London: Researchers have taken advantage of artificial intelligence (AI) to identify genes critical to the survival of a cancer cell and could help deliver personalized treatments for cancer patients, according to a new study. They looked at different types of cancer cells to understand the different genetic dependencies to identify the genes, according to the study.
Researchers at the University of Sussex, UK, have achieved this by developing a prediction algorithm that determines which genes are essential in the cell by analyzing genetic changes in the tumor. This can be used to identify actionable targets that, over time, could guide oncologists in personalizing treatments for cancer patients, according to the study.
“Our vision is to take advantage of the decreasing cost of DNA sequence and harness the power of AI to understand cancer cell differences and what they mean for individual patient treatment.
“Through our research, we were able to identify cell-specific genetic dependencies using only the DNA sequence and RNA levels in that cell, which can be easily and inexpensively obtained from tumor biopsy samples.” said Dr. Frances Pearl, Senior Lecturer in Bioinformatics at the University of Sussex.
“This is an incredibly exciting step in our research, which means that we can now work to improve the technology so that it can be offered to oncologists and support treatment pathways for their patients,” Pearl said.
Cancer treatments are prescribed primarily based on the location and type of cancer.
Genetic differences in tumors can make standard cancer treatments ineffective.
Using a personalized approach to guide treatment could improve life expectancy, quality of life and reduce unnecessary side effects for cancer patients, according to the study.
In each cell there are about 20,000 genes that contain the information needed to make proteins.
About 1,000 of those genes are essential, meaning they are needed for the cell to survive.
When normal cells turn into cancer cells, oncogenesor genes with the potential to cause cancer, are turned on and tumor suppressor genes are turned off, causing a rewiring of the cell.
This makes the cell dependent on a new set of genes to survive, and this can be harnessed to kill cancer cells.
By using this new AI technology to target tumor-specific gene-dependent protein products, cancer cells can be killed, leaving normal cells that do not depend on these genes relatively unscathed, according to the study.
Although the dependencies can be determined using intensive laboratory techniques, it is expensive and time-consuming and it would not be feasible to analyze all tumor samples in this way, according to the study.
