A Shortcut to Preventing Cancer

According to a new idea, mutations have few simple mechanisms to establish themselves in cells and generate tumors.

The path to cancer prevention is lengthy and tough for many researchers, but a recent study by Rice University scientists reveals that there may be shortcuts.

Rice scientist Anatoly Kolomeisky, postdoctoral researcher Hamid Teimouri, and research assistant Cade Spaulding are working on a theoretical framework that will explain how tumors caused by several genetic abnormalities may be more easily diagnosed and possibly avoided.

It accomplishes this by recognizing and disregarding transition pathways that don't contribute significantly to the fixing of mutations in a cell that subsequently develops into a tumor.

The paper, which was published in the Biophysical Journal on May 13th, 2022, outlines their investigation into the effective energy landscapes of cellular transformation pathways linked to a variety of malignancies. The capacity to reduce the number of pathways to those that are more likely to start cancer might aid in the creation of measures to stop the process before it starts.

“In some sense, cancer is a bad-luck story,” said Kolomeisky, a chemistry and chemical and biomolecular engineering professor. “We think we can decrease the probability of this bad luck by looking for low-probability collections of mutations that typically lead to cancer. Depending on the type of cancer, this can range between two mutations and 10.”

It may be possible to predict how biomolecular systems would behave by calculating the effective energies that control interactions. The theory is extensively used to predict how a protein would fold based on the sequence and interactions of its component atoms.

The Rice team is using the same concept to study cancer start pathways that operate in cells but may contain alterations that are undetectable by the body's defenses. When two or more of these mutations are fixed in a cell, they are passed along to the next generation when the cell divides and tumors form.

According to Kolomeisky's calculations, the chances favor the most dominant routes, which move mutations forward with the least amount of energy expended.

“Instead of looking at all possible chemical reactions, we identify the few that we might need to look at,” he stated. “It seems to us that most tissues involved in the initiation of cancer are trying to be as homogenous as possible. The rule is a pathway that decreases heterogeneity is always going to be the fastest on the road to tumor formation.”

Narrowing down the vast number of viable paths appears to be an insurmountable challenge. “But it turned out that using our chemical intuition and building an effective free-energy landscape helped by allowing us to calculate where in the process a mutation is likely to become fixated in a cell,” Kolomeisky said.

The researchers began by concentrating on pathways containing only two mutations that, when corrected, result in the initiation of a tumor. More mutations may complicate computations, according to Kolomeisky, but the technique will stay the same.

Much of the credit goes to Spaulding, who developed the algorithms that considerably simplify the computations under Teimouri's leadership. When the visiting research assistant first approached Kolomeisky to seek advice, he was 12 years old. He joined the Rice lab last year at the age of 16 after graduating two years early from a Houston high school. He will attend Trinity University in San Antonio this autumn.

“Cade has outstanding ability in computer programming and in implementing sophisticated algorithms despite his very young age,” Kolomeisky added. “He came up with the most efficient Monte Carlo simulations to test our theory, where the size of the system can involve up to a billion cells.”

Spaulding said the project combined his interests in chemistry, physics, and biology with his computer programming talents in a way that he enjoys. “It was good way to combine all of the branches of science and also programming, which is what I find most interesting,” he explained.

The research builds on a report published in 2019 in which the Rice group studied stochastic (random) processes to figure out why certain malignant cells manage to escape the body's defenses and spread the disease.

Understanding how those cells become malignant in the first place, on the other hand, may help prevent them from becoming cancerous in the first place. “This has implications for personalized medicine,” he remarked. “If a tissue test can find mutations, our framework might tell you if you are likely to develop a tumor and whether you need to have more frequent checkups. I think this powerful framework can be a tool for prevention.”