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Hypothesis

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A Testable Model of Temporal Genomic Memory in Cancer Initiation Driven by Metabolic-Epigenetic Coupling

Submitted:

09 May 2026

Posted:

11 May 2026

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Abstract
Cancer initiation is commonly interpreted through mutation-centered models in which tumor development results from the progressive accumulation of genetic alterations. Although this framework remains essential, it does not fully account for the long latency of many cancers, the persistence of cellular phenotypes after removal of environmental stressors, or the stable epigenetic changes associated with chronic metabolic and inflammatory disease. This article proposes a testable theoretical framework termed Temporal Genomic Memory. The model suggests that prolonged biological exposures, including chronic inflammation, metabolic stress, oxidative injury, immune dysregulation, and environmental pressure, may be progressively encoded within epigenetic and RNA-mediated regulatory systems. These signals may be compressed into relatively stable molecular information signatures that shape future transcriptional responses. Under triggering conditions such as aging, immune decline, renewed inflammation, or metabolic imbalance, these stored regulatory states may be reactivated through molecular recall mechanisms, thereby altering cellular behavior and increasing susceptibility to oncogenic transformation. A simplified mathematical representation is introduced to describe biological signal accumulation, regulatory compression, and recall activation over time. The hypothesis does not replace somatic mutation theory; rather, it adds a complementary temporal-regulatory layer linking metabolic history, epigenetic memory, mitochondrial signaling, and cancer initiation. A practical experimental strategy is proposed to examine whether prolonged metabolic stress can generate persistent epigenetic and transcriptional signatures after stress withdrawal.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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