Cancer as a disorder of patterning information: computational and biophysical perspectives on the cancer problem

Abstract

TOPICAL REVIEWCancer as a disorder of patterning information: computational and biophysical perspectives on the cancer problem IntroductionCancer is well-recognized not only as an extremely pernicious medical problem, but also as a group of phenomena deeply connected to the fundamental questions of evolution, multicellularity, pattern (disregulation, and the interplay between the genome and the environment [1,2]. Two fundamental paradigms currently divide the field. One is that cancer results from disorders of genetics: cancer cells are fundamentally broken due to genomic mutation or instability, and their clonal progeny form tumors and metastases. This view is sometimes called the SMT, somatic mutation theory [3][4][5]. A competing perspective is that of cancer as a circuit disease-a disorder of the complex biophysical, transcriptional, and epigenetic dynamics that regulate cellular state and the ability of cells to cooperate in vivo [6][7][8]. Under this view (sometimes called the tissue organization field theory or TOFT, [9,10]), cancer is akin to a traffic jam [11]-the problem is not a permanent discrete alteration within a founder cell and all of its clonal descendants, but an undesirable stable attractor in the complex network of controls that normally guides anatomical homeostasis [12].The relative merits of the two models have been discussed extensively [10,[13][14][15][16][17] AbstractThe current paradigm views cancer as arising clonally from a degradation of genetic information in single cells. A complementary perspective, originating at the dawn of modern developmental biology, is that cancer is the result of a system disorder of algorithms that normally orchestrate individual cell activities toward specific anatomical structures and away from tumorigenesis. A view of cancer as a disease of geometry focuses on the pathways that allow cells to cooperate to build and maintain large-scale anatomical patterning. Cancer may result when cells stop maintaining higher-order structures and reduce the boundary of their computational selves to a single-cell level, reverting to a unicellular lifestyle in which the rest of the organism is merely part of the environment at the expense of which all living things survive. While this view has been widely discussed, little progress has been made in providing a quantitative, mechanistic framework within which this perspective's specific and unique implications for treatment strategies can be tested and biomedically exploited. Here, we highlight two recent areas of progress which may facilitate much-needed progress on the cancer problem. First, we review the roles that endogenous bioelectrical networks, operating across many tissues in vivo, play as a medium of information processing in tumor suppression, progression, and reprogramming. Second, we provide a primer to the development of computational theory and tools for quantifying the information and causal control structures in cancer and other complex biological systems. Rigorous mathematical formalisms now exist to...

The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

“…The communication that enables cells to join into collectives that make decisions about the growth and form of organ-level structures (i.e., what to sculpt and when to stop) can go awry, resulting in cancer (Chernet and Levin, 2013a;Moore et al, 2017). Despite highly diverse molecular and clinical manifestations, one common aspect points to the key: in carcinogenic transformation (Yamasaki et al, 1995;Ruch and Trosko, 2001), cells become isolated from the physiological signals that bind them into unified networks (the essential role of bioelectricity in this process is discussed in the next section).…”

The Cognitive Lens: a primer on conceptual tools for analysing information processing in developmental and regenerative morphogenesis

“…As a further consequence of its higher-level form, cognition does not require a special organ like the brain (we illustrate this important point in §3f with the help of a learningbased example). Even single cells in a multi-cellular organism [46] or single-celled organisms like bacteria possess basal cognitive capacities [2,9], and interestingly use brain-like bioelectric dynamics [48]. Escherichia coli, for example, has pathways for perception and for adaptation, which enables it to efficiently perform chemotaxis, tolerating a broad range of environmental uncertainty by implementing a memory-based mechanism [9].…”

“…Even single cells in a multi-cellular organism [46] or single-celled organisms like bacteria possess basal cognitive capacities [2,9], and interestingly use brain-like bioelectric dynamics [48]. Escherichia coli, for example, has pathways for perception and for adaptation, which enables it to efficiently perform chemotaxis, tolerating a broad range of environmental uncertainty by implementing a memory-based mechanism [9]. While some authors believe that life is fundamentally cognitive (requiring information processing at the genetic, physiological and behavioural levels to stay alive in a hostile environment), this is not necessarily the case.…”

“…R. Soc. B 374: 20180369 normalization (tumour reprogramming) allows cells to functionally rejoin a metazoan collective [9]. Such dynamic plasticity and anatomical homeostasis (figure 1e) represent clear examples of pattern memory and flexible decisionmaking by cells, tissues and organs: systems-level functions such as recognizing damage, building exactly what is needed in the right location, and ceasing activity when the correct target morphology is achieved [2].…”

Post-SSRI Sexual Dysfunction: A Bioelectric Mechanism?

“…[12][13][14] Recent work in this field has revealed the importance of bioelectric networks not only in embryogenesis but also in adult regeneration, stem cell biology, cancer, and immune system function. [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] Importantly, recent computational models predicted that some bioelectric circuits exhibit a kind of memory, in which induced changes of V mem are actively maintained. [28][29][30][31] Research in model systems, such as regenerative planarian flatworms (an important model for human neurophysiology and pharmacology [32][33][34][35][36][37] ), has revealed a remarkable longterm memory that can be induced by alterations to endogenous ion flows.…”