Math Is Used To Kill Cancer Cells

The fight against cancer continues unabated as it remains the second leading cause of death worldwide — and researchers are continuously looking for new methods and new drugs to combat the disease.  We have all heard of new chemotherapeutic drugs developed to fight cancer, as well as novel and exciting treatments such as proton beam therapy, but until recently, no one would have believed that math could destroy cancer. You will certainly wonder how it is possible. Should you pay attention to math? 

The study authors, Dr. Bell and Dr. Mads Kaern along with their research team established a mathematical model that described an infectious process and how virus replicated, spread, and activated the body’s cellular defense mechanisms.  The research findings were published in the journal Nature Communications recently.  Nature Communications is a weekly peer-reviewed scientific journal published by the Nature Publishing Group.

A Collaboration Between Mathematicians and Biologists

The study was a very rare collaboration between mathematicians who are experts in computer modeling and cancer researchers who are biologists.  Cancer researchers and applied mathematicians had never collaborated successfully prior to this study and were able to model one type of cancer cell and one type of virus.  Future plans include collaborating with researchers in New York City who have been exploring increasing the potency of oncolytic viruses. 

Both cancer cells and normal cells are designed to protect themselves from invading cells by an inbuilt defense mechanism, and compromising their immunity.  By differentiating the main physiological differences within normal and cancerous cells, they recognized that modifying the virus genome might counter the anti-viral defense mechanism in cancer cells.  The focus is on the viability and potency of oncolytic viruses, which are artificial and target the cancerous cells only.  The cancer cells grow rapidly and they must be killed quickly before they spread. 

The mathematical model was successful in copying a viral infection along with the resistance the cancer cells put up.  The genetics of the virus was modified to attack only cancer cells at a speed that can destroy them as quickly as possible before they get a chance to build up any defense mechanism against potential harm.  The model prediction was 100 percent accurate and successful in destroying cancer cells in mice. 

The mathematical model that was conceptualized by the researchers described an infection process, how the virus multiplies, spreads, and activates cellular defense mechanisms.  Interestingly, the model simulations were accurate to a large extent and successfully eliminated cancer in a mouse. 

Dr. Bell, the study author, noted, "Unfortunately, cancer is a very complicated and diverse disease, and some viruses work well in some circumstances and not well in others.  As a result, there has been a lot of effort in trying to modify the viruses to make them safe, so they don't target healthy tissue and yet are more efficient in eliminating cancer cells.”  Dr. Bell works as a senior scientist at the Ottawa Hospital Research Institute.  He is also a professor at the University of Ottawa’s Faculty of Medicine. 

“Computational cell biology” is used to kill cancer cells

The use of oncolytic viruses is called virotherapy.  Previously, researchers used naturally occurring oncolytic viruses to prevent cancerous cell growth.  Some of the viruses used included poliovirus, the Coxsackie virus, etc.  “T-VEC” virus that causes cold sores was used by some scientists to help in the management of skin cancer or melanoma.  However, the use of virotherapy took a backseat with the advent of advances in treatment using chemotherapy and radiation therapy. 

Scientists warn that mathematical models must not be considered a “cure-all” for curing cancer, although the research findings look promising at this time. 

says Dr. Kaern, who is a medical faculty member and Canada Research Chair at the Ottawa Institute of Systems Biology in the University. 

“Computational cell biology” works to first make the cancer cells sick, and then kills them.  You would not think that cancer cells are susceptible to infections, but the Ottawa researchers are employing sophisticated mathematical modeling and engineering viruses to infect cancer cells and then cause their destruction.  The research team refers to the modeling as ‘predictive modeling.’ 

Using predictive modeling, the team is analyzing how different treatment techniques and genetic modifications might possibly allow oncolytic viruses to deal with the anti-cancer defense mechanism in cancer cells and kill them while leaving the surrounding healthy tissue untouched.  The genetically modified viruses target the proliferative capacity of cancer cells that allow them to grow unchecked. 

The theory is that probably the viruses are able to better replicate in cancer cells because they have the ability to divide more with an increased metabolic rate.  The viruses exploit that ability of explosive replication and aggressively replicate themselves within the cancer cells.  Therefore, the modeled viruses must be capable of doing that and leave the surrounding tissues unharmed.  They must be modeled not to replicate within healthy cells and tissues.  Surprisingly, it takes only one single oncolytic virus to make contact with one cancer cell and begin the process!

Benefit of Mathematical Models 

The benefit of mathematical models is that they can predict outcomes rapidly and bypass the time-consuming methods of testing different treatments.  The pace of research can move at a faster rate with this model. 

An innovation grant from the Hecht Foundation of the Canadian Cancer Society funded the research study.  This research is only the beginning and a framework to explore the complexity of cancer. 

An Update

Since this article was initially published, scores of new studies have emerged to assess the efficacy of mathematical models in the fight against cancer. The model has been put to practical use in tumor eradication and plotting the path of tumor development. Mathematical modeling, which relies on game theory, is also being put to use to help scientists predict what kinds of drug resistance are likely to develop in the future. It's an exciting development that may save countless lives.