Cancer evolution is mathematical - Big Think

Cancer evolution is mathematical – Big Think

Cancer is often thought of as a disease resulting from genetic mutations that cause cells to divide uncontrollably and invade other parts of the body. But the spread of cells far from their origins is actually a normal process in some cases. The embryo buries itself in the uterus at the beginning of pregnancy. Immune cells spread from the lymph nodes to sites of infection to attack invading bacteria. And the germ cells migrate to where the gonad will be in early human development.

Cancer is not a uniform disease. Cancer is rather a disease of phenotypic plasticity, meaning that tumor cells can change from one form or function to another. This includes reversion to less mature states and loss of normal function, which can result in treatment resistanceor by completely changing their cell type, which facilitates metastases.

In addition to the direct changes to your DNA in cancer, a key factor in cancer progression is where and when your DNA is activated. If your DNA contains the “words” that define individual genes, then epigenetics is the “grammar” of your genome, telling those genes whether to turn them on or off in a given tissue. Even though all tissues in the body have almost exactly the same DNA sequence, they can all perform different functions due to chemical and structural changes that change which genes are activated and how. This “epigenome“may be influenced by environmental exposures such as diet, adding a dimension to how researchers understand the drivers of health beyond the DNA code inherited from your parents.

I am a cancer researcherAnd my lab at johns hopkins university studies how differences between normal tissues are controlled by an epigenetic code and how this code is disrupted in cancer. In our recently published reviewcolleague Andre Levchenko at Yale University and describe a novel approach to understanding cancer plasticity by combining epigenetics with mathematics. Specifically, we propose how the concept of stochasticity can shed light on why cancers metastasize and become resistant to treatments.

What is stochasticity?

Stochasticity is a mathematical concept that refers to the idea that the randomness of the steps in a process affects the predictability of its outcome. Albert Einstein famous studied this concept applied to the movement of particles in suspension in a liquid or a gas. Researchers can apply stochasticity to study spread, resistance and evolution of COVID-19the behavior of sotck exchange and almost anyone gambling in a casino.

A key way to measure the stochasticity of a process is entropy, which quantifies the degree of uncertainty of a result. For example, a fair toss has an entropy of one, or low information, because there is no way to predict whether the toss will be heads or tails. But a weighted toss has zero entropy, or high information, because the outcome is already known and no new information will be gained by tossing the coin.

Researchers can use entropy to measure the amount of information noise in telecommunications. Entropy can also help players beat the wordle game. The word with the highest entropy and therefore the greatest new information expected after each guess would be your best bet.

Epigenetics links stochasticity and cancer

Integrating stochasticity and entropy into biology allows researchers to better understand phenotypic plasticity in cancer. It could even reconceptualize development by including reversibility or going against the “arrow of time”. It starts from a plus classical perspective of embryonic development which views tissues as gradually and irreversibly differentiating towards their final state as they develop.

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Experimental and computational biologists use entropy to understand the underlying randomness of how cells are internally organizedto respond to environmental signals And mature and form tissues.

Stochasticity in epigenetics is essential to the evolution of cancer. For example, a condition called Barrett’s esophagus occurs when healthy cells in the esophagus develop characteristics more like cells lining the gut, which can ultimately lead to esophageal cancer. This is caused by gradual random changes in the epigenetic code, and this change happens faster once it reaches a certain threshold. The stochastic nature of these epigenetic changes also leads to increased entropy in the function of these genes and progression to cancer.

By measuring gene activity and epigenetic changes in individual cells, biologists and mathematicians can compare the entropy of cancer cells with the normal cells around them. Scientists are now beginning to identify regions of the genome that mediate cancer stochasticity. A yet to be peer-reviewed study found that entropy is related to how chromosomes are physically packed together in the kernel, another key epigenetic mechanism to control gene activity in cancer.

There is also a connection between entropy and aging. My colleagues and I have found that human aging is associated with increased epigenetic entropy in sun-damaged skin. Parts of the genome that have high entropy experience further loss of epigenetic information in sun-exposed skin, which can lead to cancer. Recently, researchers have identified DNA damage as a cause of this age-associated entropy in mice. So if epigenetic entropy increases with aging and is linked to DNA damage, this could help explain why cancer risk rises sharply with age.

By identifying how epigenetic entropy triggers cancer, scientists could better detect cancer early and design drugs that reduce entropy and thus decrease the risk of tumor spreading and resistance to treatment.

And perhaps most importantly, epigenetic entropy shows that fully understanding cancer is impossible without math. Biology is catching up with other hard sciences by incorporating mathematical methods into biological experimentation.

This article is republished from The conversation under Creative Commons license. Read it original article.

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