The lung cancer blood test, published in Nature Communications, searches for tiny fragments of DNA released by the tumor cells. "We believe that a blood test, or'liquid biopsy,' for lung cancer could be a good way to enhance screening efforts, because it would be easy to do, broadly accessible, and cost-effective," study first author Dimitrios Mathios said. DELFI uses machine learning to spot the patterns of DNA pieces that are associated with tumors, including their size and how many of them are present, and score them based on how likely they are to indicate cancer. Searching for lung cancer's signature: The researchers put DELFI to the test using blood samples from 796 patients in the U.S., Denmark, and the Netherlands. When combined with a clinical evaluation of risk markers, the use of a protein biomarker, and CT scans, the model correctly flagged 94% of lung cancers.

Powered by artificial intelligence, a new lung cancer blood test developed at Johns Hopkins, combined with other metrics, correctly identified 94% of cancer cases in almost 800 patients. The lung cancer blood test, published in Nature Communications, searches for tiny fragments of DNA released by the tumor cells. The AI looks for patterns in this shattered DNA, rather than looking for specific pieces of cancer DNA like other blood tests in development, New Atlas explained. Lung cancer kills the most people in the world, the authors note, "largely due to the late stage at diagnosis where treatments are less effective than at earlier stages" -- and lung cancer rates are increasing, worldwide. "We believe that a blood test, or'liquid biopsy,' for lung cancer could be a good way to enhance screening efforts, because it would be easy to do, broadly accessible, and cost-effective," study first author Dimitrios Mathios said. The DNA difference: Blood tests for cancer typically focus on finding pieces of mutated tumor DNA.