A new AI protocol bypasses genomic sequencing for improved access and equity in cancer care.
UC San Diego medical researchers and engineers have developed a new generation of artificial intelligence tools that can replace expensive and time-consuming genomic testing required for cancer treatment.
The new AI protocol, called DeepHRD and now published in the Journal of Clinical Oncology, can quickly detect clinically actionable genomic alterations directly from tumor biopsy slides.
The team’s work will further efforts to reduce delays, cost and inequalities in precision oncology.
“A cancer patient today can expect to wait crucial weeks after their initial tumor diagnosis for a standard genomic test, resulting in life-threatening delays in treatment,” senior author Ludmil Alexandrov, professor of bioengineering and cellular and molecular medicine at UCSD, said in a press release.
The collaborators in Alexandrov’s lab, which bridges bioengineering and medicine, were motivated by the potential of precision oncology to tailor an individual patient’s treatment options.
Citing high costs along with the wait time in traditional methods, lead author Erik Bergstrom, also a postdoctoral researcher in Alexandrov’s lab, said the team “wanted to see if we could develop a completely different approach to resolve this serious issue by designing AI to circumvent the need for genomic testing.”
The work – a collaboration among several biomedical and engineering departments at UCSD – focused on leveraging the minimum amount of patient information that is available early in the diagnostic process.
“Our AI, applied directly to a traditional tissue slide, allows accurate, instantaneous detection of cancer genomic biomarkers,” Bergstrom said, explaining the team sought AI identification of a specific biomarker for homologous recombination deficiency (HRD), a condition in which a cancerous cell loses a specific DNA damage repair mechanism.
“This AI approach saves the patient critical time,” Alexandrov added. “Oncologists can prescribe treatment immediately after initial tissue diagnosis.”
Even more promising: the AI test has a negligible failure rate, while current genomic tests have a failure rate of 20 to 30 percent, often leading to re-testing.
The new technology will remove barriers of time and money to allow immediate, universal access and equality to actionable genomic biomarker detection — required for precision therapy — for people with advanced cancers, according to the study’s co-senior author Dr. Scott Lippman, UCSD distinguished professor of medicine, Center for Engineering and Cancer and Moores Cancer Center member.
“There is no question that this approach is the future of precision oncology,” Lippman said.
© lajolla.ca
