We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us
RANDOX LABORATORIES

Download Mobile App




AI Blood Test Detects Liver Cancer

By LabMedica International staff writers
Posted on 21 Nov 2022
Print article
Image: Liver cancer is the third leading cause of cancer deaths worldwide (Photo courtesy of Pexels)
Image: Liver cancer is the third leading cause of cancer deaths worldwide (Photo courtesy of Pexels)

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. It is estimated that 400 million people worldwide are at higher risk of developing hepatocellular cancer (HCC), a type of liver cancer, because of cirrhosis from chronic liver diseases including chronic viral hepatitis or non-alcoholic fatty liver disease. Now, a novel artificial intelligence blood testing technology developed by researchers to successfully detect lung cancer in a 2021 study has 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 among DNA from cancer cells shed into the bloodstream, known as cell-free DNA (cfDNA).

The DELFI technology uses a blood test to measure the way DNA is packaged inside the nucleus of a cell by studying the size and amount of cell-free DNA present in the circulation from different regions across the genome. Healthy cells package DNA like a well-organized suitcase, in which different regions of the genome are placed carefully in various compartments. The nuclei of cancer cells, by contrast, are like more disorganized suitcases, with items from across the genome thrown in haphazardly. When cancer cells die, they release DNA fragments 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 genomic regions. The DELFI approach only requires low-coverage sequencing, enabling this technology to be cost-effective in a screening setting.

In the most recent study, investigators at the Johns Hopkins Kimmel Cancer Center (Baltimore, MD, USA) performed the test - which was previously shown to accurately classify lung cancer - on cfDNA fragments isolated from the plasma samples. They analyzed the patterns of fragmentation across each sample to develop a DELFI score. The team used the DELFI technology on blood plasma samples obtained from 724 individuals in the U.S., the European Union (E.U.) and Hong Kong to detect HCC. 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 their liver cancers. Of the 724 plasma samples studied, 501 were collected in the U.S. and E.U. 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. For validation, an additional 223 plasma samples were analyzed from individuals in Hong Kong and included samples from 90 people with HCC, 66 with hepatitis B virus (HBV), 35 with HBV-related liver cirrhosis and 32 people with no underlying risk factors.

Scores were low for cancer-free individuals with viral hepatitis or cirrhosis (median DELFI score was 0.078 and 0.080, respectively), but, on average, 5 to 10 times higher for the 75 HCC patients in the U.S./E.U. samples, with high scores observed across all cancer stages, 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 test detected fragmentation changes in the content and packaging of liver cancer genomes, including from genome regions associated with liver-specific activity. The DELFI technology detected liver cancers at their earliest stages, with an overall sensitivity - or ability to accurately detect a cancer - of 88% and a specificity of 98%, which means it almost never incorrectly provided a false positive result, among people at average risk. In samples collected from those at high risk of HCC, the test had 85% sensitivity and 80% specificity. The researchers say next steps include validating this approach in larger studies for clinical use.

“Increased early detection of liver cancer could save lives, but currently available screening tests are underutilized and miss many cancers,” said Victor 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.

“Currently, less than 20% of the high-risk population get screened for liver cancer due to accessibility and suboptimal test performance. This new blood test can double the number of liver cancer cases detected, compared to the standard blood test available, and increase early cancer detection,” added Amy Kim, M.D., assistant professor of medicine at the Johns Hopkins University School of Medicine and co-senior author on the study.

Related Links:
Johns Hopkins Medicine

Platinum Member
COVID-19 Rapid Test
OSOM COVID-19 Antigen Rapid Test
Magnetic Bead Separation Modules
MAG and HEATMAG
Anti-Cyclic Citrullinated Peptide Test
GPP-100 Anti-CCP Kit
Gold Member
ADAMTS-13 Protease Activity Test
ATS-13 Activity Assay

Print article

Channels

Clinical Chemistry

view channel
Image: The 3D printed miniature ionizer is a key component of a mass spectrometer (Photo courtesy of MIT)

3D Printed Point-Of-Care Mass Spectrometer Outperforms State-Of-The-Art Models

Mass spectrometry is a precise technique for identifying the chemical components of a sample and has significant potential for monitoring chronic illness health states, such as measuring hormone levels... Read more

Hematology

view channel
Image: The CAPILLARYS 3 DBS devices have received U.S. FDA 510(k) clearance (Photo courtesy of Sebia)

Next Generation Instrument Screens for Hemoglobin Disorders in Newborns

Hemoglobinopathies, the most widespread inherited conditions globally, affect about 7% of the population as carriers, with 2.7% of newborns being born with these conditions. The spectrum of clinical manifestations... Read more

Immunology

view channel
Image: A false color scanning election micrograph of lung cancer cells grown in culture (Photo courtesy of Anne Weston)

AI Tool Precisely Matches Cancer Drugs to Patients Using Information from Each Tumor Cell

Current strategies for matching cancer patients with specific treatments often depend on bulk sequencing of tumor DNA and RNA, which provides an average profile from all cells within a tumor sample.... Read more

Microbiology

view channel
Image: Microscope image showing human colorectal cancer tumor with Fusobacterium nucleatum stained in a red-purple color (Photo courtesy of Fred Hutch Cancer Center)

Mouth Bacteria Test Could Predict Colon Cancer Progression

Colon cancer, a relatively common but challenging disease to diagnose, requires confirmation through a colonoscopy or surgery. Recently, there has been a worrying increase in colon cancer rates among younger... Read more

Pathology

view channel
Image: Fingertip blood sample collection on the Babson Handwarmer (Photo courtesy of Babson Diagnostics)

Unique Hand-Warming Technology Supports High-Quality Fingertip Blood Sample Collection

Warming the hand is an effective way to facilitate blood collection from a fingertip, yet off-the-shelf solutions often do not fulfill laboratory requirements. Now, a unique hand-warming technology has... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.