Evolution and cancer: a mathematical biology approach

Part II: A new perspective for modeling the bone remodeling process: Biology, mechanics, and pathologies

In this paper, we explore the effects of biological (pathological) and mechanical damage on bone tissue within a benchmark model. Using the Finite Element Methodology, we analyze and numerically test the model's components, capabilities, and performance under physiologically and pathologically relevant conditions. Our findings demonstrate the model's effectiveness in simulating bone remodeling processes and self-repair mechanisms for micro-damage induced by biological internal conditions and mechanical external ones within bone tissue. This article is the second part of a series, where the first part presented the mathematical model and the biological and physical significance of the terms used in a simplified benchmark model. It explored the bone remodeling model's application, implementation, and results under physiological conditions.

A coupled mathematical model between bone remodeling and tumors: a study of different scenarios using Komarova's model

This paper aims to construct a general framework of coupling tumor-bone remodeling processes in order to produce plausible outcomes of the effects of tumors on the number of osteoclasts, osteoblasts, and the frequency of the bone turnover cycle. In this document, Komarova's model has been extended to include the effect of tumors on the bone remodeling processes. Thus, we explored three alternatives for coupling tumor presence into Komarova's model: first, using a "damage" parameter that depends on the tumor cell concentration. A second model follows the original structure of Komarova, including the tumor presence in those equations powered up to a new parameter, called the paracrine effect of the tumor on osteoclasts and osteoblasts; the last model is replicated from Ayati and collaborators in which the impact of the tumor is included into the paracrine parameters. Through the models, we studied their stability and considered some examples that can reproduce the tumor effects seen in clinic and experimentally. Therefore, this paper has three parts: the exposition of the three models, the results and discussion (where we explore some aspects and examples of the solution of the models), and the conclusion.

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.

Small non-coding RNAs as regulators of structural evolution and carcinogenesis

Small non-coding RNAs (sncRNAs) are part of non-coding oligonucleotide regulators with wide physiologic and morphologic functions. They control genetic programing of cells, and may modulate processes of differentiation and death. Biogenesis of sncRNAs is now known, and some sncRNAs have been proposed as markers of malignization. Epigenetic therapy is based on the use of newly discovered genetic modifiers, such as sncRNAs, micro-RNAs, and theirs mimics. However, role of sncRNAs in structural evolution and mechanisms of adaptation is not clearly understood. Certainly, non-coding RNAs participate in processes of cellular and organismal adaptation as well as cellular and tissue structural transformation as response to changing of environmental neighbouring. Investigations into these functions of sncRNAs may be the basis of future epigenetic environmental medicine.

Sensing risk, fearing uncertainty: systems science approach to change

Background: Medicine devotes its primary focus to understanding change, from cells to network relationships; observations of non-linearity are inescapable. Recent events provide extraordinary examples of major non-linear surprises within the societal system: human genome-from anticipated 100,000+ genes to only 20,000+; junk DNA-initially ignored but now proven to control genetic processes; economic reversals-bursting of bubbles in technology, housing, finance; foreign wars; relentless rise in obesity, neurodegenerative diseases. There are two attributes of systems science that are especially relevant to this research: One—it offers a method for creating a structural context with a guiding path to pragmatic knowledge; and, two—it gives pre-eminence to sensory input capable to register, evaluate, and react to change.

Materials/Methods: Public domain records of change, during the last 50 years, have been studied in the context of systems science, the dynamic systems model, and various cycles.

Results/Conclusions:Change is dynamic, ever-present, never isolated, and of variable impact; it reflects innumerable relationships among contextual systems; change can be perceived as risk or uncertainty depending upon how the assessment is made; risk is quantifiable by sensory input and generates a degree of rational optimism; uncertainty is not quantifiable and evokes fear; trust is key to sharing risk; the measurable financial credit can be a proxy for societal trust; expanding credit dilutes trust; when a credit bubble bursts, so will trust; absence of trust paralyzes systems' relationships leading to disorganized complexity which prevents value creation and heightens the probability of random events; disappearance of value, accompanied by chaos, threatens all systems. From personal health to economic sustainability and collective rationality, most examined components of the societal system were found not to be optimized and trust was not in evidence.

TrAp: a tree approach for fingerprinting subclonal tumor composition

Revealing the clonal composition of a single tumor is essential for identifying cell subpopulations with metastatic potential in primary tumors or with resistance to therapies in metastatic tumors. Sequencing technologies provide only an overview of the aggregate of numerous cells. Computational approaches to de-mix a collective signal composed of the aberrations of a mixed cell population of a tumor sample into its individual components are not available. We propose an evolutionary framework for deconvolving data from a single genome-wide experiment to infer the composition, abundance and evolutionary paths of the underlying cell subpopulations of a tumor. We have developed an algorithm (TrAp) for solving this mixture problem. In silico analyses show that TrAp correctly deconvolves mixed subpopulations when the number of subpopulations and the measurement errors are moderate. We demonstrate the applicability of the method using tumor karyotypes and somatic hypermutation data sets. We applied TrAp to Exome-Seq experiment of a renal cell carcinoma tumor sample and compared the mutational profile of the inferred subpopulations to the mutational profiles of single cells of the same tumor. Finally, we deconvolve sequencing data from eight acute myeloid leukemia patients and three distinct metastases of one melanoma patient to exhibit the evolutionary relationships of their subpopulations.

Quantum biology at the cellular level--elements of the research program

Quantum biology is emerging as a new field at the intersection between fundamental physics and biology, promising novel insights into the nature and origin of biological order. We discuss several elements of QBCL (quantum biology at cellular level) - a research program designed to extend the reach of quantum concepts to higher than molecular levels of biological organization. We propose a new general way to address the issue of environmentally induced decoherence and macroscopic superpositions in biological systems, emphasizing the 'basis-dependent' nature of these concepts. We introduce the notion of 'formal superposition' and distinguish it from that of Schroedinger's cat (i.e., a superposition of macroscopically distinct states). Whereas the latter notion presents a genuine foundational problem, the former one contradicts neither common sense nor observation, and may be used to describe cellular 'decision-making' and adaptation. We stress that the interpretation of the notion of 'formal superposition' should involve non-classical correlations between molecular events in a cell. Further, we describe how better understanding of the physics of Life can shed new light on the mechanism driving evolutionary adaptation (viz., 'Basis-Dependent Selection', BDS). Experimental tests of BDS and the potential role of synthetic biology in closing the 'evolvability mechanism' loophole are also discussed.