Modeling cancer as a complex adaptive system: Genetic instability and .

By

Kenneth J. Pienta, M.D., University of Michigan

Correspondance may be addressed to:

Kenneth J. Pienta, M.D. University of Michigan Comprehensive Cancer Center 1500 E. Medical Center Drive 7303 CCGC Ann Arbor, MI 48109-0946 P: 734-647-3421 F: 734-647-9480 Email: [email protected]

1 Introduction

Generally, we consider evolution as the fundamental strategy of life at the level of the organism. It is how we became who we are via an interplay of genetic variation and phenotypic selection [1]. The premise of evolution is that genes and hence, gene variants, are selected because they encode functions that in some way improve the chance of organism survival [2, 3]. This premise can be passed onto the level of the cancer cell. A tumor can be considered to be an organism or species that is able to speed up the evolutionary process by millions of years to select properties that help it survive and thrive within the macrocosm of the human body.

In cancer (or tumors), the welfare of the single cancer cell becomes independent of its neighbors. Although cancer is known to be a multitude of diseases that involves multiple phenotypes, this is a single and unifying theme for all cancer cells [4]. As we build a model of cancer as a complex adaptive system based on and Darwinian laws, we need to use this unifying principle to understand the genesis of a metastatic cancer [5, 6].

Cancer risk in the context of an evolutionary paradigm

How then does a cancer cell evolve from a normal cell (see Figure 1). At the most basic level, it is the result of DNA damage that counts towards a survival advantage [2]. A to the must occur in a place where it A) does not lead to the death of the cell; B) does not occur in a sequence of DNA that does not change behavior, and C) occurs in a place that conveys a growth or survival advantage. Meaningful DNA damage is the result of gene – environment interactions on multiple levels. First, cells may inherit “susceptibility” for damage from parental alleles. This can be at a very recognizable and measurable level, for example, a damaged DNA repair enzyme in Li-Fraumeni syndrome [4]. On this genetic background, the cells are assaulted by a variety of genome damaging exposures. These include radiation, viruses, microbes, carcinogens, chemicals, hormones, and other agents that are too numerous to list. But these risk factors to the genome are modulated in two important ways prior to their ability to damage the DNA.

First, these factors must pass through a phalanx of both organ- and non-organ specific intrinsic risk modulators. Intrinsic risk modulators are inherited traits that do not contribute directly to DNA damage, but modulate the environment that the cells are exposed to. Examples include how well metabolizing enzymes function to modulate drug and hormone activity (pharmacogenomics) as well as how well a hormone such as testosterone binds to the androgen receptor based on the number of CAG repeats in the promoter region [7]. In addition, before the damaging agent can cause mutation, it must evade extrinsic risk modulators. Extrinsic risk modulators are best characterized by chemoprevention agents such as antioxidants. Dietary factors such as selenium and vitamin E have been demonstrated to remove damaging oxygen radicals from the intracellular environment by catalyzing their breakdown to water [8, 9]. If the damaging agent escapes all of these potential protective mechanisms, it still must damage the DNA in a susceptible place that will allow a survival advantage [2,4]. Most to the DNA are either deleterious or neutral – very few are adaptive [1]. In bacteria, for example, it is estimated that only one in 10,000 mutations provide an adaptive advantage [1, 10]. It is probable that in for the much more complex human genome that this ratio would be much higher.

2

These gene – environment interactions that contribute to cancer can be understood in the context of any number of evolutionary paradigms (Table 1). In breast cancer, a woman may inherit the allele that contains BRCA-1, a gene important in maintaining normal breast cell function. This starts the cell down the cancer pathway. Similarly, an antelope could inherit a rare allele and is born an albino, immediately putting it at a disadvantage to the other, camouflaged, members of the herd. Cancer cells are subject to a wide variety of genotoxic insults that could potentially cause mutation and selective pressure. These are mirrored by the same types of insults that a herd of animals must survive, for example, changes in weather, ability to withstand infections, etc. These risks are modulated by inherent factors. In cells, for example, drug metabolizing enzymes. In animals, muscle fiber length (running speed). The risks are also modulated by extrinsic agents. For cells, are there chemoprevention agents present? For animals, presence of other protective species, the ability to migrate, and the number of adult males present to ward off attack.

Cancer evolution in the context of recent human evolution

Each cancer and the cancer cells that compose it has a distinct phenotype, however, cancers do share a group of common characteristics [4, 11, 12]. A tumor is the result of a collection of cancer cells that are actively acquiring mutations that allow the emergence of a successful clone of cells. This is a highly inefficient process and tumors are filled with clones of cells that will not survive long term and are undergoing apoptosis () as a result of harmful mutations, hypoxia, immune surveillance, etc. Some cells, however, manage to acquire enough mutations and acquire the characteristics of a successful cancer cell. This can be compared, at least on one level, to the evolution of human civilization. A key difference in these two types of evolution is that we believe that as human beings we evolved our societies as a result of conscious decisions that increased our chances for species survival. To understand cancer clonal expansion we have to explain cancer cell growth and survival in terms of an unconscious process. This is much more likely to be modeled by early evolution as we pulled ourselves out of the sea and became multicellular organisms. However, the exercise in comparing the successful cancer cell successfully colonizing a new metastatic site to human civilization and colonization is worthwhile (see Table 2).

1) Unlimited replicative potential

Cancer cells are immortal. This does not mean that each cell itself lives forever (just like humans). This means that the cell population doubles without limit and creates uncontrolled clonal expansion. In non-cancerous cells, a cell can double approximately 50 times before it undergoes and dies [13]. This has been termed the Hayflick number and is the result of an internal cell doubling clock built onto the end of each chromosome termed the telomeres [14]. Telomeres are specific strands of DNA that shorten with each cell division. At a critical shortened length, the cells undergo apoptosis, or programmed cell death. Cancer cells reactivate and enzyme, telomerase, which maintains the length of telomeres with each cell division by adding base pairs back onto the telomeres, thereby maintaining length integrity.

2) , mutation, and natural selection

3

A fundamental characteristic of cancer is the generation of tumor cell heterogeneity, i.e, cells with multiple mutated phenotypes, through a mechanism of genetic instability [15-20]. There are multiple ways that genetic instability can be generated (chromosomal instability and microsatellite instability) and observed. For example, tumor cells exhibit karyotypes that are grossly changed in quantity and quality from the complement of normal cell chromosomes

Radman and colleagues have suggested that two different models can explain mutations in evolution [1]. In one model, there is a low mutation rate in a very large population. In the second model, there is a high mutation rate in a limited population with coincident intense recombination, permitting the rare adaptive mutation to become separated from frequent deleterious mutations [1]. The latter type of evolution can be seen in bacterial populations under stress. It is likely that the evolution of cancer is a combination of these two models. The initial mutations within a cell destined to become cancer happen as a result of a low mutation rate within a large population of cells. These mutations occur as a result of the interplay between susceptibility alleles and the environment as outlined above. Within the expanding clone, a mutation eventually occurs that induces a “mutator phenotype” with coincident high mutation rates and the generation of tumor cell populations with a heterogeneous set of properties over a relatively short period of time. While this mutator phenotype may occur as a result of chance, it may also be facilitated by the exposure of the cells to stresses, such as hypoxia as the size of the tumor increases. Indeed, it has been demonstrated that hypoxia induces genetic instability in cancer cell populations [21, 22]. The emergence of the mutator phenotype rapidly selects cells with the most robust survival advantages. This robust phenotype can be observed clinically. A cancer can be in remission for many years and then present with metastatic disease that quickly kills the patient over a matter of weeks or months [23].

3) Protection from death

There are multiple redundant pathways in place to maintain the fidelity of the cellular systems to prevent mutation and damage. More often than not, deleterious mutations lead to the initiation of programmed cell death. Teleologically, this is built into systems to protect the rest of the cell population. There are multiple apoptotic pathways within cells in response to different types of cellular damage [24, 25]. Cancer cells have acquired mutations that allow damage to occur and accumulate without activating apoptotic pathways. It is almost unbelievable the amount of genetic ruin, mutation, and rearrangement that a cancer cell can accumulate and still be viable, functional, and robust [26].

4) No inhibition of growth

For an organism or organ such as the liver to function in a coordinated fashion, it must control the individual cells that compose it, just as a society must. But for the human population to grow and expand, it must outfit groups to leave the population base and find new areas to populate. In cancer cells, this growth inhibition is controlled by anchorage –dependent growth and maintenance. If a society sends out an individual to explore who is ill – equipped, that explorer will likely perish. If a normal cell becomes disconnected from its neighbors or the basement membrane that it resides on, apoptosis is triggered and the cell dies. Cancer cells have

4 acquired mutations that allow them to grow independent of attachment to a basement membrane or to other cells [27-29]. This anchorage independence releases the cell from communicating with its neighbors and breaks down the fundamental fidelity of the organism system. Several cell attachment proteins have been identified that have been demonstrated to be altered in cancer cells. These mutations also allow the cancer cell the freedom to leave the primary tumor environment and start down the path of metastasis [30].

5) Ability to ensure a nutrient supply

A group of cancer cells undergoing clonal expansion can only become approximately a cubic millimeter in size (20 population doublings, one million cells) without a blood supply to oxygenate the cells [31]. A critical step in successful cancer development is the release of factors such as vascular endothelial growth factor (VEGF) from the cancer cells to attract new blood vessels growth (neovascularity of angiogenesis) [32, 33]. This is a good example of how cancer cells, even in the presence of tumor cell heterogeneity, must unconsciously cooperate with each other. No single cell produces enough VEGF to stimulate the growth of a new blood supply by itself. Enough individual cell or clones must then have the ability to each secrete VEGF into the surrounding environment to allow a gradient of growth factor to be established to attract new blood vessels.

6) Population expansion and growth beyond natural boundaries

Cancer rarely kills its host because of its growth in one single organ. The majority of these cancers can be successfully treated by surgery and/or radiation. Even untreated, a solitary cancer can grow in the primary organ for years before becoming clinically evident. Cancer kills because it spreads to other organs (metastasizes). This certainly requires the mutations that allow uncontrolled growth, anchorage independent growth, apoptosis evasion, and new blood vessel growth. But it also requires the acquisition of several other adaptation properties. Even though the cancer cell does not require its neighbors to grow, to be lethal it has to acquire properties that allow it to leave the primary tumor environment. For the cancer cell population to grow, it must breakdown it surrounding tissue environment. This periphery of the tumor is the most oxygenated and has the richest nutrient gradients. For the cancer cells to keep expanding into this environment there must be a selective pressure for cells that can invade into that environment. It has been demonstrated that cancer cells secrete high amounts of proteases that breakdown the confining extracellular matrix of surrounding tissue [34]. This allows continued growth of the clonal populations without starvation. It also allow cells to find their way into the circulation and lymphatic system and spread to other parts of the organism. What is not clear is that if these types of mutations are the result of selective pressure or the simple result of an intrinsically unstable genetic system (see genetic instability, above).

7) Evasion of enemies during growth and expansion

At every level in its life, the cancer cell, and its daughter clones, must evade the immune system. The immune system is a remarkable adaptable system that seeks out and destroys foreign and harmful agents within the organism. Cancer cells have developed several ways to evade the surveillance of the immune system [35]. In fact, it appears that in some ways, it

5 appears that cancer cells flourish in lymph nodes, the way stations for the white blood cells that the body uses to fight infection and foreign bodies. Every cancer evaluation asks first, is the cancer in the lymph nodes nearby? How it survives in this hostile environment is unclear. Many cancer cells have lost proteins (antigens) on their cell surface that let the body recognize them as foreign. Other cancer cells secrete cytokines such as transforming growth factor beta (TGFß) which inhibits the function of the immune system cells [36].

8) Successful colonization (successful metastasis)

Successful colonization Adaptation to the use of Building a new site, growth factors in the new learning to eat new foods, environment and applying and applying all of the traits all of the traits above in a outlined above in a new new environment. environment

All of the acquired mutations, whether they were acquired through selective pressure via adaptation to continued hostile environmental hurdles or by chance accumulation, result in a cancer cell clonal population that successfully metastasizes and grows in multiple new organ sites [4, 30, 37]. This clearly resembles colonial expansion and if the cancer was a thinking set of individuals, is exactly what you would expect to happen. A final trait that is needed is the ability to survive and flourish in new environments. This requires adapting to use the growth factors that the new environment is rich in. For example, prostate cancer cells grow well in the bone marrow, partly because transferrin is a potent growth factor for them and is present in high amounts in the bone [38].

Modeling cancer as a complex adaptive system at the level of the cell

Cancer cells acquire the multiple traits necessary to survive within the greater macroenvironment of the host. We can also model the tumor, i.e, the collection of cancer cells, as acting in concert to function as a complex adaptive system – one that exhibits emergent properties (see Table 3). In this model, the individual cancer cells act as the individual agents of the complex adaptive system [6, 39, 40, 41]. Each cell can act independently, but may also interact to create the tumor with its resultant properties.

1. Cells are the agents of the cancer complex adaptive system

Complex systems are organized as a finite number of states, which can be defined by Boolean networks. A Boolean network is an array of elements, with a particular rule associated with it, linked by a finite number of inputs. As the number of elements and links increases, the number of initial states of the system also increases. By cycling through the network (i.e. applying the elements rules as influenced by their links), however, one finds that the number of states the system occupies is limited to certain specific state-cycles (attractors). By taking the square root of the number of elements in a network, one can approximate the number of attractors. Therefore, Boolean networks obey a power law. Kauffman used these networks to show how the size of an organism’s genome is related to the number of cell types it generates [42]. For example, a sponge has approximately 10,000 genes and about 12 cell types. Humans

6 have about 30,000 – 40,000 genes and over 250 cell types. A Boolean network with 100,000 elements, with each element linked to two others, has the potential of 1030,000 states. In fact, only 370 states are realized. Each of these states is an attractor, likewise each cell type in a human body is a state-cycle attractor of the genome. A state-cycle attractor is defined by certain boundary conditions. In the cell, it has been proposed that these boundary conditions are defined by the ribonucleic acid (RNA)-protein complex termed the nuclear matrix [15, 43]. The nuclear matrix, therefore, may define the boundary conditions of a cell. Perturbation of the steady state attractor through mutation may upset the genetic stability and cause the cell to enter the carcinogenic cascade. Cancer, then, is the result of multiple perturbations (i.e. mutations) to a cell, that result in a redefinition of its boundary conditions.

2. Genes are the building blocks that cell structure and function is based on

The six feet of DNA molecule that is present within each cell is segmented into genes that encode the proteins that interact with each other to form the structure and function of cells [12]. In normal cells, this structure and function is tightly controlled. In cancer, however, mutation leads to abnormal cellular functions and structural abnormalities.

3. Cells with similar adaptive mutations aggregate into clonal populations

There is no question that the transformation of a normal cell to a cancer can be viewed as an evolutionary process and that the tumor can be viewed as a separate species [1-6, 11, 17, 44]. With the realization that a single tumor is an assembly of heterogeneous cells, it seems more appropriate to view each clonal population within the tumor as a different species [23, 41, 45]. The members of each clone have a unique karyotype, morphology, and evolutionary fitness within the context of the global ecosystem: the human body. In this system, a tumor is a local ecosystem in which various species, clones, are in competition. As each tumor grows, it is a collection of clones that live and die. Each cubic centimeter of tumor (one gram) contains one billion individuals within it. If one assumes no death, this is equivalent to 35 generations from one aberrant cell. After ten more generations, this billion individuals has increased to one trillion cells. The population of a single tumor, therefore, surpasses the population history of mankind on this planet. The clone, or clones that survive this growth are the most fit, and can spread (i.e. metastasize) to other local ecosystems (i.e. other organs). Their “success” eventually leads to a global ecological disaster: host death. Carcinogenesis is simply the act of speciation and the populating of the human global ecosystem.

4. Cancer cells acting in concert produce properties with growth advantages

A primary tumor is a collection of cells that maintain contact and communication with adjacent cells through the extracellular and intracellular matrices, which have been collectively termed the “tissue matrix” [43]. One of the characteristics of a cancerous growth, however, is cellular heterogeneity. Therefore, although only a single tumor may exist, it may be subdivided, on a cellular level, into separate populations (the clones). For these cells or clonal populations to survive, they must exert properties to help each other survive. A good example of this is the stimulation of new blood vessel growth (neoangiogenesis) that results in the sprouting of new

7 blood vessels to the tumor with subsequent nutrient flow to the growing tumor mass that would otherwise starve.

5. Cancer cells can be defined by a set of IF/THEN rules of varying complexity

A fundamental property of complex adaptive systems is flow – the ability to model much of its actions as a set of IF/THEN rules. Previously, we and others have demonstrated how the cell signaling cascades of cells can be modeled as a series of biocircuits within the cell that can be perturbed by mutation [6, 8, 46]. IF/THEN rules can also be applied at the level of the cells themselves. For example, IF a cell produces proteases, THEN it will break down the surrounding tissue matrix environment. These rules can be applied to each of the fundamental alterations that are necessary to form a lethal cancer cell (Table 2).

6. Genetic instability gives rise to the diversity of cancer cells: Tumor cell heterogeneity

The mutations that lead to the formation of a tumor predispose the cells making up that tumor to further changes. The genetic instability inherent in a tumor allows populations of cells to adapt rapidly to new conditions. This helps explain how cancers avoid the immune system, become resistant to certain drugs, and how they are able to metastasize. The strategy undertaken by a tumor appears to repeat features of evolutionary history. In the Cambrian Period there was a great explosion of body types [47]. Fossils from the epoch exhibit a far greater variation in gross morphology than exists today. Likewise, a tumor, due to its genetic pliability, can try innumerable cellular phenotypes “searching” for one that can thrive in the current environment (host organ) or spread to different environments (metastatic target organ), and discarding unfit cells. The fact that tumors exhibit high death rates supports this contention [23]. Most of the cells in a tumor die because they were incapable of forming strategies that allowed them to survive in their current environment.

7. Complex adaptive systems change how strongly they interact with others in a way that maximizes the average fitness of the system

Tagging can, and does occur, at multiple levels within any system. At the level of the biocircuit within the cell, a tag can represent a phosphorylated or ubiquinated protein which signals that it should be recycled. At the level of immune system, tagging can represent an antigen on a cell surface that allows the white blood cells to recognize it as “self.” Metastasis of a tumor can be taken as proof that the cells comprising that tumor have altered their interactions and connections not only with adjacent tumor cells, but also with the cells that form the lining of blood vessels. Metastasis requires active interactions between the cancer cells themselves and their environment. For cancer cells to enter the blood stream, their connection with other cancer cells must be weakened. In the bloodstream, cancer cells bind to each other as well as platelets to survive the turbulence. To escape the blood stream, the cancer cells must then successfully bind to the endothelial cells of the target organ [30, 37]. All of these actions occur by altering the expression of cell-cell adhesion molecules in a dynamic fashion.

8 8. Tumor cell heterogeneity gives cancer an internal model to give cells growth advantaged that appear to be “anticipatory”

The word “anticipatory” can suggest a connotation that somehow a complex adaptive system is conscious of its actions. On the contrary, the strength of modeling through a complex adaptive system is that it needs no conscious thought process to from complicated, rule – based systems. The culmination of genetic instability and tumor cell heterogeneity is the acquisition of mutations requisite for a robust and lethal cancer. Cancer can do this because it can recapitulate evolution at a rate almost beyond our comprehension.

Conclusion – Applying complexity theory towards a cure for cancer

The ultimate question is whether understanding cancer in terms of evolution and complexity theory can help us cure the disease. “Cancer” is a complicated set of diseases arising in a variety of organs, however, these diseases share the similar properties outlined here. Currently, approximately half of all cancers are cured by surgical removal, radiation, or chemotherapy. The other half of cancers are lethal because they have metastasized (and, therefore, are not removable) and because they are resistant to known therapies (a result of tumor cell heterogeneity).

What implications does the complex adaptive nature of cancer have for future research and treatment? It may be possible to turn a molecular process of therapeutic evolution against the evolutionary power of the cancer cell by designing a therapeutic approach that mimics and counters tumor evolution at a molecular level so that drug diversity can negate tumor cell heterogeneity and take away the advantage the cancer cell has to overcome our present treatments. At a very simple level, the cancer could select its own drugs. This could be accomplished by using a randomized library of RNA sequences termed aptamers and permit the lethal cancer cells to bind to the aptamers with the highest affinity and specificity [48-52]. These specific aptamers would be amplified and then conjugated to radionuclides and cytotoxic drugs.

This is a novel approach to the treatment of resistant cancers. This technique essentially floods the cell with billions of random RNA sequences and allows the cancer cell to select out specific molecules to bind that it is expressing. Aptamers are modified oligonucleotides that are isolated by the systematic evolution of ligands by an exponential enrichment (SELEX) process. They are globular molecules that can recognize and bind with high affinity to a variety of cellular constituents. They are intermediate in size between small peptides and single chain antibody fragments. One their main advantages for cancer targeting and therapy is their small size compared to antibodies, which can result in improved cancer tissue permeation and delivery of lethal agents [53]. Molecular evolution using random libraries of polymers might be used to select high affinity binding components specific for prostate tumor cells. This pitting of molecular evolution against tumor evolution will permit a wide diversity of tightly binding synthetic ligands to match the biological diversity of the tumor cells. One type of these polymers that can be used includes highly diverse RNA molecules synthesized with random sequences and that are relatively inert to RNAse hydrolysis. A 15-mer of random nucleotides produces over a billion different RNA aptamers. These mixtures of aptamers can be differentially selected for their ability to bind tightly to cancer tissue while not binding to normal tissue. The specific

9 tumor binding aptamers can then be amplified by reverse transcriptase and PCR to enrich the population of tight binding aptamers for the tumor cell. This process can be cycled over and over.

Will aptamers be better than antibodies directed against tumor cells? The tumor has developed ways to escape antibody and immunity control, but it remains unknown whether these tumor-antibody defenses can negate synthetic aptamers. Another advantage of aptamers is their more rapid tissue permeability compared to antibodies, which is advantageous for therapy.

Within a single tumor, cells are heterogeneous. Just as important, tumor types are heterogeneous between patients. This approach of selected aptamers is applicable to both types of heterogeneity. While is it expected that some aptamers may be common to all types of lethal cancers, it cannot be taken as a given. Every tumor may be different. However, these strategies give us the opportunity to explore customized therapy for individual patients. Ultimately, one would like to create a specific aptamer library for a particular patient. This could be particularly useful in the surgical patient. Cancer tissue would be used to generate a patient specific library. This patient specific library would then be used systemically to scavenge and destroy micrometastases. If and when the tumor progresses, samples from the metastatic lesions could be used to generate new libraries. In summary, the therapeutic evolution should be able to outpace the biologic evolution.

References:

1. Radman M, Matic I, Taddei F. Evolution of evolvability. Annals of the New York Academy Sciences 146-155, 1999.

2. Greaves M. Cancer causation: the Darwinian downside of past success? The Lancet Oncology 3:244-251, 2002.

3. Nowell PC. The clonal evolution of tumor cell populations. Science 194:23-28, 1976.

4. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell 100:57-70, 2000.

5. Nesse RM, Williams GC. Evolution and the origins of disease. Sci Am 279:58-65, 1998.

6. Schwab ED, Pienta KJ. Cancer as a complex adaptive system. Med Hypothesis 47:235- 241, 1996.

7. Coffey DS. Similarities of prostate and breast cancer: evolution, diet, and estrogens. Urology 57:31-38, 2001.

8. Pathak SK, Sharma, RA, Mellon JK. Chemoprevention of prostate cancer by diet- derived antioxidant agents and hormonal manipulation (Review). Int J Oncol 22:5-13, 2003.

10 9. Farinati F, Cardin R, Della Libera G, Herszenyi L, Marafin C, Molari A, Plebani M, Rugge M, Naccarato R. The role of anti-oxidants in the chemoprevention of gastric cancer. Eur J Cancer Prev 3 Suppl 2:93-7, 1994.

10. Taddei F, Radman M, Maynard-Smith J, Toupance B, Gouyon PH, Godelle B. Role of mutators in adaptive evolution. Nature 387:700-702, 1997.

11. Marusic M. Evolutionary and biological foundations of malignant tumors. Med Hypotheses 34:282-287, 1991.

12. Pienta KJ, Partin AW, Coffey DS. Cancer as a disease of DNA organization and dynamic cell structure. Cancer Res 49:2525-32, 1989.

13. Neumann AA, Reddel RR. Telomere maintenance and cancer -- look, no telomerase. Nat Rev Cancer 2:879-84, 2002.

14. Rubin H. The disparity between human cell senescence in vitro and lifelong replication in vivo. Nat Biotechnol 20:675-81, 2002.

15. Pienta KJ, Ward WS. An unstable nuclear matrix may contribute to genetic instability. Medical Hypothesis 42:45-52, 1994.

16. Nowak MA, Komarova NL, Sengupta A, Jallepalli PV, Shih Ie M, Vogelstein B, Lengauer C. The role of chromosomal instability in tumor initiation. Proc Natl Acad Sci U S A 99:16226-31, 2002.

17. Anderson GR, Stoler DL, Brenner BM. Cancer: the evolved consequence of a destabilized genome. Bioessays 23:1037-46, 2001.

18. Hoglund M, Gisselsson D, Sall T, Mitelman F. Coping with complexity. Multivariate analysis of tumor karyotypes. Cancer Genet Cytogenet 135:103-9, 2002.

19. Kerbel RS, Cornil I, Korczak, B. New insights into the evolutionary growth of tumors revealed by southern gel analysis of tumors genetically tagged with plasmid or proviral DNA insertions. J Cell Science 94:381-387, 1989.

20. MacPhee DG. The significance of deletions in spontaneous and induced mutations associated with movement of transposable DNA elements: possible implications for evolution and cancer. Mutation Res 250:35-47, 1991.

21. Yuan J, Narayanan L, Rockwell S, Glazer PM. Diminished DNA repair and elevated in mammalian cells exposed to hypoxia and low pH. Cancer Res 60:4372-6, 2000.

22. Reynolds TY, Rockwell S, Glazer PM. Genetic instability induced by the tumor microenvironment. Cancer Res 56:5754-7, 1996.

11

23. Coffey DS, Isaacs JT. Prostate tumor biology and cell kinetics-theory. Urol 17(Suppl):40-53, 1981.

24. Hussein MR., Haemel AK, Wood GS. Apoptosis and melanoma: molecular mechanisms. J Pathol 199:275-88, 2003.

25. Bowen AR, Hanks AN, Allen SM, Alexander A, Diedrich MJ, Grossman D. Apoptosis regulators and responses in human melanocytic and keratinocytic cells. J Invest Dermatol 120:48-55, 2003.

26. Hoglund M, Gisselsson D, Hansen GB, Sall T, Mitelman F. Multivariate analysis of chromosomal imbalances in breast cancer delineates cytogenetic pathways and reveals complex relationships among imbalances. Cancer Res 62:2675-80, 2002.

27. Abraham S, Zhang W, Greenberg N, Zhang M. Maspin functions as tumor suppressor by increasing cell adhesion to extracellular matrix in prostate tumor cells. J Urol 169:1157- 61, 2003.

28. Su ZZ, Gopalkrishnan RV, Narayan G, Dent P, Fisher PB. Progression elevated gene-3, PEG-3, induces genomic instability in rodent and human tumor cells. J Cell Physiol 192:34-44, 2002.

29. Kondoh N, Shuda M, Arai M, Oikawa T, Yamamoto M. Activation of anchorage- independent growth of HT1080 human fibroblasts. Mutat Res 199:273-291, 1988.

30. Cooper CR, Chay CH, Gendernalik JD, Lee HL, Bhatia J, Taichman RS, McCauley LK, Keller ET, Pienta KJ. Stromal factors involved in prostate carcinoma metastasis to bone. Cancer 97:739-47, 2003.

31. Folkman J. Role of angiogenesis in tumor growth and metastasis. Semin Oncol 29:15-8, 2002.

32. van Nieuw Amerongen GP, Koolwijk P, Versteilen A, van Hinsbergh VW. Involvement of RhoA/Rho kinase signaling in VEGF-induced endothelial cell migration and angiogenesis in vitro. Arterioscler Thromb Vasc Biol 23:211-7, 2003.

33. Chang L, Kaipainen A, Folkman J. Lymphangiogenesis new mechanisms. Ann N Y Acad Sci 979:111-9, 2002.

34. Chung AS, Yoon SO, Park SJ, Yun CH. Roles of matrix metalloproteinases in tumor metastasis and angiogenesis. J Biochem Mol Biol, 36(1): p. 128-37, 2003.

35. Nambu Y, Beer DG. Altered surface markers in lung cancer. Lack of cell-surface Fas/APO-1 expression in pulmonary adenocarcinoma may allow escape from immune surveillance. Methods Mol Med 74:259-66, 2003.

12

36. Ivanovic VV, Todorovic-Rakovic N, Demajo M, Neskovic-Konstantinovic Z, Subota V, Ivanisevic-Milovanovic O, Nikolic-Vukosavljevic D. Elevated plasma levels of transforming growth factor-beta(1) (TGF-beta(1)) in patients with advanced breast cancer: association with disease progression. Eur J Cancer 39:454-461, 2002.

37. Keller ET, Zhang J, Cooper CR, Smith PC, McCauley LK, Pienta KJ, Taichman RS. Prostate carcinoma skeletal metastases: cross-talk between tumor and bone. Cancer Metastasis Rev 20:333-49, 2001.

38. Rossi MC, Zetter BR. Selective stimulation of prostatic carcinoma cell proliferation by transferrin. Proc Natl Acad Sci U S A 89:6197-201, 1992.

39. Schwab ED, Pienta KJ. Modeling signal transduction in normal and cancer cells using complex adaptive systems. Med Hypothesis 48:111-123, 1997.

40. Holland J. Hidden order: How adaptation builds complexity. Addison-Wesley: New York, pp 1-40, 1995.

41. Chinnaiyan AM, Coffey DS, Forrest S, Goldberg E, Holland J, Kepler T, Maley C, Mitchell M, Montie JE, Morowitz M, Nelson WG, Omenn G, Perelson AS, Pienta KJ, Rubin MA, Scardino P, Shapiro JA, Wheeler T. Merging bottom-up and top-down approaches to study prostate cancer biology. Complexity 7:22-30, 2002.

42. Kauffman SA. Antichaos and adaptation. Sci Am 265:78-84, 1991.

43. Pienta KJ, Murphy BC, Getzenberg RH, Coffey DS. The tissue matrix and the regulation of gene expression in cancer cells. In: Advances in Molecular Cell Biology. JAI Press, Inc., Conn., vol. 7:131-156, 1993.

44. Temin HM. Evolution of cancer genes as a mutation-driven process. Cancer Res 48:1697-701, 1988.

45. Lewin RS. In: Complexity: Life at the Edge of Chaos. New York: Collier Books, pp. 124-127, 1993.

46. Bao JZ, Davis CC, Schmukler RE. Impedance spectroscopy of human erythrocytes: system calibration and nonlinear modeling. IEEE Trans Biomed Eng 40:364-78, 1993.

47. Kerr RA. Evolution. A trigger for the Cambrian explosion? Science 298:1547, 2002.

48. Lupold SE, Hicke BJ, Lin Y, Coffey DS. Identification and characterization of nuclease- stabilized RNA molecules that bind human prostate cancer cells via the prostate-specific membrane antigen. Cancer Res 62:4029-33, 2002.

13 49. Coffey DS. Understanding the cancer biology universe: enigmas, context and future prospects. Cancer Biol Ther 1:564-7, 2002.

50. Faria M, Ulrich H. The use of synthetic oligonucleotides as protein inhibitors and anticode drugs in cancer therapy: accomplishments and limitations. Curr Cancer Drug Targets 2:355-68, 2002.

51. Cerchia L, Hamm J, Libri D, Tavitian B, de Franciscis V. Nucleic acid aptamers in cancer medicine. FEBS Lett 528:12-6, 2002.

52. Lato SM, Ozerova ND, He K, Sergueeva Z, Shaw BR, Burke DH. Boron-containing aptamers to ATP. Nucleic Acids Res 30:1401-7, 2002.

53. Hicke BJ, Marion C, Chang YF, Gould T, Lynott CK, Parma D, Schmidt PG, Warren S. Tenascin-C aptamers are generated using tumor cells and purified protein. J Biol Chem 276:48644-54, 2001.

14

Susceptibility alleles

Exposures, Diet, Genomic damage Carcinogens

External Risk Modulators: Intrinsic Risk Modulators: Chemoprevention Pharmacogenomics

Figure 1. Cancer is a result of gene-environment interactions that lead to genetic mutations in pieces of DNA that lead to survival advantage. Every person inherits a different set of genes from their parents. Some of these genes carry with them an inherent risk or susceptibility to cancer. On this genetic background, we are exposed to multiple different carcinogens in the form of diet, infections, chemicals, radiation, etc. These exposures are processed by the body to varying extents. The carcinogen can directly cause DNA damage or its risk may be modulated by intrinsic modulators. For example, each person processes the chemicals in tobacco smoke differently based on the genetic doses of modifying enzymes. In addition, the relative risk of exposures can be altered by extrinsic modulators, such as the anti-oxidants found in chemoprevention agents. Finally, the damaging factor must mutate a relevant part of the DNA. Many mutations occur in sequences of DNA that do not provide a survival advantage but rather in survival neutral or deleterious genome sequences.

15

Table 1. Comparison of cancer cells and members of an animal herd: an evolution / natural selection paradigm.

Examples of contributors to Examples of contributors to mutations in cancer cells successful selection and evolution in individual members of a herd Susceptibility allele Loss of BRCA1: increases Loss of gene to make horns chance of developing breast cancer Exposures Diet, carcinogens, radiation, Predators, weather, diet, viruses, microbes, viruses, microbes, water inflammation, chemicals, supply, etc. hormones, etc. Intrinsic modulators Drug metabolizing Length of legs, strength of pathways muscles, etc. Extrinsic modulators Antioxidants, cancer Size of the herd, place in screening, i.e., PAP smears, the herd when attacked, etc. ability of the herd to migrate in response to changes in environment, etc

16

Table 2. Comparison of the process by which a cancer cell acquires the traits necessary for metastasis and how humans successfully colonize.

Trait to allow growth and Cancer cell – clonal Human organism – dissemination expansion (unconscious) civilization expansion (conscious) Unlimited replicative Asexual reproduction, Sexual reproduction, desire potential activation of telomerase for survival Adaptation Genetic instability, natural Evolution, natural selection selection Protection from death Loss of apoptotic pathway Safety in numbers, city activation walls, castles, etc. No growth inhibition Anchorage independent Ability to move about as growth individuals or groups without constraint Nutrient supply Stimulate new blood vessel Building of water reservoirs growth and aqueducts to bring water to the population Population expansion Activation of proteases to Expansion / invasion into breakdown surrounding neutral territory tissue Evasion of enemies Evasion of the immune Avoiding contact with surveillance system, e.g., as hostile forces that want to cells circulate prior to prevent colonization, e.g., establishing themselves in a warships trying to prevent new organ colonial expansion Successful colonization Adaptation to the use of Building a new site, growth factors in the new learning to eat new foods, environment and applying and applying all of the traits all of the traits above in a outlined above in a new new environment. environment

17

Table 3. Cancer modeled as a complex adaptive system (CAS). These elements allow the emergence of the CAS.

Elements of a Complex Adaptive System Corresponding elements of a CAS in (CAS) cancer Agents: set of active components that Cells interact selectively Building blocks: provide a mechanism for The genes that cancer cells draw on to generating a wide range of rules, tags, and acquire the properties that are necessary for internal models from a small number of survival. This often requires the activation parts of genes that are normally turned off in normal tissue. Aggregation: components group together Cells with similar adaptive mutations according to similar abilities survive while others undergo apoptosis and die. Nonlinearity: a property resulting from One cell cannot produce enough VEGF to conditional (nonadditive) interactions stimulate new blood vessel growth to between agents supply the tumor with nutrients but many cells together can. Flow: a property mediated by the IF a cell produces proteases, THEN the movement of agents within the CAS. This tissue microenvironment will be broken can be represented by a series of IF/THEN down and a cell will be able to escape its rules local environment. Diversity: a property resulting when Genetic instability gives cells adaptive agents compete and adapt to fill available advantages that allow for clonal expansion “niches” within the system and survival of the fittest. Tagging: a mechanism that facilitates The tissue matrix of the cancer cells allows interactions between and among dynamic remodeling of the system. components Internal Model: a mechanism for Cancer cells turn on genes that allow them providing agents with anticipatory actions to use multiple growth factors from a variety of different organ microenvironments – key to successful metastasis.

18