FULL TEXT - https://www.drjjamesfrost.com/post/intrinsic-cellular-computation-far-reaching-implications-for-solving-the-cancer-problem

In my article Cancer’s Intelligence I conjectured that cancer is able to compute survival solutions to future environmental changes that it has not yet encountered. That is, that cancer can predict the future and ready itself to adapt to new, yet unseen environmental conditions, whether a change in oxygen tension or a chemotherapeutic drug.

A recent, exceedingly relevant paper entitled Trade-offs between cost and information in cellular prediction by Tjalma et al analyzes cellular adaptation and lays out the conditions for prediction of a survival response to an adverse environmental change. The cellular response is an intrinsically computed solution to future external events using the cell’s internal computational machinery. Historically, it has been thought that only higher organisms “can predict the future environment and initiate a response ahead of time”, but this is not the case.

At bottom, energy and time are two key computational limits. Energy (free energy) for computation, storing information, and the protein synthesis needed for future actions limits computation of the optimal solution for future survival moves.  Time is a factor in computing solutions and a in sensing and sampling the current and past environments sufficiently finely for accurate predictions. Optimal time averaging for the cell is key, which also has the advantage of filtering noise.

The Tjalma article elucidates the informational bounds a cell can possibly have about the future. The costs of a bit of informational sampling and processing are computed and compared.  As information-processing humans, we extract only the most useful information from the past environment as we plan future actions – the cell does the same. How and under what conditions a cell approaches the information bound for its internal computation is examined in detail by exploring Markovian and non-Markovian models and by examining the necessary fineness of temporal sampling of the environment and the cell’s computational speed. The information bottleneck theory is key in this analysis, as it dictates information compression for storage and its costs.

The article is a challenging, yet rewarding read and one that is intimately related to the vast computation ability of the cancer cell and more importantly, cancer cell networks. In a way, this article is the missing link between cancer’s computation from instantaneous, present environmental conditions – the constrained regime held by most cancer biologists – to the tracking and selective sampling of the past and the present to the response to yet-unseen future events – just as human and higher animal computation occurs.

For more information on the molecular imaging aspects of cancer characterization, treatment, and monitoring, please visit BioMolecular Imaging, LLC http://biomolecularimaging.com

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Intrinsic Cellular Computation: Far Reaching Implications for Solving the Cancer Problem

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Intrinsic Cellular Computation: Far Reaching Implications for Solving the Cancer Problem

Dr. J. James Frost