Are the somatic mutation and tissue organization field theories of carcinogenesis incompatible?

Critically assessing atavism, an evolution-centered and deterministic hypothesis on cancer

Cancer is most commonly viewed as resulting from somatic mutations enhancing proliferation and invasion. Some hypotheses further propose that these new capacities reveal a breakdown of multicellularity allowing cancer cells to escape proliferation and cooperation control mechanisms that were implemented during evolution of multicellularity. Here we critically review one such hypothesis, named "atavism," which puts forward the idea that cancer results from the re-expression of normally repressed genes forming a program, or toolbox, inherited from unicellular or simple multicellular ancestors. This hypothesis places cancer in an interesting evolutionary perspective that has not been widely explored and deserves attention. Thinking about cancer within an evolutionary framework, especially the major transitions to multicellularity, offers particularly promising perspectives. It is therefore of the utmost important to analyze why one approach that tries to achieve this aim, the atavism hypothesis, has not so far emerged as a major theory on cancer. We outline the features of the atavism hypothesis that, would benefit from clarification and, if possible, unification.

Initiation of Cancer: The Journey From Mutations in Somatic Cells to Epigenetic Changes in Tissue-resident VSELs

Multiple theories exist to explain cancer initiation, although a consensus on this is crucial for developing effective therapies. 'Somatic mutation theory' suggests that mutations in somatic cells during DNA repair initiates cancer but this concept has several attached paradoxes. Research efforts to identify quiescent cancer stem cells (CSCs) that survive therapy and result in metastasis and recurrence have remained futile. In solid cancers, CSCs are suggested to appear during epithelial-mesenchymal transition by the dedifferentiation and reprogramming of epithelial cells. Pluripotent and quiescent very small embryonic-like stem cells (VSELs) exist in multiple tissues but remain elusive owing to their small size and scarce nature. VSELs are developmentally connected to primordial germ cells, undergo rare, asymmetrical cell divisions and are responsible for the regular turnover of cells to maintain tissue homeostasis throughout life. VSELs are directly vulnerable to extrinsic endocrine insults because they express gonadal and gonadotropin hormone receptors. VSELs undergo epigenetic changes due to endocrine insults and transform into CSCs. CSCs exhibit genomic instability and develop mutations due to errors during DNA replication while undergoing excessive proliferation and clonal expansion to form spheroids. Thus tissue-resident VSELs offer a connection between extrinsic insults and variations in cancer incidence reported in various body tissues. To conclude, cancer is indeed a stem cell disease with mutations occurring as a consequence. In addition to immunotherapy, targeting mutations, and Lgr5 + organoids for developing new therapeutics, targeting CSCs (epigenetically altered VSELs) by improving their niche and epigenetic status could serve as a promising strategy to treat cancer.

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).

Towards in-vivo label-free detection of brain tumor margins with epi-illumination tomographic quantitative phase imaging

Brain tumor surgery involves a delicate balance between maximizing the extent of tumor resection while minimizing damage to healthy brain tissue that is vital for neurological function. However, differentiating between tumor, particularly infiltrative disease, and healthy brain in-vivo remains a significant clinical challenge. Here we demonstrate that quantitative oblique back illumination microscopy (qOBM)-a novel label-free optical imaging technique that achieves tomographic quantitative phase imaging in thick scattering samples-clearly differentiates between healthy brain tissue and tumor, including infiltrative disease. Data from a bulk and infiltrative brain tumor animal model show that qOBM enables quantitative phase imaging of thick fresh brain tissues with remarkable cellular and subcellular detail that closely resembles histopathology using hematoxylin and eosin (H&E) stained fixed tissue sections, the gold standard for cancer detection. Quantitative biophysical features are also extracted from qOBM which yield robust surrogate biomarkers of disease that enable (1) automated tumor and margin detection with high sensitivity and specificity and (2) facile visualization of tumor regions. Finally, we develop a low-cost, flexible, fiber-based handheld qOBM device which brings this technology one step closer to in-vivo clinical use. This work has significant implications for guiding neurosurgery by paving the way for a tool that delivers real-time, label-free, in-vivo brain tumor margin detection.

Over a century of cancer research: Inconvenient truths and promising leads

Despite over a century of intensive efforts, the great gains promised by the War on Cancer nearly 50 years ago have not materialized. Since 1999, we have analyzed the lack of progress in explaining and "curing" cancer by examining the merits of the premises that determine how cancer is understood and treated. Our ongoing critical analyses have aimed at clarifying the sources of misunderstandings at the root of the cancer puzzle while providing a plausible and comprehensive biomedical perspective as well as a new theory of carcinogenesis that is compatible with evolutionary theory. In this essay, we explain how this new theory, the tissue organization field theory (TOFT), can help chart a path to progress for cancer researchers by explaining features of cancer that remain unexplainable from the perspective of the still hegemonic somatic mutation theory (SMT) and its variants. Of equal significance, the premises underlying the TOFT offer new perspectives on basic biological phenomena.

Process analysis of carcinogenesis: concept derivation of the tissue function "preservation of a homogeneous gene expression"

A new system for maintaining homogeneous gene expression in tissue and for destroying through apoptosis nonconforming cells is introduced. This functionality is called the "similarity comparison." Accordingly, the survival of mutated cells is hindered due to reduced gene expression. That, in turn, maintains the homogeneity of the tissue and prevents tumors from developing. The concept of the similarity comparison is that every stationary cell in every tissue constantly screens the gene expression of its neighbors. Cells process the signals, and when the difference between neighbors exceeds some threshold, a signal is triggered. An under-expressing cell then either increases its gene expression or apoptosis occurs. The oversight role of the similarity comparison can, under certain conditions, be disrupted, such that mutated cells in the tissue can survive. This is possible only when surrounding normal cells exhibit reduced gene expression. In this case, the normal cells and mutated cells have similar gene expression, and the signal for apoptosis is not triggered. The mutated cells survive, and a tumor can develop. The importance of the similarity comparison as an oversight mechanism is studied. Examples are considered.

An Emergence Framework of Carcinogenesis

Experimental paradigms provide the framework for the understanding of cancer, and drive research and treatment, but are rarely considered by clinicians. The somatic mutation theory (SMT), in which cancer is considered a genetic disease, has been the predominant traditional model of cancer for over 50 years. More recently, alternative theories have been proposed, such as tissue organization field theory (TOFT), evolutionary models, and inflammatory models. Key concepts within the various models have led to them being difficult to reconcile. Progressively, it has been recognized that biological systems cannot be fully explained by the physicochemical properties of their constituent parts. There is an increasing call for a 'systems' approach. Incorporating the concepts of 'emergence', 'systems', 'thermodynamics', and 'chaos', a single integrated framework for carcinogenesis has been developed, enabling existing theories to become compatible as alternative mechanisms, facilitating the integration of bioinformatics and providing a structure in which translational research can flow from both 'benchtop to bedside' and 'bedside to benchtop'. In this review, a basic understanding of the key concepts of 'emergence', 'systems', 'system levels', 'complexity', 'thermodynamics', 'entropy', 'chaos', and 'fractals' is provided. Non-linear mathematical equations are included where possible to demonstrate compatibility with bioinformatics. Twelve principles that define the 'emergence framework of carcinogenesis' are developed, with principles 1-10 encapsulating the key concepts upon which the framework is built and their application to carcinogenesis. Principle 11 relates the framework to cancer progression. Principle 12 relates to the application of the framework to translational research. The 'emergence framework of carcinogenesis' collates current paradigms, concepts, and evidence around carcinogenesis into a single framework that incorporates previously incompatible viewpoints and ideas. Any researcher, scientist, or clinician involved in research, treatment, or prevention of cancer can employ this framework.

Holistic paradigm in carcinogenesis: Genetics, epigenetics, immunity, inflammation and oral infections

Recent debate among the experts of cancer research regarding the main causes of carcinogenesis encouraged us to review the etiology of cancer pathogenesis. The somatic mutation theory attributes carcinogenesis to random errors in DNA multiplication while the tissue organization field theory ascribes causation to environmental factors. We recognize complexity in cancer pathogenesis and accept the premise of both DNA multiplication errors and environmental factors in cancer development. Furthermore, it should also be noted that the combination of these factors and the relative importance of the each differ in various types of cancers. For example, in some cancers, genetics plays a prominent role while in others environment such as obesity plays a much stronger role. Additionally, the cancer mitigating factors should also be considered. The balance of cancer-enhancing and cancer-suppressing forces determines the cancer incidence. Ultimately, identifying the lifestyle factors that revise somatic mutations or epigenetic alterations will lead to a clear understanding of pathogenic mechanisms of cancer and to the optimal preventive strategies. This narrative review evaluates the published evidence on carcinogenesis pertaining to the whole organism (thus, holistic) incorporating genetics, epigenetics, immunology, inflammation and infections with emphasis on oral infections.

Weakly coupled map lattice models for multicellular patterning and collective normalization of abnormal single-cell states

We present a weakly coupled map lattice model for patterning that explores the effects exerted by weakening the local dynamic rules on model biological and artificial networks composed of two-state building blocks (cells). To this end, we use two cellular automata models based on (i) a smooth majority rule (model I) and (ii) a set of rules similar to those of Conway's Game of Life (model II). The normal and abnormal cell states evolve according to local rules that are modulated by a parameter κ. This parameter quantifies the effective weakening of the prescribed rules due to the limited coupling of each cell to its neighborhood and can be experimentally controlled by appropriate external agents. The emergent spatiotemporal maps of single-cell states should be of significance for positional information processes as well as for intercellular communication in tumorigenesis, where the collective normalization of abnormal single-cell states by a predominantly normal neighborhood may be crucial.

SMT and TOFT Integrable After All: A Reply to Bizzarri and Cucina

In a previous paper recently published in this journal, we argue that the two main theories of carcinogenesis (SMT and TOFT) should be considered as compatible, at the metaphysical, epistemological and biological levels. In a reply to our contribution, Bizzarri and Cucina claim we are wrong since SMT and TOFT are opposite and incompatible paradigms. Here, we show that their arguments are not satisfactory. Indeed, the authors go through the same mistakes that we already addressed. In particular, they confuse reductionism, as an ontological frame, and genetic determinism, as a causal pathway. Beside, they make an inadequate use of the Kuhnian notion of paradigm shift. Finally, we confirm our previous conclusion: there is no strong argument to totally abandon the somatic mutation theory. It describes a partial causal pathway, compatible with the one proposed by TOFT.

Insulin-like growth factor (IGF) axis in cancerogenesis

Determination of the role of insulin-like growth factor (IGF) family components in carcinogenesis of several human tumors is based on numerous epidemiological and pre-clinical studies, experiments in vivo and in vitro and on attempts at application of drugs affecting the IGF axis. Investigative hypotheses in original studies were based on biological functions manifested by the entire family of IGF (ligands, receptors, linking proteins, adaptor molecules). In the context of carcinogenesis the most important functions of IGF family involve intensification of proliferation and inhibition of cell apoptosis and effect on cell transformation through synthesis of several regulatory proteins. IGF axis controls survival and influences on metastases of cells. Interactions of IGF axis components may be of a direct or indirect nature. The direct effects are linked to activation of PI3K/Akt signaling pathway, in which the initiating role is first of all played by IGF-1 and IGF-1R. Activity of this signaling pathway leads to an increased mitogenesis, cell cycle progression, and protection against different apoptotic stresses. Indirect effects of the axis depend on interactions between IGF and other molecules important for cancer etiology (e.g. sex hormones, products of suppressor genes, viruses, and other GFs) and the style of life (nutrition, physical activity). From the clinical point of view, components of IGF system are first of all considered as diagnostic serous and/or tissue biomarkers of a given cancer, prognostic factors and attractive target of modern anti-tumor therapies. Several mechanisms in which IGF system components act in the process of carcinogenesis need to be clarified, mainly due to multifactorial etiology of the neoplasms. Pin-pointing of the role played in carcinogenesis by any single signaling pathway remains particularly difficult. The aim of this review is to summarize the current data of several epidemiological studies, experiments in vitro and on animal models, to increase our understanding of the complex role of IGF family components in the most common human cancers.

SMT and TOFT: Why and How They are Opposite and Incompatible Paradigms

The Somatic Mutation Theory (SMT) has been challenged on its fundamentals by the Tissue Organization Field Theory of Carcinogenesis (TOFT). However, a recent publication has questioned whether TOFT could be a valid alternative theory of carcinogenesis to that presented by SMT. Herein we critically review arguments supporting the irreducible opposition between the two theoretical approaches by highlighting differences regarding the philosophical, methodological and experimental approaches on which they respectively rely. We conclude that SMT has not explained carcinogenesis due to severe epistemological and empirical shortcomings, while TOFT is gaining momentum. The main issue is actually to submit SMT to rigorous testing. This concern includes the imperatives to seek evidence for disproving one's hypothesis, and to consider the whole, and not just selective evidence.

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.

Genomics, microRNA, epigenetics, and proteomics for future diagnosis, treatment and monitoring response in upper GI cancers

One major objective for our evolving understanding in the treatment of cancers will be to address how a combination of diagnosis and treatment strategies can be used to integrate patient and tumor variables with an outcome-oriented approach. Such an approach, in a multimodal therapy setting, could identify those patients (1) who should undergo a defined treatment (personalized therapy) (2) in whom modifications of the multimodal therapy due to observed responses might lead to an improvement of the response and/or prognosis (individualized therapy), (3) who might not benefit from a particular toxic treatment regimen, and (4) who could be identified early on and thereby be spared the morbidity associated with such treatments. These strategies could lead in the direction of precision medicine and there is hope of integrating translational molecular data to improve cancer classifications. In order to achieve these goals, it is necessary to understand the key issues in different aspects of biotechnology to anticipate future directions of personalized and individualized diagnosis and multimodal treatment strategies. Providing an overview of translational data in cancers proved to be a challenge as different methods and techniques used to obtain molecular data are used and studies are based on different tumor entities with different tumor biology and prognoses as well as vastly different therapeutic approaches. The pros and cons of the available methodologies and the potential response data in genomics, microRNA, epigenetics and proteomics with a focus on upper gastrointestinal cancers are considered herein to allow for an understanding of where these technologies stand with respect to cancer diagnosis, prognosis and treatment.

The hallmarks of premalignant conditions: a molecular basis for cancer prevention

The hallmarks of premalignant lesions were first described in the 1970s, a time when relatively little was known about the molecular underpinnings of cancer. Yet it was clear there must be opportunities to intervene early in carcinogenesis. A vast array of molecular information has since been uncovered, with much of this stemming from studies of existing cancer or cancer models. Here, examples of how an understanding of cancer biology has informed cancer prevention studies are highlighted and emerging areas that may have implications for the field of cancer prevention research are described. A note of caution accompanies these examples, in that while there are similarities, there are also fundamental differences between the biology of premalignant lesions or premalignant conditions and invasive cancer. These differences must be kept in mind, and indeed leveraged, when exploring potential cancer prevention measures.

Exome sequencing of a colorectal cancer family reveals shared mutation pattern and predisposition circuitry along tumor pathways

The molecular basis of cancer and cancer multiple phenotypes are not yet fully understood. Next Generation Sequencing promises new insight into the role of genetic interactions in shaping the complexity of cancer. Aiming to outline the differences in mutation patterns between familial colorectal cancer cases and controls we analyzed whole exomes of cancer tissues and control samples from an extended colorectal cancer pedigree, providing one of the first data sets of exome sequencing of cancer in an African population against a background of large effective size typically with excess of variants. Tumors showed hMSH2 loss of function SNV consistent with Lynch syndrome. Sets of genes harboring insertions-deletions in tumor tissues revealed, however, significant GO enrichment, a feature that was not seen in control samples, suggesting that ordered insertions-deletions are central to tumorigenesis in this type of cancer. Network analysis identified multiple hub genes of centrality. ELAVL1/HuR showed remarkable centrality, interacting specially with genes harboring non-synonymous SNVs thus reinforcing the proposition of targeted mutagenesis in cancer pathways. A likely explanation to such mutation pattern is DNA/RNA editing, suggested here by nucleotide transition-to-transversion ratio that significantly departed from expected values (p-value 5e-6). NFKB1 also showed significant centrality along with ELAVL1, raising the suspicion of viral etiology given the known interaction between oncogenic viruses and these proteins.

SMT or TOFT? How the two main theories of carcinogenesis are made (artificially) incompatible

The building of a global model of carcinogenesis is one of modern biology's greatest challenges. The traditional somatic mutation theory (SMT) is now supplemented by a new approach, called the Tissue Organization Field Theory (TOFT). According to TOFT, the original source of cancer is loss of tissue organization rather than genetic mutations. In this paper, we study the argumentative strategy used by the advocates of TOFT to impose their view. In particular, we criticize their claim of incompatibility used to justify the necessity to definitively reject SMT. First, we note that since it is difficult to build a non-ambiguous experimental demonstration of the superiority of TOFT, its partisans add epistemological and metaphysical arguments to the debate. This argumentative strategy allows them to defend the necessity of a paradigm shift, with TOFT superseding SMT. To do so, they introduce a notion of incompatibility, which they actually use as the Kuhnian notion of incommensurability. To justify this so-called incompatibility between the two theories of cancer, they move the debate to a metaphysical ground by assimilating the controversy to a fundamental opposition between reductionism and organicism. We show here that this argumentative strategy is specious, because it does not demonstrate clearly that TOFT is an organicist theory. Since it shares with SMT its vocabulary, its ontology and its methodology, it appears that a claim of incompatibility based on this metaphysical plan is not fully justified in the present state of the debate. We conclude that it is more cogent to argue that the two theories are compatible, both biologically and metaphysically. We propose to consider that TOFT and SMT describe two distinct and compatible causal pathways to carcinogenesis. This view is coherent with the existence of integrative approaches, and suggests that they have a higher epistemic value than the two theories taken separately.

Multilevel modeling and value of information in clinical trial decision support

Background

Clinical trials are the main method for evaluating safety and efficacy of medical interventions and have produced many advances in improving human health. The Women’s Health Initiative overturned a half-century of harmful practice in hormone therapy, the National Lung Screening Trial identified the first successful lung cancer screening tool and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial overturned decades-long assumptions. While some trials identify unforeseen safety issues or harms, many fail to demonstrate efficacy. Large trials require substantial resources; to ensure reliable outcomes, we must seek ways to improve the predictive information used as the basis of trials.

Results

Here we demonstrate a modeling framework for linking knowledge of underlying biological mechanism to evaluate the expectation of trial outcomes. Key features include the ability to propagate uncertainty in biological mechanism to uncertainty in trial outcome and mechanisms for identifying knowledge gaps most responsible for unexpected outcomes. The framework was used to model the effect of selenium supplementation for prostate cancer prevention and parallels the Selenium and Vitamin E Cancer Prevention Trial that showed no efficacy despite suggestive data from secondary endpoints in the Nutritional Prevention of Cancer trial and found increased incidence of high-grade prostate cancer in certain subgroups.

Conclusion

Using machine learning methods, we identified the parameters of the model that are most predictive of trial outcome and found that the top four are directly related to the rates of reactions producing methylselenol and transporting extracellular selenium into the cell as selenide. This modeling process demonstrates how the approach can be used in advance of a large clinical trial to identify the best targets for conducting further research to reduce the uncertainty in the trial outcome.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-014-0140-0) contains supplementary material, which is available to authorized users.

Epistemology of the origin of cancer: a new paradigm

Background

Carcinogenesis is widely thought to originate from somatic mutations and an inhibition of growth suppressors, followed by cell proliferation, tissue invasion, and risk of metastasis. Fewer than 10% of all cancers are hereditary; the ratio in gastric (1%), colorectal (3-5%) and breast (8%) cancers is even less. Cancers caused by infection are thought to constitute some 15% of the non-hereditary cancers. Those remaining, 70 to 80%, are called “sporadic,” because they are essentially of unknown etiology. We propose a new paradigm for the origin of the majority of cancers.

Presentation of hypothesis

Our paradigm postulates that cancer originates following a sequence of events that include (1) a pathogenic stimulus (biological or chemical) followed by (2) chronic inflammation, from which develops (3) fibrosis with associated changes in the cellular microenvironment. From these changes a (4) pre-cancerous niche develops, which triggers the deployment of (5) a chronic stress escape strategy, and when this fails to resolve, (6) a transition of a normal cell to a cancer cell occurs. If we are correct, this paradigm would suggest that the majority of the findings in cancer genetics so far reported are either late events or are epiphenomena that occur after the appearance of the pre-cancerous niche.

Testing the hypothesis

If, based on experimental and clinical findings presented here, this hypothesis is plausible, then the majority of findings in the genetics of cancer so far reported in the literature are late events or epiphenomena that could have occurred after the development of a PCN. Our model would make clear the need to establish preventive measures long before a cancer becomes clinically apparent. Future research should focus on the intermediate steps of our proposed sequence of events, which will enhance our understanding of the nature of carcinogenesis. Findings on inflammation and fibrosis would be given their warranted importance, with research in anticancer therapies focusing on suppressing the PCN state with very early intervention to detect and quantify any subclinical inflammatory change and to treat all levels of chronic inflammation and prevent fibrotic changes, and so avoid the transition from a normal cell to a cancer cell.

Implication of the hypothesis

The paradigm proposed here, if proven, spells out a sequence of steps, one or more of which could be interdicted or modulated early in carcinogenesis to prevent or, at a minimum, slow down the progression of many cancers.