Genetic chaos and antichaos in human cancers

Unveil the unseen: Exploit information hidden in noise

Noise and uncertainty are usually the enemy of machine learning, noise in training data leads to uncertainty and inaccuracy in the predictions. However, we develop a machine learning architecture that extracts crucial information out of the noise itself to improve the predictions. The phenomenology computes and then utilizes uncertainty in one target variable to predict a second target variable. We apply this formalism to PbZr0.7Sn0.3O3 crystal, using the uncertainty in dielectric constant to extrapolate heat capacity, correctly predicting a phase transition that otherwise cannot be extrapolated. For the second example – single-particle diffraction of droplets – we utilize the particle count together with its uncertainty to extrapolate the ground truth diffraction amplitude, delivering better predictions than when we utilize only the particle count. Our generic formalism enables the exploitation of uncertainty in machine learning, which has a broad range of applications in the physical sciences and beyond.

Stem Cells in the Tumor Immune Microenvironment -Part of the Cure or Part of the Disease? Ontogeny and Dichotomy of Stem and Immune Cells has Led to better Understanding

Stem cells are at the basis of tissue homeostasis, hematopoiesis and various regenerative processes. Epigenetic changes in their somatically imprinted genes, prolonged exposure to mutagens/carcinogens or alteration of their niche can lead to the development of an enabling environment for tumor growth and progression. The involvement of stem cells in both health and disease becomes even more compelling with ontogeny as embryonic and extraembryonic stem cells which persist into adulthood in well established and specific niche may have distinct implications in tumorigenesis. Immune surveillance plays an important role in this interplay since the response of immune cells toward the oncogenic process can range from reactivity to placidity and even complicity, being orchestrated by intercellular molecular dialogues with the other key players of the tumor microenvironment. With the current understanding that every developing and adult tissue contains inherent stem and progenitor cells, in this manuscript we review the most relevant interactions carried out between the stem cells, tumor cells and immune cells in a bottom-up incursion through the tumor microenvironment beginning from the perivascular niche and going through the tumoral parenchyma and the related stroma. With the exploitation of various factors that influence the behavior of immune effectors toward stem cells and other resting cells in their niche, new therapeutic strategies to tackle the polarization of immune effectors toward a more immunogenic phenotype may arise.

The seen and the unseen: Molecular classification and image based-analysis of gastrointestinal cancers

Gastrointestinal cancers account for 22.5% of cancer related deaths worldwide and represent circa 20% of all cancers. In the last decades, we have witnessed a shift from histology-based to molecular-based classifications using genomic, epigenomic, and transcriptomic data. The molecular based classification revealed new prognostic markers and may aid the therapy selection. Because of the high-costs to perform a molecular classification, in recent years immunohistochemistry-based surrogate classification were developed which permit the stratification of patients, and in parallel multiple groups developed hematoxylin and eosin whole slide image analysis for sub-classifying these entities. Hence, we are witnessing a return to an image-based classification with the purpose to infer hidden information from routine histology images that would permit to detect the patients that respond to specific therapies and would be able to predict their outcome. In this review paper, we will discuss the current histological, molecular, and immunohistochemical classifications of the most common gastrointestinal cancers, gastric adenocarcinoma, and colorectal adenocarcinoma, and will present key aspects for developing a new artificial intelligence aided image-based classification of these malignancies.

On the intrinsic nature of viral pathogenesis: The assumption of a Darwinian paradigm to describe COVID-19 pandemic

Our hypothesis about evolution of the COVID-19 pandemic foresees an inverse relation between infectivity (R0) and lethality (L) of SARS-CoV-2. The above parameters are driven by a continuing mutation process granting the virus a clear survival advantage over virulence. For interpreting this relation we adopted a simple equation, R0 × L ≈ k, by which R0 and L depend upon a constant k, that corresponds to an intrinsic property of the viral species involved. The hypothesis was verified by following changes of the R0 and L terms of the formula in the different variants of SARS-CoV-2 that progressively appeared. A further validation came when the equation was applied to pandemic and epidemic influenza type A viruses, Ebola virus and measles virus. We believe this equation that considers virus biology in Darwinian terms could be extremely useful to better face infectious viral threats and validate virus-host molecular interactions relevant to viral pathogenesis.

Cancer as a form of life: Musings of the cancer and evolution symposium

Advanced cancer is one of the major problems in oncology as currently, despite the recent technological and scientific advancements, the mortality of metastatic disease remains very high at 70-90%. The field of oncology is in urgent need of novel ideas in order to improve quality of life and prognostic of cancer patients. The Cancer and Evolution Symposium organized online October 14-16, 2020 brought together a group of specialists from different fields that presented innovative strategies for better understanding, preventing, diagnosing, and treating cancer. Today still, the main reasons behind the high incidence and mortality of advanced cancer are, on one hand, the paucity of funding and effort directed to cancer prevention and early detection, and, on the other hand, the lack of understanding of the cancer process itself. I argue that besides being a disease, cancer is also a form of life, and, this frame of reference may provide a fresh look on this complex process. Here, I provide a different angle to several contemporary cancer theories discussing them from the perspective of "cancer-forms of life" (i.e. bionts) point of view. The perspectives and the several "bionts" introduced here, by no means exclusive or comprehensive, are just a shorthand that will hopefully encourage the readers, to further explore the contemporary oncology theoretical landscape.

PTRH2: an adhesion regulated molecular switch at the nexus of life, death, and differentiation

Peptidyl-tRNA hydrolase 2 (PTRH2; Bit-1; Bit1) is an underappreciated regulator of adhesion signals and Bcl2 expression. Its key roles in muscle differentiation and integrin-mediated signaling are central to the pathology of a recently identified patient syndrome caused by a cluster of Ptrh2 gene mutations. These loss-of-function mutations were identified in patients presenting with severe deleterious phenotypes of the skeletal muscle, endocrine, and nervous systems resulting in a syndrome called Infantile-onset Multisystem Nervous, Endocrine, and Pancreatic Disease (IMNEPD). In contrast, in cancer PTRH2 is a potential oncogene that promotes malignancy and metastasis. PTRH2 modulates PI3K/AKT and ERK signaling in addition to Bcl2 expression and thereby regulates key cellular processes in response to adhesion including cell survival, growth, and differentiation. In this Review, we discuss the state of the science on this important cell survival, anoikis and differentiation regulator, and opportunities for further investigation and translation. We begin with a brief overview of the structure, regulation, and subcellular localization of PTRH2. We discuss the cluster of gene mutations thus far identified which cause developmental delays and multisystem disease. We then discuss the role of PTRH2 and adhesion in breast, lung, and esophageal cancers focusing on signaling pathways involved in cell survival, cell growth, and cell differentiation.

How Does a Tumor Get Its Shape? MicroRNAs Act as Morphogens at the Cancer Invasion Front

The generation and organization of the invasion front shape of neoplasms is an intriguing problem. The intimate mechanism is not yet understood, but the prevailing theory is that it represents an example of morphogenesis. Morphogenesis requires the presence of specific molecules, known as morphogens (activators and inhibitors), which can diffuse and elicit dose-dependent responses in their target cells. Due to their ability to modulate most of the coding transcriptome, their well-established role in embryogenesis, and their capacity to rapidly move between neighboring and distant cells, we propose microRNAs as inhibitors that could shape the cancer invasion front. In order to explain the genesis of the tumor border, we use Alan Turing’s reaction diffusion model, refined by Meinhardt and Gierer. This assumes the existence of an activator called a, and an inhibitor called h, which we hypothesize could be a freely moving microRNA. We used the fractal dimension as a measure of tumor border irregularity. We observed that the change in fractal dimension associates with variations in the diffusion coefficient of the activator (D_a) or the inhibitor (D_h). We determined that the fractal dimension remains constant (i.e., the irregularity of the tumor border does not change) across a D_h interval, which becomes narrower as D_a rises. We therefore conclude that a change in fractal dimension occurs when the balance between D_a and D_h is disrupted. Biologically, this could be explained by a faulty distribution of the inhibitor caused by an abnormal density of the intercellular connection network. From a translational perspective, if experimentally confirmed, our observations can be used for a better diagnosis of cancer aggressiveness.

Proteomics reveals the importance of the dynamic redistribution of the subcellular location of proteins in breast cancer cells

At the molecular level, living cells are enormously complicated complex adaptive systems in which intertwined genomic, transcriptomic, proteomic and metabolic networks all play a crucial role. At the same time, cells are spatially heterogeneous systems in which subcellular compartmentalization of different functions is ubiquitous and requires efficient cross-compartmental communication. Dynamic redistribution of multitudinous proteins to different subcellular locations in response to cellular functional state is increasingly recognized as a crucial characteristic of cellular function that seems to be at least as important as overall changes in protein abundance. Characterization of the subcellular spatial dynamics of protein distribution is a major challenge for proteomics and recent results with MCF7 breast cancer cells suggest that this may be of particular importance for cancer cells.

Key principles of miRNA involvement in human diseases

Although rapid progress in our understanding of the functions of miRNA has been made by experimentation and computational approach, a considerable effort still has to be done in determining the general principles that govern the miRNA's mode of action in human diseases. We will further discuss how these principles are being progressively approached by molecular studies, as well as the importance of miRNA in regulating different target genes and functions in specific biological contexts. There is a great demand to understand the principles of context - specific miRNA target recognition in order to design future experiments and models of normal developmental and disease states.

MicroRNAs and ceRNAs: therapeutic implications of RNA networks

INTRODUCTION

A new concept of gene regulation, in which competitive endogenous RNAs (ceRNAs) compete for common microRNAs (miRNAs), suggests that mRNA targets have an active role as key elements in the regulation of miRNA availability within cells. ceRNAs are considered to be natural decoys of miRNA activity and can influence the expression of multiple miRNAs.

AREAS COVERED

A new complex network of indirect interaction among the RNA transcripts competing for the same pool of miRNAs has been described; in this network, the nodes are the targets, and the links between the nodes are the miRNAs the targets have in common, which form smaller subnetworks. The incidence, state and severity of cancer can be evaluated on the basis of this network signature. The study of these new genome-scale regulatory networks involving miRNAs and ceRNAs may provide information that researchers can use to fine-tune these networks to improve responses to cancer therapy and/or develop new therapeutic interventions.

EXPERT OPINION

Combinational approaches based on complex regulatory ceRNA networks (ceRNETs) may be one of the most promising strategies for silencing important mediators of cancer-promoting pathways. Targeting a single miRNA may in fact represent a combined intervention that acts on the feedback and compensatory pathways that can impair treatment response or cause treatment resistance.

Spatial chaos and complexity in the intracellular space of cancer and normal cells

Background

One of the most challenging problems in biological image analysis is the quantification of the dynamical mechanism and complexity of the intracellular space. This paper investigates potential spatial chaos and complex behavior of the intracellular space of typical cancer and normal cell images whose structural details are revealed by the combination of scanning electron microscopy and focused ion beam systems. Such numerical quantifications have important implications for computer modeling and simulation of diseases.

Methods

Cancer cell lines derived from a human head and neck squamous cell carcinoma (SCC-61) and normal mouse embryonic fibroblast (MEF) cells produced by focused ion beam scanning electron microscopes were used in this study. Spatial distributions of the organelles of cancer and normal cells can be analyzed at both short range and long range of the bounded dynamical system of the image space, depending on the orientations of the spatial cell. A procedure was designed for calculating the largest Lyapunov exponent, which is an indicator of the potential chaotic behavior in intracellular images. Furthermore, the sample entropy and regularity dimension were applied to measure the complexity of the intracellular images.

Results

Positive values of the largest Lyapunov exponents (LLEs) of the intracellular space of the SCC-61 were obtained in different spatial orientations for both long-range and short-range models, suggesting the chaotic behavior of the cell. The MEF has smaller positive values of LLEs in the long range than those of the SCC-61, and zero vales of the LLEs in the short range analysis, suggesting a non-chaotic behavior. The intracellular space of the SCC-61 is found to be more complex than that of the MEF. The degree of complexity measured in the spatial distribution of the intracellular space in the diagonal direction was found to be approximately twice larger than the complexity measured in the horizontal and vertical directions.

Conclusion

Initial findings are promising for characterizing different types of cells and therefore useful for studying cancer cells in the spatial domain using state-of-the-art imaging technology. The measures of the chaotic behavior and complexity of the spatial cell will help computational biologists gain insights into identifying associations between the oscillation patterns and spatial parameters of cells, and appropriate model for simulating cancer cell signaling networks for cancer treatment and new drug discovery.

Beyond the oncogene paradigm: understanding complexity in cancerogenesis

In the past decades, an enormous amount of precious information has been collected about molecular and genetic characteristics of cancer. This knowledge is mainly based on a reductionistic approach, meanwhile cancer is widely recognized to be a 'system biology disease'. The behavior of complex physiological processes cannot be understood simply by knowing how the parts work in isolation. There is not solely a matter how to integrate all available knowledge in such a way that we can still deal with complexity, but we must be aware that a deeply transformation of the currently accepted oncologic paradigm is urgently needed. We have to think in terms of biological networks: understanding of complex functions may in fact be impossible without taking into consideration influences (rules and constraints) outside of the genome. Systems Biology involves connecting experimental unsupervised multivariate data to mathematical and computational approach than can simulate biologic systems for hypothesis testing or that can account for what it is not known from high-throughput data sets. Metabolomics could establish the requested link between genotype and phenotype, providing informations that ensure an integrated understanding of pathogenic mechanisms and metabolic phenotypes and provide a screening tool for new targeted drug.

Genetic redundancy in human cervical carcinoma cells: identification of cells with "normal" properties

Although it is generally assumed that cancer arises from a singular cell, a tumor must be considered as a dynamic and emergent biological structure, whose organizing principle is determined by genetic and epigenetic modifications, occurring variably in response to microenvironmental selection conditions. As previously shown, HPV-positive cervical carcinoma cells have lost their ability to induce IFN-beta upon TNF-alpha treatment. However, regarding cancer as a non-linear system, which may, even in the absence of an apparent selection pressure, fluctuate between different "metastable" phenotypes, we demonstrate that TNF-alpha mediated IFN-beta induction is not irreversibly disturbed in all cells. Using the IFN-beta sensitive Encephalomyocarditis virus (EMCV) as a tool to monitor antiviral activity in long-term established malignant HeLa cells, rare IFN-beta expressing clones were rescued from a population of non-responsive and EMCV-sensitive cells. Antiviral activity was mediated by the re-expression of IRF-1 and p48 (IRF-9), both key regulatory molecules normally found to be suppressed in cervical carcinoma cells. Upon inoculating of selected clones into immunocompromised animals, a reduced or even an absence of tumorigenicity of initially highly malignant cells could be discerned. These data indicate that both the absence of interferon signaling and the ability to form tumors were reversed in a minority of cells. We provide a paradigm for the existence of innate genetic redundancy mechanisms, where a particular phenotype persists and can be isolated without application of drugs generally changing the epigenetic context.