A new blood test with artificial intelligence detects liver cancer!


A new AI blood-testing technique developed and used by Johns Hopkins Kimmel Cancer Center researchers 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.

A blood test called DELFI (DNA Fragment Evaluation for Early Interception) detects fragmentation changes among DNA from cancer cells that drop into the bloodstream, known as cell-free DNA (cfDNA). In the latest study, researchers used DELFI technology on blood plasma samples obtained from 724 individuals in the United States, the European Union (EU), and Hong Kong to screen for hepatocellular carcinoma (HCC), a type of liver cancer.

The researchers believe this is the first independently validated genome-wide segmentation analysis in two high-risk populations and across different racial and ethnic groups for different causes associated with HCC.

Their findings were reported on November 18 Cancer discovery And at the American Association for Cancer Research Special Conference: Accurate Prevention, Early Detection, and Intercepting Cancer.

It is estimated that 400 million people worldwide are more likely to develop liver cancer due to cirrhosis than from chronic liver disease including chronic viral hepatitis or non-alcoholic fatty liver disease, according to a global analysis of the burden of liver disease (J Liver Diseases2019).

“Increased early detection of liver cancer can save lives, but currently available screening tests are underutilized and miss many cancers,” says Victor Velculescu, MD, PhD, professor of oncology and associate director of the Cancer Genetics and Epigenetics Program at the Center. Johns Hopkins Kimmel Cancer Institute, who co-led the study with Zakaria Foda, MD, PhD, gastroenterologist fellow, Akshaya Anapragada, MD/PhD. student, and Amy Kim, MD, assistant professor of medicine at the Johns Hopkins University School of Medicine.

Of the 724 plasma samples studied, 501 were collected in the US and EU and included samples from 75 people with hepatocellular carcinoma (HCC) to train and validate a machine learning model, a type of artificial intelligence that uses data and algorithms to improve accuracy, explains Fouda. . For validation, an additional 223 plasma samples from individuals in Hong Kong were analyzed and included samples from 90 subjects with liver cancer, 66 with hepatitis B virus (HBV), 35 with HBV-associated cirrhosis and 32 subjects without underlying risk factors.

The DELFI technique uses a blood test to measure the way DNA is packaged within a cell’s nucleus by examining the volume and amount of cell-free DNA present in circulation from different regions across the genome. Healthy cells pack their DNA like a well-organized bag, with different regions of the genome carefully tucked into different compartments. By contrast, the nuclei of cancer cells are like disorganized suitcases, with elements of the genome thrown in at random. When cancer cells die, they release fragments of DNA in a chaotic manner into the bloodstream.

DELFI identifies the presence of cancer by examining millions of cfDNA fragments for abnormal patterns, including the size and amount of DNA in different regions of the genome. The researchers say the DELFI approach requires only low-coverage sequencing, making this technology cost-effective in the screening setting.

In the latest study, the researchers ran the test — which has previously been shown to accurately classify lung cancer — on cfDNA fragments isolated from plasma samples. They analyzed fragmentation patterns across each sample to develop a DELFI score.

Scores were low for non-cancer individuals with viral hepatitis or cirrhosis (mean DELFI score was 0.078 and 0.080, respectively), but, on average, 5 to 10 times higher for the 75 HCC patients in the US/ EU, with high scores observed across all stages of cancer, including early stage 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 revealed segmentation changes in the content and packaging of HCC genomes, including from regions of the genome associated with liver specific activity.

The DELFI technique detected early-stage liver cancers, with an overall sensitivity — or the ability to accurately detect cancer — of 88% and a specificity of 98%, meaning it never incorrectly provided a false positive, among people at intermediate risk. In samples collected from those at high risk of developing HCC, the test had a sensitivity of 85% and a specificity of 80%.

“Currently, less than 20% of the population at high risk are screened for liver cancer due to accessibility and suboptimal test performance. This new blood test could double the number of cases of liver cancer detected, compared to the standard blood test available, and increase early detection. cancer,” says Kim, co-lead author of the study.

The researchers say the next steps include validating this approach in larger studies of clinical use.

More than 800,000 people are diagnosed with liver cancer worldwide each year, and it is a leading cause of cancer deaths worldwide, according to the American Cancer Society.

In addition to Velculescu, Foda, Annapragada, and Kim, the other researchers were Kavya Boyapati, Daniel Bruhm, Nicholas Vulpescu, Jamie Medina, Dimitrios Mathios, Stephen Cristiano, Noushin Niknafs, Harry Luu, Michael Goggins, Robert Anders, Jing Sun, Shruti Meta, David Thomas, Gregory Kirk, Vilmos Adolph, Gillian Bhalen, and Robert Sharpf.

The research was supported by the Dr. Miriam and Sheldon J. Foundation. INTIME Lung Lung Cancer Interception Dream Team Grant, MARC Foundation for Cancer Research, research grant from Delfi Diagnostics, National Institutes of Health awards CA121113, CA006973, CA233259, GM136577, CA237624 and CA062924, and Department of Defense CDMRP W81XWH-20-1-0605 award. Stand Up to Cancer is a program of the Entertainment Industry Foundation operated by the American Association for Cancer Research.

Researchers disclose the following competing interests: Velculescu is the founder of Delfi Diagnostics, serves on the Board of Directors and as an advisor to this organization, and owns Delfi Diagnostics stock, which is subject to certain restrictions under Johns Hopkins University policy. In addition, Johns Hopkins University owns shares in Delfi Diagnostics. Velculescu divested his interest in Personalized Genome Diagnostics (PGDx) to LabCorp in February 2022. He is an inventor on patent applications filed by Johns Hopkins University related to cancer genetic analyzes and cell-free DNA for cancer detection that have been licensed to one or more entities, including These include Delfi Diagnostics, LabCorp, Qiagen, Sysmex, Agios, Genzyme, Esoterix, Ventana, and ManaT Bio. Under the terms of these licensing agreements, the University and the inventors are entitled to receive fees and royalty distributions. Velculescu serves as a consultant for Danaher, Takeda Pharmaceuticals, and Veron Therapeutics. Scharpf is the founder and advisor to Delfi Diagnostics and owns shares of Delfi Diagnostics subject to certain restrictions under university policy. These arrangements have been reviewed and approved by Johns Hopkins University in accordance with its conflict of interest policies.



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