City Research Online

Abstract

The immune system encounters innumerable cells every day and must decide whether these cells are healthy and thus must be tolerated, or are malignant and thus must be eliminated. These decisions are made from imperfect molecular signals in a complex, noisy environment. Errors in classification may lead to diseases such as cancer and autoimmunity. In this paper, we use ideas from cancer biosemiotics and signal detection theory to formalize this notion and show that cancer and autoimmunity are two sides of the same semiotic corruption problem, rather than separate pathologies. We show how biological factors such as noise, aging, deceptive signaling, and chronic inflammation all converge on reducing the discriminability of the immune system. Using this framework, we make two clinical predictions that are consistent with results from randomized clinical trials: 1) checkpoint inhibitors increase the aggressiveness of the immune classifier, leading to improved tumor control at the cost of higher rates of immune-related adverse events, and 2) the adverse side effects associated with checkpoint inhibitors will be more systemic than those associated with antigen-directed therapies. Then, we allow the immune system's reference for normalcy to update over time, and show that the lag between the true tissue state and the immune system's perception of it leads to a transient shift in the aggressiveness/tolerance of the classifier. In accordance with the discontinuity theory of immunity, we show that abrupt changes are registered as abnormal, whereas gradual changes are absorbed into the immune system's notion of normalcy. Although we frame this discussion in the context of cancer, it applies more broadly to any biological classification problem in which the state of the sender is unknown, and signals are imperfect and corruptible.

Publication Type:	Article
Additional Information:	© 2026 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
Publisher Keywords:	biosemiotics, semiotic corruption, cancer, autoimmunity, signal detection theory, discontinuity theory
Subjects:	Q Science > QA Mathematics R Medicine > RC Internal medicine R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Departments:	School of Science & Technology School of Science & Technology > Department of Mathematics
SWORD Depositor:	Symplectic Administrator

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