Concepts+of+Evolutionary+Biology+Applied+to+the+Treatment+of+Cancer

Purpose: **This wiki aims to highlight cancer treatment strategies that take on an evolutionary perspective, in particular that of benign cell boosters.**

toc =**Introduction:**=

Many of the concepts of evolution (such as natural selection) apply to the environment of a tumor as much as they apply to other traditional topics in evolutionary biology. A population of cancer cells in a tumor can be likened to any population of organisms in which natural selection takes place. Within a population of cancer cells, there is heritable variation, and this variation affects the survivability of each cancer cell (fitness). This heritable variation also allows cancer cells to divide and pass on their exact mutations to daughter cells.

At each stage of cancer development, cancer cells acquire mutations that give them a competitive advantage over neighboring cells. The mutations that cancer cells accumulate make them and their “progeny” well adapted to the harsh environment (low levels of oxygen and nutrients, etc.) of a tumor, relative to normal tissue. The mutations also enhance cell proliferation, which increases the size of the population of aberrant cells and the rate of tumorigenesis. Over time, the original mutant ancestor and its offspring can become the dominant clone in the tumor.



The rate of evolution in a population of cancer cells is dependent on:
 * The rate of mutation: genetic changes allow for cancer cells to become well adapted and survive in tumor micro-environments
 * The number of individuals in a population: cancer cells employ mechanisms to increase cell proliferation, which increases the number of individual cells in a tumor. The larger the population, the greater the chance for mutations that increase survivability of cancer cells.
 * The rate of reproduction: the more progeny produced, the larger the population, which again leads to higher survival rates for cancer cells.
 * Selective advantage enjoyed by surviving mutant individuals: the advantage conferred by mutations must allow cancer cells to survive and gradually become malignant.

=**How can we create treatments with this in mind:**=

Since a tumor is comprised of a multitude of cell types, each from different cell lineages, it is likely that in a population of cancer cells there will be a mutant which is resistant to chemotherapies we can apply. As Carlo C. Maley, Ph.D., an assistant professor in the Molecular and Cellular Oncogenesis Program at the Wistar Institute, adequately states:

"When you apply chemotherapy to a population of tumor cells, you're quite likely to have a resistant mutant somewhere in that population of billions or even trillions of cells. This is the central problem in oncology. The reason we haven't been able to cure cancer is that we're selecting for resistant tumor cells. When we spray a field with pesticide, we select for resistant pests. It's the same idea."

Much in the same way that when a field is sprayed and only the resistant pests survive and reproduce, when we apply chemotherapy we only kill the cancer cells which are not resistant to the drug. Essentially, what we are doing is weeding out the competition for the mutant, resistant cancer cells. The cancer cells that are resistant do not have to compete with other cancer cells within a neoplasm for nutrients and space, and are allowed to proliferate out of control and eventually become the dominant cell type. This, obviously, presents various problems: one being that if another drug were used to attempt to eliminate the newly formed tumor it would run the risk of selecting for another mutated cancer cell (a process that would seem to waste time); and second, this somewhat cyclical process might be costly for the patient (especially considering that some drugs may be more costly than others). However, if we look through at this problem through the lens of evolutionary biology, we can take advantage of the evolutionary processes occurring in various cancers and attempt eliminate resistant cells by:


 * 1) Emphasizing early detection and limiting the amount of time cancerous cell lineages have to evolve, thereby making the overall population less diverse - making the few, aberrant cells easier to target and eliminate through other means
 * 2) Attacking early cancer cells aggressively, eliminating the population before it has time to diversify (with the above goal in mind)
 * 3) Using a combination of drugs, since it is less likely that a mutant cancer cell will be resistant to a "cocktail" of drugs
 * 4) Targeting and inhibiting processes outside of cancer cells (such as angiogenesis) that aid in the development of tumors and that are not as diverse as cancer cells in terms of how they arise
 * 5) Manipulating cellular competition and helping benign cells or non-drug-resistant cell lineages outcompete the more aggressive cancer cells.

For our purposes in this project, we will mainly focus on the 5th treatment strategy. If we can find treatments that in some way create competition (such as it would occur in any population of organisms) among cancer cells and allow benign cells and non-drug-resistant cells to have a competitive advantage and be able to outcompete the more malignant cells that we cannot treat with more conventional methods, then we could reduce the recurrence of tumors in patients. = = =**Manipulating Cellular Competition:**=


 * Adaptive Therapy:** "The goal of adaptive therapy is to enforce a stable tumor burden by permitting a significant population of chemosensitive cells to survive so that they, in turn, suppress proliferation of the less fit but chemoresistant subpopulations."



Regular Chemotherapy uses the maximum dose possible in order to kill as many cells before the patient's symptoms become too severe (or even lethal). Keeping the patient at maximum toxicity is important because it allows more of the cells to die as quickly as possible. Maximum toxicity is the amount a patient can survive, or the tolerable amount of side effects a patient can live with. The problem with this is that within most tumors their are chemo-sensitive and chemo-resistant cells. The treatment kills all of the chemo-sensitive cells while leaving all of the resistant cells able to grow and proliferate as explained in the previous sections. This leads to recurrence with a neoplasm that is completely resistant to the former treatment.

However, the chemo-resistant cells are less fit than the sensitive cells in an environment without chemotherapy. This allows for the ecosystem within the cancer cells to regulate itself so that the sensitive cells will out compete the resistant cells, but when the sensitive cells are killed it gives the resistant cells an enormous advantage. They are able to grow and proliferate and share their mutation to all their offspring resulting in a new tumor that is completely resistant. The adaptive therapy approach uses the Darwin fitness model to try new methods of treatment. Instead of bombarding the tumor with chemotherapy, they plan to use a fixed amount to keep the tumor a safe size (meaning that the patient will essentially not notice it in terms of his health). Using this approach they allow the chemo-sensitive cells to be "pruned," while also allowing them to keep the chemo-resistant cells in an unfavorable environment.

According to Gatneby et. al., this approach has shown an increased survival rate in patients while also keeping the tumor size at a manageable level. This treatment also has hopes of a complete "cure" if the treatment is able to continue long enough. The potential is that the chemo-resistant cells will be out competed and die off completely due to the increased fitness of the chemo-sensitive cells. At this point treatment could be used to completely kill all of the sensitive cells and remove the entirety of the tumor. However, this is a best-case scenario. It would be hard to tell when the chemo-resistant cells had died off and when it would be appropriate to revert to the earlier form of treatment. Another advantage of the treatment is that if the cancer begins to get too large after adaptive therapy, you can fall back on the traditional methods and kill off the remaining chemo-sensitive cells to increase the lifespan as much as possible. Thus, it still allows for traditional therapy, which would just postpone, if nothing else, the time before the cancer becomes resistant.

There is, however, a newer treatment option that is being researched, which does something slightly different and could be more effective in preventing the recurrence of tumors (and possibly present a cure). The main difference is that the following treatment is still attempting to remove a cancer completely.

=**Benign Cell Boosters:**=

The general principle of this treatment is to increase the relative fitness of benign or chemosensitive cells with respect to more malignant cells. The increase in fitness of these cells will allow them to outcompete the more malignant cells and keep them from becoming the dominant cell type in the tumor microenvironment.

There are a few ways to increase the fitness of benign and/or chemosensitive cells:

1) Increase their proliferation rate

2) Decrease their rate of cell apoptosis and other forms of cell mortality

3) Boost their ability to compete for space and nutrients

Proposed advantages: these boosters would be nontoxic as they would not kill or damage cells; the booster would benefit not only preexisting benign cells in a neoplasm, but any dysplastic (cells with cytological abnormalities on the verge of becoming more malignant) cells that mutate into a more benign state (since the benign state would make cells more likely to survive, some of these abnormal cells might undergo a mutation that makes them benign in order to increase their fitness).

In a study (“Cancer Prevention Strategies That Address the Evolutionary Dynamics of Neoplastic Cells: Simulating Benign Cell Boosters and Selection for Chemosensitivity”) conducted by researchers at the American Association of Cancer Research (AACR), they performed an //in silico// (via computer simulation) experiment in order to determine the efficacy of such a therapy. We will examine this study in depth and provide our own thinking at the end to illustrate the potential limitations of this therapy and its effectiveness in comparison to other more conventional treatments. Due to the recentness of any such kind of therapy, this research is the only real major study done so far. Hence, our analysis of the effectiveness of such a therapy will be limited, but this study does offer some key information as to the potential future of benign cell boosters and related cancer-treatment strategies.

What the researchers did: Essentially, they simulated the evolutionary dynamics in a population of neoplastic stem cells. They represented each stem cell explicitly and simulated the processes of mutation, mitosis and apoptosis in each one. They distributed the cells on a 2d surface wrapped in the shape of a column to represent a Barrett’s esophagus neoplasm.


 * The Model:**

The researchers developed a computer-based simulation of a neoplasm with a set of parameters, as illustrated in the figure above. The parameters were constants that represented either the state of the cell (parameters involving loci, for example) or the environment of the cells ("Time of chemotherapy," etc.). These parameters came together to simulate a population of cancer cells in a neoplasm.

Researchers simulated a population of 4,096 cells (according to their research, other simulations of 10^6 cells have been shown to be qualitatively similar to smaller populations) that did not grow over time (simulating the characteristics of Barrett’s esophagus neoplasms). The cells divided on average once every four days within the simulation. The model simulated a period of 11, 22, and 33 years or 8,000, 16,000 and 24,000 “time steps”. Each time step simulated a period of 12 hours and was used to represent the state of a cell in terms of age. The state of a cell was also represented by a diploid set of loci (the location of a gene or DNA sequence on a chromosome). The four categories for the loci were:

1) Selective loci with dominant mutations (essentially oncogenes)
 * If a cell acquired a mutation in a single allele of a dominant locus, it conferred a selective advantage onto the cell (the mutation activated an oncogene that promoted cancer)

2) Selective loci with recessive mutations (tumor suppressor genes)
 * If a cell acquired a mutation in both alleles of a recessive locus, it conferred a selective advantage onto the cell (the mutation eliminated the tumor suppressor gene, which then caused the cell to become cancerous)

3) A mutator locus (a mutation in a DNA repair gene, for instance)
 * A mutation in a mutator locus would result in an increase in the rate of mutation

4) Various drug-resistance loci
 * A mutation in these loci would confer resistance to a drug associated with whatever locus was mutated

The “selective advantage” resulting from a lesion in a locus (just one mutation for a dominant allele and two mutations for a recessive allele) was a decrease in the average generation time of the cell by 12 hours per locus (making the cell divide faster). So the mutation in one locus (say a dominant allele) would cause the cell to divide once every 3.5 days (as opposed to once every 4 days as in the beginning of the simulation). As soon as a cell divided, one of the daughter cells would remain and the other would either die or kick out a neighbor with a 50% chance of either scenario (thereby maintaining the same number of cells at all times).

The researchers assumed that mutations were passed on at mitosis and that DNA synthesis was mitogenic, so essentially an increase in the rate of mitosis increased the rate of mutations over time – the more cells that divided (which was influenced by a mutation in one allele of the dominant locus or two alleles of the recessive locus of any one cell), the more mitogenic events that occurred, and thus the higher the mutation rate in the neoplasm.

So, how did they simulate the occurrence of mutations in the loci of each cell?

Mutations were simulated using a Bernouli process: per cell generation, an allele mutated with the probability of 10^-6. This value is roughly one order of magnitude higher than what is observed //in vitro// (normally, we see an allele mutated 1 out of every 10 million cell generations or mitosis events). Due to limited computer processing power (and time), however, the researchers had to increase the rate of mutation. Furthermore, once a mutation occurred in a loci, a separate parameter was used to determine whether the mutation was reversible.
 * Note: when a mutation occurs, there is a small probability that it can mutate back to its original form

The researchers defined the latest dysplastic stage (before the neoplasm would move into stage four) as mutations in three dominant loci and two recessive loci (with both recessive alleles mutated). They called this stage "high-grade dysplasia" (HGD). After the simulation ended at 33 years, the researchers ran the model for an additional 5 years to check for the presence of these high-grade dysplasia cells (as this would indicate the effectiveness of the particular method of treatment they were examining)


 * Modeling Cytotoxic Therapies:**

Researchers applied Cytotoxic therapies in single time steps. The efficacy of the therapy was represented as the likelihood of the therapy killing a sensitive cell in one time step (which occurred 100% percent of the time in their results). In order for a cell to become resistant to a drug, the number of independent drug resistance loci that would have to be mutated would need to be equal to the number of therapies applied. For example, if a cocktail of 3 drugs were simulated, then a cell would need mutations in three independent loci in order to survive. The researchers did not take into account loci that conferred resistance against multiple drugs, however. They simulated each parameter (the number of drugs applied, r = 1 to 6) at least 2,500 times and close to 169,200 times for conditions that had a low probability of producing HGD. Again, they could only test the efficacy of the drugs in high-grade dysplasias. They also varied the mutation rate from 1x10^-6, 2x10^-6, 4x10^-6and10^-5.


 * Modeling Benign Cell Boosters:**

The benign cell boosters targeted specific loci, and only cells that did not have a mutant allele at the locus were affected (i.e. were sensitive to the booster). In order to simulate a benign cell booster, researchers decreased the generation time of benign cells that were sensitive to the supposed booster drug. Sensitive cells divided one time step faster than HGD cells (once every 3.5 days). They simulated four different kinds of benign cell boosters:

1) One that targeted a locus lacking a mutation in a dominant allele

2) One that targeted a locus lacking two mutations in recessive alleles (cells with one mutation in a recessive allele, but one wild-type allele were still sensitive to the booster drug).

3) One that targeted the mutator locus

4) One that targeted a cytotoxic drug resistance locus

The boosters were applied for a period of 5 years after the 33-year simulation in order to facilitate cellular competition.

For their study they used three variations on the model. The first one was a combination of cytotoxic chemotherapies, the second was benign cell boosters, and the third was a mix of both benign cell boosters and chemotherapy. They applied the drugs for each of the three condition at four separate time points: 11 years (8,000 time steps), 22 years (16,000 time steps), 33 years (24,000 time steps), and five years after therapy was finished. They defined a cure as the presence of high grade dysplasia (HGD) before treatment, and the absence of HGD five years after the treatment. Minimal residual disease was characterized by less than 1% occurrence of HGD cells five years after the therapy.
 * Results:**

(Cancer Epidemiology, Biomarkers, and Prevention)
 * Cytotoxic Drugs**: The results of using multiple drugs showed high efficacy in newly developed neoplasms with low mutation rates. When mutation rates rose, over time, the cytotoxic therapy became virtually useless (less than 10% effective).

In this figure, when the mutation rate was low (1e-06) a combination of 6 drugs at 33 years yielded close to 100 percent of cured patients. As the mutations rate increase, however, the efficacy of the drugs decreases significantly after the initial 11 year period. In the last scenario, the efficacy of the drug is low throughout the entire 33-year period (although a small rise occurs between the use of 2 and 3 drugs - this might be the result of an error, but there is no mention of it within the study).

(Cancer Epidemiology, Biomarkers, and Prevention)
 * Benign Cell Boosters Alone**: Benign Cell Boosters alone were applied for the five years of follow up. Instead of a complete cure where 100% of malignant cells were terminated, Benign Cell Boosters would more often result in minimal residual disease where less than one percent of high grade dysplasia remained.

The boosters would target cells without mutations, but there was a chance that the dysplastic cells would out compete the benign cells. However, because the cells always had the ability to revert back from their mutations dysplastic cells could lose their mutation and begin to benefit from the booster as well as the cells that had never mutated. After time, this increases the fitness of benign cells so they are able to out compete the HGD cells. The boosters were most effective where there was the least amount of mutation. They found that mutations at the mutator or neutral loci were not necessary for creating High Grade Dysplasias and thus selecting for wild type phenotypes was not successful in the prevention of HGD cells. The only time the booster failed was when it was selecting for genes that indirectly increased dysplastic growth or if the booster was started too late. If the booster was started at a time point when the dysplastic cells had already completely taken over the benign cells, or had left a population so small they could not grow regardless, then it was not effective.


 * Cytotoxic Therapies and Benign Cell Boosters**: Three different styles were tried using the combination of cytotoxic therapies and boosters. The first was using both simultaneously, the second was using benign cell boosters and five years after with the follow up attacking with chemo, and finally the "Sucker's Gambit". The Sucker's Gambit increased the proliferation rate (fitness) of cells that are not necessarily benign, but sensitive to cytotoxic therapy. After these Chemo sensitive cells had out competed the other cells heavy doses of cytotoxic therapy were used to completely eliminate the tumor.

(Cancer Epidemiology, Biomarkers, and Prevention) In early stages (11 years) all the treatments work well. At later stages (33 years) the Sucker's Gambit has a much higher rate of complete termination of all HGD cells (Fisher's Exact test P < 0.001). The booster alone and multiple cytotoxic therapies alone seem to function similarly, but boosters were only able to get the neoplasm to a state of minimal residual disease, as opposed to complete removal by cytotoxic therapies.


 * Discussion (from study): **

It seems that benign cell boosters, unlike other traditional therapies, are effective even late in progression. This would be a major advantage considering that for many patients the efficacy of drugs seems to decrease the longer they take them (again, this relates to the issue introduced in the very beginning of the wiki that drugs select for resistant cancer cells, and eventually the resistant cancer cells become the dominant cell type in the tumor population). However, they must be applied over longer periods of time in order to foster the competition necessary to drive the dysplastic cells to extinction. Moreover, the booster must also target a characteristic of cells that is related to the benign state (in other words, the booster must target a loci that is conferring the benign phenotype onto the cell). Otherwise, we might also target dysplastic cells that carry the same target. It is possible for dysplastic cells to develop extracellular factors that prevent the benign cell booster from doing its job, thereby achieving a “resistance” to the booster (although the cells are resistant in the sense that benign cells will not be afforded the opportunity to compete with them for resources). These limitations, and more to follow, all bring into the question the effectiveness of benign cell boosters.

From the results presented, it seems that the boosters resulted in minimal residual disease (essentially a constant number of HGD cells were around, but never fully developed). This process of maintaining a low and relatively harmless number of dysplastic cells is similar to the “pruning” analogy associated with adaptive therapy. Benign cell boosters might be effective in simply preventing the emergence and growth of new HGD cells. Their results also suggest that a combination of cytotoxins and boosters that select for chemosensitivity (not necessarily a “benign” phenotype) can also be effective in treating cancer ( the suckers gambit showed the highest rate of termination of HGD cells after 33 years). Although, the representation of chemotherapy was simplified in that the researchers did not vary the drug dosage that cells experienced after the application of the benign cell booster – due to physical formation of a tumor, certain cells would be more exposed to drugs than other cells (mainly those cells in the interior of tumors would be less exposed). This surely would impact the results that the researchers collected with respect to the efficacy of cytotoxins with and without benign cell boosters.

Furthermore, their work illustrates that benign cell boosters fail mostly when there are no benign cells left to boost or improve. In the following figure, we can see that where non-benign phenotypes could be back mutated to a benign state, the previous constraint did not influence the effectiveness of the benign cell booster.

However, back mutations are much more uncommon, and mutations that make up for previous deletions are much more likely to occur.

The researchers further suggested inoculating neoplasms with benign cells (where there were no more benign cells left to boost) - literally injecting cancer cells (although benign) into a patient! This, however, and they realize this in their following statement, would not work for tumors that have metastasized. This is because the malignant cells in metastatic tumors are no longer spatially constrained. It would not be practical to inject benign cancer cells in all places the tumor metastasized. There is also the unavoidable outcome that injecting cells would increase the mass of the neoplasm dramatically; the mass could be surgically removed, but this would depend on the location of the tumor, although this might not be the case in all tissues (as in this particular study with Barrett’s esophagus neoplasm, which tend to remain constant in size even with the advent of benign cell proliferation). Furthermore, there is always the possibility that the injected benign cells could pick up a mutation making them dysplastic and the booster would increase their fitness and lead to them proliferating, although this is a general problem with benign cell boosters (as benign cells already being boosted could mutate into malignant cells).

Another interesting point that the researchers make clear is that they only looked at one particular mechanism of boosting benign cells: through reproduction. As illustrated in the model, the only difference between HGD cells and cells sensitive to the booster was that the latter divided one time step faster. There could be other ways of boosting the fitness of benign cells (such, as the researchers suggest, by reducing the rate of apoptosis in benign cells) that could also them outcompete the dysplastic cells.

Lastly, it is important to recognize that this model and these results are all based on experiments // in silico //. The researchers realize that the next step in this research would be to do experiments // in vitro // or in animal models (most likely mice). It would also be necessary to include interactions between benign cells and dysplastic cells resulting from cytokines (small cell-signaling protein molecules used for intercellular communication – Wikipedia) and contact inhibition (a characteristic of normal cells to stop proliferating when they come into contact with one another).


 * Steps to Developing a Benign Cell Booster:**

Something important to note is that there is a chance that benign cell boosters already exist and are even at work in current medications. However, because researchers are only currently looking for drugs that affect malignant cells they have not been noticed yet (no one is looking for drugs that improve the fitness of benign cells). So the first step would be do develop ways we can detect these benign cell boosters, and once we learn more about how they work, we can focus on how to make them.

The premise behind benign cell boosters is altering the cellular environment to give a competitive advantage to benign cells so they can out compete malignant cells. They have already found several drugs show promise for giving benign cells an advantage. These include a change in diet, eating selenium, cyclooxygenase-2 inhibitors, or nosteroidal anti-inflammatory drugs. (Cancer Epidemiology, Biomarkers, and Prevention)

They plan on starting the search for potential benign cell boosters by screening for clonal competition. The theory they provide for this screening is taking two distinct clones where one was more dysplastic than the other. Then the two clones would be injected together into an animal, which would be used as a model for a human. They predict that without any drugs the more dysplastic clone would out compete the benign clone. Benign cell boosters could then be identified by those that produce neoplasm populations of the purely benign clone. After they have found potential benign cell boosters such as these than they will repeat it on different types of cells and different cell lines until they establish its effectiveness.

The researchers looked at one model done by Akakura et. al. that could be used to indicate intracellular competition between benign and malignant cells in a neoplasm. In that study, the researchers tested androgen dependent cells by turning androgen on and off and determining if the androgen dependent cells would die off and leave the androgen independent cells. Androgens are a group of hormones that include testosterone and androstenedione; androgens are also converted to estrogens, which are known to cause several types of cancer. This model demonstrated how an androgen sensitive clone may have a competitive advantage when androgen suppression was halted. If they could link androgen sensitivity to benign cells then this would be a start. The benign state could then be linked to androgen independence or dependence.

However, they state that this is reliant on all the cells that are androgen dependent being benign (or vice versa) so that they can control which are at a competitive advantage. It seems unlikely that all the cells would be divided so nicely.

This model is promising for clonal screening. They propose that by changing the substrate and putting it into the neoplasm you could select for cells dependent on that substrate. After the neoplasm has grown you would remove the substrate and calculate regression, and define the particular cells that are using this substrate. This could be beneficial because even if a treatment is not discovered they could still delay the cancer progression by stopping consumption of nutrients or substrates that are beneficial to the neoplasm.

Throughout all of these experiments and hypotheses they claim that, "designing a therapy to boost benign cells proved infeasible, without also boosting the dysplastic cells," (p. 1383) demonstrating that they are not actually able to produce a benign cell booster at this time. However, they say that they could use the "Sucker's Gambit" with these treatments and models. They would infuse the neoplasm with a substrate that was similar to the cytotoxic drugs so that the cells that could absorb it (Chemo-sensitive) and would have a competitive advantage. Then, after the cells had out competed the substrate independent cells, they would infuse the cells with cytotoxins that act similarly to the substrate, hopefully removing the neoplasm.

Finally they give guidelines for producing these experiments which will be useful for future studies, so that the validity of the experiment can be determined before too much labor has been expended. Their model shows that selecting for loci that are directly related to carcinogenesis is more effective than selecting for loci indirectly related to carcinogenesis via genetic instability. Their study also demonstrates that benign cell boosters would only be effective if it gave the benign cells a significant advantage.

=**Limitations:**=

1) The entire test was //in silico // i.e. a computer simulation. This is beneficial for generating potential outcomes, but it does not show how real cells and organisms would react. Due to the nature of the program the cells are limited by the constraints of the program, and thus it is only as realistic as the programmers are able to make it. There are many aspects that seem to imitate actual cells but are not exact. Throughout the model they have a fixed population of cells (4,096), realistically the population of the neoplasm would grow as the cells proceeded to proliferate. They did this in order to focus on the proportions of benign versus dysplastic and other ratios within the cells, but it does not accurately portray life, which could effect their results and how they would react with non-simulated cancer tissue. There are other issues with inaccuracy that are present due to the sheer complexity of a living model that cannot be accounted for within a computer system. But, d ue to the absence of benign cell boosters and the inability to create them, this study gives an insight into how these treatments could potentially be used and could give insight into methods for developing these therapies.

2) Another issue we found was in their use of the model of androgen dependent and independent cells. By using this model they stated that if cells happened to be benign they would also have to be androgen dependent. This seemed unlikely that all the androgen dependent (or independent) cells would also be benign. It is possible, but it would mean that the genes for androgen dependence and malignancy would need to be linked in order for this theory to be true. And since this theory is the basis for most of their future tests it is important that it supported. This could be another way treatments are looked at, though. If they are able to find where a malignancy arises and find if there is a gene next to it that codes for something else, then they could develop and test a benign cell booster that way.

3) The entire experiment was done on a two-dimensional surface, wrapped up (like a tube) to represent the barrett's esophagus neoplasm. The researchers stated that although a three-dimensional model could have been used, they decided against it. We are quite surprised that they chose not to do so (they do not give any further explanation as to why they did that) considering that they later make the point (highlighted in the discussion section) that cells along the interior of a tumor would not be as exposed to applied cytotoxins as those on the surface of the tumor. In a two-dimensional figure, one would imagine that all the cells would be exposed to the drug since there are no cells on the interior (the tube is "hollow"): this would inflate the results (it would seem as if the a cytotoxin was more effective than it would actually be in culture). A three-dimensional model would have yielded results more closely related to what the actual efficacy of a particular drug might be. Furthermore, the researchers results showed that a combination of benign cell boosters and cytotoxins resulted in lower levels of HGD cells (closer to "cured"), but these results might also be skewed since the two-dimensional model was utilized.

4) Although a benign cell booster has not yet been developed, the premise of a drug of that nature is that it would foster competition between benign and dysplastic cells. This, however, would take some time: the benign cell booster would need to be applied over a long period of time to create the intracellular competition necessary to drive the dysplastic cells to extinction. There are two issues that arise out of this predicament: one involves money and the other involves time. Again, a benign cell booster has not yet been developed, so we are merely speculating, but presumably a booster would need to be applied multiple times throughout a patient's life (as was done in the simulation). Each application of the booster (unless patients could buy enough at one point to somehow last them for their entire lives) would cost money; unfortunately, the money required to buy the booster might be out of a patient's fiscal reach. With respect to time, a patient might not live long enough to see the effects of the benign cell booster. If the benign cell booster takes time to increase the fitness of benign cells and then even more time in seeing the gradual extermination of the dysplastic cells, a patient might die (due to the effects of the tumor) before the benign cell booster could bring his tumor under control.

=Are Benign Cells Boosters Worth It?=

Benign cell boosters have shown great potential for slowing the development of malignant cancers, and potentially even curing cancers completely. They show promise in reducing the amount of dysplastic cells and using the Sucker’s Gambit they were simulated to completely cure a neoplasm. If a benign cell booster was discovered, we would certainly recommend it as a viable option (although tests in culture and human models would need to be conducted in order to confirm the validity of the simulation in the study). However, finding a way to actually develop these treatments proves problematic at the moment, as we have described previously. As of now, there is no way of creating a drug that will target a specific loci associated with a benign state (we have no way of making drugs that selective or knowing what loci are associated with a benign state). Furthermore, there are no concrete plans that have been established in order to try and find benign cell boosters (trying to find to just find plausible substrates or nutrients that would have this effect on cells could take an extraneous amount of research anyways). Because of this we do not recommend an increase in the research of benign cell boosters, and instead think it would be more pertinent to focus on other therapies, that are equally promising, but more **accessible**. Adaptive therapy for example has been used and tested with promising results.

(Gatenby et. al.)

Results of animals who have been treated with adaptive therapy (green), no treatment (blue), and standard chemotherapy treatment (Pink) Adaptive therapy demonstrated a significantly smaller mean tumor burden than both other groups.

We believe that resources for cancer research should be allocated to other areas, such as adaptive therapy or other similar treatments, as opposed to benign cell boosters. While benign cell boosters should definitely continue to be studied, we recommend that they not reach the forefront of the research for cancer treatment. Potentially, in a few years it might be more feasible to develop and discover benign cell boosters. However, until this day we cannot recommend them over more conventional therapies.

=References:=



The Wistar Institute. "Does Natural Selection Drive The Evolution Of Cancer?." //ScienceDaily//, 17 Nov. 2006. Web. 31 May 2012.

"Another Perspective on Cancer: Evolution Within." Understanding Evolution. University of California Museum of Paleontology. 22 August 2008 

Maley, Carlo C., Brian J. Reid, and Stephanie Forrest. "Cancer Prevention Strategies That Address the Evolutionary Dynamics of Neoplastic Cells: Simulating Benign Cell Boosters and Selection for Chemosensitivity." //Cancer Epidemiology, Biomarkers & Prevention// (2004): 1375-384. //Cancer Prevention Strategies That Address the Evolutionary Dynamics of Neoplastic Cells: Simulating Benign Cell Boosters and Selection for Chemosensitivity//. American Association for Cancer Research, 18 Mar. 2004. Web. 31 May 2012. .

Gatenby R.A., Silva A.S., Gillies R. J. and Frieden B.R. (2009) Adaptive therapy. Cancer Res 69:4894-4903 "[|http://cancerres.aacrjournals.org/content/69/11/4894.full.html#related-urls]"

Gatenby, R. A. (2009). A change of strategy in the war on cancer. // Nature //, // 459 // , 508-509. Retrieved from http://www.nature.com/nature/journal/v459/n7246/full/459508a.html