Tumor progression: Chance and necessity in Darwinian and Lamarckian somatic (mutationless) evolution

Graphene-Based Photodynamic Therapy and Overcoming Cancer Resistance Mechanisms: A Comprehensive Review

Photodynamic therapy (PDT) is a non-invasive therapy that has made significant progress in treating different diseases, including cancer, by utilizing new nanotechnology products such as graphene and its derivatives. Graphene-based materials have large surface area and photothermal effects thereby making them suitable candidates for PDT or photo-active drug carriers. The remarkable photophysical properties of graphene derivates facilitate the efficient generation of reactive oxygen species (ROS) upon light irradiation, which destroys cancer cells. Surface functionalization of graphene and its materials can also enhance their biocompatibility and anticancer activity. The paper delves into the distinct roles played by graphene-based materials in PDT such as photosensitizers (PS) and drug carriers while at the same time considers how these materials could be used to circumvent cancer resistance. This will provide readers with an extensive discussion of various pathways contributing to PDT inefficiency. Consequently, this comprehensive review underscores the vital roles that graphene and its derivatives may play in emerging PDT strategies for cancer treatment and other medical purposes. With a better comprehension of the current state of research and the existing challenges, the integration of graphene-based materials in PDT holds great promise for developing targeted, effective, and personalized cancer treatments.

Involvement of CircRNAs in regulating The "New Generation of Cancer Hallmarks": A Special Depiction on Hepatocellular Carcinoma

The concept of 'Hallmarks of Cancer' is an approach of reducing the enormous complexity of cancer to a set of guiding principles. As the underlying mechanism of cancer are portrayed, we find that we gain insight and additional aspects of the disease arise. The understanding of the tumor microenvironment (TME) brought a new dimension and led to the discovery of novel hallmarks such as senescent cells, non-mutational epigenetic reprogramming, polymorphic microbiomes and unlocked phenotypic plasticity. Circular RNAs (circRNAs) are single-stranded, covalently closed RNA molecules that are ubiquitous across all species. Recent studies on the circRNAs have highlighted their crucial function in regulating the formation of human malignancies through a range of biological processes. The primary goal of this review is to clarify the role of circRNAs in the most common form of liver cancer, hepatocellular carcinoma (HCC). This review also addressed the topic of how circRNAs affect HCC hallmarks, including the new generation hallmarks. Finally, the enormous applications that these rapidly expanding ncRNA molecules serve in the functional and molecular development of effective HCC diagnostic biomarkers and therapeutic targets.

Transcriptional state dynamics lead to heterogeneity and adaptive tumor evolution in urothelial bladder carcinoma

Intra-tumor heterogeneity contributes to treatment failure and poor survival in urothelial bladder carcinoma (UBC). Analyzing transcriptome from a UBC cohort, we report that intra-tumor transcriptomic heterogeneity indicates co-existence of tumor cells in epithelial and mesenchymal-like transcriptional states and bi-directional transition between them occurs within and between tumor subclones. We model spontaneous and reversible transition between these partially heritable states in cell lines and characterize their population dynamics. SMAD3, KLF4 and PPARG emerge as key regulatory markers of the transcriptional dynamics. Nutrient limitation, as in the core of large tumors, and radiation treatment perturb the dynamics, initially selecting for a transiently resistant phenotype and then reconstituting heterogeneity and growth potential, driving adaptive evolution. Dominance of transcriptional states with low PPARG expression indicates an aggressive phenotype in UBC patients. We propose that phenotypic plasticity and dynamic, non-genetic intra-tumor heterogeneity modulate both the trajectory of disease progression and adaptive treatment response in UBC.

Exploring tumor-normal cross-talk with TranNet: Role of the environment in tumor progression

There is a growing awareness that tumor-adjacent normal tissues used as control samples in cancer studies do not represent fully healthy tissues. Instead, they are intermediates between healthy tissues and tumors. The factors that contribute to the deviation of such control samples from healthy state include exposure to the tumor-promoting factors, tumor-related immune response, and other aspects of tumor microenvironment. Characterizing the relation between gene expression of tumor-adjacent control samples and tumors is fundamental for understanding roles of microenvironment in tumor initiation and progression, as well as for identification of diagnostic and prognostic biomarkers for cancers. To address the demand, we developed and validated TranNet, a computational approach that utilizes gene expression in matched control and tumor samples to study the relation between their gene expression profiles. TranNet infers a sparse weighted bipartite graph from gene expression profiles of matched control samples to tumors. The results allow us to identify predictors (potential regulators) of this transition. To our knowledge, TranNet is the first computational method to infer such dependencies. We applied TranNet to the data of several cancer types and their matched control samples from The Cancer Genome Atlas (TCGA). Many predictors identified by TranNet are genes associated with regulation by the tumor microenvironment as they are enriched in G-protein coupled receptor signaling, cell-to-cell communication, immune processes, and cell adhesion. Correspondingly, targets of inferred predictors are enriched in pathways related to tissue remodelling (including the epithelial-mesenchymal Transition (EMT)), immune response, and cell proliferation. This implies that the predictors are markers and potential stromal facilitators of tumor progression. Our results provide new insights into the relationships between tumor adjacent control sample, tumor and the tumor environment. Moreover, the set of predictors identified by TranNet will provide a valuable resource for future investigations.

How Can the Microbiome Induce Carcinogenesis and Modulate Drug Resistance in Cancer Therapy?

Over the years, cancer has been affecting the lives of many people globally and it has become one of the most studied diseases. Despite the efforts to understand the cell mechanisms behind this complex disease, not every patient seems to respond to targeted therapies or immunotherapies. Drug resistance in cancer is one of the limiting factors contributing to unsuccessful therapies; therefore, understanding how cancer cells acquire this resistance is essential to help cure individuals affected by cancer. Recently, the altered microbiome was observed to be an important hallmark of cancer and therefore it represents a promising topic of cancer research. Our review aims to provide a global perspective of some cancer hallmarks, for instance how genetic and epigenetic modifications may be caused by an altered human microbiome. We also provide information on how an altered human microbiome can lead to cancer development as well as how the microbiome can influence drug resistance and ultimately targeted therapies. This may be useful to develop alternatives for cancer treatment, i.e., future personalized medicine that can help in cases where traditional cancer treatment is unsuccessful.

A non-mutated TROP2 fingerprint in cancer genetics

The advent of high throughput DNA sequencing is providing massive amounts of tumor-associated mutation data. Implicit in these analyses is the assumption that, by acquiring a series of hallmark changes, normal cells evolve along a neoplastic path. However, the lack of correlation between cancer risk and global exposure to mutagenic factors provides arguments against this model. This suggested that additional, non-mutagenic factors are at work in cancer development. A candidate determinant is TROP2, that stands out for its expression in the majority of solid tumors in human, for its impact on the prognosis of most solid cancers and for its role as driver of cancer growth and metastatic diffusion, through overexpression as a wild-type form. The Trop-2 signaling network encompasses CREB1, Jun, NF-κB, Rb, STAT1 and STAT3, through induction of cyclin D1 and MAPK/ERK. Notably, Trop-2-driven pathways vastly overlap with those activated by most functionally relevant/most frequently mutated RAS and TP53, and are co-expressed in a large fraction of individual tumor cases, suggesting functional overlap. Mutated Ras was shown to synergize with the TROP2-CYCLIND1 mRNA chimera in transforming primary cells into tumorigenic ones. Genomic loss of TROP2 was found to promote carcinogenesis in squamous cell carcinomas through modulation of Src and mutated Ras pathways. DNA methylation and TP53 status were shown to cause genome instability and TROP gene amplification, together with Trop-2 protein overexpression. These findings suggest that mutagenic and the TROP2 non-mutagenic pathways deeply intertwine in driving transformed cell growth and malignant progression of solid cancers.

Exploring tumor-normal cross-talk with TranNet: role of the environment in tumor progression

There is a growing awareness that tumor-adjacent normal tissues used as control samples in cancer studies do not represent fully healthy tissues. Instead, they are intermediates between healthy tissues and tumors. The factors that contribute to the deviation of such control samples from healthy state include exposure to the tumor-promoting factors, tumor-related immune response, and other aspects of tumor microenvironment. Characterizing the relation between gene expression of tumor-adjacent control samples and tumors is fundamental for understanding roles of microenvironment in tumor initiation and progression, as well as for identification of diagnostic and prognostic biomarkers for cancers. To address the demand, we developed and validated TranNet, a computational approach that utilizes gene expression in matched control and tumor samples to study the relation between their gene expression profiles. TranNet infers a sparse weighted bipartite graph from gene expression profiles of matched control samples to tumors. The results allow us to identify predictors (potential regulators) of this transition. To our knowledge, TranNet is the first computational method to infer such regulation. We applied TranNet to the data of several cancer types and their matched control samples from The Cancer Genome Atlas (TCGA). Many predictors identified by TranNet are genes associated with regulation by the tumor microenvironment as they are enriched in G-protein coupled receptor signaling, cell-to-cell communication, immune processes, and cell adhesion. Correspondingly, targets of inferred predictors are enriched in pathways related to tissue remodelling (including the epithelial-mesenchymal Transition (EMT)), immune response, and cell proliferation. This implies that the predictors are markers and potential stromal facilitators of tumor progression. Our results provide new insights for the relationships between tumor adjacent control sample, tumor and the tumor environment. Moreover, the set of predictors identified by TranNet will provide a valuable resource for future investigations. The TranNet method was implemented in python, source codes and the data sets used for and generated during this study are available at the Github site https://github.com/ncbi/TranNet .

Small Non-Coding RNAs in Human Cancer

Small non-coding RNAs are widespread in the biological world and have been extensively explored over the past decades. Their fundamental roles in human health and disease are increasingly appreciated. Furthermore, a growing number of studies have investigated the functions of small non-coding RNAs in cancer initiation and progression. In this review, we provide an overview of the biogenesis of small non-coding RNAs with a focus on microRNAs, PIWI-interacting RNAs, and a new class of tRNA-derived small RNAs. We discuss their biological functions in human cancer and highlight their clinical application as molecular biomarkers or therapeutic targets.

miR-23b-3p, miR-124-3p and miR-218-5p Synergistic or Additive Effects on Cellular Processes That Modulate Cervical Cancer Progression? A Molecular Balance That Needs Attention

In cervical cancer (CC), miR-23b-3p, miR-124-3p, and miR-218-5p have been found to act as tumor suppressors by regulating cellular processes related to progression and metastasis. The objective of the present review is to provide an update on the experimental evidence about the role of miR-23b-3p, miR-124-3p, and miR-218-5p in the regulation of CC progression. Additionally, we present the results of a bioinformatic analysis that suggest that these miRNAs have a somewhat redundant role in the same cellular processes that may result in a synergistic effect to promote CC progression. The results indicate that specific and common target genes for miR-23b-3p, miR-124-3p, and miR-218-5p regulate proliferation, migration, apoptosis, and angiogenesis, all processes that are related to CC maintenance and progression. Furthermore, several target genes may regulate cancer-related signaling pathways. We found that a total of 271 proteins encoded by the target mRNAs of miR-23b-3p, miR-124-3p, or miR-218-5p interact to regulate the cellular processes previously mentioned, and some of these proteins are regulated by HPV-16 E7. Taken together, information analysis indicates that miR-23b-3p, miR-124-3p, and miR-218-5p may potentiate their effects to modulate the cellular processes related to the progression and maintenance of CC with and without HPV-16 involvement.

Asymmetric inheritance of cytoophidia could contribute to determine cell fate and plasticity: The onset of alternative differentiation patterns in daughter cells may rely on the acquisition of either CTPS or IMPDH cytoophidia: The onset of alternative differentiation patterns in daughter cells may rely on the acquisition of either CTPS or IMPDH cytoophidia

Two enzymes involved in the synthesis of pyrimidine and purine nucleotides, CTP synthase (CTPS) and IMP dehydrogenase (IMPDH), can assemble into a single or very few large filaments called rods and rings (RR) or cytoophidia. Most recently, asymmetric cytoplasmic distribution of organelles during cell division has been described as a decisive event in hematopoietic stem cell fate. We propose that cytoophidia, which could be considered as membrane-less organelles, may also be distributed asymmetrically during mammalian cell division as previously described for Schizosaccharomyces pombe. Furthermore, because each type of nucleotide intervenes in distinct processes (e.g., membrane synthesis, glycosylation, and G protein-signaling), alterations in the rate of synthesis of specific nucleotide types could influence cell differentiation in multiple ways. Therefore, we hypothesize that whether a daughter cell inherits or not CTPS or IMPDH filaments determines its fate and that this asymmetric inheritance, together with the dynamic nature of these structures enables plasticity in a cell population.

Scales of Cancer Evolution: Selfish Genome or Cooperating Cells?

Simple Summary

Cancer continuously evolves its ability to survive in time-varying microenvironment, which results, regarding the therapeutic context, in its therapeutic resistance. As it is accepted that the development of resistance is the direct consequence of intratumour heterogeneity, its evolutionary etiology is intensively studied. Models of carinogenesis are often assessed accordingly to how well they fit into the evolutionary scenario. In the paper, the relevant observations and concepts in cancer research, such as intratumour heterogeneity, cell plasticity, and Markov cell state dynamics, are reviewed and integrated into an evolutionary model. The possibility that the interaction between cancer cells can be interpreted as cooperation is proposed.

Abstract

The exploitation of the evolutionary modus operandi of cancer to steer its progression towards drug sensitive cancer cells is a challenging research topic. Integrating evolutionary principles into cancer therapy requires properly identified selection level, the relevant timescale, and the respective fitness of the principal selection unit on that timescale. Interpretation of some features of cancer progression, such as increased heterogeneity of isogenic cancer cells, is difficult from the most straightforward evolutionary view with the cancer cell as the principal selection unit. In the paper, the relation between the two levels of intratumour heterogeneity, genetic, due to genetic instability, and non-genetic, due to phenotypic plasticity, is reviewed and the evolutionary role of the latter is outlined. In analogy to the evolutionary optimization in a changing environment, the cell state dynamics in cancer clones are interpreted as the risk diversifying strategy bet hedging, optimizing the balance between the exploitation and exploration of the cell state space.

Hallmarks of Cancer: New Dimensions

The hallmarks of cancer conceptualization is a heuristic tool for distilling the vast complexity of cancer phenotypes and genotypes into a provisional set of underlying principles. As knowledge of cancer mechanisms has progressed, other facets of the disease have emerged as potential refinements. Herein, the prospect is raised that phenotypic plasticity and disrupted differentiation is a discrete hallmark capability, and that nonmutational epigenetic reprogramming and polymorphic microbiomes both constitute distinctive enabling characteristics that facilitate the acquisition of hallmark capabilities. Additionally, senescent cells, of varying origins, may be added to the roster of functionally important cell types in the tumor microenvironment. SIGNIFICANCE: Cancer is daunting in the breadth and scope of its diversity, spanning genetics, cell and tissue biology, pathology, and response to therapy. Ever more powerful experimental and computational tools and technologies are providing an avalanche of "big data" about the myriad manifestations of the diseases that cancer encompasses. The integrative concept embodied in the hallmarks of cancer is helping to distill this complexity into an increasingly logical science, and the provisional new dimensions presented in this perspective may add value to that endeavor, to more fully understand mechanisms of cancer development and malignant progression, and apply that knowledge to cancer medicine.

Towards the First Principles in Biology and Cancer: New Vistas in Computational Systems Biology of Cancer

These days many leading scientists argue for a new paradigm for cancer research and propose a complex systems-view of cancer supported by empirical evidence. As an example, Thea Newman (2021) has applied "the lessons learned from physical systems to a critique of reductionism in medical research, with an emphasis on cancer". It is the understanding of this author that the mesoscale constructs that combine the bottom-up as well as top-down approaches, are very close to the concept of emergence. The mesoscale constructs can be said to be those effective components through which the system allows itself to be understood. A short list of basic concepts related to life/biology fundamentals are first introduced to demonstrate a lack of emphasis on these matters in literature. It is imperative that physical and chemical approaches are introduced and incorporated in biology to make it more conceptually sound, quantitative, and based on the first principles. Non-equilibrium thermodynamics is the only tool currently available for making progress in this direction. A brief outline of systems biology, the discovery of emergent properties, and metabolic modeling are introduced in the second part. Then, different cancer initiation concepts are reviewed, followed by application of non-equilibrium thermodynamics in the metabolic and genomic analysis of initiation and development of cancer, stressing the endogenous network hypothesis (ENH). Finally, extension of the ENH is suggested to include a cancer niche (exogenous network hypothesis). It is expected that this will lead to a unifying systems-biology approach for a future combination of the analytical and synthetic arms of two major hypotheses of cancer models (SMT and TOFT).

Functional Characterization of Brain Tumor-Initiating Cells and Establishment of GBM Preclinical Models that Incorporate Heterogeneity, Therapy, and Sex Differences

Glioblastoma (GBM) is the most common primary brain cancer in adults where tumor cell heterogeneity and sex differences influence clinical outcomes. Here, we functionally characterize three male and three female patient-derived GBM cell lines, identify protumorigenic BTICs, and create novel male and female preclinical models of GBM. Cell lines were evaluated on the following features: proliferation, stemness, migration, tumorigenesis, clinical characteristics, and sensitivity to radiation, TMZ, rhTNFSF10 (rhTRAIL), and rhBMP4 All cell lines were classified as GBM according to epigenetic subtyping, were heterogenous and functionally distinct from one another, and re-capitulated features of the original patient tumor. In establishing male and female preclinical models, it was found that two male-derived GBM cell lines (QNS108 and QNS120) and one female-derived GBM cell line (QNS315) grew at a faster rate in female mice brains. One male-derived GBM cell line (QNS108) decreased survival in female mice in comparison with male mice. However, no survival differences were observed for mice injected with a female-derived cell line (QNS315). In summary, a panel of six GBM patient-derived cell lines were functionally characterized, and it was shown that BTIC lines can be used to construct sex-specific models with differential phenotypes for additional studies.

New Insight to Overcome Tumor Resistance: An Overview from Cellular to Clinical Therapies

Disease relapse caused by drug resistance still represents a major clinical hurdle in cancer treatments. Tumor cells may take advantage of different intracellular and genetic systems attenuating the drug effects. Resistant cells or minimal residual disease (MRD) cells have strong clinical relevance, as they might give rise to secondary tumors when the therapy is concluded. Thus, MRDs are crucial therapeutic targets in order to prevent tumor relapse. Therefore, several groups aim at understanding how MRDs are orginated, characterizing their molecular features, and eradicating them. In this review, we will describe MRD from a genetic, evolutionary, and molecular point of view. Moreover, we will focus on the new in vitro, in vivo, preclinical, and clinical studies that aim at eradicating tumor resistance.

Bridging Tumorigenesis and Therapy Resistance With a Non-Darwinian and Non-Lamarckian Mechanism of Adaptive Evolution

Although neo-Darwinian (and less often Lamarckian) dynamics are regularly invoked to interpret cancer's multifarious molecular profiles, they shine little light on how tumorigenesis unfolds and often fail to fully capture the frequency and breadth of resistance mechanisms. This uncertainty frames one of the most problematic gaps between science and practice in modern times. Here, we offer a theory of adaptive cancer evolution, which builds on a molecular mechanism that lies outside neo-Darwinian and Lamarckian schemes. This mechanism coherently integrates non-genetic and genetic changes, ecological and evolutionary time scales, and shifts the spotlight away from positive selection towards purifying selection, genetic drift, and the creative-disruptive power of environmental change. The surprisingly simple use-it or lose-it rationale of the proposed theory can help predict molecular dynamics during tumorigenesis. It also provides simple rules of thumb that should help improve therapeutic approaches in cancer.

Is cancer a disease set up by cellular stress responses?

For several decades, the somatic mutation theory (SMT) has been the dominant paradigm on cancer research, leading to the textbook notion that cancer is fundamentally a genetic disease. However, recent discoveries indicate that mutations, including "oncogenic" ones, are widespread in normal somatic cells, suggesting that mutations may be necessary but not sufficient for cancer to develop. Indeed, a fundamental but as yet unanswered question is whether or not the first step in oncogenesis corresponds to a mutational event. On the other hand, for some time, it has been acknowledged the important role in cancer progression of molecular processes that participate in buffering cellular stress. However, their role is considered secondary or complementary to that of putative oncogenic mutations. Here we present and discuss evidence that cancer may have its origin in epigenetic processes associated with cellular adaptation to stressful conditions, and so it could be a direct consequence of stress-buffering mechanisms that allow cells with aberrant phenotypes (not necessarily associated with genetic mutations) to survive and propagate within the organism. We put forward the hypothesis that there would be an inverse correlation between the activation threshold of the cellular stress responses (CSRs) and the risk of cancer, so that species or individuals with low-threshold CSRs will display a higher incidence or risk of cancer.

Starvation and Climate Change—How to Constrain Cancer Cell Epigenetic Diversity and Adaptability to Enhance Treatment Efficacy

Advanced metastatic cancer is currently not curable and the major barrier to eliminating the disease in patients is the resistance of subpopulations of tumor cells to drug treatments. These resistant subpopulations can arise stochastically among the billions of tumor cells in a patient or emerge over time during therapy due to adaptive mechanisms and the selective pressures of drug therapies. Epigenetic mechanisms play important roles in tumor cell diversity and adaptability, and are regulated by metabolic pathways. Here, I discuss knowledge from ecology, evolution, infectious disease, species extinction, metabolism and epigenetics to synthesize a roadmap to a clinically feasible approach to help homogenize tumor cells and, in combination with drug treatments, drive their extinction. Specifically, cycles of starvation and hyperthermia could help synchronize tumor cells and constrain epigenetic diversity and adaptability by limiting substrates and impairing the activity of chromatin modifying enzymes. Hyperthermia could also help prevent cancer cells from entering dangerous hibernation-like states. I propose steps to a treatment paradigm to help drive cancer extinction that builds on the successes of fasting, hyperthermia and immunotherapy and is achievable in patients. Finally, I highlight the many unknowns, opportunities for discovery and that stochastic gene and allele level epigenetic mechanisms pose a major barrier to cancer extinction that warrants deeper investigation.

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.

An evolutionary approach to clonally complex hematologic disorders

Emerging clonal complexity has brought into question the way in which we perceive and, in turn, treat disorders of the hematopoietic system. Former models of cell-intrinsic clonal dominance driven by acquisition of driver genes in a stereotypic sequence are often insufficient in explaining observations such as clonal hematopoiesis, and new paradigms are in order. Here, we review the evidence both within the hematologic malignancy field and also borrow from perspectives rooted in evolutionary biology to reframe pathogenesis of hematologic disorders as dynamic processes involving complex interplays of genetic and non-genetic subclones and the tissue microenvironment in which they reside.

Reconciling Non-Genetic Plasticity with Somatic Evolution in Cancer

Post-treatment progression of tumors is commonly explained by somatic Darwinian evolution (i.e., selection of cells carrying genetic mutations that create more aggressive cell traits). But cancer genome and transcriptome analyses now paint a picture far more complex, prompting us to see beyond the Darwinian scheme: non-genetic cell phenotype plasticity explained by alternative stable gene expression states ('attractors'), may also produce aggressive phenotypes that can be selected for, without mutations. Worse, treatment may even induce cell state transitions into more malignant attractors. We review recent evidence for non-genetic mechanisms of progression, explain the theoretical foundation of attractor transitions behind treatment-induced increase of aggressiveness, and provide a framework for unifying genetic and non-genetic dynamics in tumor progression.

Engineering in Medicine To Address the Challenge of Cancer Drug Resistance: From Micro- and Nanotechnologies to Computational and Mathematical Modeling

Drug resistance has profoundly limited the success of cancer treatment, driving relapse, metastasis, and mortality. Nearly all anticancer drugs and even novel immunotherapies, which recalibrate the immune system for tumor recognition and destruction, have succumbed to resistance development. Engineers have emerged across mechanical, physical, chemical, mathematical, and biological disciplines to address the challenge of drug resistance using a combination of interdisciplinary tools and skill sets. This review explores the developing, complex, and under-recognized role of engineering in medicine to address the multitude of challenges in cancer drug resistance. Looking through the "lens" of intrinsic, extrinsic, and drug-induced resistance (also referred to as "tolerance"), we will discuss three specific areas where active innovation is driving novel treatment paradigms: (1) nanotechnology, which has revolutionized drug delivery in desmoplastic tissues, harnessing physiochemical characteristics to destroy tumors through photothermal therapy and rationally designed nanostructures to circumvent cancer immunotherapy failures, (2) bioengineered tumor models, which have benefitted from microfluidics and mechanical engineering, creating a paradigm shift in physiologically relevant environments to predict clinical refractoriness and enabling platforms for screening drug combinations to thwart resistance at the individual patient level, and (3) computational and mathematical modeling, which blends in silico simulations with molecular and evolutionary principles to map mutational patterns and model interactions between cells that promote resistance. On the basis that engineering in medicine has resulted in discoveries in resistance biology and successfully translated to clinical strategies that improve outcomes, we suggest the proliferation of multidisciplinary science that embraces engineering.

Cancer immunotherapy via targeted TGF-β signalling blockade in TH cells

Cancer arises from malignant cells that exist in dynamic multilevel interactions with the host tissue. Cancer therapies aiming to directly kill cancer cells, including oncogene-targeted therapy and immune-checkpoint therapy that revives tumour-reactive cytotoxic T lymphocytes, are effective in some patients^1,2, but acquired resistance frequently develops^3,4. An alternative therapeutic strategy aims to rectify the host tissue pathology, including abnormalities in the vasculature that foster cancer progression^5,6; however, neutralization of proangiogenic factors such as vascular endothelial growth factor A (VEGFA) has had limited clinical benefits^7,8. Here, following the finding that transforming growth factor-β (TGF-β) suppresses T helper 2 (T_H2)-cell-mediated cancer immunity⁹, we show that blocking TGF-β signalling in CD4⁺ T cells remodels the tumour microenvironment and restrains cancer progression. In a mouse model of breast cancer resistant to immune-checkpoint or anti-VEGF therapies^10,11, inducible genetic deletion of the TGF-β receptor II (TGFBR2) in CD4⁺ T cells suppressed tumour growth. For pharmacological blockade, we engineered a bispecific receptor decoy by attaching the TGF-β-neutralizing TGFBR2 extracellular domain to ibalizumab, a non-immunosuppressive CD4 antibody^12,13, and named it CD4 TGF-β Trap (4T-Trap). Compared with a non-targeted TGF-β-Trap, 4T-Trap selectively inhibited T_H cell TGF-β signalling in tumour-draining lymph nodes, causing reorganization of tumour vasculature and cancer cell death, a process dependent on the T_H2 cytokine interleukin-4 (IL-4). Notably, the 4T-Trap-induced tumour tissue hypoxia led to increased VEGFA expression. VEGF inhibition enhanced the starvation-triggered cancer cell death and amplified the antitumour effect of 4T-Trap. Thus, targeted TGF-β signalling blockade in helper T cells elicits an effective tissue-level cancer defence response that can provide a basis for therapies directed towards the cancer environment.

Phenotypic noise and the cost of complexity

Experimental studies demonstrate the existence of phenotypic diversity despite constant genotype and environment. Theoretical models based on a single phenotypic character predict that during an adaptation event, phenotypic noise should be positively selected far from the fitness optimum because it increases the fitness of the genotype, and then be selected against when the population reaches the optimum. It is suggested that because of this fitness gain, phenotypic noise should promote adaptive evolution. However, it is unclear how the selective advantage of phenotypic noise is linked to the rate of evolution, and whether any advantage would hold for more realistic, multidimensional phenotypes. Indeed, complex organisms suffer a cost of complexity, where beneficial mutations become rarer as the number of phenotypic characters increases. Using a quantitative genetics approach, we first show that for a one-dimensional phenotype, phenotypic noise promotes adaptive evolution on plateaus of positive fitness, independently from the direct selective advantage on fitness. Second, we show that for multidimensional phenotypes, phenotypic noise evolves to a low-dimensional configuration, with elevated noise in the direction of the fitness optimum. Such a dimensionality reduction of the phenotypic noise promotes adaptive evolution and numerical simulations show that it reduces the cost of complexity.

Detecting heterogeneity in and between breast cancer cell lines

Background

Cellular heterogeneity in tumor cells is a well-established phenomenon. Genetic and phenotypic cell-to-cell variability have been observed in numerous studies both within the same type of cancer cells and across different types of cancers. Another known fact for metastatic tumor cells is that they tend to be softer than their normal or non-metastatic counterparts. However, the heterogeneity of mechanical properties in tumor cells are not widely studied.

Results

Here we analyzed single-cell optical stretcher data with machine learning algorithms on three different breast tumor cell lines and show that similar heterogeneity can also be seen in mechanical properties of cells both within and between breast tumor cell lines. We identified two clusters within MDA-MB-231 cells, with cells in one cluster being softer than in the other. In addition, we show that MDA-MB-231 cells and MDA-MB-436 cells which are both epithelial breast cancer cell lines with a mesenchymal-like phenotype derived from metastatic cancers are mechanically more different from each other than from non-malignant epithelial MCF-10A cells.

Conclusion

Since stiffness of tumor cells can be an indicator of metastatic potential, this result suggests that metastatic abilities could vary within the same monoclonal tumor cell line.

Principles and mechanisms of non-genetic resistance in cancer

As well as undergoing genetic evolution, cancer cells can alter their epigenetic state to adapt and resist treatment. This non-genetic evolution is emerging as a major component of cancer resistance. Only now are we beginning to acquire the necessary data and tools to establish some of the underlying principles and mechanisms that define when, why and how non-genetic resistance occurs. Preliminary studies suggest that it can exist in a number of forms, including drug persistence, unstable non-genetic resistance and, most intriguingly, stable non-genetic resistance. Exactly how they each arise remains unclear; however, epigenetic heterogeneity and plasticity appear to be important variables. In this review, we provide an overview of these different forms of non-genetic resistance, before exploring how epigenetic heterogeneity and plasticity influence their emergence. We highlight the distinction between non-genetic Darwinian selection and Lamarckian induction and discuss how each is capable of generating resistance. Finally, we discuss the potential interaction between genetic and non-genetic adaptation and propose the idea of ‘the path of most resistance’, which outlines the variables that dictate whether cancers adapt through genetic and/or epigenetic means. Through these discussions, we hope to provide a conceptual framework that focuses future studies, whose insights might help prevent or overcome non-genetic resistance.

Time-dependent saddle-node bifurcation: Breaking time and the point of no return in a non-autonomous model of critical transitions

There is a growing awareness that catastrophic phenomena in biology and medicine can be mathematically represented in terms of saddle-node bifurcations. In particular, the term "tipping", or critical transition has in recent years entered the discourse of the general public in relation to ecology, medicine, and public health. The saddle-node bifurcation and its associated theory of catastrophe as put forth by Thom and Zeeman has seen applications in a wide range of fields including molecular biophysics, mesoscopic physics, and climate science. In this paper, we investigate a simple model of a non-autonomous system with a time-dependent parameter p(τ) and its corresponding "dynamic" (time-dependent) saddle-node bifurcation by the modern theory of non-autonomous dynamical systems. We show that the actual point of no return for a system undergoing tipping can be significantly delayed in comparison to the breaking time τ ^ at which the corresponding autonomous system with a time-independent parameter p a = p ( τ ^ ) undergoes a bifurcation. A dimensionless parameter α = λ p 0 3 V - 2 is introduced, in which λ is the curvature of the autonomous saddle-node bifurcation according to parameter p(τ), which has an initial value of p ₀ and a constant rate of change V. We find that the breaking time τ ^ is always less than the actual point of no return τ ^∗ after which the critical transition is irreversible; specifically, the relation τ * - τ ^ ≃ 2.338 ( λ V ) - 1 3 is analytically obtained. For a system with a small λV, there exists a significant window of opportunity ( τ ^ , τ ^∗) during which rapid reversal of the environment can save the system from catastrophe.

Toward Minimal Residual Disease-Directed Therapy in Melanoma

Many patients with advanced cancers achieve dramatic responses to a panoply of therapeutics yet retain minimal residual disease (MRD), which ultimately results in relapse. To gain insights into the biology of MRD, we applied single-cell RNA sequencing to malignant cells isolated from BRAF mutant patient-derived xenograft melanoma cohorts exposed to concurrent RAF/MEK-inhibition. We identified distinct drug-tolerant transcriptional states, varying combinations of which co-occurred within MRDs from PDXs and biopsies of patients on treatment. One of these exhibited a neural crest stem cell (NCSC) transcriptional program largely driven by the nuclear receptor RXRG. An RXR antagonist mitigated accumulation of NCSCs in MRD and delayed the development of resistance. These data identify NCSCs as key drivers of resistance and illustrate the therapeutic potential of MRD-directed therapy. They also highlight how gene regulatory network architecture reprogramming may be therapeutically exploited to limit cellular heterogeneity, a key driver of disease progression and therapy resistance.

Single-cell analysis resolves the cell state transition and signaling dynamics associated with melanoma drug-induced resistance

Continuous BRAF inhibition of BRAF mutant melanomas triggers a series of cell state changes that lead to therapy resistance and escape from immune control before establishing acquired resistance genetically. We used genome-wide transcriptomics and single-cell phenotyping to explore the response kinetics to BRAF inhibition for a panel of patient-derived BRAFV600 -mutant melanoma cell lines. A subset of plastic cell lines, which followed a trajectory covering multiple known cell state transitions, provided models for more detailed biophysical investigations. Markov modeling revealed that the cell state transitions were reversible and mediated by both Lamarckian induction and nongenetic Darwinian selection of drug-tolerant states. Single-cell functional proteomics revealed activation of certain signaling networks shortly after BRAF inhibition, and before the appearance of drug-resistant phenotypes. Drug targeting those networks, in combination with BRAF inhibition, halted the adaptive transition and led to prolonged growth inhibition in multiple patient-derived cell lines.

Precision Oncology: Between Vaguely Right and Precisely Wrong

Precision Oncology seeks to identify and target the mutation that drives a tumor. Despite its straightforward rationale, concerns about its effectiveness are mounting. What is the biological explanation for the "imprecision?" First, Precision Oncology relies on indiscriminate sequencing of genomes in biopsies that barely represent the heterogeneous mix of tumor cells. Second, findings that defy the orthodoxy of oncogenic "driver mutations" are now accumulating: the ubiquitous presence of oncogenic mutations in silent premalignancies or the dynamic switching without mutations between various cell phenotypes that promote progression. Most troublesome is the observation that cancer cells that survive treatment still will have suffered cytotoxic stress and thereby enter a stem cell-like state, the seeds for recurrence. The benefit of "precision targeting" of mutations is inherently limited by this counterproductive effect. These findings confirm that there is no precise linear causal relationship between tumor genotype and phenotype, a reminder of logician Carveth Read's caution that being vaguely right may be preferable to being precisely wrong. An open-minded embrace of the latest inconvenient findings indicating nongenetic and "imprecise" phenotype dynamics of tumors as summarized in this review will be paramount if Precision Oncology is ultimately to lead to clinical benefits. Cancer Res; 77(23); 6473-9. ©2017 AACR.

Cancer is an adaptation that selects in animals against energy dissipation

As cancer usually follows reproduction, it is generally assumed that cancer does not select. Graham has however argued that juvenile cancer, which precedes reproduction, could during evolution have implemented a "cancer selection" that resulted in novel traits that suppress this juvenile cancer; an example is protection against UV sunlight-induced cancer, required for the emergence of terrestrial animals from the sea. We modify the cancer selection mechanism to the posited "cancer adaptation" mechanism, in which juvenile mortality is enhanced through the diminished care received by juveniles from their (grand) parents when these suffer from cancer in old age. Moreover, it is posited that the cancer adaptation selects against germline "dissipative genes", genes that result in enhanced free energy dissipation. Cancer's progression is interpreted as a cascade at increasing scale of repeated amplification of energy dissipation, a cascade involving heat shock, the Warburg effect, the cytokine IL-6, tumours, and hypermetabolism. Disturbance of any physiological process must enhance energy dissipation if the animal remains functioning normally, what explains multicausality, why "everything gives you cancer". The hypothesis thus comprises two newly invoked partial processes-diminished (grand) parental care and dissipation amplification-and results in a "selection against enhanced energy dissipation" which gives during evolution the benefit of energy conservation. Due to this benefit, cancer would essentially be an adaptation, and not a genetic disease, as assumed in the "somatic mutation theory". Cancer by somatic mutations is only a side process. The cancer adaptation hypothesis is substantiated by (1) cancer's extancy, (2) the failure of the somatic mutation theory, (3) cancer's initiation by a high temperature, (4) the interpretation of cancer's progression as a thermal process, and (5) the interpretation of tumours as organs that implement thermogenesis. The hypothesis could in principle be verified by monitoring in a population over several generations (1) the presence of dissipative genes, (2) the incidence of cancer, and (3) the beneficial effect of dissipative gene removal by cancer on starvation/famine survival.

Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation

BACKGROUND

Drug-induced drug resistance in cancer has been attributed to diverse biological mechanisms at the individual cell or cell population scale, relying on stochastically or epigenetically varying expression of phenotypes at the single cell level, and on the adaptability of tumours at the cell population level.

SCOPE OF REVIEW

We focus on intra-tumour heterogeneity, namely between-cell variability within cancer cell populations, to account for drug resistance. To shed light on such heterogeneity, we review evolutionary mechanisms that encompass the great evolution that has designed multicellular organisms, as well as smaller windows of evolution on the time scale of human disease. We also present mathematical models used to predict drug resistance in cancer and optimal control methods that can circumvent it in combined therapeutic strategies.

MAJOR CONCLUSIONS

Plasticity in cancer cells, i.e., partial reversal to a stem-like status in individual cells and resulting adaptability of cancer cell populations, may be viewed as backward evolution making cancer cell populations resistant to drug insult. This reversible plasticity is captured by mathematical models that incorporate between-cell heterogeneity through continuous phenotypic variables. Such models have the benefit of being compatible with optimal control methods for the design of optimised therapeutic protocols involving combinations of cytotoxic and cytostatic treatments with epigenetic drugs and immunotherapies.

GENERAL SIGNIFICANCE

Gathering knowledge from cancer and evolutionary biology with physiologically based mathematical models of cell population dynamics should provide oncologists with a rationale to design optimised therapeutic strategies to circumvent drug resistance, that still remains a major pitfall of cancer therapeutics. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

Learning about the Importance of Mutation Prevention from Curable Cancers and Benign Tumors

Some cancers can be cured by chemotherapy or radiotherapy, presumably because they are derived from those cell types that not only can die easily but also have already been equipped with mobility and adaptability, which would later allow the cancers to metastasize without the acquisition of additional mutations. From a viewpoint of biological dispersal, invasive and metastatic cells may, among other possibilities, have been initial losers in the competition for resources with other cancer cells in the same primary tumor and thus have had to look for new habitats in order to survive. If this is really the case, manipulation of their ecosystems, such as by slightly ameliorating their hardship, may prevent metastasis. Since new mutations may occur, especially during and after therapy, to drive progression of cancer cells to metastasis and therapy-resistance, preventing new mutations from occurring should be a key principle for the development of new anticancer drugs. Such new drugs should be able to kill cancer cells very quickly without leaving the surviving cells enough time to develop new mutations and select resistant or metastatic clones. This principle questions the traditional use and the future development of genotoxic drugs for cancer therapy.

Precritical State Transition Dynamics in the Attractor Landscape of a Molecular Interaction Network Underlying Colorectal Tumorigenesis

From the perspective of systems science, tumorigenesis can be hypothesized as a critical transition (an abrupt shift from one state to another) between proliferative and apoptotic attractors on the state space of a molecular interaction network, for which an attractor is defined as a stable state to which all initial states ultimately converge, and the region of convergence is called the basin of attraction. Before the critical transition, a cellular state might transit between the basin of attraction for an apoptotic attractor and that for a proliferative attractor due to the noise induced by the inherent stochasticity in molecular interactions. Such a flickering state transition (state transition between the basins of attraction for alternative attractors from the impact of noise) would become more frequent as the cellular state approaches near the boundary of the basin of attraction, which can increase the variation in the estimate of the respective basin size. To investigate this for colorectal tumorigenesis, we have constructed a stochastic Boolean network model of the molecular interaction network that contains an important set of proteins known to be involved in cancer. In particular, we considered 100 representative sequences of 20 gene mutations that drive colorectal tumorigenesis. We investigated the appearance of cancerous cells by examining the basin size of apoptotic, quiescent, and proliferative attractors along with the sequential accumulation of gene mutations during colorectal tumorigenesis. We introduced a measure to detect the flickering state transition as the variation in the estimate of the basin sizes for three-phenotype attractors from the impact of noise. Interestingly, we found that this measure abruptly increases before a cell becomes cancerous during colorectal tumorigenesis in most of the gene mutation sequences under a certain level of stochastic noise. This suggests that a frequent flickering state transition can be a precritical phenomenon of colorectal tumorigenesis.

Protecting the normal in order to better kill the cancer

Chemotherapy is the only option for oncologists when a cancer has widely spread to different body sites. However, almost all currently available chemotherapeutic drugs will eventually encounter resistance after their initial positive effect, mainly because cancer cells develop genetic alterations, collectively coined herein as mutations, to adapt to the therapy. Some patients may still respond to a second chemo drug, but few cases respond to a third one. Since it takes time for cancer cells to develop new mutations and then select those life-sustaining ones via clonal expansion, "run against time for mutations to emerge" should be a crucial principle for treatment of those currently incurable cancers. Since cancer cells constantly change to adapt to the therapy whereas normal cells are stable, it may be a better strategy to shift our focus from killing cancer cells per se to protecting normal cells from chemotherapeutic toxicity. This new strategy requires the development of new drugs that are nongenotoxic and can quickly, in just hours or days, kill cancer cells without leaving the still-alive cells with time to develop mutations, and that should have their toxicities confined to only one or few organs, so that specific protections can be developed and applied.

Can a minimal replicating construct be identified as the embodiment of cancer?

Genomic instability is a hallmark of cancer. Cancer cells that exhibit abnormal chromosomes are characteristic of most advanced tumours, despite the potential threat represented by accumulated genetic damage. Carcinogenesis involves a loss of key components of the genetic and signalling molecular networks; hence some authors have suggested that this is part of a trend of cancer cells to behave as simple, minimal replicators. In this study, we explore this conjecture and suggest that, in the case of cancer, genomic instability has an upper limit that is associated with a minimal cancer cell network. Such a network would include (for a given microenvironment) the basic molecular components that allow cells to replicate and respond to selective pressures. However, it would also exhibit internal fragilities that could be exploited by appropriate therapies targeting the DNA repair machinery. The implications of this hypothesis are discussed.

Staging for cervix cancer: Role of radiology, surgery and clinical assessment

Staging is necessary in determining the extent of disease, its prognosis and in the formulation of optimal treatment protocols for patients with cancer. Clinical examination of patients and subsequent histopathological assessment when available has traditionally been used to determine the application of different primary and adjuvant treatment modalities. Over the years, surgery, radiotherapy and chemotherapy all have been used either singly or in combinations, and the resulting survival and patterns of failure studies have contributed much in the development of less toxic and more effective protocols. All three modalities of treatments work through separate mechanisms, and they are effective in different stages of cervix cancer. Even within the same stage, the extent of the disease, tumour volume, tissue infiltration and lymph-node metastases requires the use of differing protocols for the disease control. More recently, advances in magnetic resonance imaging (MRI) and positron emission tomography/computerised tomography (PET/CT) have made it possible to examine many of the prognostic factors non-invasively. In addition to clinical assessment, surgical and radiological staging has enabled us to triage patients far more accurately for surgery or for primary radiotherapy, such as unnecessary multimodality treatments are avoided. Only patients with poor prognosis are subjected to a combined modality treatment. Those with poorer prognosis still can be selected for clinical studies exploring new treatment.

Genetic and non-genetic instability in tumor progression: link between the fitness landscape and the epigenetic landscape of cancer cells

Genetic instability is invoked in explaining the cell phenotype changes that take place during cancer progression. However, the coexistence of a vast diversity of distinct clones, most prominently visible in the form of non-clonal chromosomal aberrations, suggests that Darwinian selection of mutant cells is not operating at maximal efficacy. Conversely, non-genetic instability of cancer cells must also be considered. Such mutation-independent instability of cell states is most prosaically manifest in the phenotypic heterogeneity within clonal cell populations or in the reversible switching between immature "cancer stem cell-like" and more differentiated states. How are genetic and non-genetic instability related to each other? Here, we review basic theoretical foundations and offer a dynamical systems perspective in which cancer is the inevitable pathological manifestation of modes of malfunction that are immanent to the complex gene regulatory network of the genome. We explain in an accessible, qualitative, and permissively simplified manner the mathematical basis for the "epigenetic landscape" and how the latter relates to the better known "fitness landscape." We show that these two classical metaphors have a formal basis. By combining these two landscape concepts, we unite development and somatic evolution as the drivers of the relentless increase in malignancy. Herein, the cancer cells are pushed toward cancer attractors in the evolutionarily unused regions of the epigenetic landscape that encode more and more "dedifferentiated" states as a consequence of both genetic (mutagenic) and non-genetic (regulatory) perturbations-including therapy. This would explain why for the cancer cell, the principle of "What does not kill me makes me stronger" is as much a driving force in tumor progression and development of drug resistance as the simple principle of "survival of the fittest."

Gene networks of fully connected triads with complete auto-activation enable multistability and stepwise stochastic transitions

Fully-connected triads (FCTs), such as the Oct4-Sox2-Nanog triad, have been implicated as recurring transcriptional motifs embedded within the regulatory networks that specify and maintain cellular states. To explore the possible connections between FCT topologies and cell fate determinations, we employed computational network screening to search all possible FCT topologies for multistability, a dynamic property that allows the rise of alternate regulatory states from the same transcriptional network. The search yielded a hierarchy of FCTs with various potentials for multistability, including several topologies capable of reaching eight distinct stable states. Our analyses suggested that complete auto-activation is an effective indicator for multistability, and, when gene expression noise was incorporated into the model, the networks were able to transit multiple states spontaneously. Different levels of stochasticity were found to either induce or disrupt random state transitioning with some transitions requiring layovers at one or more intermediate states. Using this framework we simulated a simplified model of induced pluripotency by including constitutive overexpression terms. The corresponding FCT showed random state transitioning from a terminal state to the pluripotent state, with the temporal distribution of this transition matching published experimental data. This work establishes a potential theoretical framework for understanding cell fate determinations by connecting conserved regulatory modules with network dynamics. Our results could also be employed experimentally, using established developmental transcription factors as seeds, to locate cell lineage specification networks by using auto-activation as a cipher.

Competing views on cancer

Despite intense research efforts that have provided enormous insight, cancer continues to be a poorly understood disease. There has been much debate over whether the cancerous state can be said to originate in a single cell or whether it is a reflection of aberrant behaviour on the part of a 'society of cells'. This article presents, in the form of a debate conducted among the authors, three views of how the problem might be addressed. We do not claim that the views exhaust all possibilities. These views are (a) the tissue organization field theory (TOFT) that is based on a breakdown of tissue organization involving many cells from different embryological layers, (b) the cancer stem cell (CSC) hypothesis that focuses on genetic and epigenetic changes that take place within single cells, and (c) the proposition that rewiring of the cell's protein interaction networks mediated by intrinsically disordered proteins (IDPs) drives the tumorigenic process. The views are based on different philosophical approaches. In detail, they differ on some points and agree on others. It is left to the reader to decide whether one approach to understanding cancer appears more promising than the other.

The epigenetic landscape in the course of time: Conrad Hal Waddington's methodological impact on the life sciences

It seems that the reception of Conrad Hal Waddington's work never really gathered speed in mainstream biology. This paper, offering a transdisciplinary survey of approaches using his epigenetic landscape images, argues that (i) Waddington's legacy is much broader than is usually recognized--it is widespread across the life sciences (e.g. stem cell biology, developmental psychology and cultural anthropology). In addition, I will show that (ii) there exist as yet unrecognized heuristic roles, especially in model building and theory formation, which Waddington's images play within his work. These different methodological facets envisioned by Waddington are used as a natural framework to analyze and classify the manners of usage of epigenetic landscape images in post-Waddingtonian 'landscape approaches'. This evaluation of Waddington's pictorial legacy reveals that there are highly diverse lines of traditions in the life sciences, which are deeply rooted in Waddington's methodological work.

Ovarian cancer evolution through stochastic genome alterations: defining the genomic role in ovarian cancer

Ovarian cancer is the fifth leading cause of death among women worldwide. Characterized by complex etiology and multi-level heterogeneity, its origins are not well understood. Intense research efforts over the last decade have furthered our knowledge by identifying multiple risk factors that are associated with the disease. However, it is still unclear how genetic heterogeneity contributes to tumor formation, and more specifically, how genome-level heterogeneity acts as the key driving force of cancer evolution. Most current genomic approaches are based on 'average molecular profiling.' While effective for data generation, they often fail to effectively address the issue of high level heterogeneity because they mask variation that exists in a cell population. In this synthesis, we hypothesize that genome-mediated cancer evolution can effectively explain diverse factors that contribute to ovarian cancer. In particular, the key contribution of genome replacement can be observed during major transitions of ovarian cancer evolution including cellular immortalization, transformation, and malignancy. First, we briefly review major updates in the literature, and illustrate how current gene-mediated research will offer limited insight into cellular heterogeneity and ovarian cancer evolution. We next explain a holistic framework for genome-based ovarian cancer evolution and apply it to understand the genomic dynamics of a syngeneic ovarian cancer mouse model. Finally, we employ single cell assays to further test our hypothesis, discuss some predictions, and report some recent findings.

How changes in extracellular matrix mechanics and gene expression variability might combine to drive cancer progression

Changes in extracellular matrix (ECM) structure or mechanics can actively drive cancer progression; however, the underlying mechanism remains unknown. Here we explore whether this process could be mediated by changes in cell shape that lead to increases in genetic noise, given that both factors have been independently shown to alter gene expression and induce cell fate switching. We do this using a computer simulation model that explores the impact of physical changes in the tissue microenvironment under conditions in which physical deformation of cells increases gene expression variability among genetically identical cells. The model reveals that cancerous tissue growth can be driven by physical changes in the microenvironment: when increases in cell shape variability due to growth-dependent increases in cell packing density enhance gene expression variation, heterogeneous autonomous growth and further structural disorganization can result, thereby driving cancer progression via positive feedback. The model parameters that led to this prediction are consistent with experimental measurements of mammary tissues that spontaneously undergo cancer progression in transgenic C3(1)-SV40Tag female mice, which exhibit enhanced stiffness of mammary ducts, as well as progressive increases in variability of cell-cell relations and associated cell shape changes. These results demonstrate the potential for physical changes in the tissue microenvironment (e.g., altered ECM mechanics) to induce a cancerous phenotype or accelerate cancer progression in a clonal population through local changes in cell geometry and increased phenotypic variability, even in the absence of gene mutation.

Cancer: tilting at windmills?

One of the striking characteristics of cancer cells is their phenotypic diversity and ability to switch phenotypes in response to environmental fluctuations. Such phenotypic changes (e.g. from drug-sensitive to drug-resistant), which are critical for survival and proliferation, are widely believed to arise due to mutations in the cancer cell's genome. However, there is growing concern that such a deterministic view is not entirely consistent with multiple lines of evidence which indicate that cancer can arise in the absence of mutations and can even be reversed to normalcy despite the mutations. In this Commentary, we wish to present an alternate view that highlights how stochasticity in protein interaction networks (PINs) may play a key role in cancer initiation and progression. We highlight the potential role of intrinsically disordered proteins (IDPs) and submit that targeting IDPs can lead to new insights and treatment protocols for cancer.