The trade-offs between communication and computation in cancer wasn't something I was thinking about when I wrote Cancer’s Intelligence. I purely considered the computational and decision engine aspects of cancer as an intelligent biologic entity.
However, a recent publication entitled Communication consumes 35 times more energy than computation in the human cortex, but both costs are needed to predict synapse number by WB Levy and VG Calvert sharply points out to me that I had omitted an important counterpart of computation: communication.
I thought to myself, "Communication or information transfer is essential to transmit the results of an intelligent decision engine of any system to the active components of that system."
Since energy is always limited, the optimal balance between computation and communication is a requirement for cancer's efficient survival as a system of genotypically and phenotypically diverse cells, from the primary tumor to the tumor microenvironment to metastases and the metastatic niche. As Levy and Calvert carefully examine the energetic costs for computation and communication in the brain, so must we accomplish the same for cancer, including bits per joule, channel capacity, and maximal entropy constraints on efficiency. In contrast to the human brain, for cancer the goal is to understand computation and communication in order to radically disrupt them and destroy the cancer.
Cancer is currently attacked by disrupting communication at the level of cellular receptors and other signaling proteins, but there is no well understood underlying theory to guide treatment from the communication or computation standpoints. In Cancer’s Intelligence I outlined several approaches to the cancer computation problem and in Symmetry and symmetry breaking in cancer: a foundational approach to the cancer problem I outlined some approaches to blocking communication, e.g., attacking cancer network nodes of greatest broken symmetry where network vulnerability is highest.
Future cancer investigations will benefit by taking note of the Levy and Calvert work and creating similar theoretical underpinnings for cancer.
References:
William B Levy
Victoria G. Calvert
Keywords: computation and communication modeling models, physical computing, system functions, scientific study, Trade-offs and Sensor Selection energy
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