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Artificial intelligence-based blood test offers a reliable way to identify lung cancer

Artificial intelligence-based blood test offers a reliable way to identify lung cancer
Artificial intelligence-based blood test offers a reliable way to identify lung cancer


Researchers at the Johns Hopkins Kimmel Cancer Center and elsewhere have developed and tested a liquid biopsy that uses artificial intelligence techniques to identify patterns of DNA fragments associated with lung cancer and may help detect the disease earlier.

In a prospective study published June 3, Cancer DetectionThe research team demonstrated that artificial intelligence technology can identify people who are susceptible to lung cancer based on DNA fragment patterns in their blood. The study enrolled approximately 1,000 participants with or without cancer who met criteria for traditional lung cancer screening with low-dose computed tomography (CT). Participants were recruited at 47 centers in 23 states in the United States. According to the research team's computer modeling, the new blood test could accelerate lung cancer screening and reduce mortality by identifying patients who are at highest risk and would benefit from follow-up CT screening.

“We have a simple blood test that can be done in the doctor's office to tell patients if they have signs of lung cancer and if they should get a follow-up CT scan,” said Victor E. Berculescu, M.D., Ph.D., professor of oncology and co-director of the Cancer Genetics and Epigenetics Program at the Johns Hopkins Kimmel Cancer Center and corresponding author of the study. Lung cancer is the deadliest cancer in the United States, according to the National Cancer Institute, and the world, according to the World Health Organization. Screening high-risk patients annually with CT scans can help detect lung cancer early, when it is most treatable, and prevent deaths from lung cancer. The U.S. Preventive Services Task Force recommends screening 15 million people nationwide between the ages of 50 and 80 who have a history of smoking, but only about 6 to 10 percent of eligible people get screened each year. The time it takes to arrange an appointment and go for a test, and the low radiation dose the scan exposes people to, may make them reluctant to get tested, Berculescu explained.

To overcome some of these hurdles, Berculescu and his colleagues over the past five years have developed a test that uses artificial intelligence to detect patterns of DNA fragments found in lung cancer patients. The test exploits differences in the way DNA is wrapped in normal and cancer cells: In healthy cells, DNA is neatly and consistently folded, like a rolled up ball of yarn, while the DNA of cancer cells is more disordered. When both types of cells die, fragments of their DNA are shed into the blood. The DNA fragments of cancer patients tend to be more disordered and irregular than those of people without cancer.

The researchers trained artificial intelligence software to identify specific patterns of DNA fragments found in the blood of 576 people with and without lung cancer. They then checked that the method worked in a second group of 382 people with and without cancer. Analysis showed that the test has a negative predictive value of 99.8%, meaning that only 2 out of 1,000 people tested would likely miss lung cancer.

According to the group's computer simulations, if the test could help raise lung cancer screening rates by 50 percent within five years, it could quadruple the number of lung cancers detected and increase the proportion of cancers detected early, when they are most treatable, by about 10 percent, preventing about 14,000 cancer deaths over that five-year period.

“This test is cheap and can be implemented on a large scale,” Berculescu said. “We believe it will make lung cancer testing more accessible and available to more people, which will lead to more cancers being found and treated earlier.”

The test is currently available from DELFI Diagnostics as a laboratory-based test under the Clinical Laboratory Improvement Act, but the team plans to seek U.S. Food and Drug Administration approval as a screening test for lung cancer. Velculescu and his colleagues also plan to investigate whether a similar approach could be used to detect other types of cancer.

Robert B. Scharf of Johns Hopkins is a co-author on the study. Additional co-authors include Cleveland Clinic, DELFI Diagnostics, Medicus Economics LLC, Miami Cancer Institute, Pan American Oncology Center, University of Washington, Centura Health, Vanderbilt Health, Stratevi, Massachusetts General Hospital, Medical University of South Carolina, Department of Veterans Affairs, Perelman School of Medicine at the University of Pennsylvania, NYU Langone Health, Allegheny Health Network and Memorial Sloan Kettering Cancer Center.

This research was supported in part by DELFI Diagnostics, the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, Stand Up To Cancer-LUNGevity-American Lung Association Lung Cancer Interception Dream Team Translational Research Grant, Stand Up To Cancer-DCS International Translational Cancer Research Dream Team Grant, Gray Foundation, The Honorable Tina Brozman Foundation, Commonwealth Foundation, Cole Foundation, and the National Institutes of Health.

Mr. Velculescu and Mr. Scharpf are inventors on a patent application filed by Johns Hopkins University relating to cell-free DNA for cancer detection that has been licensed to DELFI Diagnostics, LabCorp, Qiagen, Sysmex, Agios, Genzyme, Esoterix, Ventana and ManaT Bio. Mr. Velculescu sold his shares in Personal Genome Diagnostics (PGDx) to LabCorp in February 2022. Mr. Velculescu is a founder of DELFI Diagnostics, serves on the board of directors and owns stock in DELFI Diagnostics. Mr. Scharpf is a founder and consultant to DELFI Diagnostics and owns stock in DELFI Diagnostics. Mr. Velculescu, Mr. Scharpf and Johns Hopkins University have received royalties and fees from the company. Johns Hopkins University also owns stock in DELFI Diagnostics. Dr. Velculescu serves as an advisor for Viron Therapeutics and Epitope. These relationships are managed by the Johns Hopkins University Conflict of Interest Policy.




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