Cancer therapy

The evolutionary approach

Cancer Therapy: An Evolved Approach Cassandra Willyard, Scientific American

Translation: InoSMI

About six years ago, Alberto Bardelli felt a decline in his scientific work. As a biologist and cancer specialist at the University of Turin in Italy, he studied targeted therapies using drugs tailored to those mutations that cause tumor growth. The chosen strategy seemed promising, and the condition of some patients began to improve strikingly. However, at some point, inevitably, their tumors became resistant to drugs. Bardelli saw their illness escalate again. "I hit a wall," he admits. Bardelli realized that the problem was not related to specific mutations: it was evolution itself. "Unfortunately, we are dealing with one of the most powerful forces on our planet," he emphasizes.

Scientists have long understood that tumors evolve. As they grow, mutations arise and genetically special cells appear. These cells, which are resistant to the drugs used, survive and expand. Whatever drugs doctors use, tumors, apparently, adapt to them. And it is difficult for scientists to stop this process, because it develops inside the body for a long time. "Previously, we constantly told patients that cancer develops in a Darwinian style, but we did not have a huge amount of data at our disposal so that it could actually be formally proved," notes Charles Swanton, a specialist in cancer diseases at the Francis Crick Institute in London (Francis Crick Institute).

But the situation is starting to change. Thanks to advances in step-by-step technology, the creation of large-scale collections of samples and clinical data, scientists are getting a more accurate picture of how cancer evolves, and at the same time the underlying causes of resistance are revealed, and in some cases, it becomes clear how it can be overcome. Currently, there is an increase in the arsenal of therapeutic possibilities, and biologists are trying to take advantage of the results obtained.

"Cancer is constantly adapting, and therefore we need to do the same," Bardelli emphasizes. In the same spirit, last year he shifted the focus of his laboratory's work towards studying the evolution of cancer. His team has developed a model of how colon and rectal cancer responds to targeted therapy, which is used in combination and which, potentially, can show the ways in which it will be possible to prevent tumor cells from gaining resistance. "We have excellent data regarding the ability to detect evolution and influence it," he said.

Tree of Life

Cancer cells have an amazing set of mutations. In 2012, when Swanton and his colleagues analyzed numerous biopsy variants taken from people suffering from kidney cancer, it turned out that none of the samples were repeated. Members of his team studied not only primary, but also satellite tumors – so–called metastases - spreading through the body of patients. In each of them, the team members found more than 100 mutations in various analyzed tumor samples, and only a third of their total number was detected in all samples.

The relationships between different cancer cells of the same person can be represented in the same way as evolutionary biologists depict the relationships between species: you can draw a phylogenetic tree and branch schemes, along which you can trace the path of "descendants" to their common ancestors. Mutations occurring in the first malignant cell, marked on the trunk of the evolutionary tree, end up in tumor cells, while those mutations that occur after can be detected on the branches of the tree. In order to destroy the tumor, it is necessary, according to Swanton, to attack mutations in the trunk.

There are already therapies aimed at these stem mutations, and they often show amazing results at the first stage. But then there is the resistance that Bardelli is talking about. "To a large extent, we are fixated on the idea that the smaller the tumor, the better, but we lose sight of what remains after it," Swanton emphasizes. "There are often resistant clones that are not amenable to treatment." However, he believes that by targeting multiple trunk mutations at the same time, researchers can try to destroy cancer cells. The chances of an individual cancer cell evading two or three prolonged attacks are small.

One possible way to achieve this is to use combinations of targeted therapies. "In theory, this option could work," says Bert Vogelstein, a cancer genetics specialist at the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University in Baltimore, Maryland. In fact, when he and evolutionary biologist Martin Nowak from Harvard University in Cambridge, Massachusetts, modeled this strategy, they found that two targeted drugs, against the effects of which there is no common resistance mechanism, would be enough to control metastatic cancer. For people with a large number of metastases, this model suggests the use of three therapies.

Specialists have already started testing combinations of targeted therapies in clinical settings. However, Swanson emphasizes that today there are no targeted drugs for a significant number of mutations. And combining existing drugs in a way that would not harm the patient turned out to be a difficult issue. Therefore, Swanson focused his attention on immunotherapy – that is, on a strategy that helps the immune system recognize and eliminate cancer cells.

The immune system recognizes threats, in part, by observing the surface of cells and searching for molecules called antigens that can transmit signals about the presence of problems inside. Genetic defects in the DNA of a cancer cell can sometimes encode antigens, which then trigger an immune response. However, Swanton and his colleagues are not sure of the importance of the question of whether the immune system responds to the antigen emerging from the evolutionary trunk of cancer, or to the antigen that arises in its branches.

In an article published in March, Swanton and his colleagues studied samples from the Cancer Genome Atlas, a collection of genetic and clinical materials obtained from several thousand people with cancer. The researchers concluded that lung cancers with a large number of stem antigens – as well as a significant proportion of stem antigens compared to branch antigens – live longer than those with either few stem antigens or a higher proportion of branch antigens. Moreover, people with a large number of stem antigens seem to respond better to immune therapy. According to Swanton, this makes sense, because the immune system identifies stem antigens as its targets and strikes at most cancer cells, rather than "plucking off small twigs."

This kind of research is still at its early stage, but Swanton is conducting clinical trials as an example that can confirm his conclusions. The study, called TRACERx (Tracking Cancer Evolution through Treatment (Rx), will monitor 850 people diagnosed with lung cancer during their treatment, and in some cases until the very moment of their death. In the course of this study, genetic changes in their tumors will be documented in order to understand how cancer evolves and how treatment affects this process. When Swanton gets this kind of data, he hopes to raise enough money to test an evolution-based treatment strategy.

One approach will be to identify immune cells in the tumor, grow them in the laboratory and return them to the patient's body – this technique is called adaptive cell transfer. Such strategies, which are already being used, make it possible to identify immune cells capable of recognizing any cancer antigens, but Swanton's team will choose those that primarily recognize stem antigens that appear on all cancer cells.

This strategy will not be cheap, but it is not cheap either, in which a number of targeted therapies receive a small amount of funding, which ultimately do not give any result. "Each course of therapy costs from $10,000 to $100,000," says Swanson. If scientists can develop a therapy that can cure cancer metastases, then "the entire cost-benefit analysis, as well as economic models of health, will be significantly changed."

Cellular rivals

The application of evolutionary principles can help the immune system defeat tumors. Robert Gatenby, a molecular oncologist at the Moffitt Cancer Center, located in Tampa, Florida, sets himself a more modest task: he hopes to help people live with this disease. Gantby began analyzing cancer as an evolutionary problem in the early 1990s when he worked at the Fox Chase Cancer Center in Philadelphia, Pennsylvania. He saw so many people with relapses that cancer began to seem to him less of a biological problem and more of a sorcery. "It looks like a substance representing the forces of evil, which constantly returns and nullifies all the most worthy efforts." But when he began to think about cancer from the point of view of evolution, the problem again began to seem solvable.

Gantby began to create a mathematical model of this disease to develop the best treatment option for it. His model proceeds from the fact that many oncologists use the wrong approach. Usually doctors prescribe the maximum dose of chemotherapy that a patient can withstand, and thus assume to destroy as many cancer cells as possible. At the same time, they hope that they will be able to destroy the cancer even before there is resistance.

However, recent studies show that in cancer tumors, drug-resistant cells are formed long before the start of therapy. The population of resistant cells remains insignificant, because the ability to resist strongly affects well-being. If a patient receives a significant dose of chemotherapy, resistance cells become more active than those that are susceptible to drugs. Gantby compares resistance to drugs with an umbrella: "If it rains, the umbrella turns out to be very useful. But if it doesn't rain, it turns into a burden." Gantby believes that he will be able to use the natural competition between susceptible and resistant cells due to different dosage options and the time of use of drugs.

He recently tested this idea on mice with two types of breast cancer. When he and his colleagues exposed mice to the standard maximum permissible dose of chemotherapy using paclitaxel, tumors immediately reappeared as soon as the treatment process was over. His team also tried to skip sessions when the tumor began to shrink, but this did not give a positive result. The third group of mice received a standard dose of chemotherapy, but at the moment when their tumor began to shrink, the specialists reduced the dose of exposure. It was this strategy that proved to be the best for the survival of mice, and its application allowed three out of five test mice to continue to live without taking medications.

Such a treatment option involves adapting to how the tumor responds to therapy, as well as maintaining a balance between resistant and susceptible cells. "In my opinion, this is one of the most striking achievements in the field of cancer biology, because it is a relatively simple option," says Carlo Maley, a biologist at Arizona State University in Tempe, working with the Gantby group.

In May 2015, the Mottiff Cancer Center launched a pilot study to determine whether an approach based on such adaptive therapy could help people suffering from prostate cancer. Doctors will examine the levels of prostate specific antigen (PSA), a kind of marker of the development of this disease. Then they assume to use the standard method or stop using it depending on what they see. Scientists have used intermittent therapy in the past, but the protocols used were based on strictly controlled cycles. "In the case of adaptive therapy, the use–not-use cycles are determined by the reaction of the tumor," Gantby emphasizes. He also plans to use the molecular and clinical data accumulated during attempts to develop computer models capable of controlling the adaptive therapy process in the future.

Double message

Doctors have discovered the work of another evolutionary paradigm. In January, Jeffrey Engelman, a breast cancer specialist from the Massachusetts General Hospital in Boston, Massachusetts, and his colleagues described in detail in the New England Journal of Medicine the treatment process of a 52-year-old patient suffering from lung cancer and metastases caused by it. Genetic changes occurred in the tumor of this woman, as a result of which a deformed version of the ALK protein was formed, and therefore doctors first used the drug crizotinib (crizotinib), which restrains the actions of ALK. The patient had a positive reaction, but then a relapse occurred.

The second-generation therapy also proved to be ineffective, and therefore, less than a year later, doctors switched to the third-generation therapy, which is still in clinical trials. This method gave a positive result for some time, but after less than a year, this woman's liver began to fail, and she had to be hospitalized. The doctors then discovered that the third-generation therapy had caused a new mutation that made her cancer susceptible to crizotinib again. When they started using this drug, her kidney recovered and her condition improved to such an extent that she was able to leave the hospital.

For Engelman and his colleagues, this woman's renewed susceptibility to crizotinib turned out to be a happy accident. However, doctors will probably be able to intentionally direct cancer along this path. Gantby calls this strategy evolutionary with a double bond, and he explains it this way: imagine trying to control the rat population by using predators such as hawks, which are able to grab their prey by falling on it from the sky. This type of predator behavior selects in favor of those rodents that hide under the bushes. Therefore, you can add snakes that are also hiding in the bushes. Snakes will promote selection in favor of those rats that prefer open space, which will make them vulnerable to hawks, explains Gantby. The same idea can be applied to cancers. That is, you can use one treatment that will make the cancer susceptible to the action of another, and then apply them alternately.

"This is not a whack-a-mole game," says Gantby, "but rather an elaborate method using evolutionary dynamics."

Most likely, here we are not referring to a computer game 40 years ago, but an idiom like the Russian "monkey labor" - VM

This is exactly the strategy that Ben Solomon, a cancer specialist at the Peter MacCallum Cancer Centre in Melbourne, Australia, plans to use during the upcoming trials. Many people suffering from lung cancer have mutations in a gene called EGFR. Some drugs have been approved to affect EGFR mutations, but tumors are constantly developing resistance to them. In about half of the patients, this resistance is caused by a mutation in the EGFR, called T790M. Last year, the U.S. Food and Drug Administration approved a targeted drug called osimertinib (osimertinib), which inhibits standard EGFR and T790M mutations, but patients who respond to it face relapse within a year.

Solomon and his colleagues plan to start testing the drug osimertinib on patients, and then monitor resistance by examining the DNA of the tumor circulating in their blood. The researchers expect to see a reduction in mutations in T790M. When that happens, they will switch to using the first generation EGFR inhibitor, which does not restrain T790M. When the T790M level rises, specialists will return to using osimertinib. "Our hypothesis is that this will delay the emergence of resistance to osimertinib, because we do not maintain this level of selective pressure," Solomon emphasizes. He hopes to get final approval for his research soon.

There is no guarantee that any of these strategies will be successful. But even if the planned experiment fails, its results will help researchers refine their theories and address some more significant and as yet unknown questions. For example, how do genetically diverse cells in a tumor interact with each other, and what is the role of the cellular environment they possess? Kornelia Polyak, an oncologist at Harvard Medical School in Boston, believes that cancer researchers are more focused on mutations inside the cell and do not consider how mutated cells can affect the cells next to them. "This is a largely unexplored area," she says.

The dynamics inside the tumor is extremely complex, but Edelman is not afraid of this. Clinical analysis will help researchers understand this problem. "Such guesses will allow us to get closer to the possibility of having an increasingly significant impact," he says. – Depressive feelings arise when you don't know what is happening to us at all."

This article is reprinted with permission, and it was first published on April 13, 2016.

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