/mL protein concentration).

Ancient hot and cold genes and chemotherapy resistance emergence.

We use a microfabricated ecology with a doxorubicin gradient and population fragmentation to produce a strong Darwinian selective pressure that drives forward the rapid emergence of doxorubicin resistance in multiple myeloma (MM) cancer cells. RNA sequencing of the resistant cells was used to examine (i) emergence of genes with high de novo substitution densities (i.e., hot genes) and (ii) genes never substituted (i.e., cold genes). The set of cold genes, which were 21% of the genes sequenced, were further winnowed down by examining excess expression levels. Both the most highly substituted genes and the most highly expressed never-substituted genes were biased in age toward the most ancient of genes. This would support the model that cancer represents a revision back to ancient forms of life adapted to high fitness under extreme stress, and suggests that these ancient genes may be targets for cancer therapy.

Inhibition of clot formation in deterministic lateral displacement arrays for processing large volumes of blood for rare cell capture.

Microfluidic deterministic lateral displacement (DLD) arrays have been applied for fractionation and analysis of cells in quantities of ~100 µL of blood, with processing of larger quantities limited by clogging in the chip. In this paper, we (i) demonstrate that this clogging phenomenon is due to conventional platelet-driven clot formation, (ii) identify and inhibit the two dominant biological mechanisms driving this process, and (iii) characterize how further reductions in clot formation can be achieved through higher flow rates and blood dilution. Following from these three advances, we demonstrate processing of 14 mL equivalent volume of undiluted whole blood through a single DLD array in 38 minutes to harvest PC3 cancer cells with ~86% yield. It is possible to fit more than 10 such DLD arrays on a single chip, which would then provide the capability to process well over 100 mL of undiluted whole blood on a single chip in less than one hour.

Emergence of antibiotic resistance from multinucleated bacterial filaments.

Bacteria can rapidly evolve resistance to antibiotics via the SOS response, a state of high-activity DNA repair and mutagenesis. We explore here the first steps of this evolution in the bacterium Escherichia coli. Induction of the SOS response by the genotoxic antibiotic ciprofloxacin changes the E. coli rod shape into multichromosome-containing filaments. We show that at subminimal inhibitory concentrations of ciprofloxacin the bacterial filament divides asymmetrically repeatedly at the tip. Chromosome-containing buds are made that, if resistant, propagate nonfilamenting progeny with enhanced resistance to ciprofloxacin as the parent filament dies. We propose that the multinucleated filament creates an environmental niche where evolution can proceed via generation of improved mutant chromosomes due to the mutagenic SOS response and possible recombination of the new alleles between chromosomes. Our data provide a better understanding of the processes underlying the origin of resistance at the single-cell level and suggest an analogous role to the eukaryotic aneuploidy condition in cancer.