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Curing cancer - Reductionism versus complexity

Originally posted at Nat Pernick's Curing Cancer Blog on 14 November 2020, revised 7 April 2022.

The war on cancer
In 1971, President Richard M. Nixon announced the beginning of the "war on cancer" in the United States (see President Nixon's 1971 State of the Union at 15:03). Fifty years later, despite massive government expenditures (Kolata: Grant System Leads Cancer Researchers to Play It Safe, New York Times, 27Jun09, Brawley 2021) and testimonials that the war on cancer "did everything it was supposed to do" (NCI: National Cancer Act of 1971, accessed 3Apr22), cancer is still a leading cause of death (Centers for Disease Control and Prevention, accessed 3Apr22, Cancer Statistics 2022) with high mortality from cancer of the lung, colon, pancreas and breast (Cancer Facts & Figures 2022).

The limitations of reductionism
Our war on cancer has failed because our basic approach to biology is wrong. Biologic thinking has traditionally relied on reductionism, the theory that the behavior of the whole is equal to the sum of the behavior of the parts. Based on this theory, sophisticated systems are presumed to be combinations of simpler systems that can be reduced to simpler parts (Mazzocchi 2008); this implies that disease is due to flawed parts and treatment merely needs to identify and repair or destroy the damaged parts. Although logical and rational, reductionism does not accurately describe the functioning of complex systems, including human biology.

Complex systems
In complex systems, the properties of the entire system are not simply the sum of the individual properties but are also determined by interactions between the parts (Kane 2015). If one views the entire system as a whole, novel properties emerge from the parts and their interactions. For example, one can assemble a large number of biological molecules (proteins and other organic compounds), and while individually these molecules are relatively inert, they are capable of interacting in unique ways with each other. Moreover, if confined to a small space to promote interactions, the result may be a living system, a self-sustaining web of reactions that can reproduce and evolve, properties that could not even be imagined by studying each part in isolation (Kauffman 1993, Pernick 2017).

Other applicable examples of complex systems are communities formed by individuals and electric grids composed of individual power plants. In each complex system, the result is more dynamic and intricate than could be predicted from studying each component by itself (Complexity Explained website, accessed 5Apr22).

Self-organized criticality
Complex systems often exhibit self-organized criticality, the tendency of large systems with many components to evolve to a critical state or "tipping point" (Bak, How Nature Works 1999). For example, when dropping individual grains of sand onto a surface, each grain will typically just add to a growing sandpile. Occasionally, it triggers a small avalanche of the sandpile. Less frequently, it will trigger a larger avalanche, and only rarely, will cause the entire sandpile to collapse. So, what is different about the grain of sand that just sits there, and the grain of sand that triggers an avalanche? Surprisingly, there is no difference. The grain that appears to do nothing actually causes subtle structural changes in the sandpile, thus promoting an eventual collapse after a sufficient number of grains are dropped. Although we focus on each grain and its contribution to the outcome, the functional unit is the sandpile itself.

Similarly, cellular networks composed of biological molecules, cells, tissues and organs are poised at a critical state in which small perturbations will typically cause no change but occasionally may cause small network changes. Rarely, a seemingly trivial event sets in motion a large systemic response, leading to a major reconfiguration of the system (Bak, How Nature Works 1999), such as the initial steps toward malignancy. Although cancer scientists tend to focus on initial or "driver" mutations, complexity theory suggests that we should focus on the cellular networks as the functional units to more fully understand the etiology of cancer.

Cancer is due to the tradeoffs of maintaining critical states
The human body is composed of a myriad of interacting networks that provide flexibility and are poised at the critical states necessary to enable embryonic development, to facilitate the inflammatory response to trauma and infection and to provide the capability for our species to evolve in a changing environment. However, the tradeoff for maintaining these critical states is that cancer, a type of catastrophic systemic failure, is inevitable. We can reduce its incidence, we can detect it earlier and we can treat it more effectively but attaining a "world without cancer" (American Cancer Society, accessed 5Apr22) is not possible.
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