Control of cancer formation by intrinsic genetic noise and microenvironmental cues

A gray box framework that optimizes a white box logical model using a black box optimizer for simulating cellular responses to perturbations

Predicting cellular responses to perturbations requires interpretable insights into molecular regulatory dynamics to perform reliable cell fate control, despite the confounding non-linearity of the underlying interactions. There is a growing interest in developing machine learning-based perturbation response prediction models to handle the non-linearity of perturbation data, but their interpretation in terms of molecular regulatory dynamics remains a challenge. Alternatively, for meaningful biological interpretation, logical network models such as Boolean networks are widely used in systems biology to represent intracellular molecular regulation. However, determining the appropriate regulatory logic of large-scale networks remains an obstacle due to the high-dimensional and discontinuous search space. To tackle these challenges, we present a scalable derivative-free optimizer trained by meta-reinforcement learning for Boolean network models. The logical network model optimized by the trained optimizer successfully predicts anti-cancer drug responses of cancer cell lines, while simultaneously providing insight into their underlying molecular regulatory mechanisms.

The inherent fragility of collective proliferative control

Tissues achieve and maintain their sizes through active feedback, whereby cells collectively regulate proliferation and differentiation so as to facilitate homeostasis and the ability to respond to disturbances. One of the best understood feedback mechanisms-renewal control-achieves remarkable feats of robustness in determining and maintaining desired sizes. Yet in a variety of biologically relevant situations, we show that stochastic effects should cause rare but catastrophic failures of renewal control. We define the circumstances under which this occurs and raise the possibility such events account for important non-genetic steps in the development of cancer. We further suggest that the spontaneous stochastic reversal of these events could explain cases of cancer normalization or dormancy following treatment. Indeed, we show that the kinetics of post-treatment recurrence for many cancers are often better fit by a model of stochastic re-emergence due to loss of collective proliferative control, than by deterministic models of cancer relapse.

Critical transition and reversion of tumorigenesis

Cancer is caused by the accumulation of genetic alterations and therefore has been historically considered to be irreversible. Intriguingly, several studies have reported that cancer cells can be reversed to be normal cells under certain circumstances. Despite these experimental observations, conceptual and theoretical frameworks that explain these phenomena and enable their exploration in a systematic way are lacking. In this review, we provide an overview of cancer reversion studies and describe recent advancements in systems biological approaches based on attractor landscape analysis. We suggest that the critical transition in tumorigenesis is an important clue for achieving cancer reversion. During tumorigenesis, a critical transition may occur at a tipping point, where cells undergo abrupt changes and reach a new equilibrium state that is determined by complex intracellular regulatory events. We introduce a conceptual framework based on attractor landscapes through which we can investigate the critical transition in tumorigenesis and induce its reversion by combining intracellular molecular perturbation and extracellular signaling controls. Finally, we present a cancer reversion therapy approach that may be a paradigm-changing alternative to current cancer cell-killing therapies.

Tumour Stem Cells in Breast Cancer

Tumour stem cells (CSCs) are a self-renewing population that plays important roles in tumour initiation, recurrence, and metastasis. Although the medical literature is extensive, problems with CSC identification and cancer therapy remain. This review provides the main mechanisms of CSC action in breast cancer (BC): CSC markers and signalling pathways, heterogeneity, plasticity, and ecological behaviour. The dynamic heterogeneity of CSCs and the dynamic transitions of CSC⁻ non-CSCs and their significance for metastasis are considered.

A Stochastic Binary Model for the Regulation of Gene Expression to Investigate Responses to Gene Therapy

Simple Summary

Gene editing technologies reached a turning point toward epigenetic modulation for cancer treatment. Gene networks are complex systems composed of multiple non-trivially coupled elements capable of reliably processing dynamical information from the environment despite unavoidable randomness. However, this functionality is lost when the cells are in a diseased state. Hence, gene-editing-based therapeutic design can be viewed as a gene network dynamics modulation toward a healthy state. Enhancement of this control relies on mathematical models capable of effectively describing the regulation of stochastic gene expression. We use a two-state stochastic model for gene expression to investigate treatment response with a switching target gene. We show the necessity of modulating multiple gene-expression-related processes to reach a heterogeneity-reduced specific response using epigenetic-targeting cancer treatment designs. Our approach can be used as an additional tool for developing epigenetic-targeting treatments.

Abstract

In this manuscript, we use an exactly solvable stochastic binary model for the regulation of gene expression to analyze the dynamics of response to a treatment aiming to modulate the number of transcripts of a master regulatory switching gene. The challenge is to combine multiple processes with different time scales to control the treatment response by a switching gene in an unavoidable noisy environment. To establish biologically relevant timescales for the parameters of the model, we select the RKIP gene and two non-specific drugs already known for changing RKIP levels in cancer cells. We demonstrate the usefulness of our method simulating three treatment scenarios aiming to reestablish RKIP gene expression dynamics toward a pre-cancerous state: (1) to increase the promoter’s ON state duration; (2) to increase the mRNAs’ synthesis rate; and (3) to increase both rates. We show that the pre-treatment kinetic rates of ON and OFF promoter switching speeds and mRNA synthesis and degradation will affect the heterogeneity and time for treatment response. Hence, we present a strategy for reaching increased average mRNA levels with diminished heterogeneity while reducing drug dosage by simultaneously targeting multiple kinetic rates that effectively represent the chemical processes underlying the regulation of gene expression. The decrease in heterogeneity of treatment response by a target gene helps to lower the chances of emergence of resistance. Our approach may be useful for inferring kinetic constants related to the expression of antimetastatic genes or oncogenes and for the design of multi-drug therapeutic strategies targeting the processes underpinning the expression of master regulatory genes.

Gene by Environment Interactions reveal new regulatory aspects of signaling network plasticity

Phenotypes can change during exposure to different environments through the regulation of signaling pathways that operate in integrated networks. How signaling networks produce different phenotypes in different settings is not fully understood. Here, Gene by Environment Interactions (GEIs) were used to explore the regulatory network that controls filamentous/invasive growth in the yeast Saccharomyces cerevisiae. GEI analysis revealed that the regulation of invasive growth is decentralized and varies extensively across environments. Different regulatory pathways were critical or dispensable depending on the environment, microenvironment, or time point tested, and the pathway that made the strongest contribution changed depending on the environment. Some regulators even showed conditional role reversals. Ranking pathways' roles across environments revealed an under-appreciated pathway (OPI1) as the single strongest regulator among the major pathways tested (RAS, RIM101, and MAPK). One mechanism that may explain the high degree of regulatory plasticity observed was conditional pathway interactions, such as conditional redundancy and conditional cross-pathway regulation. Another mechanism was that different pathways conditionally and differentially regulated gene expression, such as target genes that control separate cell adhesion mechanisms (FLO11 and SFG1). An exception to decentralized regulation of invasive growth was that morphogenetic changes (cell elongation and budding pattern) were primarily regulated by one pathway (MAPK). GEI analysis also uncovered a round-cell invasion phenotype. Our work suggests that GEI analysis is a simple and powerful approach to define the regulatory basis of complex phenotypes and may be applicable to many systems.

[Epithelial-stromal interactions in pancreatic adenocarcinoma: the role of stroma in disease progression]

Pancreatic ductal adenocarcinoma (PDAC) is the most common and difficult to treat form of pancreas cancer. PDAC and other solid cancers contain both tumor cells and normal connective tissue cells called stromal cells, which are responsible for the excess production of extracellular matrix. It is known that in more than 90% of PDAC tumors and in many other types of cancer, mutations of the KRAS gene are observed, the reciprocal signaling of which has been shown between tumor and stromal cells in vitro. Pancreatic stromal stellate cells are considered precursors of activated or tumor-associated fibroblasts (CAFs), which are an increasing population of cells that proliferate in situ or are recruited into the tumor. CAFs are a heterogeneous population of stromal fibroblasts with different molecular profiles that change during tumorigenesis. Both immunosuppressive and immunosuppressive subsets of CAFs can coexist in the stroma of a single tumor. Based on the heterogeneity of the intertumor stroma, attempts are being made to classify PDAC and predict the course of the disease.

The Cell-Isolation Capsules with Rod-Like Channels Ensure the Survival and Response of Cancer Cells to Their Microenvironment

Current macrocapsules with semipermeable but immunoprotective polymeric membranes are attractive devices to achieve the purpose of immunoisolation, however, their ability to allow diffusion of essential nutrients and oxygen is limited, which leads to a low survival rate of encapsulated cells. Here, a novel method is reported by taking advantage of thermotropic liquid crystals, sodium laurylsulfonate (SDS) liquid crystals (LCs), and rod-like crystal fragments (LCFs) to develop engineered alginate hydrogels with rod-like channels. This cell-isolation capsule with an engineered alginate hydrogel-wall allows small molecules, large molecules, and bacteria to diffuse out from the capsules freely but immobilizes the encapsulated cells inside and prevents cells in the microenvironment from moving in. The encapsulated cells show a high survival rate with isolation of host immune cells and long-term growth with adequate nutrients and oxygen supply. In addition, by sharing and responding to the normal molecular and vesicular microenvironment (NMV microenvironment), encapsulated cancer cells display a transition from tumorous phenotypes to ductal features of normal epithelial cells. Thus, this device will be potentially useful for clinical application in cell therapy by secreting molecules and for establishment of patient-derived xenograft (PDX) models that are often difficult to achieve for certain types of tumors, such as prostate cancer.

Deciphering the molecular mechanism of the cancer formation by chromosome structural dynamics

Cancer reflects the dysregulation of the underlying gene network, which is strongly related to the 3D genome organization. Numerous efforts have been spent on experimental characterizations of the structural alterations in cancer genomes. However, there is still a lack of genomic structural-level understanding of the temporal dynamics for cancer initiation and progression. Here, we use a landscape-switching model to investigate the chromosome structural transition during the cancerization and reversion processes. We find that the chromosome undergoes a non-monotonic structural shape-changing pathway with initial expansion followed by compaction during both of these processes. Furthermore, our analysis reveals that the chromosome with a more expanding structure than those at both the normal and cancer cell during cancerization exhibits a sparse contact pattern, which shows significant structural similarity to the one at the embryonic stem cell in many aspects, including the trend of contact probability declining with the genomic distance, the global structural shape geometry and the spatial distribution of loci on the chromosome. In light of the intimate structure-function relationship at the chromosomal level, we further describe the cell state transition processes by the chromosome structural changes, suggesting an elevated cell stemness during the formation of the cancer cells. We show that cell cancerization and reversion are highly irreversible processes in terms of the chromosome structural transition pathways, spatial repositioning of chromosomal loci and hysteresis loop of contact evolution analysis. Our model draws a molecular-scale picture of cell cancerization from the chromosome structural perspective. The process contains initial reprogramming towards the stem cell followed by the differentiation towards the cancer cell, accompanied by an initial increase and subsequent decrease of the cell stemness.

Emerging Role of Chimeric RNAs in Cell Plasticity and Adaptive Evolution of Cancer Cells

Gene fusions can give rise to somatic alterations in cancers. Fusion genes have the potential to create chimeric RNAs, which can generate the phenotypic diversity of cancer cells, and could be associated with novel molecular functions related to cancer cell survival and proliferation. The expression of chimeric RNAs in cancer cells might impact diverse cancer-related functions, including loss of apoptosis and cancer cell plasticity, and promote oncogenesis. Due to their recurrence in cancers and functional association with oncogenic processes, chimeric RNAs are considered biomarkers for cancer diagnosis. Several recent studies demonstrated that chimeric RNAs could lead to the generation of new functionality for the resistance of cancer cells against drug therapy. Therefore, targeting chimeric RNAs in drug resistance cancer could be useful for developing precision medicine. So, understanding the functional impact of chimeric RNAs in cancer cells from an evolutionary perspective will be helpful to elucidate cancer evolution, which could provide a new insight to design more effective therapies for cancer patients in a personalized manner.

Changes in Biomechanical Properties of A375 Cells Due to the Silencing of TMSB4X Expression Are Not Directly Correlated with Alterations in Their Stemness Features

Thymosin β4 (Tβ4) is a small, 44-amino acid polypeptide. It has been implicated in multiple processes, including cell movement, angiogenesis, and stemness. Previously, we reported that melanoma cell lines differ in Tβ4 levels. Studies on stable clones with silenced TMSB4X expression showed that Tβ4 impacted adhesion and epithelial-mesenchymal transition progression. Here, we show that the cells with silenced TMSB4X expression exhibited altered actin cytoskeleton’s organization and subcellular relocalization of two intermediate filament proteins: Nestin and Vimentin. The rearrangement of the cell cytoskeleton resulted in changes in the cells’ topology, height, and stiffness defined by Young’s modulus. Simultaneously, only for some A375 clones with a lowered Tβ4 level, we observed a decreased ability to initiate colony formation in soft agar, tumor formation in vivo, and alterations in Nanog’s expression level transcription factor regulating stemness. Thus, we show for the first time that in A375 cells, biomechanical properties are not directly coupled to stemness features, and this cell line is phenotypically heterogeneous.

Emerging role of tumor cell plasticity in modifying therapeutic response

Resistance to cancer therapy is a major barrier to cancer management. Conventional views have proposed that acquisition of resistance may result from genetic mutations. However, accumulating evidence implicates a key role of non-mutational resistance mechanisms underlying drug tolerance, the latter of which is the focus that will be discussed here. Such non-mutational processes are largely driven by tumor cell plasticity, which renders tumor cells insusceptible to the drug-targeted pathway, thereby facilitating the tumor cell survival and growth. The concept of tumor cell plasticity highlights the significance of re-activation of developmental programs that are closely correlated with epithelial-mesenchymal transition, acquisition properties of cancer stem cells, and trans-differentiation potential during drug exposure. From observations in various cancers, this concept provides an opportunity for investigating the nature of anticancer drug resistance. Over the years, our understanding of the emerging role of phenotype switching in modifying therapeutic response has considerably increased. This expanded knowledge of tumor cell plasticity contributes to developing novel therapeutic strategies or combination therapy regimens using available anticancer drugs, which are likely to improve patient outcomes in clinical practice.

Disruption of EGF Feedback by Intestinal Tumors and Neighboring Cells in Drosophila

In healthy adult organs, robust feedback mechanisms control cell turnover to enforce homeostatic equilibrium between cell division and death [1, 2]. Nascent tumors must subvert these mechanisms to achieve cancerous overgrowth [3-7]. Elucidating the nature of this subversion can reveal how cancers become established and may suggest strategies to prevent tumor progression. In adult Drosophila intestine, a well-studied model of homeostatic cell turnover, the linchpin of cell equilibrium is feedback control of the epidermal growth factor (EGF) protease Rhomboid (Rho). Expression of Rho in apoptotic cells enables them to secrete EGFs, which stimulate nearby stem cells to undergo replacement divisions [8]. As in mammals, loss of adenomatous polyposis coli (APC) causes Drosophila intestinal stem cells to form adenomas [9]. Here, we demonstrate that Drosophila APC-/- tumors trigger widespread Rho expression in non-apoptotic cells, resulting in chronic EGF signaling. Initially, nascent APC-/- tumors induce rho in neighboring wild-type cells via acute, non-autonomous activation of Jun N-terminal kinase (JNK). During later growth and multilayering, APC-/- tumors induce rho in tumor cells by autonomous downregulation of E-cadherin (E-cad) and consequent activity of p120-catenin. This sequential dysregulation of tumor non-autonomous and -autonomous EGF signaling converts tissue-level feedback into feed-forward activation that drives cancerous overgrowth. Because Rho, EGF receptor (EGFR), and E-cad are associated with colorectal cancer in humans [10-17], our findings may shed light on how human colorectal tumors progress.

Drugs modulating stochastic gene expression affect the erythroid differentiation process

To better understand the mechanisms behind cells decision-making to differentiate, we assessed the influence of stochastic gene expression (SGE) modulation on the erythroid differentiation process. It has been suggested that stochastic gene expression has a role in cell fate decision-making which is revealed by single-cell analyses but studies dedicated to demonstrate the consistency of this link are still lacking. Recent observations showed that SGE significantly increased during differentiation and a few showed that an increase of the level of SGE is accompanied by an increase in the differentiation process. However, a consistent relation in both increasing and decreasing directions has never been shown in the same cellular system. Such demonstration would require to be able to experimentally manipulate simultaneously the level of SGE and cell differentiation in order to observe if cell behavior matches with the current theory. We identified three drugs that modulate SGE in primary erythroid progenitor cells. Both Artemisinin and Indomethacin decreased SGE and reduced the amount of differentiated cells. On the contrary, a third component called MB-3 simultaneously increased the level of SGE and the amount of differentiated cells. We then used a dynamical modelling approach which confirmed that differentiation rates were indeed affected by the drug treatment. Using single-cell analysis and modeling tools, we provide experimental evidence that, in a physiologically relevant cellular system, SGE is linked to differentiation.

β-Catenin: A Metazoan Filter for Biological Noise?

Molecular noise refers to fluctuations of biological signals that facilitate phenotypic heterogeneity in a population. While endogenous mechanisms exist to limit genetic noise in biological systems, such restrictions are sometimes removed to propel phenotypic variability as an adaptive strategy. Herein, we review evidence for the potential role of β-catenin in restricting gene expression noise by transcriptional and post-transcriptional mechanisms. We discuss mechanisms that restrict intrinsic noise subsequent to nuclear mobilization of β-catenin. Nuclear β-catenin promotes initiation of transcription but buffers against the resultant noise by restraining transcription elongation. Acceleration of cell cycle, mediated via Wnt/β-catenin downstream signals, further diminishes intrinsic noise by curtailing the efficiency of protein synthesis. Extrinsic noise, on the other hand, is restricted by β-catenin–mediated regulation of major cellular stress pathways.

Gene Expression Noise Produces Cell-to-Cell Heterogeneity in Eukaryotic Homologous Recombination Rate

Variation in gene expression among genetically identical individual cells (called gene expression noise) directly contributes to phenotypic diversity. Whether such variation can impact genome stability and lead to variation in genotype remains poorly explored. We addressed this question by investigating whether noise in the expression of genes affecting homologous recombination (HR) activity either directly (RAD52) or indirectly (RAD27) confers cell-to-cell heterogeneity in HR rate in Saccharomyces cerevisiae. Using cell sorting to isolate subpopulations with various expression levels, we show that spontaneous HR rate is highly heterogeneous from cell-to-cell in clonal populations depending on the cellular amount of proteins affecting HR activity. Phleomycin-induced HR is even more heterogeneous, showing that RAD27 expression variation strongly affects the rate of recombination from cell-to-cell. Strong variations in HR rate between subpopulations are not correlated to strong changes in cell cycle stage. Moreover, this heterogeneity occurs even when simultaneously sorting cells at equal expression level of another gene involved in DNA damage response (BMH1) that is upregulated by DNA damage, showing that the initiating DNA damage is not responsible for the observed heterogeneity in HR rate. Thus gene expression noise seems mainly responsible for this phenomenon. Finally, HR rate non-linearly scales with Rad27 levels showing that total amount of HR cannot be explained solely by the time- or population-averaged Rad27 expression. Altogether, our data reveal interplay between heterogeneity at the gene expression and genetic levels in the production of phenotypic diversity with evolutionary consequences from microbial to cancer cell populations.

Evaluation of the in vitro Antitumor Activity of Nanostructured Cyclotides in Polymers of Eudragit® L 100-55 and RS 30 D

Background:

Cancer is a major cause of mortality and morbidity and given the limitations of many current cancer drugs, there is great need to discover and develop novel treatments. An alternative to the conventional drug discovery path is to exploit new classes of natural compounds such as cyclotides. This peptide family is characterized by linked C- and N-termini and a structural fold called the cyclic cystine knot (CCK). The CCK fold is responsible for the exceptional enzymatic, chemical and thermal stability of cyclotides.

Methods:

In the present study, an alternative to traditional cancer treatments, involving new nanomaterials and nanocarriers allowing efficient cyclotide delivery, is proposed. Using the polymers Eudragit® L 100-55 and RS 30 D, the cyclotides kalata B2 and parigidin-br1 (PBR1) were nanocapsulated, and nanoparticles 91 nm and 188 nm in diameter, respectively, were produced.

Results:

An encapsulation rate of up to 95% was observed. In vitro bioassays showed that the nanostructured cyclotides were partially able to control the development of the colorectal adenocarcinoma cell line CACO2 and the breast cancer cell line MCF-7.

Conclusion:

Data reported herein indicate that nanoformulated cyclotides exhibit antitumor activity and sustained drug release. Thus, the system using Eudragit® nanocapsules seems to be efficient for cyclotide encapsulation and probably could be used to target specific tumors in future studies.

Defining rules for cancer cell proliferation in TRAIL stimulation

Owing to their self-organizing evolutionary plasticity, cancers remain evasive to modern treatment strategies. Previously, for sensitizing tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-resistant human fibrosarcoma (HT1080), we developed and validated a dynamic computational model that showed the inhibition of protein kinase (PK)C, using bisindolylmaleimide (BIS) I, enhances apoptosis with 95% cell death. Although promising, the long-term effect of remaining ~ 5% cells is a mystery. Will they remain unchanged or are they able to proliferate? To address this question, here we adopted a discrete spatiotemporal cellular automata model utilizing simple rules modified from the famous "Conway's game of life". Based on three experimental initializations: cell numbers obtained from untreated (high), treatment with TRAIL only (moderate), and treatment with TRAIL and BIS I (low), the simulations show cell proliferation in time and space. Notably, when all cells are fixed in their initial space, the proliferation is rapid for high and moderate cell numbers, however, slow and steady for low number of cells. However, when mesenchymal-like random movement was introduced, the proliferation becomes significant even for low cell numbers. Experimental verification showed high proportion of mesenchymal cells in TRAIL and BIS I treatment compared with untreated or TRAIL only treatment. In agreement with the model with cell movement, we observed rapid proliferation of the remnant cells in TRAIL and BIS I treatment over time. Hence, our work highlights the importance of mesenchymal-like cellular movement for cancer proliferation. Nevertheless, re-treatment of TRAIL and BIS I on proliferating cancers is still largely effective.

Intravital imaging of glioma border morphology reveals distinctive cellular dynamics and contribution to tumor cell invasion

The pathogenesis of glioblastoma (GBM) is characterized by highly invasive behavior allowing dissemination and progression. A conclusive image of the invasive process is not available. The aim of this work was to study invasion dynamics in GBM using an innovative in vivo imaging approach. Primary brain tumor initiating cell lines from IDH-wild type GBM stably expressing H2B-Dendra2 were implanted orthotopically in the brains of SCID mice. Using high-resolution time-lapse intravital imaging, tumor cell migration in the tumor core, border and invasive front was recorded. Tumor cell dynamics at different border configurations were analyzed and multivariate linear modelling of tumor cell spreading was performed. We found tumor border configurations, recapitulating human tumor border morphologies. Not only tumor borders but also the tumor core was composed of highly dynamic cells, with no clear correlation to the ability to spread into the brain. Two types of border configurations contributed to tumor cell spreading through distinct invasion patterns: an invasive margin that executes slow but directed invasion, and a diffuse infiltration margin with fast but less directed movement. By providing a more detailed view on glioma invasion patterns, our study may improve accuracy of prognosis and serve as a basis for personalized therapeutic approaches.

A multi-state model of chemoresistance to characterize phenotypic dynamics in breast cancer

The development of resistance to chemotherapy is a major cause of treatment failure in breast cancer. While mathematical models describing the dynamics of resistant cancer cell subpopulations have been proposed, experimental validation has been difficult due to the complex nature of resistance that limits the ability of a single phenotypic marker to sufficiently identify the drug resistant subpopulations. We address this problem with a coupled experimental/modeling approach to reveal the composition of drug resistant subpopulations changing in time following drug exposure. We calibrate time-resolved drug sensitivity assays to three mathematical models to interrogate the models' ability to capture drug response dynamics. The Akaike information criterion was employed to evaluate the three models, and it identified a multi-state model incorporating the role of population heterogeneity and cellular plasticity as the optimal model. To validate the model's ability to identify subpopulation composition, we mixed different proportions of wild-type MCF-7 and MCF-7/ADR resistant cells and evaluated the corresponding model output. Our blinded two-state model was able to estimate the proportions of cell types with an R-squared value of 0.857. To the best of our knowledge, this is the first work to combine experimental time-resolved drug sensitivity data with a mathematical model of resistance development.

Mechanical and Systems Biology of Cancer

Mechanics and biochemical signaling are both often deregulated in cancer, leading toincreased cell invasiveness, proliferation, and survival. The dynamics and interactions of cytoskeletal components control basic mechanical properties, such as cell tension, stiffness, and engagement with the extracellular environment, which can lead to extracellular matrix remodeling. Intracellular mechanics can alter signaling and transcription factors, impacting cell decision making. Additionally, signaling from soluble and mechanical factors in the extracellular environment, such as substrate stiffness and ligand density, can modulate cytoskeletal dynamics. Computational models closely integrated with experimental support, incorporating cancer-specific parameters, can provide quantitative assessments and serve as predictive tools toward dissecting the feedback between signaling and mechanics and across multiple scales and domains in tumor progression.

Perspective: Engineering noise in biological systems towards predictive stochastic design

Significant progress has been made towards engineering both single-cell and multi-cellular systems through a combination of synthetic and systems biology, nanobiotechnology, pharmaceutical science, and computational approaches. However, our ability to engineer systems that begin to approach the complexity of natural pathways is severely limited by important challenges, e.g. due to noise, or the fluctuations in gene expression and molecular species at multiple scales (e.g. both intra- and inter-cellular fluctuations). This barrier to engineering requires that biological noise be recognized as a design element with fundamentals that can be actively controlled. Here we highlight studies of an emerging discipline that collectively strives to engineer noise towards predictive stochastic design using interdisciplinary approaches at multiple-scales in diverse living systems.

Molecular paleopathology and paleo-oncology-State of the art, potentials, limitations and perspectives

This paper reviews the current knowledge on molecular paleopathology with respect to oncological information. This covers both the information on the protein level (proteome) as well as the gene level (genome) and includes data on carcinogenic factors - such as molecular evidence for oncogenic viral infections. Currently, relatively little data is available for neoplastic disease in paleopathology. Likewise, few studies describe the biochemical or immunohistochemical analysis of tumors - a tool to potentially classify the tumor type and the underlying primary tumor in metastases. On the gene level, two studies described distinct molecular mutations in either a tumor-driving oncogene or a tumor suppressor gene, both being excellent examples for paleo-oncological studies. The paucity of historic tumor material - particularly when only osseous remains are available - represents the most hindering factor for molecular paleo-oncology. This can only be overcome in future by both the thorough investigation of mummified archaeological biomaterial and the improvement of analytical assays in order to trace even minute amounts of tumor material in osseous lesions.

Fine-tuning of noise in gene expression with nucleosome remodeling

Engineering stochastic fluctuations of gene expression (or “noise”) is integral to precisely bias cellular-fate decisions and statistical phenotypes in both single-cell and multi-cellular systems. Epigenetic regulation has been shown to constitute a large source of noise, and thus, engineering stochasticity is deeply intertwined with epigenetics. Here, utilizing chromatin remodeling, we report that Caffeic acid phenethyl ester (CA) and Pyrimethamine (PYR), two inhibitors of BAF250a, a subunit of the Brahma-associated factor (BAF) nucleosome remodeling complex, enable differential and tunable control of noise in transcription and translation from the human immunodeficiency virus long terminal repeat promoter in a dose and time-dependent manner. CA conserves noise levels while increasing mean abundance, resulting in direct tuning of the transcriptional burst size, while PYR strictly increases transcriptional initiation frequency while conserving a constant transcriptional burst size. Time-dependent treatment with CA reveals non-continuous tuning with noise oscillating at a constant mean abundance at early time points and the burst size increasing for treatments after 5 h. Treatments combining CA and Protein Kinase C agonists result in an even larger increase of abundance while conserving noise levels with a highly non-linear increase in variance of up to 63× untreated controls. Finally, drug combinations provide non-antagonistic combinatorial tuning of gene expression noise and map a noise phase space for future applications with viral and synthetic gene vectors. Active remodeling of nucleosomes and BAF-mediated control of gene expression noise expand a toolbox for the future design and engineering of stochasticity in living systems.

Microenvironmental Signals and Biochemical Information Processing: Cooperative Determinants of Intratumoral Plasticity and Heterogeneity

Intra-tumor cellular heterogeneity is a major challenge in cancer therapy. Tumors are composed of multiple phenotypic subpopulations that vary in their ability to initiate metastatic tumors and in their sensitivity to chemotherapy. In many cases, cells can transition between these subpopulations, not by genetic mutation, but instead through reversible changes in signal transduction or gene expression programs. This plasticity begins at the level of the microenvironment where local autocrine and paracrine signals, exosomes, tumor–stroma interactions, and extracellular matrix (ECM) composition create a signaling landscape that varies over space and time. The integration of this complex array of signals engages signaling pathways that control gene expression. The resulting modulation of gene expression programs causes individual cells to sample a wide array of phenotypic states that support tumor growth, dissemination, and therapeutic resistance. In this review, we discuss how information flows dynamically within the microenvironmental landscape to inform cell state decisions and to create intra-tumoral heterogeneity. We address the role of plasticity in the acquisition of transient and prolonged drug resistant states and discuss how targeted pharmacological modification of the signaling landscape may be able to constrain phenotypic plasticity, leading to improved treatment responses.

The Emerging Role of Vitamin B6 in Inflammation and Carcinogenesis

Vitamin B6 serves as a coenzyme catalyzing more than 150 enzymes regulating metabolism and synthesis of proteins, carbohydrates, lipids, heme, and important bioactive metabolites. For several years vitamin B6 and its vitamers (B6) were recognized as antioxidant and antiinflammatory and in modulating immunity and gene expression. During the last 10 years, there were growing reports implicating B6 in inflammation and inflammation-related chronic illnesses including cancer. It is unclear if the deficiency of B6 or additional intake of B6, above the current requirement, should be the focus. Whether the current recommended daily intake for B6 is adequate should be revisited, since B6 is important to human health beyond its role as a coenzyme and its status is affected by many factors including but not limited to age, obesity, and inflammation associated with chronic illnesses. A link between inflammation B6 status and carcinogenesis is not yet completely understood. B6-mediated synthesis of H₂S, a gasotransmitter, and taurine in health and disease, especially in maintaining mitochondrial integrity and biogenesis and inflammation, remains an important area to be explored. Recent developments in the molecular role of B6 and its direct interaction with inflammasomes, and nuclear receptor corepressor and coactivator, receptor-interacting protein 140, provide a strong impetus to further explore the multifaceted role of B6 in carcinogenesis and human health.

Regulation of genome organization and gene expression by nuclear mechanotransduction

It is well established that cells sense chemical signals from their local microenvironment and transduce them to the nucleus to regulate gene expression programmes. Although a number of experiments have shown that mechanical cues can also modulate gene expression, the underlying mechanisms are far from clear. Nevertheless, we are now beginning to understand how mechanical cues are transduced to the nucleus and how they influence nuclear mechanics, genome organization and transcription. In particular, recent progress in super-resolution imaging, in genome-wide application of RNA sequencing, chromatin immunoprecipitation and chromosome conformation capture and in theoretical modelling of 3D genome organization enables the exploration of the relationship between cell mechanics, 3D chromatin configurations and transcription, thereby shedding new light on how mechanical forces regulate gene expression.

Phenotypic Plasticity and Cell Fate Decisions in Cancer: Insights from Dynamical Systems Theory

Waddington's epigenetic landscape, a famous metaphor in developmental biology, depicts how a stem cell progresses from an undifferentiated phenotype to a differentiated one. The concept of "landscape" in the context of dynamical systems theory represents a high-dimensional space, in which each cell phenotype is considered as an "attractor" that is determined by interactions between multiple molecular players, and is buffered against environmental fluctuations. In addition, biological noise is thought to play an important role during these cell-fate decisions and in fact controls transitions between different phenotypes. Here, we discuss the phenotypic transitions in cancer from a dynamical systems perspective and invoke the concept of "cancer attractors"-hidden stable states of the underlying regulatory network that are not occupied by normal cells. Phenotypic transitions in cancer occur at varying levels depending on the context. Using epithelial-to-mesenchymal transition (EMT), cancer stem-like properties, metabolic reprogramming and the emergence of therapy resistance as examples, we illustrate how phenotypic plasticity in cancer cells enables them to acquire hybrid phenotypes (such as hybrid epithelial/mesenchymal and hybrid metabolic phenotypes) that tend to be more aggressive and notoriously resilient to therapies such as chemotherapy and androgen-deprivation therapy. Furthermore, we highlight multiple factors that may give rise to phenotypic plasticity in cancer cells, such as (a) multi-stability or oscillatory behaviors governed by underlying regulatory networks involved in cell-fate decisions in cancer cells, and (b) network rewiring due to conformational dynamics of intrinsically disordered proteins (IDPs) that are highly enriched in cancer cells. We conclude by discussing why a therapeutic approach that promotes "recanalization", i.e., the exit from "cancer attractors" and re-entry into "normal attractors", is more likely to succeed rather than a conventional approach that targets individual molecules/pathways.

Stroma-derived Fibrinogen-like Protein 2 Activates Cancer-associated Fibroblasts to Promote Tumor Growth in Lung Cancer

Fibrinogen-like protein 2 (Fgl2), a member of the fibrinogen super family, is a pleiotropic cytokine that impacts diverse cellular functions. Previous studies have shown that tumor cell-derived Fgl2 promotes tumorigenesis and metastasis in immune-deficient mice, and it also functions as an immune-suppressive modulator in glioblastoma multiform (GMB). This study aimed to evaluate whether and how tumor stroma-derived Fgl2 affects tumorigenesis and tumor progression. We established the syngeneic transplantable Lewis lung carcinoma (LLC) model in Fgl2-knock-out (Fgl2-KO) mice and we found that deficiency of host Fgl2 is associated with reduced growth of syngeneic LLC tumors. Furthermore, we confirmed that host Fgl2 deficiency significantly decreased the accumulation of myeloid-derived suppressor cells (MDSCs) through down-regulation of chemokine (C-X-C motif) ligand 12 (CXCL12) expression. More importantly, we demonstrated that Fgl2 induced an activated and pro-tumorigenic phenotype of cancer-associated fibroblasts (CAFs) which are the principal source of CXCL12 in the tumor microenvironment (TME). Our results present a novel role of stroma-derived Fgl2 in CAF activation and function, suggesting that Fgl2 is an effective therapeutic target for treating lung cancer.

Modeling the process of human tumorigenesis

Modelling the genesis of human cancers is at a scientific turning point. Starting from primary sources of normal human cells, it is now possible to reproducibly generate several types of malignant cell populations. Powerful methods for clonally tracking and manipulating their appearance and progression in serially transplanted immunodeficient mice are also in place. These developments circumvent historic drawbacks inherent in analyses of cancers produced in model organisms, established human malignant cell lines, or highly heterogeneous patient samples. In this review, we survey the advantages, contributions and limitations of current de novo human tumorigenesis strategies and note several exciting prospects on the horizon.

A better understanding of the earliest stages of human cancer formation can enable future improvements in early detection, diagnosis and treatment. In this review, the authors summarize the methods enabling de novo tumorigenesis protocols to be applied to human cells and the insights derived from them to date, as well as the exciting and relevant technical developments anticipated to extend even further the utility of these strategies.

Impact of Metabolism on T-Cell Differentiation and Function and Cross Talk with Tumor Microenvironment

The immune system and metabolism are highly integrated and multilevel interactions between metabolic system and T lymphocyte signaling and fate exist. Accumulating evidence indicates that the regulation of nutrient uptake and utilization in T cells is critically important for the control of their differentiation and manipulating metabolic pathways in these cells can shape their function and survival. This review will discuss some potential cell metabolism pathways involved in shaping T lymphocyte function and differentiation. It will also describe show subsets of T cells have specific metabolic requirements and signaling pathways that contribute to their respective function. Examples showing the apparent similarity between cancer cell metabolism and T cells during activation are illustrated and finally some mechanisms being used by tumor microenvironment to orchestrate T-cell metabolic dysregulation and the subsequent emergence of immune suppression are discussed. We believe that targeting T-cell metabolism may provide an additional opportunity to manipulate T-cell function in the development of novel therapeutics.

Evolution from genetics to phenotype: reinterpretation of NSCLC plasticity, heterogeneity, and drug resistance

Lung cancer is the leading cause of cancer-related deaths worldwide. Targeted therapy is beneficial in most cases, but the development of drug resistance stands as an obstacle to good prognosis. Multiple mechanisms were explored such as genetic alterations, activation of bypass signaling, and phenotypic transition. These intrinsic and/or extrinsic dynamic regulations facilitate tumor cell survival in meeting the demands of signaling under different stimulus. This review introduces lung cancer plasticity and heterogeneity and their correlation with drug resistance. While cancer plasticity and heterogeneity play an essential role in the development of drug resistance, the manipulation of them may bring some inspirations to cancer prognosis and treatment. That is to say, lung cancer plasticity and heterogeneity present us with not only challenges but also opportunities.

Differential expression of CCN family members CYR611, CTGF and NOV in gastric cancer and their association with disease progression

CCN is an acronym for cysteine-rich protein 61 (CYR61), connective tissue growth factor (CTGF) and nephroblastoma overexpressed (NOV). Aberrations of certain CCN members including CYR61, CTGF, Wnt1-inducible signalling pathway protein (WISP)-1 and -3 have been reported in gastric cancer. The present study aimed to examine the clinical relevance of NOV along with CYR61 and CTGF in gastric cancer by analysing their transcript levels. CYR61, CTGF and NOV transcript expression in 324 gastric cancer samples with paired adjacent normal gastric tissues were determined using real-time quantitative PCR and the results were statistically analysed against patient clinicopathological data using SPSS software. NOV mRNA levels in gastric cancer tissues were significantly elevated when compared with levels in their paired adjacent non-cancerous tissues. Local advanced tumours with invasive expansion (T3 and T4) expressed higher levels of NOV (p=0.013) compared with the less invasive tumours (T1 and T2). CYR61 transcript levels were also significantly increased in gastric cancers compared with levels in the adjacent non-cancerous tissues. Kaplan-Meier survival curves revealed that patients with CYR61-low transcript levels had longer overall survival (OS) (p=0.018) and disease-free survival (DFS) (p=0.015). NOV overexpression promoted the in vitro proliferation of AGS cells while the knockdown resulted in a reduced proliferation of HGC27 cells. A similar effect was observed for the invasion of these two gastric cancer cell lines. NOV expression was increased in gastric cancer which was associated with local invasion and distant metastases. Taken together, the expression of NOV and CYR61 was increased in gastric cancer. The elevated expression of CYR61 was associated with poorer survival. NOV promoted proliferation and invasion of gastric cancer cells. Further investigations may highlight their predictive and therapeutic potential in gastric cancer.

Role of the Polycomb Repressive Complex 2 (PRC2) in Transcriptional Regulation and Cancer

The chromatin environment is modulated by a machinery of chromatin modifiers, required for the specification and maintenance of cell fate. Many mutations in the machinery have been linked to the development and progression of cancer. In this review, we give a brief introduction to Polycomb group (PcG) proteins, their assembly into Polycomb repressive complexes (PRCs) and the normal physiological roles of these complexes with a focus on the PRC2. We review the many findings of mutations in the PRC2 coding genes, both loss-of-function and gain-of-function, associated with human cancers and discuss potential molecular mechanisms involved in the contribution of PRC2 mutations to cancer development and progression. Finally, we discuss some of the recent advances in developing and testing drugs targeting the PRC2 as well as emerging results from clinical trials using these drugs in the treatment of human cancers.

Oncogenic KRAS Regulates Tumor Cell Signaling via Stromal Reciprocation

Oncogenic mutations regulate signaling within both tumor cells and adjacent stromal cells. Here, we show that oncogenic KRAS (KRAS(G12D)) also regulates tumor cell signaling via stromal cells. By combining cell-specific proteome labeling with multivariate phosphoproteomics, we analyzed heterocellular KRAS(G12D) signaling in pancreatic ductal adenocarcinoma (PDA) cells. Tumor cell KRAS(G12D) engages heterotypic fibroblasts, which subsequently instigate reciprocal signaling in the tumor cells. Reciprocal signaling employs additional kinases and doubles the number of regulated signaling nodes from cell-autonomous KRAS(G12D). Consequently, reciprocal KRAS(G12D) produces a tumor cell phosphoproteome and total proteome that is distinct from cell-autonomous KRAS(G12D) alone. Reciprocal signaling regulates tumor cell proliferation and apoptosis and increases mitochondrial capacity via an IGF1R/AXL-AKT axis. These results demonstrate that oncogene signaling should be viewed as a heterocellular process and that our existing cell-autonomous perspective underrepresents the extent of oncogene signaling in cancer. VIDEO ABSTRACT.

Immunomediated Pan-cancer Regulation Networks are Dominant Fingerprints After Treatment of Cell Lines with Demethylation

Pan-cancer studies are particularly relevant not only for addressing the complexity of the inherently observed heterogeneity but also for identifying clinically relevant features that may be common to the cancer types. Immune system regulations usually reveal synergistic modulation with other cancer mechanisms and in combination provide insights on possible advances in cancer immunotherapies. Network inference is a powerful approach to decipher pan-cancer systems dynamics. The methodology proposed in this study elucidates the impacts of epigenetic treatment on the drivers of complex pan-cancer regulation circuits involving cell lines of five cancer types. These patterns were observed from differential gene expression measurements following demethylation with 5-azacytidine. Networks were built to establish associations of phenotypes at molecular level with cancer hallmarks through both transcriptional and post-transcriptional regulation mechanisms. The most prominent feature that emerges from our integrative network maps, linking pathway landscapes to disease and drug-target associations, refers primarily to a mosaic of immune-system crosslinked influences. Therefore, characteristics initially evidenced in single cancer maps become motifs well summarized by network cores and fingerprints.