Texas Tech University

Chemistry Professor Studies Cancer Treatments Without Risk to Subjects

Glenys Young

May 10, 2017


Jorge A. Morales is using a supercomputer to discover how cancer therapies work.

Jorge A. Morales
Jorge A. Morales

Cancer doctors and researchers know radiation therapy works, but they don't know exactly why. Testing this question in human subjects would be possible, but it would add further health risks to people already suffering from cancer.

So Texas Tech University's Jorge A. Morales, an associate professor of chemistry, is taking a different approach. With the use of a supercomputer, he's helping to give scientists a better understanding of the process without risking the lives or health of cancer patients.

Radiation therapy, a standard cancer treatment, shoots high-energy particles into the body to destroy or damage cancer cells. Despite a century's worth of technological improvements that have made the process highly effective, physicians must still walk a fine line to deliver enough radiation to kill tumors, while sparing surrounding healthy tissue.

"Historically, radiation has been a blunt tool,” said Matt Vaughn, director of Life Science Computing at the Texas Advanced Computing Center (TACC). "However, it's become ever more precise because we understand the physics and biology of systems that we're shooting radiation into and have improved our capability to target the delivery of that radiation.”

SLEND simulation of H+ + cytosine at = 1 keV (C=grey, H=white, colliding H+=yellow, N=blue and O=red).
The simulation predicts the cytosine's ring opening and the ablation of a NH2 group as prototypical reactions of proton-induced DNA damage reactions during proton cancer therapy.

X-ray radiation is the most frequently used form of high-energy treatment; however, a new treatment is emerging that uses a beam of protons to deliver energy directly to the tumor with minimal damage on surrounding tissues and without the side effects of X-ray therapy. Like X-ray radiation, proton therapy blasts tumors with beams of particles. But where traditional radiation uses photons or focused light beams, proton therapy uses proton ions – hydrogen atoms that have lost an electron.

Proton beams have a unique physical characteristic known as the "Bragg peak” that allows the greatest part of its energy to be transferred to a specific area within the body where it has a maximum destructive effect. X-ray radiation, on the other hand, deposits energy and kills cells along the whole length of the beam. This can lead to unintended cell damage and even secondary cancer that can develop years later.

Like many forms of cancer therapy, clinicians know that proton therapy works, but precisely how it works has been a bit of a mystery.

The basic principle is not in question: proton ions collide with water molecules, which make up 70 percent of cells, triggering the release of secondary ions, electrons, reactive molecules and free radicals that damage the DNA of cancerous cells. The proton ions also collide with the DNA directly, breaking bonds and crippling DNA's ability to replicate.

Because of their high rate of division and reduced ability to repair damaged DNA, cancerous cells are much more vulnerable to DNA attacks than normal cells and are killed at a higher rate. Furthermore, a proton beam can be focused on a tumor area, thus causing maximum damage on cancerous cells and minimum damage on surrounding healthy cells.

However, beyond this general microscopic picture, the mechanics of the process have been hard to determine.

"As happens in cancer therapy, they know empirically that it works but they don't know precisely why,” said Morales, a leading proponent of the computational analysis of proton therapy. "To do experiments with human subjects is dangerous, so the best way is through computer simulation.”

Morales has been running computer simulations of proton-cancer-therapy chemical reactions using quantum dynamics models on TACC's Stampede supercomputer to investigate the fundamentals of the process. Computational experiments can mimic the dynamics of the proton-cell interactions at the molecular level without causing damage to a patient and can reveal what happens when the proton beam and cells' materials collide from start to finish, with atomic-level accuracy.

Quantum simulations are necessary because the electrons and atoms that are the basis for proton cancer therapy's effectiveness do not behave according to the laws of classical physics. They are guided by the laws of quantum mechanics, which involve probabilities of location, speed and reactions' occurrences, rather than the precisely defined versions of those three variables.

Morales' studies on Stampede, reported in PLOS One in March 2017 as well as in Molecular Physics and Chemical Physics Letters (in 2015 and 2014, respectively), have determined the basic byproducts of protons colliding with water within the cell and with nucleotides and clusters of DNA bases – the basic units of DNA. The studies shed light on how the protons and their water radiolysis products damage DNA.

The results of Morales' computational experiments match the limited data from physical chemistry experiments, leading to greater confidence in their ability to capture the quantum behavior in action.

Though fundamental in nature, the insights and data that Morales' simulations produce help researchers understand proton cancer therapy at the microscale and help modulate factors like dosage and beam direction.

"The results are all very promising, and we're excited to extend our research further,” Morales said. "These simulations will bring about a unique way to understand and control proton cancer therapy that, at a very low cost, will help to drastically improve the treatment of cancer patients without risking human subjects.”

The work is currently supported by a grant from Cancer Prevention Research Institute of Texas and was started with a previous CAREER award from the National Science Foundation. Stampede was developed and deployed with support from the National Science Foundation.

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