NOV 09, 2019 4:41 AM PST

Using machine learning to discover new cancer treatments

Flashback fifty years ago and many of the modern world’s inventions and discoveries would have been undreamed of – including using machines to discover new anti-cancer drugs. But that’s exactly what’s happening. New research published in eLife by scientists at Sanford Burnham Prebys Medical Discovery Institute details how an algorithm is helping to develop epigenetic drug screens and the potential that this technology has for cancer and other diseases.

Scientists used machine learning to discover new anti-cancer developments. Photo: Pixabay

Senior author Alexey Terskikh, Ph.D. is an associate professor in Sanford Burnham Prebys' Development, Aging and Regeneration Program. Terskikh commented on the study saying, "In order to identify the rare few drug candidates that induce desired epigenetic effects, scientists need methods to screen hundreds of thousands of potential compounds. Our study describes a powerful image-based approach that enables high-throughput epigenetic drug discovery."

The image-based approach Terskikh is referring to is Microscopic Imaging of Epigenetic Landscapes (MIEL), a type of high-content phenotypic screening that is more advanced than past technologies in its ability to, as the authors write, “capture the nuclear staining patterns of epigenetic marks and employ machine learning to accurately distinguish between such patterns.”

Is all that sounding a little complicated? Let’s break it down in simpler terms by first grasping the concept of epigenetics. Watch the video below to understand how epigenetics works.

A little clearer now? So, what the researchers in Terskikh’s lab did was take advantage of a machine-learning algorithm to track the epigenetic changes in cells for more than 220 drugs, in order to determine just how the compounds are working. Through this process, they were able to identify certain drugs that can target and potentially treat glioblastoma, the most fatal kind of brain cancer. They say this method could be useful in identifying compounds that could treat other types of cancer, as well as heart disease and mental illness.

The researchers are hoping to put their algorithms into the commercial field as soon as possible. "Our method is ready for immediate use by pharmaceutical companies looking to develop epigenetic drug screens," says first author Chen Farhy, Ph.D., a postdoctoral researcher in the Terskikh lab. "Industry and academic researchers working on mechanistic studies may also benefit from this method, as the algorithm can detect and categorize epigenetic changes induced by experimental treatments, genetic manipulations or other approaches."

Sources: eLife, Science Daily

About the Author
  • Kathryn is a curious world-traveller interested in the intersection between nature, culture, history, and people. She has worked for environmental education non-profits and is a Spanish/English interpreter.
You May Also Like
AUG 29, 2021
Cancer
Researchers Bioprint Deadly Brain Tumor with 3D Printer
AUG 29, 2021
Researchers Bioprint Deadly Brain Tumor with 3D Printer
Researchers have managed to print an entire active and viable glioblastoma tumor- the deadliest form of brain cancer- us ...
SEP 30, 2021
Cancer
Gut Microbiota Influences Colon Cancer Development
SEP 30, 2021
Gut Microbiota Influences Colon Cancer Development
The gut microbiome consists of all the microorganisms living in an individual’s digestive system. Various factors ...
OCT 14, 2021
Cancer
Mechanism of Resistance to Colorectal Cancer Treatment Uncovered
OCT 14, 2021
Mechanism of Resistance to Colorectal Cancer Treatment Uncovered
Colorectal cancer develops when a series of changes occur across multiple genes.  While researchers have paid signi ...
OCT 21, 2021
Cancer
Exercise: A Secret Weapon to Combat Prostate Cancer?
OCT 21, 2021
Exercise: A Secret Weapon to Combat Prostate Cancer?
Exercise oncology is an evolving science that considers the addition of physical activity regimens to the treatment ...
DEC 23, 2021
Cancer
Optimizing the Recovery Room Could Help Reduce the Recurrence of Bladder Cancer
DEC 23, 2021
Optimizing the Recovery Room Could Help Reduce the Recurrence of Bladder Cancer
It is estimated that nearly 84,000 people will be diagnosed with bladder cancer in the United States this year ...
DEC 27, 2021
Cancer
Improving Immunotherapy with a Novel Nanoparticle
DEC 27, 2021
Improving Immunotherapy with a Novel Nanoparticle
Malignant pleural effusion (MPE) occurs in cancer patients experiencing a buildup of fluid and tumor cells in the pleura ...
Loading Comments...