New Study On Cancer Reveals That the Disease Can Be Identified Early and Prevented with Ease

The algorithm basically focuses on pathways that lead to the development of tumors in different parts of the body.

Scientists of Rice University have come up with a framework that not only detects different types of cancers but also helps in their prevention.

Developed by scientist Anatoly Kolomeisky, postdoctoral researcher Hamid Teimouri, and research assistant Cade Spaulding, the concept highlights their analysis of cellular transformation pathways linked to numerous cancers and the ability to pin-point the paths that will probably lead to the origin of the disease.

According to Kolomeisky, a professor of chemistry and of chemical and biomolecular engineering, the framework will help in the identification of "low-probability collections of mutations" that generally result in cancer.

Cancer preventing tool
Anatoly Kolomeisky and Hamid Teimouri Twitter

In simple words, the team is aiming to spot mutations present in the cells that go on to develop tumors when the cells divide. In the midst of this process, they ignore the pathways that do not contribute to the establishment of a tumor.

Their algorithm basically favors the prepotent pathways that take the mutations forward without spending too much energy, SciTech Daily reported.

"Instead of looking at all possible chemical reactions, we identify the few that we might need to look at," Kolomeisky said.

This new study was inspired by a Rice lab modeled stochastic process in 2019 that was focused on understanding the need of some cancer cells to get control of the body's defenses and spread to different parts of the body.

Esophageal Cancer

Kolomeisky elaborated that determining the root cause of the cells becoming cancerous in the first place was probably a good start. Calling their framework 'a tool for prevention,' the scientists explained that it could have a major positive impact on personalized medicine also, as it can warn the patient by detecting the presence of a possible tumor.

The team added later that this project was a great learning opportunity for them as it incorporated an amazing mix of chemistry, physics and biology with computer programming. "It was good way to combine all of the branches of science and also programming, which is what I find most interesting," Spaulding mentioned.

The study titled, Optimal Pathways Control Fixation of Multiple Mutations During Cancer Initiation was published in the Biophysical Journal on 13 May 2022.