Download 1 Modeling cancer as a complex adaptive system: Genetic instability

Modeling cancer as a complex adaptive system: Genetic instability and evolution.
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 natural selection 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 mutation to
the genome 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 mutations 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 (programmed cell death) 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 senescence 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) Adaptation, 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
growth factors in the new
environment and applying
all of the traits above in a
new environment.
Building a new site,
learning to eat new foods,
and applying all of the traits
outlined above in a new
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 47:235241, 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 dietderived 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
mutagenesis 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 169:115761, 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 anchorageindependent 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 nucleasestabilized 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,
Carcinogens
Intrinsic Risk Modulators:
Pharmacogenomics
Genomic damage
External Risk Modulators:
Chemoprevention
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
mutations in cancer cells
Susceptibility allele
Exposures
Intrinsic modulators
Extrinsic modulators
Loss of BRCA1: increases
chance of developing breast
cancer
Diet, carcinogens, radiation,
viruses, microbes,
inflammation, chemicals,
hormones, etc.
Drug metabolizing
pathways
Antioxidants, cancer
screening, i.e., PAP smears,
etc.
16
Examples of contributors to
successful selection and
evolution in individual
members of a herd
Loss of gene to make horns
Predators, weather, diet,
viruses, microbes, water
supply, etc.
Length of legs, strength of
muscles, etc.
Size of the herd, place in
the herd when attacked,
ability of the herd to
migrate in response to
changes in environment, etc
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
dissemination
Cancer cell – clonal
expansion (unconscious)
Unlimited replicative
potential
Adaptation
Asexual reproduction,
activation of telomerase
Genetic instability, natural
selection
Loss of apoptotic pathway
activation
Anchorage independent
growth
Protection from death
No growth inhibition
Nutrient supply
Stimulate new blood vessel
growth
Population expansion
Activation of proteases to
breakdown surrounding
tissue
Evasion of the immune
surveillance system, e.g., as
cells circulate prior to
establishing themselves in a
new organ
Adaptation to the use of
growth factors in the new
environment and applying
all of the traits above in a
new environment.
Evasion of enemies
Successful colonization
17
Human organism –
civilization expansion
(conscious)
Sexual reproduction, desire
for survival
Evolution, natural selection
Safety in numbers, city
walls, castles, etc.
Ability to move about as
individuals or groups
without constraint
Building of water reservoirs
and aqueducts to bring
water to the population
Expansion / invasion into
neutral territory
Avoiding contact with
hostile forces that want to
prevent colonization, e.g.,
warships trying to prevent
colonial expansion
Building a new site,
learning to eat new foods,
and applying all of the traits
outlined above in a new
environment
Table 3. Cancer modeled as a complex adaptive system (CAS). These elements allow the
emergence of the CAS.
Elements of a Complex Adaptive System
(CAS)
Agents: set of active components that
interact selectively
Building blocks: provide a mechanism for
generating a wide range of rules, tags, and
internal models from a small number of
parts
Aggregation: components group together
according to similar abilities
Nonlinearity: a property resulting from
conditional (nonadditive) interactions
between agents
Flow: a property mediated by the
movement of agents within the CAS. This
can be represented by a series of IF/THEN
rules
Diversity: a property resulting when
agents compete and adapt to fill available
“niches” within the system
Tagging: a mechanism that facilitates
interactions between and among
components
Internal Model: a mechanism for
providing agents with anticipatory actions
Corresponding elements of a CAS in
cancer
Cells
The genes that cancer cells draw on to
acquire the properties that are necessary for
survival. This often requires the activation
of genes that are normally turned off in
normal tissue.
Cells with similar adaptive mutations
survive while others undergo apoptosis and
die.
One cell cannot produce enough VEGF to
stimulate new blood vessel growth to
supply the tumor with nutrients but many
cells together can.
IF a cell produces proteases, THEN the
tissue microenvironment will be broken
down and a cell will be able to escape its
local environment.
Genetic instability gives cells adaptive
advantages that allow for clonal expansion
and survival of the fittest.
The tissue matrix of the cancer cells allows
dynamic remodeling of the system.
Cancer cells turn on genes that allow them
to use multiple growth factors from a
variety of different organ
microenvironments – key to successful
metastasis.
18