The article begins with observations that sit uneasily with a strictly mutation-centered account. The same mutations can be found in tumor tissue and surrounding healthy tissue, while healthy tissue may contain thousands of mutations involving cancer-related genes. Some pediatric malignancies show few or no detectable mutations, and malignant cells can sometimes return to an ordered, nonmalignant phenotype when their three-dimensional context is restored. Hanselmann does not claim that mutations lack causal importance. Instead, he interprets this evidence as a reason to regard somatic mutation theory as a context-limited generalization rather than a universal law, while maintaining that discoveries involving oncogenes, tumor suppressor genes and signaling pathways remain indispensable to cancer research.

At the center of the proposal is a systemic definition of the cell: a structurally distinct, heterogeneous and self-sustaining whole that operates far from thermodynamic equilibrium. It continuously exchanges matter and energy, maintains ordered structures, responds to stimuli, transports materials, proliferates and adapts its phenotype to its environment. Drawing on general systems theory, Hanselmann argues that changes in individual components, including genes, influence but do not fully determine cellular behavior. The resulting behavior is an emergent property of the interacting system. This framing treats the cell as a hierarchy of feedback-controlled subsystems whose collective organization can constrain and redirect the behavior of individual parts.

EMMI provides four access points for examining this totality of molecular interactions. Energy covers ATP production, localization and the work sustained by metabolism. Matter/Milieu includes intracellular and extracellular electrolytes, metabolites, oxygen, pH, nutrients and other molecular constituents, together with conditions exchanged across the cell membrane. Mechanics/Structure encompasses morphology, the cytoskeleton, organelles, membranes, cell-cell adhesion and the extracellular matrix. Information includes DNA, RNA, proteins, lipids and metabolites insofar as they carry regulatory information or signal through the cellular network. These domains are not independent compartments: a disturbance in one can alter the others. Hypoxia illustrates this coupling by reducing ATP production, changing intracellular metabolites and pH, remodeling the cytoskeleton and extracellular matrix, and activating hypoxia-responsive gene expression.

Several familiar cancer mechanisms fit within the multidimensional framework, but their roles are reinterpreted. The Warburg effect—preferential use of aerobic glycolysis even when sufficient oxygen is available—is presented as a shift in cellular energy handling that can affect metabolism, protein homeostasis, the intracellular environment and mechanical properties. Chronic inflammation is described as a persistent alteration of the tissue environment that can influence differentiation and malignant transformation without necessarily involving a directly mutagenic agent. Mechanical context is also treated as an active control variable. Experiments cited in the paper found that aggressive breast cancer cells could regain more ordered, nonmalignant behavior in a suitable three-dimensional environment, while tumor cells cultured on soft substrates or suitable gels could differentiate and display more normal proliferation. These observations support context sensitivity, but they do not establish that mechanics alone causes cancer.

The framework gives particular attention to the fact that the same molecule can matter in different ways. ATP is assigned primarily to Energy, yet at physiological intracellular concentrations it can also act as an aggregation inhibitor that supports protein solubility, making it relevant to Matter/Milieu. The tumor suppressor p53 is associated with genetic information and repair while also influencing mitochondrial energy metabolism, autophagy and redox balance. The extracellular matrix acts as a mechanical environment while also storing growth factors and signaling molecules, and it can influence pH through electrostatic effects. Hanselmann describes these assignments as context-dependent and deliberately non-orthogonal. Multiple classification is not evidence of imprecision in his model, but a reflection of biological contingency; an assignment valid in every tissue and cellular state would misrepresent the systems being studied.

Self-organization is a central concept, illustrated in the article by the reconstitution of cellular structures in homogenized Xenopus oocytes. Rather than treating organized structure as an exceptional event, the paper presents it as a basal feature of living systems. In this view, the presence of particular mutations cannot by itself account for cancer because tumor formation requires a shift in the attractor, or stable state, of the cellular network. Emergence helps explain why populations of cancer cells collectively migrate, resist chemotherapeutic agents, induce angiogenesis and evade immunity in ways that individual cells do not. Intratumoral heterogeneity is similarly treated as an expression of systemic dynamics involving stochastic gene expression, epigenetic diversification, environmental feedback and nonlinear responses. The framework is intended to clarify possible mechanisms behind collective tumor behavior, but the article does not present EMMI as a quantitative theory that predicts individual clinical outcomes.

Complexity is also reflected in nonlinear dynamics, variability, robustness, contingency and convergence. Cellular regulatory networks contain feedback loops operating across markedly different time scales, from rapid ion-channel activity to slower changes in gene expression. Such systems can switch abruptly between stable states, while relatively small perturbations can have disproportionate effects in highly interconnected networks. At the same time, cells and tissues maintain function through redundancy, modularity and alternative pathways, which helps explain why some targeted interventions can be absorbed by network reorganization. Contingency introduces the cell’s developmental, division and environmental history, while convergence describes how cells with different genetic origins can acquire similar metabolic, proliferative or invasive states when placed in the same context. Examples discussed include the different consequences of KRAS mutations in pancreatic and colorectal cancers, and NOTCH signaling that is oncogenic in some tissues but tumor-suppressive in others.

Hanselmann proposes three levels of contingency to distinguish possible context effects. Weight contingency means that a molecular node retains its function and direction of effect but contributes with different strength in different settings. Sign contingency means that the same molecular state promotes a malignant phenotype in one context but counteracts it in another. Category contingency means that a molecule performs a qualitatively different function and therefore belongs primarily to a different EMMI domain, as cytochrome c does when it transports electrons in the mitochondrial respiratory chain but contributes to apoptosome formation after release into the cytosol. The author cautions that category changes should be admitted only when an experimentally documented functional switch exists, preventing the framework from becoming unfalsifiable through convenient relabeling. These levels are proposed as a heuristic systematics, not as an established biological classification.

The paper ultimately recasts somatic mutation theory as a “pragmatic law”: a biological regularity that provides useful explanations and predictions within defined contexts without claiming exceptionless validity. Its philosophical foundation is Sandra Mitchell’s concept of integrative pluralism, according to which complex biological phenomena require complementary explanatory levels rather than either strict reductionism or disconnected perspectives. To make EMMI operational, a researcher would define an emergent readout, such as a change in differentiation state or DNA content, specify parameters from each EMMI variable, perturb one variable and measure the others alongside the readout. This approach could test how energy, environment, mechanics and information are coupled under controlled conditions. The article remains explicitly conceptual: EMMI is not a topological model, makes no claim about network degree distributions, predicts no power-law exponents and permits no quantitative network-analytic derivations. Its proposed value is methodological—a structured way to ask which contextual mechanisms may determine cancer development rather than merely accompany it.

Subject of Research: A conceptual systems-complexity framework for cancer as a context-dependent cellular state

Article Title: Origin of cancer: what is a (cancer) cell? A systems-complexity perspective – principles of cellular systems [part 1]

Article References: Hanselmann, R. G. (2026). Origin of cancer: what is a (cancer) cell? A systems-complexity perspective – principles of cellular systems [part 1]. Frontiers in Cell and Developmental Biology, 14, Article 1936518. https://doi.org/10.3389/fcell.2026.1936518

Image Credits: AI Generated

DOI: 10.3389/fcell.2026.1936518

Keywords: cancer biology, cellular systems, EMMI model, carcinogenesis, genetic mutations, tumor microenvironment, systemic oncology, emergence, contingency, integrative pluralism, Origin, cancer