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New AI blood testing technology detects more than 80% of liver cancers
A novel artificial intelligence blood testing technology developed and used by researchers at the Johns Hopkins Kimmel Cancer Center to successfully detect lung cancer in a 2021 study has now detected more than 80% of liver cancers in a new study of 724 people. The blood test, called DELFI (DNA Evaluation of Fragments for Early Interception), detects fragmentation changes in the DNA of cancer cells released into the bloodstream, known as cell-free DNA (cfDNA). In the latest study, researchers used DELFI technology on blood plasma samples from 724 people in the United States, the European Union (EU), and Hong Kong to detect hepatocellular...
New AI blood testing technology detects more than 80% of liver cancers
A novel artificial intelligence blood testing technology developed and used by researchers at the Johns Hopkins Kimmel Cancer Center to successfully detect lung cancer in a 2021 study has now detected more than 80% of liver cancers in a new study of 724 people.
The blood test, called DELFI (DNA Evaluation of Fragments for Early Interception), detects fragmentation changes in the DNA of cancer cells released into the bloodstream, known as cell-free DNA (cfDNA). In the latest study, researchers used DELFI technology on blood plasma samples from 724 people in the United States, the European Union (EU) and Hong Kong to detect hepatocellular cancer (HCC), a type of liver cancer.
The researchers believe this is the first genome-wide fragmentation analysis independently validated in two high-risk populations and across different racial and ethnic groups with different causes associated with liver cancer.
Their results were reported on November 18thCancer discovery and at theAmerican Association for Cancer Research Special Conference: Precision Prevention, Early Detection, and Interception of Cancer.
According to a global analysis of the burden of liver disease (J. Hepatology, 2019).
“Increased early detection of liver cancer could save lives, but currently available screening tests are underused and miss many cancers,” he saysVictor Velculescu, M.D., Ph.D., professor of oncology and co-director of the Cancer Genetics and Epigenetics Program at the Johns Hopkins Kimmel Cancer Center, who co-led the study with Zachariah Foda, M.D., Ph.D., gastroenterology fellow, Akshaya Annapragada, MD/Ph.D. students andAmy Kim, MD, assistant professor of medicine at theJohns Hopkins University School of Medicine.
Of the 724 plasma samples examined, 501 were collected in the US and EU and included samples from 75 people with HCC to train and validate the machine learning model, a type of artificial intelligence that uses data and algorithms to improve accuracy, explains Foda. For validation, an additional 223 plasma samples from people in Hong Kong were analyzed, including samples from 90 people with HCC, 66 with hepatitis B virus (HBV), 35 with HBV-related liver cirrhosis and 32 people without underlying risk factors.
The DELFI technology uses a blood test to measure how DNA is packaged in the cell nucleus by examining the size and amount of cell-free DNA present in circulation from different regions of the genome. Healthy cells pack the DNA like a well-sorted suitcase, in which different regions of the genome are carefully stored in different compartments. In contrast, the nuclei of cancer cells are more like disorganized suitcases into which items from across the genome are randomly thrown. When cancer cells die, they chaotically release DNA fragments into the bloodstream.
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DELFI identifies the presence of cancer by examining millions of cfDNA fragments for abnormal patterns, including the size and amount of DNA in different genomic regions. The DELFI approach requires only low-coverage sequencing, making this technology cost-effective in a screening setting, the researchers say.
In the latest study, researchers performed the test - previously shown to accurately classify lung cancer - on cfDNA fragments isolated from the plasma samples. They analyzed the fragmentation patterns in each sample to develop a DELFI score.
Values were low for cancer-free individuals with viral hepatitis or cirrhosis (mean DELFI scores were 0.078 and 0.080, respectively), but were on average 5 to 10 times higher for the 75 HCC patients in the US/EU samples with high values observed in all cancer stages, including early disease (DELFI scores for stage 0 = 0.46, Stage A = 0.61, Stage B = 0.83 and Stage C = 0.92). In addition, the assay detected fragmentation changes in the content and packaging of liver cancer genomes, including genomic regions associated with liver-specific activity.
The DELFI technology detected liver cancer in its earliest stages with an overall sensitivity - or ability to accurately detect a cancer - of 88% and a specificity of 98%, meaning it almost never, on average, gave a false positive result. In samples collected from people at high risk of HCC, the test had a sensitivity of 85% and a specificity of 80%.
Currently, less than 20% of the high-risk population is screened for liver cancer due to accessibility and suboptimal testing performance. This new blood test can double the number of liver cancer cases detected compared to the standard available blood test and improve early cancer detection.”
Amy Kim, MD, assistant professor of medicine at Johns Hopkins University School of MedicineCo-senior author of the study
The researchers say next steps include validating this approach in larger studies for clinical use.
According to the American Cancer Society, liver cancer is diagnosed in more than 800,000 people worldwide each year and is a leading cause of cancer-related deaths worldwide.
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