Curing Cancer – Part 6 – Key systemic network issues

24 January 2021

This is my sixth essay about curing cancer based on the principles of complexity theory. This essay proposes strategies for curative therapy regarding key systemic networks other than those affecting the primary tumor, which were discussed in Curing Cancer – Part 5.

1. Disrupt the inflammatory process that plays a central role in promoting and sustaining carcinogenesis. Tumors have been described as wounds that do not heal (Dvorak 1986, Dvorak 2015). Activation of the inflammatory system, which promotes wound healing and accompanies many malignancies (Coussens 2002, Pernick 2020), has been considered a major cause of cancer since 1863, when Virchow speculated that some irritants enhance cell proliferation through tissue injury and chronic inflammation (Schottenfeld 2006). Inflammation is activated by many cancer risk factors, including excess weight, cigarette smoking, heavy alcohol consumption, aging and a Western diet (high fat, highly processed foods, low consumption of vegetables, fruits and whole grains) (Antwi 2016, Pernick 2020).

Inflammation may play a central role in promoting carcinogenesis because it is widely connected to other networks and it is unstable because it rapidly initiates sophisticated repair, antimicrobial and antitumor processes. Ultimately, this network instability may propagate to local and systemic networks and promote malignancy (Morgillo 2018).

Cancer disrupts the usual coordination of inflammatory networks. Sophisticated biologic processes, such as inflammation and embryogenesis, require coordination of activity, since isolated network activity by itself can be either useful or destructive, depending on its context. For inflammation, this coordination includes triggering both the process and its resolution at the same time (Serhan 2005, Serhan 2020). As the trauma is repaired or the threat from foreign organisms subsides, the resolution pathways cause networks to revert towards their initial states to prevent bystander damage to tissue (Sugimoto 2016). Cancer risk factors may also trigger the inflammatory process but through nonconventional means that do not simultaneously initiate the resolution process (Fishbein 2020). This causes persistent inflammation, which may wear down stabilizing factors in inflammatory and adjacent networks, particularly when accompanied by other risk factors, which further drives the malignant process (Shimizu 2012, Huang 2009).

Curative cancer therapy needs to antagonize or diminish this persistent inflammatory process. Suggested options include: (a) triggering pro-resolution pathways (Fishbein 2020, Park 2020); (b) using anti-inflammatory agents to diminish inflammation in general (Zappavigna 2020, Bruserud 2020); (c) mimicking the halting mechanisms associated with wound healing (Shah 2018, Kareva 2016) and liver regeneration (Abu Rmilah 2019); and (d) countering germline (inherited genetic) changes that promote instability in the inflammatory process.

2. Disrupt the microenvironment that nurtures tumor cells at primary and metastatic sites. Cancer risk factors produce a microenvironment that nurtures mutated cells, steers cellular networks towards malignant pathways (Mbeunkui 2009), helps them escape immune surveillance (Labani-Motlagh 2020) and ultimately promotes invasion by activating cells to mimic physiologic “invasion” of wounded epithelium through the extracellular matrix (Bleaken 2016, Coussens 2002). Tumors require a fertile “soil” for the cancer “seeds” to grow (Fidler 2003, Tsai 2014). For example, Hodgkin Reed-Sternberg cells produce cytokines that assist the survival and proliferation of lymphoma cells (Wang 2019) and pancreatic tumor cells produce cytokine IL1β and proinflammatory factors that establish a tumor supportive microenvironment (Das 2020, Huber 2020). From a network perspective, there is a complex crosstalk among cancer cells, host cells and the extracellular matrix (Sounni 2013).

Curative treatment should disrupt or normalize the microenvironment by targeting inflammation, the vasculature and the extracellular matrix (Mpekris 2020). For example, anti-VEGF or anti-VEGF receptor treatment can normalize vasculature by reducing vascular permeability (Gkretsi 2015). Normalizing the microenvironment may also enhance drug delivery and effectiveness (Polydorou 2017, Stylianopoulos 2018) or make existing tumors or premalignant states more susceptible to immune system attack (Ganss 2020).

It is also important to disrupt the microenvironment of possible metastatic sites. Typically, tumor cells die at secondary sites but the malignant process preconditions the otherwise hostile microenvironment of the secondary site so it can sustain their colonization (Houg 2018, Kaplan 2005).

3. Disrupt the microenvironment that promotes embryonic features associated with aggressive tumor behavior. In the microenvironment of the fertilized egg, coordinated network activity ultimately moves embryonic related networks towards mature, differentiated phenotypes in the fetus and newborn. However, cancer risk factors stimulate these networks in a non coordinated manner to trigger embryonic properties, such as rapid cell division (Kermi 2017), cell migration (Reig 2014, Kurosaka 2008) and changes to cell differentiation (Li 2014) that do not mature over time.

Curative treatment should include agents to promote this maturation, such as retinoids used in acute promyelocytic leukemia (Madan 2020), myeloid differentiation promoting cytokines (McClellan 2015), cancer cell reprogramming drugs (Gao 2019, Gong 2019) or possibly agents that halt rapid cell division in embryogenesis (Kermi 2017).

4. Repair the immune system dysfunction that coevolves with carcinogenesis. The immune system consists of a web of interacting networks whose effectiveness is systematically degraded with malignant progression. Immune dysfunction in cancer is typically not just the failure of one particular pathway (Karamitopoulou 2020). Curative treatment should attempt to improve immune system function with combinatorial therapy that targets multiple aspects of immune dysfunction (Sodergren 2020).

5. Promote the activation of gene networks supporting stable, multicellular processes and suppress networks promoting unicellular processes that support malignant type behavior. Multicellular organisms evolved from unicellular organisms by adding new genes and more intricate controls to existing networks for metabolism and replication (Trigos 2018, Trigos 2019). This enables greater communication and coordination between cells and makes possible higher level functions, such as cell differentiation and programmed cell death (Trigos 2018). The new control mechanisms keep cellular and systemic processes on track and shift the survival focus from individual cells towards the organism as a whole (Davies 2011). The operation of multicellular and unicellular programs appears to be somewhat mutually exclusive. Inflammation and DNA alterations may damage these multicellular controls, activating the existing genetic toolkit of preprogrammed, malignant behavior in unicellular networks based on what has been described as the atavism hypothesis of cancer (Davies 2011, Trigos 2017, Bussey 2017).

To restore the balance between multicellular and unicellular controls, curative treatment should activate different components of multicellular networks (Gaponova 2020, Hay 1995). In addition, treatment could target the weaknesses of cancer cells by applying a specific cellular stress that is readily dealt with by healthy cells using evolved capabilities or multicellular programming but not by cancer cells with predominantly unicellular programming (Lineweaver 2014). This includes “lethal challenges” of high dose methotrexate with leucovorin rescue (Howard 2016) or targeting other aspects of chaotic or unstable states, such as cell-extracellular matrix detachment (Crawford 2017).

6. Target the hormones that may promote tumor growth. Physiologic (i.e. normal) levels of estrogens and androgens and elevated levels of insulin are associated with breast (Dall 2017), endometrial / uterine (Rodriguez 2019), prostate (Liu 2020) and pancreatic cancer (Andersen 2017, Li 2019, Perry 2020). The primary mechanism may involve promotion of cell growth, particularly at a stage when these cells are particularly vulnerable to instability.

Simple antagonism of hormonal pathways is possible using tamoxifen for estrogens, antiandrogens for testosterone and metformin for insulin (Wan 2018). One block in these networks is apparently adequate for normalization, in contrast to the 3-5 blocks required for other tumor cell networks. Behavioral changes, such as weight loss, exercise, a healthier diet and reducing alcohol and tobacco use may also be therapeutic by either altering hormone levels or changing their interaction with other risk factors.

7. Antagonize germline changes that promote malignant behavior. Genetic testing of nontumor cells (germline testing) is recommended for all patients with pancreatic cancer (Stoffel 2019) and select patients with other cancers or family histories of cancer (Daly 2020, Lincoln 2020). Results are currently used to determine antitumor therapy (Zhu 2020) as well as for cancer screenings, reproductive choices and genetic counseling. We suggest using these results to also provide treatment that: (a) moves premalignant or malignant cells into less harmful pathways as discussed in Part 5; or (b) counters common germline changes in inflammatory, DNA repair, cell cycle stability, immune system or other networks that promote malignancy.

These blog essays have summarized proposed strategies for curative cancer therapy. The next essay will discuss random chronic stress, a newly proposed major factor in how cancer arises that cannot be prevented but can be better understood.

Curing Cancer – Part 5 – Key network issues that affect the primary tumor

17 January 2021

This is my fifth essay about curing cancer based on the principles of complexity theory (follow my blog at https://natpernickshealthblog.wordpress.com). This essay discusses key network issues for curative treatment that affect the primary tumor.

1. Kill as many tumor cells as possible. High tumor cell kill is important because: (a) tumor cells directly damage cells, tissue and organ systems, interfering with their physiologic functions which maintain life; (b)  tumor cells create an increased workload, both by producing biologic substances that interfere with optimal physiology and by stimulating a response to destroy them; and (c) tumor cells have molecular heterogeneity so killing each tumor cell may destroy a different strategy used by the tumor cell and its progeny to overcome the body’s antitumor defenses.

2. Attack multiple targets within local tumor networks. Curative treatment for adult tumors should build on our success in curing cancer in children and young adults, including childhood leukemia, Hodgkin lymphoma and testicular cancer. These cancers are caused by inherited or constitutional cancer predisposition or developmental mutations (Kentsis 2020) and exhibit a limited number of somatic (acquired) tumor mutations (Sweet-Cordero 2019). Although they typically have no prominent risk factors and show no field effects (widespread premalignant or malignant changes), curative therapy still requires combinations of 3-5 effective treatments, each with different mechanisms of action, mixed and matched for maximum effect (Mukherjee: The Emperor of All Maladies 2010). Multiple antitumor agents are necessary because biological pathways are not strictly linear. Rather, they are weblike, allowing cancer cells to bypass important steps blocked by antitumor agents (Nollmann 2020, Ozkan-Dagliyan 2020). Curing adult cancers may require even more treatment diversity due to: (a) their complex and heterogeneous mutational landscape (de Sousa 2018, Blank 2018, Samuel 2011), (b) the field effects generated by cancer promoters / risk factors acting over decades of exposure and (c) associated systemic network changes that must also be addressed by treatment (to be discussed in the next essay,  Part 6).

Drug combinations may be more effective than single agents due to synergy, the interaction of two or more substances producing a combined effect greater than the sum of their separate effects (Mokhtari 2017). Determining whether drug combinations are synergistic, additive or antagonistic is time consuming, but “deep learning,” other computational approaches and modeling methods may help screen possible combinations for effectiveness (Kuenzi 2020, Sidorov 2019). Combining different types of therapy may also be effective; for example, regional hyperthermia combined with radiotherapy may kill cancer stem cells (Oei 2017), be synergistic with immune checkpoint inhibitors (Li 2020) and improve survival (Fiorentini 2019).

3. Move local tumor cell networks into less lethal states. Curative treatment, in addition to killing large numbers of tumor cells through multiple mechanisms, should “normalize” or reduce the malignant traits of tumor cells that survive (Heudobler 2019). Fifty years ago, Kauffman discovered that a complex network of thousands of mutually regulating genes in normal cells may produce a stable equilibrium state called an attractor that corresponds to gene expression profiles specific to each cell type (Kauffman 1969, Noble 2015). Essentially, the environment of biological substances forces them to have similar behavior even though they behave very differently when isolated. Attractors have been analogized to a low energy state or valley on a topographic diagram that pulls in cells with similar network configurations (Waddington 1957). See diagrams at Vallacher 2013, Goldberg 2007.

Cell attractor pulls different cells into a common configuration

Attractors maintain cellular network stability against common disruptions in both normal cells and cancer cells. In normal cells, this stability may be disturbed by cancer “super promoters” (risk factors), acting over long time periods, that push cell networks into malignant pathways. In cancer cells, these “cancer attractors” create network stability that makes tumor cells resistant to antitumor treatment (Huang 2009, Pernick 2020).

Curative antitumor treatment problems should push tumor cells that survive the treatment towards alternative states with reduced malignant properties. Examples include retinoids for acute promyelocytic leukemia and childhood neuroblastoma (Nowak 2009), progestin for endometrial hyperplasia, a premalignant condition (Gallos 2013) and other lineage reprogramming agents (McClellan 2015, Gong 2019). Constant disturbing of parts of the network may also be useful (Cho 2016, Kim 2017).

The next essay will discuss key systemic network issues that affect cancer cells by acting outside of the primary tumor.

Curing Cancer – Part 4 – Principles of curative treatment

10 January 2021

This is my fourth essay about curing cancer based on complexity theory – follow my blog at https://natpernickshealthblog.wordpress.com. In part 3, I summarized my recommendations on curative treatment for advanced adult cancers with a poor prognosis, such as lung and pancreatic cancer. In this essay, I discuss the principles of curative treatment in greater depth.

I. Network medicine. Adult cancer is a systemic disease. It arises and is maintained due to dysfunctional cellular networks, not just mutated genes in a simple pathway. A network is defined as a complex set of interactions or relationships between different entities. By contrast, a simple pathway is a linear process with changes that occur one step at a time, such as an automobile assembly line. Scientists often think about biological pathways as a circular assembly line with small changes at each step until the pathway’s function is completed, such as activating an enzyme; then the pathway begins again. Complex biological pathways, such as those related to cell division, interact with each other at many steps, resembling sets of intersecting circles forming a network web of pathways that, when viewed as a whole, may perform a higher level function. The concept of “network medicine” emphasizes this point of view (Barabási 2011, Parini 2020).

Adult tumors may begin with local changes but large tumors are sustained by years or decades of supportive network changes throughout the body, called an altered systems biology (Koutsogiannouli 2013). Even if the tumor is destroyed by surgery, radiation or otherwise, networks outside the tumor typically will not revert to normal and may create new tumors.

II. Blocking multiple pathways. Disabling the activity of some dysfunctional networks requires combinations of treatments to block multiple pathways because these networks interact in a weblike manner and can readily bypass a single block in a particular pathway. The most consistent property of cancer cells is uncontrolled cell division, the target of most anticancer drugs. In the 1940s, Dr. Sidney Farber, a Harvard pathologist, gave his childhood leukemia patients a new drug, aminopterin, which blocked the effect of folic acid, which is needed for cells to divide (Dana-Farber Cancer Institute, accessed 2Jan21). Amazingly, these children, who usually died within weeks of diagnosis, went into remission. But their cancer soon relapsed, most likely because tumor cells bypassed this block through the web of reactions relating to cell division. We now know that it may take 3-5 drugs with different mechanisms of action to create enough blocks to completely disable these specific tumor networks (Mukherjee: The Emperor of All Maladies 2010).

III. Combinations of combinations of treatment. Adult tumors are due to network dysfunction in the local tumor as well as in many key systemic networks affecting the tumor, including inflammation and the immune system and may be promoted by hormones such as estrogen, testosterone or insulin. Normalizing or antagonizing each network may require a distinct treatment or combinations of treatments. Thus, curative therapy that affects all of these networks supporting the tumor may require combinations of combinations of treatment. This is more complicated than for childhood tumors, which are typically caused by inherited mutations (Kentsis 2020) and lack key systemic network changes.

IV. Monitoring key networks. It may be important to target these key networks which nurture and maintain the tumor and to monitor their status as treatment is given: the inflammatory process in general, the immune system’s antitumor capabilities, the microenvironment of the tumor and metastatic sites, unicellular type networks that promote malignant properties, embryonic networks that promote lack of cell differentiation and rapid growth, hormones that promotes tumor growth and germline (inherited) changes that promote malignant behavior directly or indirectly by affecting other networks. These key networks will be discussed in more depth in future essays. This monitoring, analogous to therapeutic drug monitoring of antibiotics and other antimicrobials for infectious diseases, should supplement existing radiologic and clinical studies that determine the size and extent of the known tumor. For each network, we must determine what biological molecules to monitor, how best to do so and how changes in their values should affect treatment. It may be useful to develop a cancer network score analogous to the TNM staging score for tumors that predicts prognosis and suggests future treatments.

V. Clinical trials. Extensive clinical trials will be needed to determine the effectiveness of individual treatments, combinations of treatments and combinations of combinations of treatments affecting these key networks. Additional studies will determine how to reduce side effects and what adjustments to make for particular patients. Towards this end, every cancer patient should be enrolled in a clinical trial.

VI. Strong public health programs. A curative treatment strategy includes strong public health programs to promote cancer risk reduction, effective screening programs and ensuring that all patients get adequate medical care. Risk factor reduction includes behavioral changes such as reducing smoking, excess weight and alcohol abuse and encouraging a healthy diet and exercise (European Code Against Cancer, accessed 2Jan21). At a societal level, our public health and medical care systems act as a behavioral immune system (Schaller 2015) to reduce cancer risk factors. Our physiologic immune system prevents numerous cancers from being clinically evident, as demonstrated by the high cancer rate in immunosuppressed patients due to drugs, diseases (HIV) or genetic disorders. Similarly, a well run public health system that promotes risk factor reduction and early detection prevents many cancers from arising. We should also develop more effective programs for identifying premalignant or malignant lesions in both high risk patients and current patients being monitored for relapse. At an individual level, optimal medical care promotes the reduction of behavioral risk factors, earlier detection of disease and increased use of effective treatments not available to those with inadequate care, poor performance status or severe comorbidities (Kelly 2016, Maclay 2017).

The next essay will discuss the key treatment issues affected by these principles in more detail.

Curing Cancer – Part 3 – Curative cancer treatment based on complexity theory

This is my third essay about curing cancer using the principles of complexity theory. It outlines my recommendations for curative treatment for advanced adult cancers with a poor prognosis, such as lung and pancreatic cancer.

Curative treatment should address the following principles:

I. Network medicine. Adult cancer is a systemic disease. It arises and is maintained due to dysfunctional cellular networks, not just mutated genes. Advanced disease is due to an altered systems biology (Koutsogiannouli 2013) with changes in networks beyond the tumor that typically will not revert to normal if the tumor is destroyed. Thus, focusing on “network medicine” is mandatory (Barabási 2011).

In contrast, cancer in children and young adults may not be a systemic disease because it is due to inherited or developmental mutations that primarily affect only the tumor cells (Kentsis 2020). Unlike adult cancer, it is not due to risk factors and there may be minimal involvement of the inflammatory system, immune system and hormonal pathways (Curing Cancer – Part 2).

II. Blocking multiple pathways. Disabling the activity of a dysfunctional network often requires drug combinations because networks interact in a weblike manner and can readily bypass a single block in a particular pathway. For cancers of children and young adults, curative treatment typically requires at least 3 to 5 drugs to block pathways sufficiently to disrupt the cancer network (Mukherjee: The Emperor of All Maladies 2010).

III. Combinations of combinations of treatment. Since adult tumors are due to dysfunction in many key systemic networks (see below), each often requiring a different set of combinatorial therapies, curative therapy may involve combinations of combinations of treatment.

IV. Monitoring key networks. To optimize treatment, it is important to monitor the status of these key networks as treatment is given: the inflammatory process in general, the immune system’s antitumor capabilities, the tumor’s microenvironment, unicellular type networks that promote malignant properties, embryonic networks that promote lack of cell differentiation, hormonal expression that promotes tumor growth and inherited changes that promote malignant behavior. For each of these networks, we must determine what biological molecules to monitor, how best to do so, how changes in their expression should affect treatment and how these values will impact long term survival rates.

V. Clinical trials. Extensive clinical trials will be needed to determine the effectiveness of individual treatments, combinations of treatments and combinations of combinations of treatments against these key networks, as well as their effect on tumor growth and long term survival rates. Additional studies will determine how to reduce side effects and what adjustments to make for particular patients. Towards this end, every cancer patient should be enrolled in a clinical trial, a major change in the status quo.

VI. Public health and preventative programs. A curative treatment program should attempt to reduce personal behavior that promotes malignancy, such as tobacco use, excess weight and alcohol abuse; develop better screening programs to identify premalignant or malignant lesions in both high risk patients and current cancer patients being monitored for relapse; and promote strong public health programs that encourage risk factor reduction and ensure that all patients get adequate medical care.

Key network issues to be addressed by curative treatment are:

1. Kill as many tumor cells as possible.

2. Attack multiple targets within local tumor cell networks.

3. Move local tumor cell networks into less lethal pathways.

4. Disrupt the inflammatory process, which plays a central role in promoting and sustaining carcinogenesis.

5. Disrupt the microenvironment that nurtures tumor cells at primary and metastatic sites.

6. Disrupt the microenvironment that promotes an embryonic phenotype in some tumors, which is associated with aggressive tumor behavior.

7. Repair immune system dysfunction that coevolves with carcinogenesis.

8. Promote the activation of gene networks supporting stable, multicellular processes and suppress networks promoting unicellular processes that support malignant type behavior.

9. Antagonize hormonal expression that promotes tumor growth.

10. Antagonize inherited genetic changes that promote malignant behavior.

Future essays will discuss these principles and network issues in depth.

Curing Cancer, Part 2 – Adult versus childhood cancer

This is my second essay about curing cancer. See also Curing cancer, Part 1 – Reductionism vs. Complexity.

The top 10 causes of US cancer death for all ages are listed below, including the projected number of deaths in 2020 and the 5 year relative survival rate (see Cancer Facts & Figures 2020 for all cancer related statistics). The 5 year relative survival rate is the number of patients alive at 5 years after diagnosis, with or without cancer, divided by the number of patients of a similar age expected to be alive who do not have cancer, based on normal life expectancy. Note that 5 year survival is not necessarily a cure – some patients may relapse.

#1 Lung cancer, 135,720 deaths, 5 year survival 19%
#2 Colon cancer, 53,200 deaths, 5 year survival 64%
#3 Pancreatic cancer, 47,050 deaths, 5 year survival 9%
#4 Breast cancer, 42,690 deaths, 5 year survival 90%
#5 Prostate cancer, 33,330 deaths, 5 year survival 98%
#6 Liver cancer, 30,160 deaths, 5 year survival 18%
#7 Non Hodgkin lymphoma, 19,940 deaths, 5 year survival 72%
#8 Central nervous system cancer, 18,020 deaths, 5 year survival 34%
#9 Bladder cancer, 17,980 deaths, 5 year survival 77%
#10 Esophageal cancer, 16,170 deaths, 5 year survival 20%

These top 10 cancers are projected to cause 414,260 deaths or 68.3% of the total projected US cancer deaths in 2020.

Cancer in children differs from cancer in adults. Children have far fewer cases (11,050 versus 1.8 million), fewer deaths (1,190 versus 606,520), different histologic (microscopic) types and higher rates of 5 year survival:

Central nervous system cancer, 74%
Ewing sarcoma, 76%
Hodgkin lymphoma, 98%
Leukemia, 87% (91% for acute lymphocytic leukemia, 66% for acute myeloid leukemia)
Neuroblastoma, 81%
Non Hodgkin lymphoma, 91%
Osteosarcoma, 69%
Retinoblastoma, 96%
Rhabdomyosarcoma, 71%
Testicular lymphoma, 95%
Wilms tumor, 93%

Cancer survival rates are higher in children than adults because their tumors have different origins and because clinical trials are more commonly used.

Childhood tumors are typically caused by inherited or constitutional cancer predisposition or developmental mutations (Kentsis 2020), are not age related and show no “field effects” (large areas affected by premalignant or malignant change). In contrast, adult tumors are caused by risk factors acting over decades, including tobacco use and exposure to other carcinogens, alcohol use, excess weight, Western diet (high fat, few vegetables), microorganisms and parasites, constant hormonal exposure and immune system dysfunction. Adult tumors are associated with older age and show prominent field effects. For example, the average age for lung cancer patients is 70 years and many of these patients have premalignant and malignant lesions throughout their lungs because cigarette smoke damages cells throughout the respiratory tract.

There is a strong emphasis on enrolling every child with cancer in a clinical trial to compare current standard therapy for a particular risk group with a potentially better treatment that may improve survival or reduce treatment side effects. As a result, children with leukemia are sorted into different risk categories and treatment plans based on age, gender, weight, race / ethnicity, central nervous system involvement, testicular involvement, white blood cell count, characteristics of leukemic cells and genomic alterations (NCI: Childhood Acute Lymphoblastic Leukemia Treatment (PDQ®)–Health Professional Version, accessed 6Dec20).

Curing childhood tumors requires combining multiple effective treatments with different mechanisms of action (Mukherjee: The Emperor of All Maladies 2010). Often, “combinations of combinations” of treatment are needed to kill all tumor cells, even though these tumors may originate from just one mutation in one cell. Combining treatments is necessary because biologic pathways are weblike, not linear. This means that treatment directed at stopping one dangerous pathway may be ineffective because the tumor uses alternative pathways on the biologic “web” to achieve a similar function (Nollmann 2020).

To cure adult tumors, more combinations may be required than for childhood tumors because adult tumors originate from many mutations in many cells, due to multiple risk factors acting over long periods of time. Clinical trials are important because human physiology follows the principles of self-organized criticality, which indicate that we cannot easily predict the impact of treatment combinations. This is analogous to the difficulty in predicting changes in a sandpile as grains of sand are added (Bak, How Nature Works 1999, Pernick 2017). The only way to effectively test whether treatment combinations are effective and tolerable in different patient groups is with clinical trials.

It is also important to address the many systemic changes related to adult tumors that occur in the decades it takes for the tumor to arise. This will be discussed in a future essay.

Curing Cancer, Part 1 – Reductionism versus Complexity

In 1971, President Richard M. Nixon announced the beginning of the US “war on cancer” (see President Nixon’s 1971 State of the Union at 15:03). Despite massive government expenditures (Kolata: Grant System Leads Cancer Researchers to Play It Safe, New York Times, 27Jun09) and testimonials that the war on cancer “did everything it was supposed to do” (NCI: National Cancer Act of 1971, accessed 10Nov20), cancer is still a leading cause of death (Centers for Disease Control and Prevention 2016, Cancer Statistics 2020), with high mortality from cancer of the lung, colon, pancreas and breast (Cancer Facts & Figures 2020).

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 themselves can be reduced to simpler parts (Mazzocchi 2008), disease is due to flawed parts and treatment needs to merely identify and repair the damaged parts. Although logical and rational, reductionism does not actually describe how complex systems function.

In complex systems, the properties of the entire system are greater than the sum of the properties of each part due to interactions between the parts (Kane 2015). Novel properties emerge from the parts and their interactions if one views the entire system as a whole. For example, start with a large number of biological molecules (proteins and other organic compounds), each relatively inert by itself, but capable of interacting in different ways with each other. Then confine them to a small space to promote these interactions. The result may be a living system, a self-sustaining web of reactions that can reproduce and evolve, properties that could not be even imagined by studying each part (Kauffman 1993, Pernick 2017).

Other examples of complex systems include 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.

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). When dropping individual grains of sand onto a surface, each grain typically just adds to a growing sandpile. Occasionally, it triggers a small avalanche of the sandpile. Less frequently, it triggers a larger avalanche, and rarely, it causes the entire sandpile to collapse. What is different about the grain of sand that triggers an avalanche from the grain of sand that just sits there? Surprisingly, there is no difference. The grain that appears to do nothing causes subtle structural changes in the sandpile, promoting an eventual collapse after enough grains are dropped. Although we focus on each grain as being important to the outcome, the functional unit is the sandpile itself.

Similarly, cellular networks composed of biologic molecules, cells, tissues and organs are poised at a critical state in which small perturbations typically cause no change but occasionally cause small network changes. Rarely, a trivial event sets in motion a large systemic response, leading to a major reconfiguration of the system (Bak, How Nature Works 1999), such as initial steps towards 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.

The human body is composed of a myriad of interacting networks positioned at critical states, which is required for network flexibility to enable embryonic development, the inflammatory response to trauma and infection and the capability for our species to evolve to 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 13Nov20) is not possible.

End of Part 1