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Colon Cancer: A Teleonomic Information Model of Carcinogenesis

Submitted:

09 June 2026

Posted:

17 June 2026

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Abstract
The somatic mutation theory (SMT) has dominated cancer research for decades, yet The Cancer Genome Atlas (TCGA) data reveal that only 40% of colon cancers harbor KRAS mutations. This paper proposes a conceptual shift: carcinogenesis is not solely a genetic disease but an informatic disorder. Drawing on Prigogine’s thermodynamics, transcriptomic entropy, and the Woodward–Kharkevich (W–K) teleonomic information measure, we distinguish two distinct mechanisms of information failure in colon cancer. In sporadic cancers, the stem cell is genetically normal but the niche (microenvironment) is corrupt (chronic inflammation, dysbiosis, toxins) – “the right cell in the wrong place”, a state of misinformation where external signals misdirect the cell away from homeostasis. In hereditary/familial cancers, the stem cell harbours a germline defect (APC, MLH1, TP53) while the niche remains intact – “the wrong cell in the right place”, a state of ignorance where the cell cannot process correct environmental signals due to intrinsic failure. Combined cases involve both mechanisms. Using the W–K measure J(d,T)=log⁡2[P(d,T)/P(T)]J(d,T)=log2​[P(d,T)/P(T)] with target TT = 5‑year colonic epithelial homeostasis, we estimate illustrative JJ values (KRAS: –0.23 bits; TP53: –1.32 bits; Lynch: –1.73 bits; FAP: –2.32 bits; chronic inflammation: –0.74 bits). Although all produce negative JJ (information that moves the system away from the goal), the therapeutic implications are opposite: sporadic cancers call for niche‑targeted therapies (anti‑inflammatory agents, probiotics), whereas hereditary cancers call for cell‑intrinsic pathway inhibitors (Wnt inhibitors, immune checkpoint blockers). The framework generates testable hypotheses and proposes a diagnostic algorithm based on an “Information Deficit Score” combined with transcriptomic entropy measurement.
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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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