Machine-learning algorithms tuned to detecting cancer DNA in the blood could pave the way for personalized cancer care.
copyright by www.the-scientist.com
Modern cancer medicine is hampered by two big challenges—detecting cancers when they are small and offering cancer patients personalized, dynamic cancer care. To find solutions, several academic labs and biotech firms are turning to artificial intelligence, working to develop machine-learning algorithms that could help decipher weak signals in the blood that can identify cancers at an early stage and indicate whether a cancer is responding to treatment in real time.
“You have to find this needle in a haystack . . . this very weak signal amongst all of the cacophony of everything else happening in the body,” says Dave Issadore , a bioengineer at Pennsylvania State University and founder of Chip Diagnostics, which is developing a machine-learning method to diagnose disease by sequencing extracellular vesicles’ cargo.
So far, machine-learning algorithms designed to detect minute quantities of tumor DNA in a blood sample—the goal of so-called liquid biopsies—have performed well in clinical validation studies, but no self-learning algorithm has yet been approved for clinical use. These have the potential to outperform imaging and tissue biopsies in detecting and monitoring cancers by looking for mutations in DNA, RNA, and proteins directly from the blood.
“I think the dream of liquid biopsy is to, A), detect cancer when there is very little of it, and, B) detect cancers during treatment,” says Dan Landau, a clinical oncologist and researcher at Weill Cornell Medical School in New York. However, in the both contexts, liquid biopsy techniques struggle to accurately detect cancer among the infinitesimally small quantities of tumor nucleic acids in the blood. Although the technique’s performance varies between cancer types, liquid biopsies so far have been able to detect cancer in around half of early-stage patients diagnosed through imaging, giving it a sensitivity of just 50 percent.
Image Credit: The Scientist
News This Week
For about one in 13 children in the U.S., normally harmless foodstuffs such as milk, eggs and peanuts can send the body's natural defenses into overdrive. Symptoms of food allergies can vary widely, but at [...]
Frank Boehm (Nanoapps Medical Inc. Founder) has contributed to 'Platelet-Rich Plasma Applications for Achilles Tendon Repair: A Bridge between Biology and Surgery', published by International Journal of Molecular Sciences/ MDP. Abstract: Achilles tendon ruptures [...]
Using both mouse and human brain tissue, researchers at Yale School of Medicine have discovered that SARS-CoV-2 can directly infect the central nervous system and have begun to unravel some of the virus’s effects on [...]
A deep learning algorithm developed at MIT has discovered new antibiotics that can treat drug-resistant diseases by killing 35 powerful bacteria. The pathogens that the halicin antibiotic has targetted include Acinetobacter baumannii, which was nicknamed [...]
In our transforming world, digital technology has the critical mass to push our frontiers and release unlimited potential. As the wave of digital transformation soars high, improving our lives, industries and economies, we must not [...]
Scientists Discover a Way to Control the Immune System’s “Natural Killer” Cells With “Invisible” Stem Cells
UC San Francisco scientists have discovered a new way to control the immune system’s “natural killer” (NK) cells, a finding with implications for novel cell therapies and tissue implants that can evade immune rejection. The [...]
A team led by scientists at Georgia State University simulates the precise transition between the processes of DNA synthesis and proofreading DNA replication is one of the most important processes in biology, responsible for ensuring [...]